Clean up some comments

This reverts commit 5559726fd7.

Cargo.lock

@@ -5904,9 +5904,12 @@ dependencies = [
  "async-trait",
  "client",
  "collections",
+ "credentials_provider",
  "criterion",
  "ctor",
  "dap",
+ "dirs 4.0.0",
+ "editor",
  "extension",
  "fs",
  "futures 0.3.31",
@@ -5915,8 +5918,11 @@ dependencies = [
  "http_client",
  "language",
  "language_extension",
+ "language_model",
  "log",
  "lsp",
+ "markdown",
+ "menu",
  "moka",
  "node_runtime",
  "parking_lot",
@@ -5931,12 +5937,14 @@ dependencies = [
  "serde_json",
  "serde_json_lenient",
  "settings",
+ "smol",
  "task",
  "telemetry",
  "tempfile",
  "theme",
  "theme_extension",
  "toml 0.8.23",
+ "ui",
  "url",
  "util",
  "wasmparser 0.221.3",
@@ -8911,6 +8919,7 @@ dependencies = [
  "credentials_provider",
  "deepseek",
  "editor",
+ "extension",
  "fs",
  "futures 0.3.31",
  "google_ai",

assets/settings/default.json

@@ -12,7 +12,7 @@
   "theme": {
     "mode": "system",
     "light": "One Light",
-    "dark": "One Dark"
+    "dark": "One Dark",
   },
   "icon_theme": "Zed (Default)",
   // The name of a base set of key bindings to use.
@@ -29,7 +29,7 @@
   // Features that can be globally enabled or disabled
   "features": {
     // Which edit prediction provider to use.
-    "edit_prediction_provider": "zed"
+    "edit_prediction_provider": "zed",
   },
   // The name of a font to use for rendering text in the editor
   // ".ZedMono" currently aliases to Lilex
@@ -69,7 +69,7 @@
   // The OpenType features to enable for text in the UI
   "ui_font_features": {
     // Disable ligatures:
-    "calt": false
+    "calt": false,
   },
   // The weight of the UI font in standard CSS units from 100 to 900.
   "ui_font_weight": 400,
@@ -87,7 +87,7 @@
     "border_size": 0.0,
     // Opacity of the inactive panes. 0 means transparent, 1 means opaque.
     // Values are clamped to the [0.0, 1.0] range.
-    "inactive_opacity": 1.0
+    "inactive_opacity": 1.0,
   },
   // Layout mode of the bottom dock. Defaults to "contained"
   //   choices: contained, full, left_aligned, right_aligned
@@ -103,12 +103,12 @@
     "left_padding": 0.2,
     // The relative width of the right padding of the central pane from the
     // workspace when the centered layout is used.
-    "right_padding": 0.2
+    "right_padding": 0.2,
   },
   // Image viewer settings
   "image_viewer": {
     // The unit for image file sizes: "binary" (KiB, MiB) or decimal (KB, MB)
-    "unit": "binary"
+    "unit": "binary",
   },
   // Determines the modifier to be used to add multiple cursors with the mouse. The open hover link mouse gestures will adapt such that it do not conflict with the multicursor modifier.
   //
@@ -296,7 +296,7 @@
     // When true, enables drag and drop text selection in buffer.
     "enabled": true,
     // The delay in milliseconds that must elapse before drag and drop is allowed. Otherwise, a new text selection is created.
-    "delay": 300
+    "delay": 300,
   },
   // What to do when go to definition yields no results.
   //
@@ -400,14 +400,14 @@
   // Visible characters used to render whitespace when show_whitespaces is enabled.
   "whitespace_map": {
     "space": "•",
-    "tab": "→"
+    "tab": "→",
   },
   // Settings related to calls in Zed
   "calls": {
     // Join calls with the microphone live by default
     "mute_on_join": false,
     // Share your project when you are the first to join a channel
-    "share_on_join": false
+    "share_on_join": false,
   },
   // Toolbar related settings
   "toolbar": {
@@ -420,7 +420,7 @@
     // Whether to show agent review buttons in the editor toolbar.
     "agent_review": true,
     // Whether to show code action buttons in the editor toolbar.
-    "code_actions": false
+    "code_actions": false,
   },
   // Whether to allow windows to tab together based on the user’s tabbing preference (macOS only).
   "use_system_window_tabs": false,
@@ -439,7 +439,7 @@
     // Whether to show the sign in button in the titlebar.
     "show_sign_in": true,
     // Whether to show the menus in the titlebar.
-    "show_menus": false
+    "show_menus": false,
   },
   "audio": {
     // Opt into the new audio system.
@@ -472,7 +472,7 @@
     // the future we will migrate by setting this to false
     //
     // You need to rejoin a call for this setting to apply
-    "experimental.legacy_audio_compatible": true
+    "experimental.legacy_audio_compatible": true,
   },
   // Scrollbar related settings
   "scrollbar": {
@@ -511,8 +511,8 @@
       // When false, forcefully disables the horizontal scrollbar. Otherwise, obey other settings.
       "horizontal": true,
       // When false, forcefully disables the vertical scrollbar. Otherwise, obey other settings.
-      "vertical": true
-    }
+      "vertical": true,
+    },
   },
   // Minimap related settings
   "minimap": {
@@ -560,7 +560,7 @@
     // 3. "gutter" or "none" to not highlight the current line in the minimap.
     "current_line_highlight": null,
     // Maximum number of columns to display in the minimap.
-    "max_width_columns": 80
+    "max_width_columns": 80,
   },
   // Enable middle-click paste on Linux.
   "middle_click_paste": true,
@@ -583,7 +583,7 @@
     // Whether to show fold buttons in the gutter.
     "folds": true,
     // Minimum number of characters to reserve space for in the gutter.
-    "min_line_number_digits": 4
+    "min_line_number_digits": 4,
   },
   "indent_guides": {
     // Whether to show indent guides in the editor.
@@ -604,7 +604,7 @@
     //
     // 1. "disabled"
     // 2. "indent_aware"
-    "background_coloring": "disabled"
+    "background_coloring": "disabled",
   },
   // Whether the editor will scroll beyond the last line.
   "scroll_beyond_last_line": "one_page",
@@ -623,7 +623,7 @@
   "fast_scroll_sensitivity": 4.0,
   "sticky_scroll": {
     // Whether to stick scopes to the top of the editor.
-    "enabled": false
+    "enabled": false,
   },
   "relative_line_numbers": "disabled",
   // If 'search_wrap' is disabled, search result do not wrap around the end of the file.
@@ -641,7 +641,7 @@
     // Whether to interpret the search query as a regular expression.
     "regex": false,
     // Whether to center the cursor on each search match when navigating.
-    "center_on_match": false
+    "center_on_match": false,
   },
   // When to populate a new search's query based on the text under the cursor.
   // This setting can take the following three values:
@@ -684,8 +684,8 @@
       "shift": false,
       "alt": false,
       "platform": false,
-      "function": false
-    }
+      "function": false,
+    },
   },
   // Whether to resize all the panels in a dock when resizing the dock.
   // Can be a combination of "left", "right" and "bottom".
@@ -733,7 +733,7 @@
       //    "always"
       // 5. Never show the scrollbar:
       //    "never"
-      "show": null
+      "show": null,
     },
     // Which files containing diagnostic errors/warnings to mark in the project panel.
     // This setting can take the following three values:
@@ -756,7 +756,7 @@
       //    "always"
       // 2. Never show indent guides:
       //    "never"
-      "show": "always"
+      "show": "always",
     },
     // Sort order for entries in the project panel.
     // This setting can take three values:
@@ -781,8 +781,8 @@
       // Whether to automatically open files after pasting or duplicating them.
       "on_paste": true,
       // Whether to automatically open files dropped from external sources.
-      "on_drop": true
-    }
+      "on_drop": true,
+    },
   },
   "outline_panel": {
     // Whether to show the outline panel button in the status bar
@@ -815,7 +815,7 @@
       //    "always"
       // 2. Never show indent guides:
       //    "never"
-      "show": "always"
+      "show": "always",
     },
     // Scrollbar-related settings
     "scrollbar": {
@@ -832,11 +832,11 @@
       //    "always"
       // 5. Never show the scrollbar:
       //    "never"
-      "show": null
+      "show": null,
     },
     // Default depth to expand outline items in the current file.
     // Set to 0 to collapse all items that have children, 1 or higher to collapse items at that depth or deeper.
-    "expand_outlines_with_depth": 100
+    "expand_outlines_with_depth": 100,
   },
   "collaboration_panel": {
     // Whether to show the collaboration panel button in the status bar.
@@ -844,7 +844,7 @@
     // Where to dock the collaboration panel. Can be 'left' or 'right'.
     "dock": "left",
     // Default width of the collaboration panel.
-    "default_width": 240
+    "default_width": 240,
   },
   "git_panel": {
     // Whether to show the git panel button in the status bar.
@@ -876,12 +876,12 @@
       // Choices: always, auto, never, system
       // Default: inherits editor scrollbar settings
       // "show": null
-    }
+    },
   },
   "message_editor": {
     // Whether to automatically replace emoji shortcodes with emoji characters.
     // For example: typing `:wave:` gets replaced with `👋`.
-    "auto_replace_emoji_shortcode": true
+    "auto_replace_emoji_shortcode": true,
   },
   "notification_panel": {
     // Whether to show the notification panel button in the status bar.
@@ -889,7 +889,7 @@
     // Where to dock the notification panel. Can be 'left' or 'right'.
     "dock": "right",
     // Default width of the notification panel.
-    "default_width": 380
+    "default_width": 380,
   },
   "agent": {
     // Whether the agent is enabled.
@@ -911,7 +911,7 @@
       // The provider to use.
       "provider": "zed.dev",
       // The model to use.
-      "model": "claude-sonnet-4"
+      "model": "claude-sonnet-4",
     },
     // Additional parameters for language model requests. When making a request to a model, parameters will be taken
     // from the last entry in this list that matches the model's provider and name. In each entry, both provider
@@ -966,8 +966,8 @@
           "grep": true,
           "terminal": true,
           "thinking": true,
-          "web_search": true
-        }
+          "web_search": true,
+        },
       },
       "ask": {
         "name": "Ask",
@@ -984,14 +984,14 @@
           "open": true,
           "grep": true,
           "thinking": true,
-          "web_search": true
-        }
+          "web_search": true,
+        },
       },
       "minimal": {
         "name": "Minimal",
         "enable_all_context_servers": false,
-        "tools": {}
-      }
+        "tools": {},
+      },
     },
     // Where to show notifications when the agent has either completed
     // its response, or else needs confirmation before it can run a
@@ -1020,7 +1020,7 @@
     // Minimum number of lines to display in the agent message editor.
     //
     // Default: 4
-    "message_editor_min_lines": 4
+    "message_editor_min_lines": 4,
   },
   // Whether the screen sharing icon is shown in the os status bar.
   "show_call_status_icon": true,
@@ -1055,7 +1055,7 @@
     // Whether or not to show the navigation history buttons.
     "show_nav_history_buttons": true,
     // Whether or not to show the tab bar buttons.
-    "show_tab_bar_buttons": true
+    "show_tab_bar_buttons": true,
   },
   // Settings related to the editor's tabs
   "tabs": {
@@ -1094,7 +1094,7 @@
     //    "errors"
     // 3. Mark files with errors and warnings:
     //    "all"
-    "show_diagnostics": "off"
+    "show_diagnostics": "off",
   },
   // Settings related to preview tabs.
   "preview_tabs": {
@@ -1115,7 +1115,7 @@
     "enable_preview_file_from_code_navigation": true,
     // Whether to keep tabs in preview mode when code navigation is used to navigate away from them.
     // If `enable_preview_file_from_code_navigation` or `enable_preview_multibuffer_from_code_navigation` is also true, the new tab may replace the existing one.
-    "enable_keep_preview_on_code_navigation": false
+    "enable_keep_preview_on_code_navigation": false,
   },
   // Settings related to the file finder.
   "file_finder": {
@@ -1159,7 +1159,7 @@
     //   * "all": Use all gitignored files
     //   * "indexed": Use only the files Zed had indexed
     //   * "smart": Be smart and search for ignored when called from a gitignored worktree
-    "include_ignored": "smart"
+    "include_ignored": "smart",
   },
   // Whether or not to remove any trailing whitespace from lines of a buffer
   // before saving it.
@@ -1230,7 +1230,7 @@
     // Send debug info like crash reports.
     "diagnostics": true,
     // Send anonymized usage data like what languages you're using Zed with.
-    "metrics": true
+    "metrics": true,
   },
   // Whether to disable all AI features in Zed.
   //
@@ -1264,7 +1264,7 @@
       "enabled": true,
       // Minimum time to wait before pulling diagnostics from the language server(s).
       // 0 turns the debounce off.
-      "debounce_ms": 50
+      "debounce_ms": 50,
     },
     // Settings for inline diagnostics
     "inline": {
@@ -1282,8 +1282,8 @@
       "min_column": 0,
       // The minimum severity of the diagnostics to show inline.
       // Inherits editor's diagnostics' max severity settings when `null`.
-      "max_severity": null
-    }
+      "max_severity": null,
+    },
   },
   // Files or globs of files that will be excluded by Zed entirely. They will be skipped during file
   // scans, file searches, and not be displayed in the project file tree. Takes precedence over `file_scan_inclusions`.
@@ -1297,7 +1297,7 @@
     "**/.DS_Store",
     "**/Thumbs.db",
     "**/.classpath",
-    "**/.settings"
+    "**/.settings",
   ],
   // Files or globs of files that will be included by Zed, even when ignored by git. This is useful
   // for files that are not tracked by git, but are still important to your project. Note that globs
@@ -1332,14 +1332,14 @@
       // Whether or not to display the git commit summary on the same line.
       "show_commit_summary": false,
       // The minimum column number to show the inline blame information at
-      "min_column": 0
+      "min_column": 0,
     },
     "blame": {
-      "show_avatar": true
+      "show_avatar": true,
     },
     // Control which information is shown in the branch picker.
     "branch_picker": {
-      "show_author_name": true
+      "show_author_name": true,
     },
     // How git hunks are displayed visually in the editor.
     // This setting can take two values:
@@ -1351,7 +1351,7 @@
     "hunk_style": "staged_hollow",
     // Should the name or path be displayed first in the git view.
     // "path_style": "file_name_first" or "file_path_first"
-    "path_style": "file_name_first"
+    "path_style": "file_name_first",
   },
   // The list of custom Git hosting providers.
   "git_hosting_providers": [
@@ -1385,7 +1385,7 @@
       "**/secrets.yml",
       "**/.zed/settings.json", // zed project settings
       "/**/zed/settings.json", // zed user settings
-      "/**/zed/keymap.json"
+      "/**/zed/keymap.json",
     ],
     // When to show edit predictions previews in buffer.
     // This setting takes two possible values:
@@ -1403,15 +1403,15 @@
     "copilot": {
       "enterprise_uri": null,
       "proxy": null,
-      "proxy_no_verify": null
+      "proxy_no_verify": null,
     },
     "codestral": {
       "model": null,
-      "max_tokens": null
+      "max_tokens": null,
     },
     // Whether edit predictions are enabled when editing text threads in the agent panel.
     // This setting has no effect if globally disabled.
-    "enabled_in_text_threads": true
+    "enabled_in_text_threads": true,
   },
   // Settings specific to journaling
   "journal": {
@@ -1421,7 +1421,7 @@
     // May take 2 values:
     // 1. hour12
     // 2. hour24
-    "hour_format": "hour12"
+    "hour_format": "hour12",
   },
   // Status bar-related settings.
   "status_bar": {
@@ -1432,7 +1432,7 @@
     // Whether to show the cursor position button in the status bar.
     "cursor_position_button": true,
     // Whether to show active line endings button in the status bar.
-    "line_endings_button": false
+    "line_endings_button": false,
   },
   // Settings specific to the terminal
   "terminal": {
@@ -1553,8 +1553,8 @@
         // Preferred Conda manager to use when activating Conda environments.
         // Values: "auto", "conda", "mamba", "micromamba"
         // Default: "auto"
-        "conda_manager": "auto"
-      }
+        "conda_manager": "auto",
+      },
     },
     "toolbar": {
       // Whether to display the terminal title in its toolbar's breadcrumbs.
@@ -1562,7 +1562,7 @@
       //
       // The shell running in the terminal needs to be configured to emit the title.
       // Example: `echo -e "\e]2;New Title\007";`
-      "breadcrumbs": false
+      "breadcrumbs": false,
     },
     // Scrollbar-related settings
     "scrollbar": {
@@ -1579,7 +1579,7 @@
       //    "always"
       // 5. Never show the scrollbar:
       //    "never"
-      "show": null
+      "show": null,
     },
     // Set the terminal's font size. If this option is not included,
     // the terminal will default to matching the buffer's font size.
@@ -1660,12 +1660,12 @@
         "# which may be followed by trailing punctuation",
         "[.,:)}\\]>]*",
         "# and always includes trailing whitespace or end of line",
-        "([ ]+|$)"
-      ]
+        "([ ]+|$)",
+      ],
     ],
     // Timeout for hover and Cmd-click path hyperlink discovery in milliseconds. Specifying a
     // timeout of `0` will disable path hyperlinking in terminal.
-    "path_hyperlink_timeout_ms": 1
+    "path_hyperlink_timeout_ms": 1,
   },
   "code_actions_on_format": {},
   // Settings related to running tasks.
@@ -1681,7 +1681,7 @@
     // * Zed task from history (e.g. one-off task was spawned before)
     //
     // Default: true
-    "prefer_lsp": true
+    "prefer_lsp": true,
   },
   // An object whose keys are language names, and whose values
   // are arrays of filenames or extensions of files that should
@@ -1698,7 +1698,7 @@
   "file_types": {
     "JSONC": ["**/.zed/**/*.json", "**/zed/**/*.json", "**/Zed/**/*.json", "**/.vscode/**/*.json", "tsconfig*.json"],
     "Markdown": [".rules", ".cursorrules", ".windsurfrules", ".clinerules"],
-    "Shell Script": [".env.*"]
+    "Shell Script": [".env.*"],
   },
   // Settings for which version of Node.js and NPM to use when installing
   // language servers and Copilot.
@@ -1714,14 +1714,14 @@
     // `path`, but not `npm_path`, Zed will assume that `npm` is located at
     // `${path}/../npm`.
     "path": null,
-    "npm_path": null
+    "npm_path": null,
   },
   // The extensions that Zed should automatically install on startup.
   //
   // If you don't want any of these extensions, add this field to your settings
   // and change the value to `false`.
   "auto_install_extensions": {
-    "html": true
+    "html": true,
   },
   // The capabilities granted to extensions.
   //
@@ -1729,7 +1729,7 @@
   "granted_extension_capabilities": [
     { "kind": "process:exec", "command": "*", "args": ["**"] },
     { "kind": "download_file", "host": "*", "path": ["**"] },
-    { "kind": "npm:install", "package": "*" }
+    { "kind": "npm:install", "package": "*" },
   ],
   // Controls how completions are processed for this language.
   "completions": {
@@ -1780,7 +1780,7 @@
     // 4. "replace_suffix"
     //   Behaves like `"replace"` if the text after the cursor is a suffix of the completion, and like
     //   `"insert"` otherwise.
-    "lsp_insert_mode": "replace_suffix"
+    "lsp_insert_mode": "replace_suffix",
   },
   // Different settings for specific languages.
   "languages": {
@@ -1788,113 +1788,113 @@
       "language_servers": ["astro-language-server", "..."],
       "prettier": {
         "allowed": true,
-        "plugins": ["prettier-plugin-astro"]
-      }
+        "plugins": ["prettier-plugin-astro"],
+      },
     },
     "Blade": {
       "prettier": {
-        "allowed": true
-      }
+        "allowed": true,
+      },
     },
     "C": {
       "format_on_save": "off",
       "use_on_type_format": false,
       "prettier": {
-        "allowed": false
-      }
+        "allowed": false,
+      },
     },
     "C++": {
       "format_on_save": "off",
       "use_on_type_format": false,
       "prettier": {
-        "allowed": false
-      }
+        "allowed": false,
+      },
     },
     "CSS": {
       "prettier": {
-        "allowed": true
-      }
+        "allowed": true,
+      },
     },
     "Dart": {
-      "tab_size": 2
+      "tab_size": 2,
     },
     "Diff": {
       "show_edit_predictions": false,
       "remove_trailing_whitespace_on_save": false,
-      "ensure_final_newline_on_save": false
+      "ensure_final_newline_on_save": false,
     },
     "Elixir": {
-      "language_servers": ["elixir-ls", "!expert", "!next-ls", "!lexical", "..."]
+      "language_servers": ["elixir-ls", "!expert", "!next-ls", "!lexical", "..."],
     },
     "Elm": {
-      "tab_size": 4
+      "tab_size": 4,
     },
     "Erlang": {
-      "language_servers": ["erlang-ls", "!elp", "..."]
+      "language_servers": ["erlang-ls", "!elp", "..."],
     },
     "Git Commit": {
       "allow_rewrap": "anywhere",
       "soft_wrap": "editor_width",
-      "preferred_line_length": 72
+      "preferred_line_length": 72,
     },
     "Go": {
       "hard_tabs": true,
       "code_actions_on_format": {
-        "source.organizeImports": true
+        "source.organizeImports": true,
       },
-      "debuggers": ["Delve"]
+      "debuggers": ["Delve"],
     },
     "GraphQL": {
       "prettier": {
-        "allowed": true
-      }
+        "allowed": true,
+      },
     },
     "HEEX": {
-      "language_servers": ["elixir-ls", "!expert", "!next-ls", "!lexical", "..."]
+      "language_servers": ["elixir-ls", "!expert", "!next-ls", "!lexical", "..."],
     },
     "HTML": {
       "prettier": {
-        "allowed": true
-      }
+        "allowed": true,
+      },
     },
     "HTML+ERB": {
-      "language_servers": ["herb", "!ruby-lsp", "..."]
+      "language_servers": ["herb", "!ruby-lsp", "..."],
     },
     "Java": {
       "prettier": {
         "allowed": true,
-        "plugins": ["prettier-plugin-java"]
-      }
+        "plugins": ["prettier-plugin-java"],
+      },
     },
     "JavaScript": {
       "language_servers": ["!typescript-language-server", "vtsls", "..."],
       "prettier": {
-        "allowed": true
-      }
+        "allowed": true,
+      },
     },
     "JSON": {
       "prettier": {
-        "allowed": true
-      }
+        "allowed": true,
+      },
     },
     "JSONC": {
       "prettier": {
-        "allowed": true
-      }
+        "allowed": true,
+      },
     },
     "JS+ERB": {
-      "language_servers": ["!ruby-lsp", "..."]
+      "language_servers": ["!ruby-lsp", "..."],
     },
     "Kotlin": {
-      "language_servers": ["!kotlin-language-server", "kotlin-lsp", "..."]
+      "language_servers": ["!kotlin-language-server", "kotlin-lsp", "..."],
     },
     "LaTeX": {
       "formatter": "language_server",
       "language_servers": ["texlab", "..."],
       "prettier": {
         "allowed": true,
-        "plugins": ["prettier-plugin-latex"]
-      }
+        "plugins": ["prettier-plugin-latex"],
+      },
     },
     "Markdown": {
       "format_on_save": "off",
@@ -1903,135 +1903,132 @@
       "allow_rewrap": "anywhere",
       "soft_wrap": "editor_width",
       "prettier": {
-        "allowed": true
-      }
+        "allowed": true,
+      },
     },
     "PHP": {
       "language_servers": ["phpactor", "!intelephense", "!phptools", "..."],
       "prettier": {
         "allowed": true,
         "plugins": ["@prettier/plugin-php"],
-        "parser": "php"
-      }
+        "parser": "php",
+      },
     },
     "Plain Text": {
       "allow_rewrap": "anywhere",
-      "soft_wrap": "editor_width"
+      "soft_wrap": "editor_width",
     },
     "Python": {
       "code_actions_on_format": {
-        "source.organizeImports.ruff": true
+        "source.organizeImports.ruff": true,
       },
       "formatter": {
         "language_server": {
-          "name": "ruff"
-        }
+          "name": "ruff",
+        },
       },
       "debuggers": ["Debugpy"],
-      "language_servers": ["basedpyright", "ruff", "!ty", "!pyrefly", "!pyright", "!pylsp", "..."]
+      "language_servers": ["basedpyright", "ruff", "!ty", "!pyrefly", "!pyright", "!pylsp", "..."],
     },
     "Ruby": {
-      "language_servers": ["solargraph", "!ruby-lsp", "!rubocop", "!sorbet", "!steep", "..."]
+      "language_servers": ["solargraph", "!ruby-lsp", "!rubocop", "!sorbet", "!steep", "..."],
     },
     "Rust": {
-      "debuggers": ["CodeLLDB"]
+      "debuggers": ["CodeLLDB"],
     },
     "SCSS": {
       "prettier": {
-        "allowed": true
-      }
+        "allowed": true,
+      },
     },
     "Starlark": {
-      "language_servers": ["starpls", "!buck2-lsp", "..."]
+      "language_servers": ["starpls", "!buck2-lsp", "..."],
     },
     "Svelte": {
       "language_servers": ["svelte-language-server", "..."],
       "prettier": {
         "allowed": true,
-        "plugins": ["prettier-plugin-svelte"]
-      }
+        "plugins": ["prettier-plugin-svelte"],
+      },
     },
     "TSX": {
       "language_servers": ["!typescript-language-server", "vtsls", "..."],
       "prettier": {
-        "allowed": true
-      }
+        "allowed": true,
+      },
     },
     "Twig": {
       "prettier": {
-        "allowed": true
-      }
+        "allowed": true,
+      },
     },
     "TypeScript": {
       "language_servers": ["!typescript-language-server", "vtsls", "..."],
       "prettier": {
-        "allowed": true
-      }
+        "allowed": true,
+      },
     },
     "SystemVerilog": {
       "format_on_save": "off",
       "language_servers": ["!slang", "..."],
-      "use_on_type_format": false
+      "use_on_type_format": false,
     },
     "Vue.js": {
       "language_servers": ["vue-language-server", "vtsls", "..."],
       "prettier": {
-        "allowed": true
-      }
+        "allowed": true,
+      },
     },
     "XML": {
       "prettier": {
         "allowed": true,
-        "plugins": ["@prettier/plugin-xml"]
-      }
+        "plugins": ["@prettier/plugin-xml"],
+      },
     },
     "YAML": {
       "prettier": {
-        "allowed": true
-      }
+        "allowed": true,
+      },
     },
     "YAML+ERB": {
-      "language_servers": ["!ruby-lsp", "..."]
+      "language_servers": ["!ruby-lsp", "..."],
     },
     "Zig": {
-      "language_servers": ["zls", "..."]
-    }
+      "language_servers": ["zls", "..."],
+    },
   },
   // Different settings for specific language models.
   "language_models": {
-    "anthropic": {
-      "api_url": "https://api.anthropic.com"
-    },
     "bedrock": {},
     "google": {
-      "api_url": "https://generativelanguage.googleapis.com"
+      "api_url": "https://generativelanguage.googleapis.com",
     },
     "ollama": {
-      "api_url": "http://localhost:11434"
+      "api_url": "http://localhost:11434",
     },
     "openai": {
-      "api_url": "https://api.openai.com/v1"
+      "api_url": "https://api.openai.com/v1",
     },
     "openai_compatible": {},
     "open_router": {
-      "api_url": "https://openrouter.ai/api/v1"
+      "api_url": "https://openrouter.ai/api/v1",
     },
     "lmstudio": {
-      "api_url": "http://localhost:1234/api/v0"
+      "api_url": "http://localhost:1234/api/v0",
     },
     "deepseek": {
-      "api_url": "https://api.deepseek.com/v1"
+      "api_url": "https://api.deepseek.com/v1",
     },
     "mistral": {
-      "api_url": "https://api.mistral.ai/v1"
+      "api_url": "https://api.mistral.ai/v1",
     },
     "vercel": {
-      "api_url": "https://api.v0.dev/v1"
+      "api_url": "https://api.v0.dev/v1",
     },
     "x_ai": {
-      "api_url": "https://api.x.ai/v1"
+      "api_url": "https://api.x.ai/v1",
     },
-    "zed.dev": {}
+    "zed.dev": {},
   },
   "session": {
     // Whether or not to restore unsaved buffers on restart.
@@ -2040,7 +2037,7 @@
     // dirty files when closing the application.
     //
     // Default: true
-    "restore_unsaved_buffers": true
+    "restore_unsaved_buffers": true,
   },
   // Zed's Prettier integration settings.
   // Allows to enable/disable formatting with Prettier
@@ -2058,11 +2055,11 @@
     // "singleQuote": true
     // Forces Prettier integration to use a specific parser name when formatting files with the language
     // when set to a non-empty string.
-    "parser": ""
+    "parser": "",
   },
   // Settings for auto-closing of JSX tags.
   "jsx_tag_auto_close": {
-    "enabled": true
+    "enabled": true,
   },
   // LSP Specific settings.
   "lsp": {
@@ -2083,19 +2080,19 @@
     // Specify the DAP name as a key here.
     "CodeLLDB": {
       "env": {
-        "RUST_LOG": "info"
-      }
-    }
+        "RUST_LOG": "info",
+      },
+    },
   },
   // Common language server settings.
   "global_lsp_settings": {
     // Whether to show the LSP servers button in the status bar.
-    "button": true
+    "button": true,
   },
   // Jupyter settings
   "jupyter": {
     "enabled": true,
-    "kernel_selections": {}
+    "kernel_selections": {},
     // Specify the language name as the key and the kernel name as the value.
     // "kernel_selections": {
     //    "python": "conda-base"
@@ -2109,7 +2106,7 @@
     "max_columns": 128,
     // Maximum number of lines to keep in REPL's scrollback buffer.
     // Clamped with [4, 256] range.
-    "max_lines": 32
+    "max_lines": 32,
   },
   // Vim settings
   "vim": {
@@ -2123,7 +2120,7 @@
     // Specify the mode as the key and the shape as the value.
     // The mode can be one of the following: "normal", "replace", "insert", "visual".
     // The shape can be one of the following: "block", "bar", "underline", "hollow".
-    "cursor_shape": {}
+    "cursor_shape": {},
   },
   // The server to connect to. If the environment variable
   // ZED_SERVER_URL is set, it will override this setting.
@@ -2156,9 +2153,9 @@
   "windows": {
     "languages": {
       "PHP": {
-        "language_servers": ["intelephense", "!phpactor", "!phptools", "..."]
-      }
-    }
+        "language_servers": ["intelephense", "!phpactor", "!phptools", "..."],
+      },
+    },
   },
   // Whether to show full labels in line indicator or short ones
   //
@@ -2217,7 +2214,7 @@
     "dock": "bottom",
     "log_dap_communications": true,
     "format_dap_log_messages": true,
-    "button": true
+    "button": true,
   },
   // Configures any number of settings profiles that are temporarily applied on
   // top of your existing user settings when selected from
@@ -2244,5 +2241,5 @@
   // Useful for filtering out noisy logs or enabling more verbose logging.
   //
   // Example: {"log": {"client": "warn"}}
-  "log": {}
+  "log": {},
 }

crates/acp_thread/src/connection.rs

@@ -204,12 +204,21 @@ pub trait AgentModelSelector: 'static {
     }
 }
 
+/// Icon for a model in the model selector.
+#[derive(Debug, Clone, PartialEq, Eq)]
+pub enum AgentModelIcon {
+    /// A built-in icon from Zed's icon set.
+    Named(IconName),
+    /// Path to a custom SVG icon file.
+    Path(SharedString),
+}
+
 #[derive(Debug, Clone, PartialEq, Eq)]
 pub struct AgentModelInfo {
     pub id: acp::ModelId,
     pub name: SharedString,
     pub description: Option<SharedString>,
-    pub icon: Option<IconName>,
+    pub icon: Option<AgentModelIcon>,
 }
 
 impl From<acp::ModelInfo> for AgentModelInfo {

crates/agent/src/agent.rs

@@ -18,7 +18,7 @@ pub use templates::*;
 pub use thread::*;
 pub use tools::*;
 
-use acp_thread::{AcpThread, AgentModelSelector};
+use acp_thread::{AcpThread, AgentModelIcon, AgentModelSelector};
 use agent_client_protocol as acp;
 use anyhow::{Context as _, Result, anyhow};
 use chrono::{DateTime, Utc};
@@ -161,11 +161,16 @@ impl LanguageModels {
         model: &Arc<dyn LanguageModel>,
         provider: &Arc<dyn LanguageModelProvider>,
     ) -> acp_thread::AgentModelInfo {
+        let icon = if let Some(path) = provider.icon_path() {
+            Some(AgentModelIcon::Path(path))
+        } else {
+            Some(AgentModelIcon::Named(provider.icon()))
+        };
         acp_thread::AgentModelInfo {
             id: Self::model_id(model),
             name: model.name().0,
             description: None,
-            icon: Some(provider.icon()),
+            icon,
         }
     }
 
@@ -1356,7 +1361,7 @@ mod internal_tests {
                     id: acp::ModelId::new("fake/fake"),
                     name: "Fake".into(),
                     description: None,
-                    icon: Some(ui::IconName::ZedAssistant),
+                    icon: Some(AgentModelIcon::Named(ui::IconName::ZedAssistant)),
                 }]
             )])
         );

crates/agent_ui/src/acp/model_selector.rs

@@ -1,6 +1,6 @@
 use std::{cmp::Reverse, rc::Rc, sync::Arc};
 
-use acp_thread::{AgentModelInfo, AgentModelList, AgentModelSelector};
+use acp_thread::{AgentModelIcon, AgentModelInfo, AgentModelList, AgentModelSelector};
 use agent_servers::AgentServer;
 use anyhow::Result;
 use collections::IndexMap;
@@ -292,12 +292,18 @@ impl PickerDelegate for AcpModelPickerDelegate {
                                     h_flex()
                                         .w_full()
                                         .gap_1p5()
-                                        .when_some(model_info.icon, |this, icon| {
-                                            this.child(
-                                                Icon::new(icon)
+                                        .map(|this| match &model_info.icon {
+                                            Some(AgentModelIcon::Path(path)) => this.child(
+                                                Icon::from_path(path.clone())
                                                     .color(model_icon_color)
-                                                    .size(IconSize::Small)
-                                            )
+                                                    .size(IconSize::Small),
+                                            ),
+                                            Some(AgentModelIcon::Named(icon)) => this.child(
+                                                Icon::new(*icon)
+                                                    .color(model_icon_color)
+                                                    .size(IconSize::Small),
+                                            ),
+                                            None => this,
                                         })
                                         .child(Label::new(model_info.name.clone()).truncate()),
                                 )

crates/agent_ui/src/acp/model_selector_popover.rs

@@ -1,7 +1,7 @@
 use std::rc::Rc;
 use std::sync::Arc;
 
-use acp_thread::{AgentModelInfo, AgentModelSelector};
+use acp_thread::{AgentModelIcon, AgentModelInfo, AgentModelSelector};
 use agent_servers::AgentServer;
 use fs::Fs;
 use gpui::{Entity, FocusHandle};
@@ -64,7 +64,7 @@ impl Render for AcpModelSelectorPopover {
             .map(|model| model.name.clone())
             .unwrap_or_else(|| SharedString::from("Select a Model"));
 
-        let model_icon = model.as_ref().and_then(|model| model.icon);
+        let model_icon = model.as_ref().and_then(|model| model.icon.clone());
 
         let focus_handle = self.focus_handle.clone();
 
@@ -78,8 +78,13 @@ impl Render for AcpModelSelectorPopover {
             self.selector.clone(),
             ButtonLike::new("active-model")
                 .selected_style(ButtonStyle::Tinted(TintColor::Accent))
-                .when_some(model_icon, |this, icon| {
-                    this.child(Icon::new(icon).color(color).size(IconSize::XSmall))
+                .when_some(model_icon, |this, icon| match icon {
+                    AgentModelIcon::Path(path) => {
+                        this.child(Icon::from_path(path).color(color).size(IconSize::XSmall))
+                    }
+                    AgentModelIcon::Named(icon_name) => {
+                        this.child(Icon::new(icon_name).color(color).size(IconSize::XSmall))
+                    }
                 })
                 .child(
                     Label::new(model_name)

crates/agent_ui/src/agent_configuration.rs

@@ -260,11 +260,15 @@ impl AgentConfiguration {
                                 h_flex()
                                     .w_full()
                                     .gap_1p5()
-                                    .child(
+                                    .child(if let Some(icon_path) = provider.icon_path() {
+                                        Icon::from_external_svg(icon_path)
+                                            .size(IconSize::Small)
+                                            .color(Color::Muted)
+                                    } else {
                                         Icon::new(provider.icon())
                                             .size(IconSize::Small)
-                                            .color(Color::Muted),
-                                    )
+                                            .color(Color::Muted)
+                                    })
                                     .child(
                                         h_flex()
                                             .w_full()

crates/agent_ui/src/agent_model_selector.rs

@@ -73,7 +73,8 @@ impl Render for AgentModelSelector {
             .map(|model| model.model.name().0)
             .unwrap_or_else(|| SharedString::from("Select a Model"));
 
-        let provider_icon = model.as_ref().map(|model| model.provider.icon());
+        let provider_icon_path = model.as_ref().and_then(|model| model.provider.icon_path());
+        let provider_icon_name = model.as_ref().map(|model| model.provider.icon());
         let color = if self.menu_handle.is_deployed() {
             Color::Accent
         } else {
@@ -85,8 +86,17 @@ impl Render for AgentModelSelector {
         PickerPopoverMenu::new(
             self.selector.clone(),
             ButtonLike::new("active-model")
-                .when_some(provider_icon, |this, icon| {
-                    this.child(Icon::new(icon).color(color).size(IconSize::XSmall))
+                .when_some(provider_icon_path.clone(), |this, icon_path| {
+                    this.child(
+                        Icon::from_external_svg(icon_path)
+                            .color(color)
+                            .size(IconSize::XSmall),
+                    )
+                })
+                .when(provider_icon_path.is_none(), |this| {
+                    this.when_some(provider_icon_name, |this, icon| {
+                        this.child(Icon::new(icon).color(color).size(IconSize::XSmall))
+                    })
                 })
                 .selected_style(ButtonStyle::Tinted(TintColor::Accent))
                 .child(

crates/agent_ui/src/agent_ui.rs

@@ -346,9 +346,13 @@ fn init_language_model_settings(cx: &mut App) {
     cx.subscribe(
         &LanguageModelRegistry::global(cx),
         |_, event: &language_model::Event, cx| match event {
-            language_model::Event::ProviderStateChanged(_)
-            | language_model::Event::AddedProvider(_)
-            | language_model::Event::RemovedProvider(_) => {
+            language_model::Event::ProviderStateChanged(_) => {
+                update_active_language_model_from_settings(cx);
+            }
+            language_model::Event::AddedProvider(_) => {
+                update_active_language_model_from_settings(cx);
+            }
+            language_model::Event::RemovedProvider(_) => {
                 update_active_language_model_from_settings(cx);
             }
             _ => {}

crates/agent_ui/src/language_model_selector.rs

@@ -1,13 +1,12 @@
 use std::{cmp::Reverse, sync::Arc};
 
 use collections::IndexMap;
+use futures::{StreamExt, channel::mpsc};
 use fuzzy::{StringMatch, StringMatchCandidate, match_strings};
-use gpui::{
-    Action, AnyElement, App, BackgroundExecutor, DismissEvent, FocusHandle, Subscription, Task,
-};
+use gpui::{Action, AnyElement, App, BackgroundExecutor, DismissEvent, FocusHandle, Task};
 use language_model::{
-    AuthenticateError, ConfiguredModel, LanguageModel, LanguageModelProviderId,
-    LanguageModelRegistry,
+    AuthenticateError, ConfiguredModel, LanguageModel, LanguageModelProvider,
+    LanguageModelProviderId, LanguageModelRegistry,
 };
 use ordered_float::OrderedFloat;
 use picker::{Picker, PickerDelegate};
@@ -57,12 +56,12 @@ fn all_models(cx: &App) -> GroupedModels {
                 .into_iter()
                 .map(|model| ModelInfo {
                     model,
-                    icon: provider.icon(),
+                    icon: ProviderIcon::from_provider(provider.as_ref()),
                 })
         })
         .collect();
 
-    let all = providers
+    let all: Vec<ModelInfo> = providers
         .iter()
         .flat_map(|provider| {
             provider
@@ -70,7 +69,7 @@ fn all_models(cx: &App) -> GroupedModels {
                 .into_iter()
                 .map(|model| ModelInfo {
                     model,
-                    icon: provider.icon(),
+                    icon: ProviderIcon::from_provider(provider.as_ref()),
                 })
         })
         .collect();
@@ -78,10 +77,26 @@ fn all_models(cx: &App) -> GroupedModels {
     GroupedModels::new(all, recommended)
 }
 
+#[derive(Clone)]
+enum ProviderIcon {
+    Name(IconName),
+    Path(SharedString),
+}
+
+impl ProviderIcon {
+    fn from_provider(provider: &dyn LanguageModelProvider) -> Self {
+        if let Some(path) = provider.icon_path() {
+            Self::Path(path)
+        } else {
+            Self::Name(provider.icon())
+        }
+    }
+}
+
 #[derive(Clone)]
 struct ModelInfo {
     model: Arc<dyn LanguageModel>,
-    icon: IconName,
+    icon: ProviderIcon,
 }
 
 pub struct LanguageModelPickerDelegate {
@@ -91,7 +106,7 @@ pub struct LanguageModelPickerDelegate {
     filtered_entries: Vec<LanguageModelPickerEntry>,
     selected_index: usize,
     _authenticate_all_providers_task: Task<()>,
-    _subscriptions: Vec<Subscription>,
+    _refresh_models_task: Task<()>,
     popover_styles: bool,
     focus_handle: FocusHandle,
 }
@@ -116,24 +131,40 @@ impl LanguageModelPickerDelegate {
             filtered_entries: entries,
             get_active_model: Arc::new(get_active_model),
             _authenticate_all_providers_task: Self::authenticate_all_providers(cx),
-            _subscriptions: vec![cx.subscribe_in(
-                &LanguageModelRegistry::global(cx),
-                window,
-                |picker, _, event, window, cx| {
-                    match event {
-                        language_model::Event::ProviderStateChanged(_)
-                        | language_model::Event::AddedProvider(_)
-                        | language_model::Event::RemovedProvider(_) => {
-                            let query = picker.query(cx);
-                            picker.delegate.all_models = Arc::new(all_models(cx));
-                            // Update matches will automatically drop the previous task
-                            // if we get a provider event again
-                            picker.update_matches(query, window, cx)
-                        }
-                        _ => {}
+            _refresh_models_task: {
+                // Create a channel to signal when models need refreshing
+                let (refresh_tx, mut refresh_rx) = mpsc::unbounded::<()>();
+
+                // Subscribe to registry events and send refresh signals through the channel
+                let registry = LanguageModelRegistry::global(cx);
+                cx.subscribe(&registry, move |_picker, _, event, _cx| match event {
+                    language_model::Event::ProviderStateChanged(_) => {
+                        refresh_tx.unbounded_send(()).ok();
                     }
-                },
-            )],
+                    language_model::Event::AddedProvider(_) => {
+                        refresh_tx.unbounded_send(()).ok();
+                    }
+                    language_model::Event::RemovedProvider(_) => {
+                        refresh_tx.unbounded_send(()).ok();
+                    }
+                    _ => {}
+                })
+                .detach();
+
+                // Spawn a task that listens for refresh signals and updates the picker
+                cx.spawn_in(window, async move |this, cx| {
+                    while let Some(()) = refresh_rx.next().await {
+                        let result = this.update_in(cx, |picker, window, cx| {
+                            picker.delegate.all_models = Arc::new(all_models(cx));
+                            picker.refresh(window, cx);
+                        });
+                        if result.is_err() {
+                            // Picker was dropped, exit the loop
+                            break;
+                        }
+                    }
+                })
+            },
             popover_styles,
             focus_handle,
         }
@@ -504,11 +535,16 @@ impl PickerDelegate for LanguageModelPickerDelegate {
                             h_flex()
                                 .w_full()
                                 .gap_1p5()
-                                .child(
-                                    Icon::new(model_info.icon)
+                                .child(match &model_info.icon {
+                                    ProviderIcon::Name(icon_name) => Icon::new(*icon_name)
                                         .color(model_icon_color)
                                         .size(IconSize::Small),
-                                )
+                                    ProviderIcon::Path(icon_path) => {
+                                        Icon::from_external_svg(icon_path.clone())
+                                            .color(model_icon_color)
+                                            .size(IconSize::Small)
+                                    }
+                                })
                                 .child(Label::new(model_info.model.name().0).truncate()),
                         )
                         .end_slot(div().pr_3().when(is_selected, |this| {
@@ -657,7 +693,7 @@ mod tests {
             .into_iter()
             .map(|(provider, name)| ModelInfo {
                 model: Arc::new(TestLanguageModel::new(name, provider)),
-                icon: IconName::Ai,
+                icon: ProviderIcon::Name(IconName::Ai),
             })
             .collect()
     }

crates/agent_ui/src/text_thread_editor.rs

@@ -2097,7 +2097,8 @@ impl TextThreadEditor {
             .default_model()
             .map(|default| default.provider);
 
-        let provider_icon = match active_provider {
+        let provider_icon_path = active_provider.as_ref().and_then(|p| p.icon_path());
+        let provider_icon_name = match &active_provider {
             Some(provider) => provider.icon(),
             None => IconName::Ai,
         };
@@ -2109,6 +2110,16 @@ impl TextThreadEditor {
             (Color::Muted, IconName::ChevronDown)
         };
 
+        let provider_icon_element = if let Some(icon_path) = provider_icon_path {
+            Icon::from_external_svg(icon_path)
+                .color(color)
+                .size(IconSize::XSmall)
+        } else {
+            Icon::new(provider_icon_name)
+                .color(color)
+                .size(IconSize::XSmall)
+        };
+
         PickerPopoverMenu::new(
             self.language_model_selector.clone(),
             ButtonLike::new("active-model")
@@ -2116,7 +2127,7 @@ impl TextThreadEditor {
                 .child(
                     h_flex()
                         .gap_0p5()
-                        .child(Icon::new(provider_icon).color(color).size(IconSize::XSmall))
+                        .child(provider_icon_element)
                         .child(
                             Label::new(model_name)
                                 .color(color)

crates/ai_onboarding/src/agent_api_keys_onboarding.rs

@@ -1,9 +1,25 @@
 use gpui::{Action, IntoElement, ParentElement, RenderOnce, point};
-use language_model::{LanguageModelRegistry, ZED_CLOUD_PROVIDER_ID};
+use language_model::{LanguageModelProvider, LanguageModelRegistry, ZED_CLOUD_PROVIDER_ID};
 use ui::{Divider, List, ListBulletItem, prelude::*};
 
+#[derive(Clone)]
+enum ProviderIcon {
+    Name(IconName),
+    Path(SharedString),
+}
+
+impl ProviderIcon {
+    fn from_provider(provider: &dyn LanguageModelProvider) -> Self {
+        if let Some(path) = provider.icon_path() {
+            Self::Path(path)
+        } else {
+            Self::Name(provider.icon())
+        }
+    }
+}
+
 pub struct ApiKeysWithProviders {
-    configured_providers: Vec<(IconName, SharedString)>,
+    configured_providers: Vec<(ProviderIcon, SharedString)>,
 }
 
 impl ApiKeysWithProviders {
@@ -26,14 +42,19 @@ impl ApiKeysWithProviders {
         }
     }
 
-    fn compute_configured_providers(cx: &App) -> Vec<(IconName, SharedString)> {
+    fn compute_configured_providers(cx: &App) -> Vec<(ProviderIcon, SharedString)> {
         LanguageModelRegistry::read_global(cx)
             .providers()
             .iter()
             .filter(|provider| {
                 provider.is_authenticated(cx) && provider.id() != ZED_CLOUD_PROVIDER_ID
             })
-            .map(|provider| (provider.icon(), provider.name().0))
+            .map(|provider| {
+                (
+                    ProviderIcon::from_provider(provider.as_ref()),
+                    provider.name().0,
+                )
+            })
             .collect()
     }
 }
@@ -47,7 +68,14 @@ impl Render for ApiKeysWithProviders {
                 .map(|(icon, name)| {
                     h_flex()
                         .gap_1p5()
-                        .child(Icon::new(icon).size(IconSize::XSmall).color(Color::Muted))
+                        .child(match icon {
+                            ProviderIcon::Name(icon_name) => Icon::new(icon_name)
+                                .size(IconSize::XSmall)
+                                .color(Color::Muted),
+                            ProviderIcon::Path(icon_path) => Icon::from_external_svg(icon_path)
+                                .size(IconSize::XSmall)
+                                .color(Color::Muted),
+                        })
                         .child(Label::new(name))
                 });
         div()

crates/ai_onboarding/src/agent_panel_onboarding_content.rs

@@ -11,7 +11,7 @@ use crate::{AgentPanelOnboardingCard, ApiKeysWithoutProviders, ZedAiOnboarding};
 pub struct AgentPanelOnboarding {
     user_store: Entity<UserStore>,
     client: Arc<Client>,
-    configured_providers: Vec<(IconName, SharedString)>,
+    has_configured_providers: bool,
     continue_with_zed_ai: Arc<dyn Fn(&mut Window, &mut App)>,
 }
 
@@ -28,7 +28,7 @@ impl AgentPanelOnboarding {
                 language_model::Event::ProviderStateChanged(_)
                 | language_model::Event::AddedProvider(_)
                 | language_model::Event::RemovedProvider(_) => {
-                    this.configured_providers = Self::compute_available_providers(cx)
+                    this.has_configured_providers = Self::has_configured_providers(cx)
                 }
                 _ => {}
             },
@@ -38,20 +38,16 @@ impl AgentPanelOnboarding {
         Self {
             user_store,
             client,
-            configured_providers: Self::compute_available_providers(cx),
+            has_configured_providers: Self::has_configured_providers(cx),
             continue_with_zed_ai: Arc::new(continue_with_zed_ai),
         }
     }
 
-    fn compute_available_providers(cx: &App) -> Vec<(IconName, SharedString)> {
+    fn has_configured_providers(cx: &App) -> bool {
         LanguageModelRegistry::read_global(cx)
             .providers()
             .iter()
-            .filter(|provider| {
-                provider.is_authenticated(cx) && provider.id() != ZED_CLOUD_PROVIDER_ID
-            })
-            .map(|provider| (provider.icon(), provider.name().0))
-            .collect()
+            .any(|provider| provider.is_authenticated(cx) && provider.id() != ZED_CLOUD_PROVIDER_ID)
     }
 }
 
@@ -81,7 +77,7 @@ impl Render for AgentPanelOnboarding {
                 }),
             )
             .map(|this| {
-                if enrolled_in_trial || is_pro_user || !self.configured_providers.is_empty() {
+                if enrolled_in_trial || is_pro_user || self.has_configured_providers {
                     this
                 } else {
                     this.child(ApiKeysWithoutProviders::new())

crates/anthropic/src/anthropic.rs

@@ -8,7 +8,7 @@ use futures::{AsyncBufReadExt, AsyncReadExt, StreamExt, io::BufReader, stream::B
 use http_client::http::{self, HeaderMap, HeaderValue};
 use http_client::{AsyncBody, HttpClient, Method, Request as HttpRequest, StatusCode};
 use serde::{Deserialize, Serialize};
-pub use settings::{AnthropicAvailableModel as AvailableModel, ModelMode};
+pub use settings::ModelMode;
 use strum::{EnumIter, EnumString};
 use thiserror::Error;
 

crates/extension/src/extension_host_proxy.rs

@@ -29,6 +29,7 @@ pub struct ExtensionHostProxy {
     slash_command_proxy: RwLock<Option<Arc<dyn ExtensionSlashCommandProxy>>>,
     context_server_proxy: RwLock<Option<Arc<dyn ExtensionContextServerProxy>>>,
     debug_adapter_provider_proxy: RwLock<Option<Arc<dyn ExtensionDebugAdapterProviderProxy>>>,
+    language_model_provider_proxy: RwLock<Option<Arc<dyn ExtensionLanguageModelProviderProxy>>>,
 }
 
 impl ExtensionHostProxy {
@@ -54,6 +55,7 @@ impl ExtensionHostProxy {
             slash_command_proxy: RwLock::default(),
             context_server_proxy: RwLock::default(),
             debug_adapter_provider_proxy: RwLock::default(),
+            language_model_provider_proxy: RwLock::default(),
         }
     }
 
@@ -90,6 +92,15 @@ impl ExtensionHostProxy {
             .write()
             .replace(Arc::new(proxy));
     }
+
+    pub fn register_language_model_provider_proxy(
+        &self,
+        proxy: impl ExtensionLanguageModelProviderProxy,
+    ) {
+        self.language_model_provider_proxy
+            .write()
+            .replace(Arc::new(proxy));
+    }
 }
 
 pub trait ExtensionThemeProxy: Send + Sync + 'static {
@@ -375,6 +386,49 @@ pub trait ExtensionContextServerProxy: Send + Sync + 'static {
     fn unregister_context_server(&self, server_id: Arc<str>, cx: &mut App);
 }
 
+/// A function that registers a language model provider with the registry.
+/// This allows extension_host to create the provider (which requires WasmExtension)
+/// and pass a registration closure to the language_models crate.
+pub type LanguageModelProviderRegistration = Box<dyn FnOnce(&mut App) + Send + Sync + 'static>;
+
+pub trait ExtensionLanguageModelProviderProxy: Send + Sync + 'static {
+    /// Register an LLM provider from an extension.
+    /// The `register_fn` closure will be called with the App context and should
+    /// register the provider with the LanguageModelRegistry.
+    fn register_language_model_provider(
+        &self,
+        provider_id: Arc<str>,
+        register_fn: LanguageModelProviderRegistration,
+        cx: &mut App,
+    );
+
+    /// Unregister an LLM provider when an extension is unloaded.
+    fn unregister_language_model_provider(&self, provider_id: Arc<str>, cx: &mut App);
+}
+
+impl ExtensionLanguageModelProviderProxy for ExtensionHostProxy {
+    fn register_language_model_provider(
+        &self,
+        provider_id: Arc<str>,
+        register_fn: LanguageModelProviderRegistration,
+        cx: &mut App,
+    ) {
+        let Some(proxy) = self.language_model_provider_proxy.read().clone() else {
+            return;
+        };
+
+        proxy.register_language_model_provider(provider_id, register_fn, cx)
+    }
+
+    fn unregister_language_model_provider(&self, provider_id: Arc<str>, cx: &mut App) {
+        let Some(proxy) = self.language_model_provider_proxy.read().clone() else {
+            return;
+        };
+
+        proxy.unregister_language_model_provider(provider_id, cx)
+    }
+}
+
 impl ExtensionContextServerProxy for ExtensionHostProxy {
     fn register_context_server(
         &self,

crates/extension/src/extension_manifest.rs

@@ -93,6 +93,8 @@ pub struct ExtensionManifest {
     pub debug_adapters: BTreeMap<Arc<str>, DebugAdapterManifestEntry>,
     #[serde(default, skip_serializing_if = "BTreeMap::is_empty")]
     pub debug_locators: BTreeMap<Arc<str>, DebugLocatorManifestEntry>,
+    #[serde(default, skip_serializing_if = "BTreeMap::is_empty")]
+    pub language_model_providers: BTreeMap<Arc<str>, LanguageModelProviderManifestEntry>,
 }
 
 impl ExtensionManifest {
@@ -288,6 +290,57 @@ pub struct DebugAdapterManifestEntry {
 #[derive(Clone, PartialEq, Eq, Debug, Deserialize, Serialize)]
 pub struct DebugLocatorManifestEntry {}
 
+/// Manifest entry for a language model provider.
+#[derive(Clone, PartialEq, Eq, Debug, Deserialize, Serialize)]
+pub struct LanguageModelProviderManifestEntry {
+    /// Display name for the provider.
+    pub name: String,
+    /// Path to an SVG icon file relative to the extension root (e.g., "icons/provider.svg").
+    #[serde(default)]
+    pub icon: Option<String>,
+    /// Default models to show even before API connection.
+    #[serde(default)]
+    pub models: Vec<LanguageModelManifestEntry>,
+    /// Authentication configuration.
+    #[serde(default)]
+    pub auth: Option<LanguageModelAuthConfig>,
+}
+
+/// Manifest entry for a language model.
+#[derive(Clone, PartialEq, Eq, Debug, Deserialize, Serialize)]
+pub struct LanguageModelManifestEntry {
+    /// Unique identifier for the model.
+    pub id: String,
+    /// Display name for the model.
+    pub name: String,
+    /// Maximum input token count.
+    #[serde(default)]
+    pub max_token_count: u64,
+    /// Maximum output tokens (optional).
+    #[serde(default)]
+    pub max_output_tokens: Option<u64>,
+    /// Whether the model supports image inputs.
+    #[serde(default)]
+    pub supports_images: bool,
+    /// Whether the model supports tool/function calling.
+    #[serde(default)]
+    pub supports_tools: bool,
+    /// Whether the model supports extended thinking/reasoning.
+    #[serde(default)]
+    pub supports_thinking: bool,
+}
+
+/// Authentication configuration for a language model provider.
+#[derive(Clone, PartialEq, Eq, Debug, Deserialize, Serialize)]
+pub struct LanguageModelAuthConfig {
+    /// Environment variable name for the API key.
+    #[serde(default)]
+    pub env_var: Option<String>,
+    /// Human-readable name for the credential shown in the UI input field (e.g., "API Key", "Access Token").
+    #[serde(default)]
+    pub credential_label: Option<String>,
+}
+
 impl ExtensionManifest {
     pub async fn load(fs: Arc<dyn Fs>, extension_dir: &Path) -> Result<Self> {
         let extension_name = extension_dir
@@ -358,6 +411,7 @@ fn manifest_from_old_manifest(
         capabilities: Vec::new(),
         debug_adapters: Default::default(),
         debug_locators: Default::default(),
+        language_model_providers: Default::default(),
     }
 }
 
@@ -391,6 +445,7 @@ mod tests {
             capabilities: vec![],
             debug_adapters: Default::default(),
             debug_locators: Default::default(),
+            language_model_providers: BTreeMap::default(),
         }
     }
 

crates/extension_api/src/extension_api.rs

@@ -29,6 +29,27 @@ pub use wit::{
         GithubRelease, GithubReleaseAsset, GithubReleaseOptions, github_release_by_tag_name,
         latest_github_release,
     },
+    zed::extension::llm_provider::{
+        CacheConfiguration as LlmCacheConfiguration, CompletionEvent as LlmCompletionEvent,
+        CompletionRequest as LlmCompletionRequest, CredentialType as LlmCredentialType,
+        ImageData as LlmImageData, MessageContent as LlmMessageContent,
+        MessageRole as LlmMessageRole, ModelCapabilities as LlmModelCapabilities,
+        ModelInfo as LlmModelInfo, OauthHttpRequest as LlmOauthHttpRequest,
+        OauthHttpResponse as LlmOauthHttpResponse, OauthWebAuthConfig as LlmOauthWebAuthConfig,
+        OauthWebAuthResult as LlmOauthWebAuthResult, ProviderInfo as LlmProviderInfo,
+        RequestMessage as LlmRequestMessage, StopReason as LlmStopReason,
+        ThinkingContent as LlmThinkingContent, TokenUsage as LlmTokenUsage,
+        ToolChoice as LlmToolChoice, ToolDefinition as LlmToolDefinition,
+        ToolInputFormat as LlmToolInputFormat, ToolResult as LlmToolResult,
+        ToolResultContent as LlmToolResultContent, ToolUse as LlmToolUse,
+        ToolUseJsonParseError as LlmToolUseJsonParseError,
+        delete_credential as llm_delete_credential, get_credential as llm_get_credential,
+        get_env_var as llm_get_env_var, oauth_open_browser as llm_oauth_open_browser,
+        oauth_start_web_auth as llm_oauth_start_web_auth,
+        request_credential as llm_request_credential,
+        send_oauth_http_request as llm_oauth_http_request,
+        store_credential as llm_store_credential,
+    },
     zed::extension::nodejs::{
         node_binary_path, npm_install_package, npm_package_installed_version,
         npm_package_latest_version,
@@ -259,6 +280,81 @@ pub trait Extension: Send + Sync {
     ) -> Result<DebugRequest, String> {
         Err("`run_dap_locator` not implemented".to_string())
     }
+
+    /// Returns information about language model providers offered by this extension.
+    fn llm_providers(&self) -> Vec<LlmProviderInfo> {
+        Vec::new()
+    }
+
+    /// Returns the models available for a provider.
+    fn llm_provider_models(&self, _provider_id: &str) -> Result<Vec<LlmModelInfo>, String> {
+        Ok(Vec::new())
+    }
+
+    /// Returns markdown content to display in the provider's settings UI.
+    /// This can include setup instructions, links to documentation, etc.
+    fn llm_provider_settings_markdown(&self, _provider_id: &str) -> Option<String> {
+        None
+    }
+
+    /// Check if the provider is authenticated.
+    fn llm_provider_is_authenticated(&self, _provider_id: &str) -> bool {
+        false
+    }
+
+    /// Attempt to authenticate the provider.
+    fn llm_provider_authenticate(&mut self, _provider_id: &str) -> Result<(), String> {
+        Err("`llm_provider_authenticate` not implemented".to_string())
+    }
+
+    /// Reset credentials for the provider.
+    fn llm_provider_reset_credentials(&mut self, _provider_id: &str) -> Result<(), String> {
+        Err("`llm_provider_reset_credentials` not implemented".to_string())
+    }
+
+    /// Count tokens for a request.
+    fn llm_count_tokens(
+        &self,
+        _provider_id: &str,
+        _model_id: &str,
+        _request: &LlmCompletionRequest,
+    ) -> Result<u64, String> {
+        Err("`llm_count_tokens` not implemented".to_string())
+    }
+
+    /// Start streaming a completion from the model.
+    /// Returns a stream ID that can be used with `llm_stream_completion_next` and `llm_stream_completion_close`.
+    fn llm_stream_completion_start(
+        &mut self,
+        _provider_id: &str,
+        _model_id: &str,
+        _request: &LlmCompletionRequest,
+    ) -> Result<String, String> {
+        Err("`llm_stream_completion_start` not implemented".to_string())
+    }
+
+    /// Get the next event from a completion stream.
+    /// Returns `Ok(None)` when the stream is complete.
+    fn llm_stream_completion_next(
+        &mut self,
+        _stream_id: &str,
+    ) -> Result<Option<LlmCompletionEvent>, String> {
+        Err("`llm_stream_completion_next` not implemented".to_string())
+    }
+
+    /// Close a completion stream and release its resources.
+    fn llm_stream_completion_close(&mut self, _stream_id: &str) {
+        // Default implementation does nothing
+    }
+
+    /// Get cache configuration for a model (if prompt caching is supported).
+    fn llm_cache_configuration(
+        &self,
+        _provider_id: &str,
+        _model_id: &str,
+    ) -> Option<LlmCacheConfiguration> {
+        None
+    }
 }
 
 /// Registers the provided type as a Zed extension.
@@ -518,6 +614,61 @@ impl wit::Guest for Component {
     ) -> Result<DebugRequest, String> {
         extension().run_dap_locator(locator_name, build_task)
     }
+
+    fn llm_providers() -> Vec<LlmProviderInfo> {
+        extension().llm_providers()
+    }
+
+    fn llm_provider_models(provider_id: String) -> Result<Vec<LlmModelInfo>, String> {
+        extension().llm_provider_models(&provider_id)
+    }
+
+    fn llm_provider_settings_markdown(provider_id: String) -> Option<String> {
+        extension().llm_provider_settings_markdown(&provider_id)
+    }
+
+    fn llm_provider_is_authenticated(provider_id: String) -> bool {
+        extension().llm_provider_is_authenticated(&provider_id)
+    }
+
+    fn llm_provider_authenticate(provider_id: String) -> Result<(), String> {
+        extension().llm_provider_authenticate(&provider_id)
+    }
+
+    fn llm_provider_reset_credentials(provider_id: String) -> Result<(), String> {
+        extension().llm_provider_reset_credentials(&provider_id)
+    }
+
+    fn llm_count_tokens(
+        provider_id: String,
+        model_id: String,
+        request: LlmCompletionRequest,
+    ) -> Result<u64, String> {
+        extension().llm_count_tokens(&provider_id, &model_id, &request)
+    }
+
+    fn llm_stream_completion_start(
+        provider_id: String,
+        model_id: String,
+        request: LlmCompletionRequest,
+    ) -> Result<String, String> {
+        extension().llm_stream_completion_start(&provider_id, &model_id, &request)
+    }
+
+    fn llm_stream_completion_next(stream_id: String) -> Result<Option<LlmCompletionEvent>, String> {
+        extension().llm_stream_completion_next(&stream_id)
+    }
+
+    fn llm_stream_completion_close(stream_id: String) {
+        extension().llm_stream_completion_close(&stream_id)
+    }
+
+    fn llm_cache_configuration(
+        provider_id: String,
+        model_id: String,
+    ) -> Option<LlmCacheConfiguration> {
+        extension().llm_cache_configuration(&provider_id, &model_id)
+    }
 }
 
 /// The ID of a language server.

crates/extension_api/wit/since_v0.8.0/extension.wit

@@ -8,6 +8,7 @@ world extension {
     import platform;
     import process;
     import nodejs;
+    import llm-provider;
 
     use common.{env-vars, range};
     use context-server.{context-server-configuration};
@@ -15,6 +16,10 @@ world extension {
     use lsp.{completion, symbol};
     use process.{command};
     use slash-command.{slash-command, slash-command-argument-completion, slash-command-output};
+    use llm-provider.{
+        provider-info, model-info, completion-request,
+        credential-type, cache-configuration, completion-event, token-usage
+    };
 
     /// Initializes the extension.
     export init-extension: func();
@@ -164,4 +169,56 @@ world extension {
     export dap-config-to-scenario: func(config: debug-config) -> result<debug-scenario, string>;
     export dap-locator-create-scenario: func(locator-name: string, build-config-template: build-task-template, resolved-label: string, debug-adapter-name: string) -> option<debug-scenario>;
     export run-dap-locator: func(locator-name: string, config: resolved-task) -> result<debug-request, string>;
+
+    /// Returns information about language model providers offered by this extension.
+    export llm-providers: func() -> list<provider-info>;
+
+    /// Returns the models available for a provider.
+    export llm-provider-models: func(provider-id: string) -> result<list<model-info>, string>;
+
+    /// Returns markdown content to display in the provider's settings UI.
+    /// This can include setup instructions, links to documentation, etc.
+    export llm-provider-settings-markdown: func(provider-id: string) -> option<string>;
+
+    /// Check if the provider is authenticated.
+    export llm-provider-is-authenticated: func(provider-id: string) -> bool;
+
+    /// Attempt to authenticate the provider.
+    export llm-provider-authenticate: func(provider-id: string) -> result<_, string>;
+
+    /// Reset credentials for the provider.
+    export llm-provider-reset-credentials: func(provider-id: string) -> result<_, string>;
+
+    /// Count tokens for a request.
+    export llm-count-tokens: func(
+        provider-id: string,
+        model-id: string,
+        request: completion-request
+    ) -> result<u64, string>;
+
+    /// Start streaming a completion from the model.
+    /// Returns a stream ID that can be used with llm-stream-next and llm-stream-close.
+    export llm-stream-completion-start: func(
+        provider-id: string,
+        model-id: string,
+        request: completion-request
+    ) -> result<string, string>;
+
+    /// Get the next event from a completion stream.
+    /// Returns None when the stream is complete.
+    export llm-stream-completion-next: func(
+        stream-id: string
+    ) -> result<option<completion-event>, string>;
+
+    /// Close a completion stream and release its resources.
+    export llm-stream-completion-close: func(
+        stream-id: string
+    );
+
+    /// Get cache configuration for a model (if prompt caching is supported).
+    export llm-cache-configuration: func(
+        provider-id: string,
+        model-id: string
+    ) -> option<cache-configuration>;
+
 }

crates/extension_api/wit/since_v0.8.0/llm-provider.wit

@@ -0,0 +1,345 @@
+interface llm-provider {
+    /// Information about a language model provider.
+    record provider-info {
+        /// Unique identifier for the provider (e.g., "my-extension.my-provider").
+        id: string,
+        /// Display name for the provider.
+        name: string,
+        /// Path to an SVG icon file relative to the extension root (e.g., "icons/provider.svg").
+        icon: option<string>,
+    }
+
+    /// Capabilities of a language model.
+    record model-capabilities {
+        /// Whether the model supports image inputs.
+        supports-images: bool,
+        /// Whether the model supports tool/function calling.
+        supports-tools: bool,
+        /// Whether the model supports the "auto" tool choice.
+        supports-tool-choice-auto: bool,
+        /// Whether the model supports the "any" tool choice.
+        supports-tool-choice-any: bool,
+        /// Whether the model supports the "none" tool choice.
+        supports-tool-choice-none: bool,
+        /// Whether the model supports extended thinking/reasoning.
+        supports-thinking: bool,
+        /// The format for tool input schemas.
+        tool-input-format: tool-input-format,
+    }
+
+    /// Format for tool input schemas.
+    enum tool-input-format {
+        /// Standard JSON Schema format.
+        json-schema,
+        /// Simplified schema format for certain providers.
+        simplified,
+    }
+
+    /// Information about a specific model.
+    record model-info {
+        /// Unique identifier for the model.
+        id: string,
+        /// Display name for the model.
+        name: string,
+        /// Maximum input token count.
+        max-token-count: u64,
+        /// Maximum output tokens (optional).
+        max-output-tokens: option<u64>,
+        /// Model capabilities.
+        capabilities: model-capabilities,
+        /// Whether this is the default model for the provider.
+        is-default: bool,
+        /// Whether this is the default fast model.
+        is-default-fast: bool,
+    }
+
+    /// The role of a message participant.
+    enum message-role {
+        /// User message.
+        user,
+        /// Assistant message.
+        assistant,
+        /// System message.
+        system,
+    }
+
+    /// A message in a completion request.
+    record request-message {
+        /// The role of the message sender.
+        role: message-role,
+        /// The content of the message.
+        content: list<message-content>,
+        /// Whether to cache this message for prompt caching.
+        cache: bool,
+    }
+
+    /// Content within a message.
+    variant message-content {
+        /// Plain text content.
+        text(string),
+        /// Image content.
+        image(image-data),
+        /// A tool use request from the assistant.
+        tool-use(tool-use),
+        /// A tool result from the user.
+        tool-result(tool-result),
+        /// Thinking/reasoning content.
+        thinking(thinking-content),
+        /// Redacted/encrypted thinking content.
+        redacted-thinking(string),
+    }
+
+    /// Image data for vision models.
+    record image-data {
+        /// Base64-encoded image data.
+        source: string,
+        /// Image width in pixels (optional).
+        width: option<u32>,
+        /// Image height in pixels (optional).
+        height: option<u32>,
+    }
+
+    /// A tool use request from the model.
+    record tool-use {
+        /// Unique identifier for this tool use.
+        id: string,
+        /// The name of the tool being used.
+        name: string,
+        /// JSON string of the tool input arguments.
+        input: string,
+        /// Thought signature for providers that support it (e.g., Anthropic).
+        thought-signature: option<string>,
+    }
+
+    /// A tool result to send back to the model.
+    record tool-result {
+        /// The ID of the tool use this is a result for.
+        tool-use-id: string,
+        /// The name of the tool.
+        tool-name: string,
+        /// Whether this result represents an error.
+        is-error: bool,
+        /// The content of the result.
+        content: tool-result-content,
+    }
+
+    /// Content of a tool result.
+    variant tool-result-content {
+        /// Text result.
+        text(string),
+        /// Image result.
+        image(image-data),
+    }
+
+    /// Thinking/reasoning content from models that support extended thinking.
+    record thinking-content {
+        /// The thinking text.
+        text: string,
+        /// Signature for the thinking block (provider-specific).
+        signature: option<string>,
+    }
+
+    /// A tool definition for function calling.
+    record tool-definition {
+        /// The name of the tool.
+        name: string,
+        /// Description of what the tool does.
+        description: string,
+        /// JSON Schema for input parameters.
+        input-schema: string,
+    }
+
+    /// Tool choice preference for the model.
+    enum tool-choice {
+        /// Let the model decide whether to use tools.
+        auto,
+        /// Force the model to use at least one tool.
+        any,
+        /// Prevent the model from using tools.
+        none,
+    }
+
+    /// A completion request to send to the model.
+    record completion-request {
+        /// The messages in the conversation.
+        messages: list<request-message>,
+        /// Available tools for the model to use.
+        tools: list<tool-definition>,
+        /// Tool choice preference.
+        tool-choice: option<tool-choice>,
+        /// Stop sequences to end generation.
+        stop-sequences: list<string>,
+        /// Temperature for sampling (0.0-1.0).
+        temperature: option<f32>,
+        /// Whether thinking/reasoning is allowed.
+        thinking-allowed: bool,
+        /// Maximum tokens to generate.
+        max-tokens: option<u64>,
+    }
+
+    /// Events emitted during completion streaming.
+    variant completion-event {
+        /// Completion has started.
+        started,
+        /// Text content chunk.
+        text(string),
+        /// Thinking/reasoning content chunk.
+        thinking(thinking-content),
+        /// Redacted thinking (encrypted) chunk.
+        redacted-thinking(string),
+        /// Tool use request from the model.
+        tool-use(tool-use),
+        /// JSON parse error when parsing tool input.
+        tool-use-json-parse-error(tool-use-json-parse-error),
+        /// Completion stopped.
+        stop(stop-reason),
+        /// Token usage update.
+        usage(token-usage),
+        /// Reasoning details (provider-specific JSON).
+        reasoning-details(string),
+    }
+
+    /// Error information when tool use JSON parsing fails.
+    record tool-use-json-parse-error {
+        /// The tool use ID.
+        id: string,
+        /// The tool name.
+        tool-name: string,
+        /// The raw input that failed to parse.
+        raw-input: string,
+        /// The parse error message.
+        error: string,
+    }
+
+    /// Reason the completion stopped.
+    enum stop-reason {
+        /// The model finished generating.
+        end-turn,
+        /// Maximum tokens reached.
+        max-tokens,
+        /// The model wants to use a tool.
+        tool-use,
+        /// The model refused to respond.
+        refusal,
+    }
+
+    /// Token usage statistics.
+    record token-usage {
+        /// Number of input tokens used.
+        input-tokens: u64,
+        /// Number of output tokens generated.
+        output-tokens: u64,
+        /// Tokens used for cache creation (if supported).
+        cache-creation-input-tokens: option<u64>,
+        /// Tokens read from cache (if supported).
+        cache-read-input-tokens: option<u64>,
+    }
+
+    /// Credential types that can be requested.
+    enum credential-type {
+        /// An API key.
+        api-key,
+        /// An OAuth token.
+        oauth-token,
+    }
+
+    /// Cache configuration for prompt caching.
+    record cache-configuration {
+        /// Maximum number of cache anchors.
+        max-cache-anchors: u32,
+        /// Whether caching should be applied to tool definitions.
+        should-cache-tool-definitions: bool,
+        /// Minimum token count for a message to be cached.
+        min-total-token-count: u64,
+    }
+
+    /// Configuration for starting an OAuth web authentication flow.
+    record oauth-web-auth-config {
+        /// The URL to open in the user's browser to start authentication.
+        /// This should include client_id, redirect_uri, scope, state, etc.
+        auth-url: string,
+        /// The path to listen on for the OAuth callback (e.g., "/callback").
+        /// A localhost server will be started to receive the redirect.
+        callback-path: string,
+        /// Timeout in seconds to wait for the callback (default: 300 = 5 minutes).
+        timeout-secs: option<u32>,
+    }
+
+    /// Result of an OAuth web authentication flow.
+    record oauth-web-auth-result {
+        /// The full callback URL that was received, including query parameters.
+        /// The extension is responsible for parsing the code, state, etc.
+        callback-url: string,
+        /// The port that was used for the localhost callback server.
+        port: u32,
+    }
+
+    /// A generic HTTP request for OAuth token exchange.
+    record oauth-http-request {
+        /// The URL to request.
+        url: string,
+        /// HTTP method (e.g., "POST", "GET").
+        method: string,
+        /// Request headers as key-value pairs.
+        headers: list<tuple<string, string>>,
+        /// Request body as a string (for form-encoded or JSON bodies).
+        body: string,
+    }
+
+    /// Response from an OAuth HTTP request.
+    record oauth-http-response {
+        /// HTTP status code.
+        status: u16,
+        /// Response headers as key-value pairs.
+        headers: list<tuple<string, string>>,
+        /// Response body as a string.
+        body: string,
+    }
+
+    /// Request a credential from the user.
+    /// Returns true if the credential was provided, false if the user cancelled.
+    request-credential: func(
+        provider-id: string,
+        credential-type: credential-type,
+        label: string,
+        placeholder: string
+    ) -> result<bool, string>;
+
+    /// Get a stored credential for this provider.
+    get-credential: func(provider-id: string) -> option<string>;
+
+    /// Store a credential for this provider.
+    store-credential: func(provider-id: string, value: string) -> result<_, string>;
+
+    /// Delete a stored credential for this provider.
+    delete-credential: func(provider-id: string) -> result<_, string>;
+
+    /// Read an environment variable.
+    get-env-var: func(name: string) -> option<string>;
+
+    /// Start an OAuth web authentication flow.
+    ///
+    /// This will:
+    /// 1. Start a localhost server to receive the OAuth callback
+    /// 2. Open the auth URL in the user's default browser
+    /// 3. Wait for the callback (up to the timeout)
+    /// 4. Return the callback URL with query parameters
+    ///
+    /// The extension is responsible for:
+    /// - Constructing the auth URL with client_id, redirect_uri, scope, state, etc.
+    /// - Parsing the callback URL to extract the authorization code
+    /// - Exchanging the code for tokens using oauth-http-request
+    oauth-start-web-auth: func(config: oauth-web-auth-config) -> result<oauth-web-auth-result, string>;
+
+    /// Make an HTTP request for OAuth token exchange.
+    ///
+    /// This is a simple HTTP client for OAuth flows, allowing the extension
+    /// to handle token exchange with full control over serialization.
+    send-oauth-http-request: func(request: oauth-http-request) -> result<oauth-http-response, string>;
+
+    /// Open a URL in the user's default browser.
+    ///
+    /// Useful for OAuth flows that need to open a browser but handle the
+    /// callback differently (e.g., polling-based flows).
+    oauth-open-browser: func(url: string) -> result<_, string>;
+}

crates/extension_cli/src/main.rs

@@ -254,6 +254,21 @@ async fn copy_extension_resources(
         }
     }
 
+    for (_, provider_entry) in &manifest.language_model_providers {
+        if let Some(icon_path) = &provider_entry.icon {
+            let source_icon = extension_path.join(icon_path);
+            let dest_icon = output_dir.join(icon_path);
+
+            // Create parent directory if needed
+            if let Some(parent) = dest_icon.parent() {
+                fs::create_dir_all(parent)?;
+            }
+
+            fs::copy(&source_icon, &dest_icon)
+                .with_context(|| format!("failed to copy LLM provider icon '{}'", icon_path))?;
+        }
+    }
+
     if !manifest.languages.is_empty() {
         let output_languages_dir = output_dir.join("languages");
         fs::create_dir_all(&output_languages_dir)?;

crates/extension_host/Cargo.toml

@@ -22,7 +22,10 @@ async-tar.workspace = true
 async-trait.workspace = true
 client.workspace = true
 collections.workspace = true
+credentials_provider.workspace = true
 dap.workspace = true
+dirs.workspace = true
+editor.workspace = true
 extension.workspace = true
 fs.workspace = true
 futures.workspace = true
@@ -30,8 +33,11 @@ gpui.workspace = true
 gpui_tokio.workspace = true
 http_client.workspace = true
 language.workspace = true
+language_model.workspace = true
 log.workspace = true
+markdown.workspace = true
 lsp.workspace = true
+menu.workspace = true
 moka.workspace = true
 node_runtime.workspace = true
 paths.workspace = true
@@ -43,10 +49,13 @@ serde.workspace = true
 serde_json.workspace = true
 serde_json_lenient.workspace = true
 settings.workspace = true
+smol.workspace = true
 task.workspace = true
 telemetry.workspace = true
 tempfile.workspace = true
+theme.workspace = true
 toml.workspace = true
+ui.workspace = true
 url.workspace = true
 util.workspace = true
 wasmparser.workspace = true

crates/extension_host/benches/extension_compilation_benchmark.rs

@@ -143,6 +143,7 @@ fn manifest() -> ExtensionManifest {
         )],
         debug_adapters: Default::default(),
         debug_locators: Default::default(),
+        language_model_providers: BTreeMap::default(),
     }
 }
 

crates/extension_host/src/capability_granter.rs

@@ -113,6 +113,7 @@ mod tests {
             capabilities: vec![],
             debug_adapters: Default::default(),
             debug_locators: Default::default(),
+            language_model_providers: BTreeMap::default(),
         }
     }
 

crates/extension_host/src/copilot_migration.rs

@@ -0,0 +1,161 @@
+use credentials_provider::CredentialsProvider;
+use gpui::App;
+use std::path::PathBuf;
+
+const COPILOT_CHAT_EXTENSION_ID: &str = "copilot_chat";
+const COPILOT_CHAT_PROVIDER_ID: &str = "copilot_chat";
+
+pub fn migrate_copilot_credentials_if_needed(extension_id: &str, cx: &mut App) {
+    if extension_id != COPILOT_CHAT_EXTENSION_ID {
+        return;
+    }
+
+    let credential_key = format!(
+        "extension-llm-{}:{}",
+        COPILOT_CHAT_EXTENSION_ID, COPILOT_CHAT_PROVIDER_ID
+    );
+
+    let credentials_provider = <dyn CredentialsProvider>::global(cx);
+
+    cx.spawn(async move |cx| {
+        let existing_credential = credentials_provider
+            .read_credentials(&credential_key, &cx)
+            .await
+            .ok()
+            .flatten();
+
+        if existing_credential.is_some() {
+            log::debug!("Copilot Chat extension already has credentials, skipping migration");
+            return;
+        }
+
+        let oauth_token = match read_copilot_oauth_token().await {
+            Some(token) => token,
+            None => {
+                log::debug!("No existing Copilot OAuth token found to migrate");
+                return;
+            }
+        };
+
+        log::info!("Migrating existing Copilot OAuth token to Copilot Chat extension");
+
+        match credentials_provider
+            .write_credentials(&credential_key, "api_key", oauth_token.as_bytes(), &cx)
+            .await
+        {
+            Ok(()) => {
+                log::info!("Successfully migrated Copilot OAuth token to Copilot Chat extension");
+            }
+            Err(err) => {
+                log::error!("Failed to migrate Copilot OAuth token: {}", err);
+            }
+        }
+    })
+    .detach();
+}
+
+async fn read_copilot_oauth_token() -> Option<String> {
+    let config_paths = copilot_config_paths();
+
+    for path in config_paths {
+        if let Some(token) = read_oauth_token_from_file(&path).await {
+            return Some(token);
+        }
+    }
+
+    None
+}
+
+fn copilot_config_paths() -> Vec<PathBuf> {
+    let config_dir = if cfg!(target_os = "windows") {
+        dirs::data_local_dir()
+    } else {
+        std::env::var("XDG_CONFIG_HOME")
+            .map(PathBuf::from)
+            .ok()
+            .or_else(|| dirs::home_dir().map(|h| h.join(".config")))
+    };
+
+    let Some(config_dir) = config_dir else {
+        return Vec::new();
+    };
+
+    let copilot_dir = config_dir.join("github-copilot");
+
+    vec![
+        copilot_dir.join("hosts.json"),
+        copilot_dir.join("apps.json"),
+    ]
+}
+
+async fn read_oauth_token_from_file(path: &PathBuf) -> Option<String> {
+    let contents = match smol::fs::read_to_string(path).await {
+        Ok(contents) => contents,
+        Err(_) => return None,
+    };
+
+    extract_oauth_token(&contents, "github.com")
+}
+
+fn extract_oauth_token(contents: &str, domain: &str) -> Option<String> {
+    let value: serde_json::Value = serde_json::from_str(contents).ok()?;
+    let obj = value.as_object()?;
+
+    for (key, value) in obj.iter() {
+        if key.starts_with(domain) {
+            if let Some(token) = value.get("oauth_token").and_then(|v| v.as_str()) {
+                return Some(token.to_string());
+            }
+        }
+    }
+
+    None
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn test_extract_oauth_token() {
+        let contents = r#"{
+            "github.com": {
+                "oauth_token": "ghu_test_token_12345"
+            }
+        }"#;
+
+        let token = extract_oauth_token(contents, "github.com");
+        assert_eq!(token, Some("ghu_test_token_12345".to_string()));
+    }
+
+    #[test]
+    fn test_extract_oauth_token_with_prefix() {
+        let contents = r#"{
+            "github.com:user": {
+                "oauth_token": "ghu_another_token"
+            }
+        }"#;
+
+        let token = extract_oauth_token(contents, "github.com");
+        assert_eq!(token, Some("ghu_another_token".to_string()));
+    }
+
+    #[test]
+    fn test_extract_oauth_token_missing() {
+        let contents = r#"{
+            "gitlab.com": {
+                "oauth_token": "some_token"
+            }
+        }"#;
+
+        let token = extract_oauth_token(contents, "github.com");
+        assert_eq!(token, None);
+    }
+
+    #[test]
+    fn test_extract_oauth_token_invalid_json() {
+        let contents = "not valid json";
+        let token = extract_oauth_token(contents, "github.com");
+        assert_eq!(token, None);
+    }
+}

crates/extension_host/src/extension_host.rs

@@ -1,4 +1,5 @@
 mod capability_granter;
+mod copilot_migration;
 pub mod extension_settings;
 pub mod headless_host;
 pub mod wasm_host;
@@ -16,9 +17,9 @@ pub use extension::ExtensionManifest;
 use extension::extension_builder::{CompileExtensionOptions, ExtensionBuilder};
 use extension::{
     ExtensionContextServerProxy, ExtensionDebugAdapterProviderProxy, ExtensionEvents,
-    ExtensionGrammarProxy, ExtensionHostProxy, ExtensionLanguageProxy,
-    ExtensionLanguageServerProxy, ExtensionSlashCommandProxy, ExtensionSnippetProxy,
-    ExtensionThemeProxy,
+    ExtensionGrammarProxy, ExtensionHostProxy, ExtensionLanguageModelProviderProxy,
+    ExtensionLanguageProxy, ExtensionLanguageServerProxy, ExtensionSlashCommandProxy,
+    ExtensionSnippetProxy, ExtensionThemeProxy,
 };
 use fs::{Fs, RemoveOptions};
 use futures::future::join_all;
@@ -32,8 +33,8 @@ use futures::{
     select_biased,
 };
 use gpui::{
-    App, AppContext as _, AsyncApp, Context, Entity, EventEmitter, Global, Task, WeakEntity,
-    actions,
+    App, AppContext as _, AsyncApp, Context, Entity, EventEmitter, Global, SharedString, Task,
+    WeakEntity, actions,
 };
 use http_client::{AsyncBody, HttpClient, HttpClientWithUrl};
 use language::{
@@ -57,11 +58,20 @@ use std::{
 };
 use url::Url;
 use util::{ResultExt, paths::RemotePathBuf};
+use wasm_host::llm_provider::ExtensionLanguageModelProvider;
 use wasm_host::{
     WasmExtension, WasmHost,
-    wit::{is_supported_wasm_api_version, wasm_api_version_range},
+    wit::{LlmModelInfo, LlmProviderInfo, is_supported_wasm_api_version, wasm_api_version_range},
 };
 
+struct LlmProviderWithModels {
+    provider_info: LlmProviderInfo,
+    models: Vec<LlmModelInfo>,
+    is_authenticated: bool,
+    icon_path: Option<SharedString>,
+    auth_config: Option<extension::LanguageModelAuthConfig>,
+}
+
 pub use extension::{
     ExtensionLibraryKind, GrammarManifestEntry, OldExtensionManifest, SchemaVersion,
 };
@@ -70,6 +80,80 @@ pub use extension_settings::ExtensionSettings;
 pub const RELOAD_DEBOUNCE_DURATION: Duration = Duration::from_millis(200);
 const FS_WATCH_LATENCY: Duration = Duration::from_millis(100);
 
+/// Extension IDs that are being migrated from hardcoded LLM providers.
+/// For backwards compatibility, if the user has the corresponding env var set,
+/// we automatically enable env var reading for these extensions.
+const LEGACY_LLM_EXTENSION_IDS: &[&str] = &[
+    "anthropic",
+    "copilot_chat",
+    "google-ai",
+    "open_router",
+    "openai",
+];
+
+/// Migrates legacy LLM provider extensions by auto-enabling env var reading
+/// if the env var is currently present in the environment.
+fn migrate_legacy_llm_provider_env_var(manifest: &ExtensionManifest, cx: &mut App) {
+    // Only apply migration to known legacy LLM extensions
+    if !LEGACY_LLM_EXTENSION_IDS.contains(&manifest.id.as_ref()) {
+        return;
+    }
+
+    // Check each provider in the manifest
+    for (provider_id, provider_entry) in &manifest.language_model_providers {
+        let Some(auth_config) = &provider_entry.auth else {
+            continue;
+        };
+        let Some(env_var_name) = &auth_config.env_var else {
+            continue;
+        };
+
+        // Check if the env var is present and non-empty
+        let env_var_is_set = std::env::var(env_var_name)
+            .map(|v| !v.is_empty())
+            .unwrap_or(false);
+
+        if !env_var_is_set {
+            continue;
+        }
+
+        let full_provider_id: Arc<str> = format!("{}:{}", manifest.id, provider_id).into();
+
+        // Check if already in settings
+        let already_allowed = ExtensionSettings::get_global(cx)
+            .allowed_env_var_providers
+            .contains(full_provider_id.as_ref());
+
+        if already_allowed {
+            continue;
+        }
+
+        // Auto-enable env var reading for this provider
+        log::info!(
+            "Migrating legacy LLM provider {}: auto-enabling {} env var reading",
+            full_provider_id,
+            env_var_name
+        );
+
+        settings::update_settings_file(<dyn fs::Fs>::global(cx), cx, {
+            let full_provider_id = full_provider_id.clone();
+            move |settings, _| {
+                let providers = settings
+                    .extension
+                    .allowed_env_var_providers
+                    .get_or_insert_with(Vec::new);
+
+                if !providers
+                    .iter()
+                    .any(|id| id.as_ref() == full_provider_id.as_ref())
+                {
+                    providers.push(full_provider_id);
+                }
+            }
+        });
+    }
+}
+
 /// The current extension [`SchemaVersion`] supported by Zed.
 const CURRENT_SCHEMA_VERSION: SchemaVersion = SchemaVersion(1);
 
@@ -771,6 +855,11 @@ impl ExtensionStore {
 
             if let ExtensionOperation::Install = operation {
                 this.update(cx, |this, cx| {
+                    // Check for legacy LLM provider migration
+                    if let Some(manifest) = this.extension_manifest_for_id(&extension_id) {
+                        migrate_legacy_llm_provider_env_var(&manifest, cx);
+                    }
+
                     cx.emit(Event::ExtensionInstalled(extension_id.clone()));
                     if let Some(events) = ExtensionEvents::try_global(cx)
                         && let Some(manifest) = this.extension_manifest_for_id(&extension_id)
@@ -779,6 +868,9 @@ impl ExtensionStore {
                             this.emit(extension::Event::ExtensionInstalled(manifest.clone()), cx)
                         });
                     }
+
+                    // Run extension-specific migrations
+                    copilot_migration::migrate_copilot_credentials_if_needed(&extension_id, cx);
                 })
                 .ok();
             }
@@ -1217,6 +1309,11 @@ impl ExtensionStore {
             for command_name in extension.manifest.slash_commands.keys() {
                 self.proxy.unregister_slash_command(command_name.clone());
             }
+            for provider_id in extension.manifest.language_model_providers.keys() {
+                let full_provider_id: Arc<str> = format!("{}:{}", extension_id, provider_id).into();
+                self.proxy
+                    .unregister_language_model_provider(full_provider_id, cx);
+            }
         }
 
         self.wasm_extensions
@@ -1355,7 +1452,11 @@ impl ExtensionStore {
             })
             .await;
 
-            let mut wasm_extensions = Vec::new();
+            let mut wasm_extensions: Vec<(
+                Arc<ExtensionManifest>,
+                WasmExtension,
+                Vec<LlmProviderWithModels>,
+            )> = Vec::new();
             for extension in extension_entries {
                 if extension.manifest.lib.kind.is_none() {
                     continue;
@@ -1373,7 +1474,122 @@ impl ExtensionStore {
 
                 match wasm_extension {
                     Ok(wasm_extension) => {
-                        wasm_extensions.push((extension.manifest.clone(), wasm_extension))
+                        // Query for LLM providers if the manifest declares any
+                        let mut llm_providers_with_models = Vec::new();
+                        if !extension.manifest.language_model_providers.is_empty() {
+                            let providers_result = wasm_extension
+                                .call(|ext, store| {
+                                    async move { ext.call_llm_providers(store).await }.boxed()
+                                })
+                                .await;
+
+                            if let Ok(Ok(providers)) = providers_result {
+                                for provider_info in providers {
+                                    let models_result = wasm_extension
+                                        .call({
+                                            let provider_id = provider_info.id.clone();
+                                            |ext, store| {
+                                                async move {
+                                                    ext.call_llm_provider_models(store, &provider_id)
+                                                        .await
+                                                }
+                                                .boxed()
+                                            }
+                                        })
+                                        .await;
+
+                                    let models: Vec<LlmModelInfo> = match models_result {
+                                        Ok(Ok(Ok(models))) => models,
+                                        Ok(Ok(Err(e))) => {
+                                            log::error!(
+                                                "Failed to get models for LLM provider {} in extension {}: {}",
+                                                provider_info.id,
+                                                extension.manifest.id,
+                                                e
+                                            );
+                                            Vec::new()
+                                        }
+                                        Ok(Err(e)) => {
+                                            log::error!(
+                                                "Wasm error calling llm_provider_models for {} in extension {}: {:?}",
+                                                provider_info.id,
+                                                extension.manifest.id,
+                                                e
+                                            );
+                                            Vec::new()
+                                        }
+                                        Err(e) => {
+                                            log::error!(
+                                                "Extension call failed for llm_provider_models {} in extension {}: {:?}",
+                                                provider_info.id,
+                                                extension.manifest.id,
+                                                e
+                                            );
+                                            Vec::new()
+                                        }
+                                    };
+
+                                    // Query initial authentication state
+                                    let is_authenticated = wasm_extension
+                                        .call({
+                                            let provider_id = provider_info.id.clone();
+                                            |ext, store| {
+                                                async move {
+                                                    ext.call_llm_provider_is_authenticated(
+                                                        store,
+                                                        &provider_id,
+                                                    )
+                                                    .await
+                                                }
+                                                .boxed()
+                                            }
+                                        })
+                                        .await
+                                        .unwrap_or(Ok(false))
+                                        .unwrap_or(false);
+
+                                    // Resolve icon path if provided
+                                    let icon_path = provider_info.icon.as_ref().map(|icon| {
+                                        let icon_file_path = extension_path.join(icon);
+                                        // Canonicalize to resolve symlinks (dev extensions are symlinked)
+                                        let absolute_icon_path = icon_file_path
+                                            .canonicalize()
+                                            .unwrap_or(icon_file_path)
+                                            .to_string_lossy()
+                                            .to_string();
+                                        SharedString::from(absolute_icon_path)
+                                    });
+
+                                    let provider_id_arc: Arc<str> =
+                                        provider_info.id.as_str().into();
+                                    let auth_config = extension
+                                        .manifest
+                                        .language_model_providers
+                                        .get(&provider_id_arc)
+                                        .and_then(|entry| entry.auth.clone());
+
+                                    llm_providers_with_models.push(LlmProviderWithModels {
+                                        provider_info,
+                                        models,
+                                        is_authenticated,
+                                        icon_path,
+                                        auth_config,
+                                    });
+                                }
+                            } else {
+                                log::error!(
+                                    "Failed to get LLM providers from extension {}: {:?}",
+                                    extension.manifest.id,
+                                    providers_result
+                                );
+                            }
+                        }
+
+                        wasm_extensions.push((
+                            extension.manifest.clone(),
+                            wasm_extension,
+                            llm_providers_with_models,
+                        ))
                     }
                     Err(e) => {
                         log::error!(
@@ -1392,7 +1608,7 @@ impl ExtensionStore {
             this.update(cx, |this, cx| {
                 this.reload_complete_senders.clear();
 
-                for (manifest, wasm_extension) in &wasm_extensions {
+                for (manifest, wasm_extension, llm_providers_with_models) in &wasm_extensions {
                     let extension = Arc::new(wasm_extension.clone());
 
                     for (language_server_id, language_server_config) in &manifest.language_servers {
@@ -1446,9 +1662,41 @@ impl ExtensionStore {
                         this.proxy
                             .register_debug_locator(extension.clone(), debug_adapter.clone());
                     }
+
+                    // Register LLM providers
+                    for llm_provider in llm_providers_with_models {
+                        let provider_id: Arc<str> =
+                            format!("{}:{}", manifest.id, llm_provider.provider_info.id).into();
+                        let wasm_ext = extension.as_ref().clone();
+                        let pinfo = llm_provider.provider_info.clone();
+                        let mods = llm_provider.models.clone();
+                        let auth = llm_provider.is_authenticated;
+                        let icon = llm_provider.icon_path.clone();
+                        let auth_config = llm_provider.auth_config.clone();
+
+                        this.proxy.register_language_model_provider(
+                            provider_id.clone(),
+                            Box::new(move |cx: &mut App| {
+                                let provider = Arc::new(ExtensionLanguageModelProvider::new(
+                                    wasm_ext, pinfo, mods, auth, icon, auth_config, cx,
+                                ));
+                                language_model::LanguageModelRegistry::global(cx).update(
+                                    cx,
+                                    |registry, cx| {
+                                        registry.register_provider(provider, cx);
+                                    },
+                                );
+                            }),
+                            cx,
+                        );
+                    }
                 }
 
-                this.wasm_extensions.extend(wasm_extensions);
+                let wasm_extensions_without_llm: Vec<_> = wasm_extensions
+                    .into_iter()
+                    .map(|(manifest, ext, _)| (manifest, ext))
+                    .collect();
+                this.wasm_extensions.extend(wasm_extensions_without_llm);
                 this.proxy.set_extensions_loaded();
                 this.proxy.reload_current_theme(cx);
                 this.proxy.reload_current_icon_theme(cx);

crates/extension_host/src/extension_settings.rs

@@ -1,4 +1,4 @@
-use collections::HashMap;
+use collections::{HashMap, HashSet};
 use extension::{
     DownloadFileCapability, ExtensionCapability, NpmInstallPackageCapability, ProcessExecCapability,
 };
@@ -16,6 +16,10 @@ pub struct ExtensionSettings {
     pub auto_install_extensions: HashMap<Arc<str>, bool>,
     pub auto_update_extensions: HashMap<Arc<str>, bool>,
     pub granted_capabilities: Vec<ExtensionCapability>,
+    /// The extension language model providers that are allowed to read API keys
+    /// from environment variables. Each entry is a provider ID in the format
+    /// "extension_id:provider_id".
+    pub allowed_env_var_providers: HashSet<Arc<str>>,
 }
 
 impl ExtensionSettings {
@@ -60,6 +64,13 @@ impl Settings for ExtensionSettings {
                     }
                 })
                 .collect(),
+            allowed_env_var_providers: content
+                .extension
+                .allowed_env_var_providers
+                .clone()
+                .unwrap_or_default()
+                .into_iter()
+                .collect(),
         }
     }
 }

crates/extension_host/src/extension_store_test.rs

@@ -165,6 +165,7 @@ async fn test_extension_store(cx: &mut TestAppContext) {
                         capabilities: Vec::new(),
                         debug_adapters: Default::default(),
                         debug_locators: Default::default(),
+                        language_model_providers: BTreeMap::default(),
                     }),
                     dev: false,
                 },
@@ -196,6 +197,7 @@ async fn test_extension_store(cx: &mut TestAppContext) {
                         capabilities: Vec::new(),
                         debug_adapters: Default::default(),
                         debug_locators: Default::default(),
+                        language_model_providers: BTreeMap::default(),
                     }),
                     dev: false,
                 },
@@ -376,6 +378,7 @@ async fn test_extension_store(cx: &mut TestAppContext) {
                 capabilities: Vec::new(),
                 debug_adapters: Default::default(),
                 debug_locators: Default::default(),
+                language_model_providers: BTreeMap::default(),
             }),
             dev: false,
         },

crates/extension_host/src/wasm_host.rs

@@ -1,9 +1,11 @@
+pub mod llm_provider;
 pub mod wit;
 
 use crate::capability_granter::CapabilityGranter;
 use crate::{ExtensionManifest, ExtensionSettings};
 use anyhow::{Context as _, Result, anyhow, bail};
 use async_trait::async_trait;
+use collections::HashSet;
 use dap::{DebugRequest, StartDebuggingRequestArgumentsRequest};
 use extension::{
     CodeLabel, Command, Completion, ContextServerConfiguration, DebugAdapterBinary,
@@ -58,6 +60,8 @@ pub struct WasmHost {
     pub work_dir: PathBuf,
     /// The capabilities granted to extensions running on the host.
     pub(crate) granted_capabilities: Vec<ExtensionCapability>,
+    /// Extension LLM providers allowed to read API keys from environment variables.
+    pub(crate) allowed_env_var_providers: HashSet<Arc<str>>,
     _main_thread_message_task: Task<()>,
     main_thread_message_tx: mpsc::UnboundedSender<MainThreadCall>,
 }
@@ -72,12 +76,6 @@ pub struct WasmExtension {
     _task: Arc<Task<Result<(), gpui_tokio::JoinError>>>,
 }
 
-impl Drop for WasmExtension {
-    fn drop(&mut self) {
-        self.tx.close_channel();
-    }
-}
-
 #[async_trait]
 impl extension::Extension for WasmExtension {
     fn manifest(&self) -> Arc<ExtensionManifest> {
@@ -590,6 +588,7 @@ impl WasmHost {
             proxy,
             release_channel: ReleaseChannel::global(cx),
             granted_capabilities: extension_settings.granted_capabilities.clone(),
+            allowed_env_var_providers: extension_settings.allowed_env_var_providers.clone(),
             _main_thread_message_task: task,
             main_thread_message_tx: tx,
         })

crates/extension_host/src/wasm_host/wit.rs

@@ -16,7 +16,7 @@ use lsp::LanguageServerName;
 use release_channel::ReleaseChannel;
 use task::{DebugScenario, SpawnInTerminal, TaskTemplate, ZedDebugConfig};
 
-use crate::wasm_host::wit::since_v0_6_0::dap::StartDebuggingRequestArgumentsRequest;
+use crate::wasm_host::wit::since_v0_8_0::dap::StartDebuggingRequestArgumentsRequest;
 
 use super::{WasmState, wasm_engine};
 use anyhow::{Context as _, Result, anyhow};
@@ -33,6 +33,19 @@ pub use latest::CodeLabelSpanLiteral;
 pub use latest::{
     CodeLabel, CodeLabelSpan, Command, DebugAdapterBinary, ExtensionProject, Range, SlashCommand,
     zed::extension::context_server::ContextServerConfiguration,
+    zed::extension::llm_provider::{
+        CacheConfiguration as LlmCacheConfiguration, CompletionEvent as LlmCompletionEvent,
+        CompletionRequest as LlmCompletionRequest, CredentialType as LlmCredentialType,
+        ImageData as LlmImageData, MessageContent as LlmMessageContent,
+        MessageRole as LlmMessageRole, ModelCapabilities as LlmModelCapabilities,
+        ModelInfo as LlmModelInfo, ProviderInfo as LlmProviderInfo,
+        RequestMessage as LlmRequestMessage, StopReason as LlmStopReason,
+        ThinkingContent as LlmThinkingContent, TokenUsage as LlmTokenUsage,
+        ToolChoice as LlmToolChoice, ToolDefinition as LlmToolDefinition,
+        ToolInputFormat as LlmToolInputFormat, ToolResult as LlmToolResult,
+        ToolResultContent as LlmToolResultContent, ToolUse as LlmToolUse,
+        ToolUseJsonParseError as LlmToolUseJsonParseError,
+    },
     zed::extension::lsp::{
         Completion, CompletionKind, CompletionLabelDetails, InsertTextFormat, Symbol, SymbolKind,
     },
@@ -67,7 +80,7 @@ pub fn wasm_api_version_range(release_channel: ReleaseChannel) -> RangeInclusive
 
     let max_version = match release_channel {
         ReleaseChannel::Dev | ReleaseChannel::Nightly => latest::MAX_VERSION,
-        ReleaseChannel::Stable | ReleaseChannel::Preview => since_v0_6_0::MAX_VERSION,
+        ReleaseChannel::Stable | ReleaseChannel::Preview => latest::MAX_VERSION,
     };
 
     since_v0_0_1::MIN_VERSION..=max_version
@@ -997,7 +1010,6 @@ impl Extension {
             }
         }
     }
-
     pub async fn call_get_dap_binary(
         &self,
         store: &mut Store<WasmState>,
@@ -1007,6 +1019,20 @@ impl Extension {
         resource: Resource<Arc<dyn WorktreeDelegate>>,
     ) -> Result<Result<DebugAdapterBinary, String>> {
         match self {
+            Extension::V0_8_0(ext) => {
+                let dap_binary = ext
+                    .call_get_dap_binary(
+                        store,
+                        &adapter_name,
+                        &task.try_into()?,
+                        user_installed_path.as_ref().and_then(|p| p.to_str()),
+                        resource,
+                    )
+                    .await?
+                    .map_err(|e| anyhow!("{e:?}"))?;
+
+                Ok(Ok(dap_binary))
+            }
             Extension::V0_6_0(ext) => {
                 let dap_binary = ext
                     .call_get_dap_binary(
@@ -1024,7 +1050,6 @@ impl Extension {
             _ => anyhow::bail!("`get_dap_binary` not available prior to v0.6.0"),
         }
     }
-
     pub async fn call_dap_request_kind(
         &self,
         store: &mut Store<WasmState>,
@@ -1032,6 +1057,16 @@ impl Extension {
         config: serde_json::Value,
     ) -> Result<Result<StartDebuggingRequestArgumentsRequest, String>> {
         match self {
+            Extension::V0_8_0(ext) => {
+                let config =
+                    serde_json::to_string(&config).context("Adapter config is not a valid JSON")?;
+                let result = ext
+                    .call_dap_request_kind(store, &adapter_name, &config)
+                    .await?
+                    .map_err(|e| anyhow!("{e:?}"))?;
+
+                Ok(Ok(result))
+            }
             Extension::V0_6_0(ext) => {
                 let config =
                     serde_json::to_string(&config).context("Adapter config is not a valid JSON")?;
@@ -1045,13 +1080,21 @@ impl Extension {
             _ => anyhow::bail!("`dap_request_kind` not available prior to v0.6.0"),
         }
     }
-
     pub async fn call_dap_config_to_scenario(
         &self,
         store: &mut Store<WasmState>,
         config: ZedDebugConfig,
     ) -> Result<Result<DebugScenario, String>> {
         match self {
+            Extension::V0_8_0(ext) => {
+                let config = config.into();
+                let result = ext
+                    .call_dap_config_to_scenario(store, &config)
+                    .await?
+                    .map_err(|e| anyhow!("{e:?}"))?;
+
+                Ok(Ok(result.try_into()?))
+            }
             Extension::V0_6_0(ext) => {
                 let config = config.into();
                 let dap_binary = ext
@@ -1064,7 +1107,6 @@ impl Extension {
             _ => anyhow::bail!("`dap_config_to_scenario` not available prior to v0.6.0"),
         }
     }
-
     pub async fn call_dap_locator_create_scenario(
         &self,
         store: &mut Store<WasmState>,
@@ -1074,6 +1116,20 @@ impl Extension {
         debug_adapter_name: String,
     ) -> Result<Option<DebugScenario>> {
         match self {
+            Extension::V0_8_0(ext) => {
+                let build_config_template = build_config_template.into();
+                let result = ext
+                    .call_dap_locator_create_scenario(
+                        store,
+                        &locator_name,
+                        &build_config_template,
+                        &resolved_label,
+                        &debug_adapter_name,
+                    )
+                    .await?;
+
+                Ok(result.map(TryInto::try_into).transpose()?)
+            }
             Extension::V0_6_0(ext) => {
                 let build_config_template = build_config_template.into();
                 let dap_binary = ext
@@ -1091,7 +1147,6 @@ impl Extension {
             _ => anyhow::bail!("`dap_locator_create_scenario` not available prior to v0.6.0"),
         }
     }
-
     pub async fn call_run_dap_locator(
         &self,
         store: &mut Store<WasmState>,
@@ -1099,6 +1154,15 @@ impl Extension {
         resolved_build_task: SpawnInTerminal,
     ) -> Result<Result<DebugRequest, String>> {
         match self {
+            Extension::V0_8_0(ext) => {
+                let build_config_template = resolved_build_task.try_into()?;
+                let dap_request = ext
+                    .call_run_dap_locator(store, &locator_name, &build_config_template)
+                    .await?
+                    .map_err(|e| anyhow!("{e:?}"))?;
+
+                Ok(Ok(dap_request.into()))
+            }
             Extension::V0_6_0(ext) => {
                 let build_config_template = resolved_build_task.try_into()?;
                 let dap_request = ext
@@ -1111,6 +1175,149 @@ impl Extension {
             _ => anyhow::bail!("`dap_locator_create_scenario` not available prior to v0.6.0"),
         }
     }
+
+    pub async fn call_llm_providers(
+        &self,
+        store: &mut Store<WasmState>,
+    ) -> Result<Vec<latest::llm_provider::ProviderInfo>> {
+        match self {
+            Extension::V0_8_0(ext) => ext.call_llm_providers(store).await,
+            _ => Ok(Vec::new()),
+        }
+    }
+
+    pub async fn call_llm_provider_models(
+        &self,
+        store: &mut Store<WasmState>,
+        provider_id: &str,
+    ) -> Result<Result<Vec<latest::llm_provider::ModelInfo>, String>> {
+        match self {
+            Extension::V0_8_0(ext) => ext.call_llm_provider_models(store, provider_id).await,
+            _ => anyhow::bail!("`llm_provider_models` not available prior to v0.8.0"),
+        }
+    }
+
+    pub async fn call_llm_provider_settings_markdown(
+        &self,
+        store: &mut Store<WasmState>,
+        provider_id: &str,
+    ) -> Result<Option<String>> {
+        match self {
+            Extension::V0_8_0(ext) => {
+                ext.call_llm_provider_settings_markdown(store, provider_id)
+                    .await
+            }
+            _ => Ok(None),
+        }
+    }
+
+    pub async fn call_llm_provider_is_authenticated(
+        &self,
+        store: &mut Store<WasmState>,
+        provider_id: &str,
+    ) -> Result<bool> {
+        match self {
+            Extension::V0_8_0(ext) => {
+                ext.call_llm_provider_is_authenticated(store, provider_id)
+                    .await
+            }
+            _ => Ok(false),
+        }
+    }
+
+    pub async fn call_llm_provider_authenticate(
+        &self,
+        store: &mut Store<WasmState>,
+        provider_id: &str,
+    ) -> Result<Result<(), String>> {
+        match self {
+            Extension::V0_8_0(ext) => ext.call_llm_provider_authenticate(store, provider_id).await,
+            _ => anyhow::bail!("`llm_provider_authenticate` not available prior to v0.8.0"),
+        }
+    }
+
+    pub async fn call_llm_provider_reset_credentials(
+        &self,
+        store: &mut Store<WasmState>,
+        provider_id: &str,
+    ) -> Result<Result<(), String>> {
+        match self {
+            Extension::V0_8_0(ext) => {
+                ext.call_llm_provider_reset_credentials(store, provider_id)
+                    .await
+            }
+            _ => anyhow::bail!("`llm_provider_reset_credentials` not available prior to v0.8.0"),
+        }
+    }
+
+    pub async fn call_llm_count_tokens(
+        &self,
+        store: &mut Store<WasmState>,
+        provider_id: &str,
+        model_id: &str,
+        request: &latest::llm_provider::CompletionRequest,
+    ) -> Result<Result<u64, String>> {
+        match self {
+            Extension::V0_8_0(ext) => {
+                ext.call_llm_count_tokens(store, provider_id, model_id, request)
+                    .await
+            }
+            _ => anyhow::bail!("`llm_count_tokens` not available prior to v0.8.0"),
+        }
+    }
+
+    pub async fn call_llm_stream_completion_start(
+        &self,
+        store: &mut Store<WasmState>,
+        provider_id: &str,
+        model_id: &str,
+        request: &latest::llm_provider::CompletionRequest,
+    ) -> Result<Result<String, String>> {
+        match self {
+            Extension::V0_8_0(ext) => {
+                ext.call_llm_stream_completion_start(store, provider_id, model_id, request)
+                    .await
+            }
+            _ => anyhow::bail!("`llm_stream_completion_start` not available prior to v0.8.0"),
+        }
+    }
+
+    pub async fn call_llm_stream_completion_next(
+        &self,
+        store: &mut Store<WasmState>,
+        stream_id: &str,
+    ) -> Result<Result<Option<latest::llm_provider::CompletionEvent>, String>> {
+        match self {
+            Extension::V0_8_0(ext) => ext.call_llm_stream_completion_next(store, stream_id).await,
+            _ => anyhow::bail!("`llm_stream_completion_next` not available prior to v0.8.0"),
+        }
+    }
+
+    pub async fn call_llm_stream_completion_close(
+        &self,
+        store: &mut Store<WasmState>,
+        stream_id: &str,
+    ) -> Result<()> {
+        match self {
+            Extension::V0_8_0(ext) => ext.call_llm_stream_completion_close(store, stream_id).await,
+            _ => anyhow::bail!("`llm_stream_completion_close` not available prior to v0.8.0"),
+        }
+    }
+
+    pub async fn call_llm_cache_configuration(
+        &self,
+        store: &mut Store<WasmState>,
+        provider_id: &str,
+        model_id: &str,
+    ) -> Result<Option<latest::llm_provider::CacheConfiguration>> {
+        match self {
+            Extension::V0_8_0(ext) => {
+                ext.call_llm_cache_configuration(store, provider_id, model_id)
+                    .await
+            }
+            _ => Ok(None),
+        }
+    }
 }
 
 trait ToWasmtimeResult<T> {

crates/extension_host/src/wasm_host/wit/since_v0_6_0.rs

@@ -9,6 +9,7 @@ use wasmtime::component::{Linker, Resource};
 use super::latest;
 
 pub const MIN_VERSION: Version = Version::new(0, 6, 0);
+#[allow(dead_code)]
 pub const MAX_VERSION: Version = Version::new(0, 7, 0);
 
 wasmtime::component::bindgen!({
@@ -32,8 +33,6 @@ wasmtime::component::bindgen!({
     },
 });
 
-pub use self::zed::extension::*;
-
 mod settings {
     #![allow(dead_code)]
     include!(concat!(env!("OUT_DIR"), "/since_v0.6.0/settings.rs"));

crates/extension_host/src/wasm_host/wit/since_v0_8_0.rs

@@ -1,11 +1,11 @@
-use crate::wasm_host::wit::since_v0_6_0::{
+use crate::wasm_host::wit::since_v0_8_0::{
     dap::{
         AttachRequest, BuildTaskDefinition, BuildTaskDefinitionTemplatePayload, LaunchRequest,
         StartDebuggingRequestArguments, TcpArguments, TcpArgumentsTemplate,
     },
+    lsp::{CompletionKind, CompletionLabelDetails, InsertTextFormat, SymbolKind},
     slash_command::SlashCommandOutputSection,
 };
-use crate::wasm_host::wit::{CompletionKind, CompletionLabelDetails, InsertTextFormat, SymbolKind};
 use crate::wasm_host::{WasmState, wit::ToWasmtimeResult};
 use ::http_client::{AsyncBody, HttpRequestExt};
 use ::settings::{Settings, WorktreeId};
@@ -13,6 +13,7 @@ use anyhow::{Context as _, Result, bail};
 use async_compression::futures::bufread::GzipDecoder;
 use async_tar::Archive;
 use async_trait::async_trait;
+use credentials_provider::CredentialsProvider;
 use extension::{
     ExtensionLanguageServerProxy, KeyValueStoreDelegate, ProjectDelegate, WorktreeDelegate,
 };
@@ -22,12 +23,14 @@ use gpui::{BackgroundExecutor, SharedString};
 use language::{BinaryStatus, LanguageName, language_settings::AllLanguageSettings};
 use project::project_settings::ProjectSettings;
 use semver::Version;
+use smol::net::TcpListener;
 use std::{
     env,
     net::Ipv4Addr,
     path::{Path, PathBuf},
     str::FromStr,
     sync::{Arc, OnceLock},
+    time::Duration,
 };
 use task::{SpawnInTerminal, ZedDebugConfig};
 use url::Url;
@@ -1107,3 +1110,336 @@ impl ExtensionImports for WasmState {
             .to_wasmtime_result()
     }
 }
+
+impl llm_provider::Host for WasmState {
+    async fn request_credential(
+        &mut self,
+        _provider_id: String,
+        _credential_type: llm_provider::CredentialType,
+        _label: String,
+        _placeholder: String,
+    ) -> wasmtime::Result<Result<bool, String>> {
+        // For now, credential requests return false (not provided)
+        // Extensions should use get_env_var to check for env vars first,
+        // then store_credential/get_credential for manual storage
+        // Full UI credential prompting will be added in a future phase
+        Ok(Ok(false))
+    }
+
+    async fn get_credential(&mut self, provider_id: String) -> wasmtime::Result<Option<String>> {
+        let extension_id = self.manifest.id.clone();
+
+        // Check if this provider has an env var configured and if the user has allowed it
+        let env_var_name = self
+            .manifest
+            .language_model_providers
+            .get(&Arc::<str>::from(provider_id.as_str()))
+            .and_then(|entry| entry.auth.as_ref())
+            .and_then(|auth| auth.env_var.clone());
+
+        if let Some(env_var_name) = env_var_name {
+            let full_provider_id: Arc<str> = format!("{}:{}", extension_id, provider_id).into();
+            // Use cached settings from WasmHost instead of going to main thread
+            let is_allowed = self
+                .host
+                .allowed_env_var_providers
+                .contains(&full_provider_id);
+
+            if is_allowed {
+                if let Ok(value) = env::var(&env_var_name) {
+                    if !value.is_empty() {
+                        return Ok(Some(value));
+                    }
+                }
+            }
+        }
+
+        // Fall back to credential store
+        let credential_key = format!("extension-llm-{}:{}", extension_id, provider_id);
+
+        self.on_main_thread(move |cx| {
+            async move {
+                let credentials_provider = cx.update(|cx| <dyn CredentialsProvider>::global(cx))?;
+                let result = credentials_provider
+                    .read_credentials(&credential_key, cx)
+                    .await
+                    .ok()
+                    .flatten();
+                Ok(result.map(|(_, password)| String::from_utf8_lossy(&password).to_string()))
+            }
+            .boxed_local()
+        })
+        .await
+    }
+
+    async fn store_credential(
+        &mut self,
+        provider_id: String,
+        value: String,
+    ) -> wasmtime::Result<Result<(), String>> {
+        let extension_id = self.manifest.id.clone();
+        let credential_key = format!("extension-llm-{}:{}", extension_id, provider_id);
+
+        self.on_main_thread(move |cx| {
+            async move {
+                let credentials_provider = cx.update(|cx| <dyn CredentialsProvider>::global(cx))?;
+                credentials_provider
+                    .write_credentials(&credential_key, "api_key", value.as_bytes(), cx)
+                    .await
+                    .map_err(|e| anyhow::anyhow!("{}", e))
+            }
+            .boxed_local()
+        })
+        .await
+        .to_wasmtime_result()
+    }
+
+    async fn delete_credential(
+        &mut self,
+        provider_id: String,
+    ) -> wasmtime::Result<Result<(), String>> {
+        let extension_id = self.manifest.id.clone();
+        let credential_key = format!("extension-llm-{}:{}", extension_id, provider_id);
+
+        self.on_main_thread(move |cx| {
+            async move {
+                let credentials_provider = cx.update(|cx| <dyn CredentialsProvider>::global(cx))?;
+                credentials_provider
+                    .delete_credentials(&credential_key, cx)
+                    .await
+                    .map_err(|e| anyhow::anyhow!("{}", e))
+            }
+            .boxed_local()
+        })
+        .await
+        .to_wasmtime_result()
+    }
+
+    async fn get_env_var(&mut self, name: String) -> wasmtime::Result<Option<String>> {
+        let extension_id = self.manifest.id.clone();
+
+        // Find which provider (if any) declares this env var in its auth config
+        let mut allowed_provider_id: Option<Arc<str>> = None;
+        for (provider_id, provider_entry) in &self.manifest.language_model_providers {
+            if let Some(auth_config) = &provider_entry.auth {
+                if auth_config.env_var.as_deref() == Some(&name) {
+                    allowed_provider_id = Some(provider_id.clone());
+                    break;
+                }
+            }
+        }
+
+        // If no provider declares this env var, deny access
+        let Some(provider_id) = allowed_provider_id else {
+            log::warn!(
+                "Extension {} attempted to read env var {} which is not declared in any provider auth config",
+                extension_id,
+                name
+            );
+            return Ok(None);
+        };
+
+        // Check if the user has allowed this provider to read env vars
+        // Use cached settings from WasmHost instead of going to main thread
+        let full_provider_id: Arc<str> = format!("{}:{}", extension_id, provider_id).into();
+        let is_allowed = self
+            .host
+            .allowed_env_var_providers
+            .contains(&full_provider_id);
+
+        if !is_allowed {
+            log::debug!(
+                "Extension {} provider {} is not allowed to read env var {}",
+                extension_id,
+                provider_id,
+                name
+            );
+            return Ok(None);
+        }
+
+        Ok(env::var(&name).ok())
+    }
+
+    async fn oauth_start_web_auth(
+        &mut self,
+        config: llm_provider::OauthWebAuthConfig,
+    ) -> wasmtime::Result<Result<llm_provider::OauthWebAuthResult, String>> {
+        let auth_url = config.auth_url;
+        let callback_path = config.callback_path;
+        let timeout_secs = config.timeout_secs.unwrap_or(300);
+
+        self.on_main_thread(move |cx| {
+            async move {
+                let listener = TcpListener::bind("127.0.0.1:0")
+                    .await
+                    .map_err(|e| anyhow::anyhow!("Failed to bind localhost server: {}", e))?;
+                let port = listener
+                    .local_addr()
+                    .map_err(|e| anyhow::anyhow!("Failed to get local address: {}", e))?
+                    .port();
+
+                cx.update(|cx| {
+                    cx.open_url(&auth_url);
+                })?;
+
+                let accept_future = async {
+                    let (mut stream, _) = listener
+                        .accept()
+                        .await
+                        .map_err(|e| anyhow::anyhow!("Failed to accept connection: {}", e))?;
+
+                    let mut request_line = String::new();
+                    {
+                        let mut reader = smol::io::BufReader::new(&mut stream);
+                        smol::io::AsyncBufReadExt::read_line(&mut reader, &mut request_line)
+                            .await
+                            .map_err(|e| anyhow::anyhow!("Failed to read request: {}", e))?;
+                    }
+
+                    let callback_url = if let Some(path_start) = request_line.find(' ') {
+                        if let Some(path_end) = request_line[path_start + 1..].find(' ') {
+                            let path = &request_line[path_start + 1..path_start + 1 + path_end];
+                            if path.starts_with(&callback_path) || path.starts_with(&format!("/{}", callback_path.trim_start_matches('/'))) {
+                                format!("http://localhost:{}{}", port, path)
+                            } else {
+                                return Err(anyhow::anyhow!(
+                                    "Unexpected callback path: {}",
+                                    path
+                                ));
+                            }
+                        } else {
+                            return Err(anyhow::anyhow!("Malformed HTTP request"));
+                        }
+                    } else {
+                        return Err(anyhow::anyhow!("Malformed HTTP request"));
+                    };
+
+                    let response = "HTTP/1.1 200 OK\r\n\
+                        Content-Type: text/html\r\n\
+                        Connection: close\r\n\
+                        \r\n\
+                        <!DOCTYPE html>\
+                        <html><head><title>Authentication Complete</title></head>\
+                        <body style=\"font-family: system-ui, sans-serif; display: flex; justify-content: center; align-items: center; height: 100vh; margin: 0;\">\
+                        <div style=\"text-align: center;\">\
+                        <h1>Authentication Complete</h1>\
+                        <p>You can close this window and return to Zed.</p>\
+                        </div></body></html>";
+
+                    smol::io::AsyncWriteExt::write_all(&mut stream, response.as_bytes())
+                        .await
+                        .ok();
+                    smol::io::AsyncWriteExt::flush(&mut stream).await.ok();
+
+                    Ok(callback_url)
+                };
+
+                let timeout_duration = Duration::from_secs(timeout_secs as u64);
+                let callback_url = smol::future::or(
+                    accept_future,
+                    async {
+                        smol::Timer::after(timeout_duration).await;
+                        Err(anyhow::anyhow!(
+                            "OAuth callback timed out after {} seconds",
+                            timeout_secs
+                        ))
+                    },
+                )
+                .await?;
+
+                Ok(llm_provider::OauthWebAuthResult {
+                    callback_url,
+                    port: port as u32,
+                })
+            }
+            .boxed_local()
+        })
+        .await
+        .to_wasmtime_result()
+    }
+
+    async fn send_oauth_http_request(
+        &mut self,
+        request: llm_provider::OauthHttpRequest,
+    ) -> wasmtime::Result<Result<llm_provider::OauthHttpResponse, String>> {
+        let http_client = self.host.http_client.clone();
+
+        self.on_main_thread(move |_cx| {
+            async move {
+                let method = match request.method.to_uppercase().as_str() {
+                    "GET" => ::http_client::Method::GET,
+                    "POST" => ::http_client::Method::POST,
+                    "PUT" => ::http_client::Method::PUT,
+                    "DELETE" => ::http_client::Method::DELETE,
+                    "PATCH" => ::http_client::Method::PATCH,
+                    _ => {
+                        return Err(anyhow::anyhow!(
+                            "Unsupported HTTP method: {}",
+                            request.method
+                        ));
+                    }
+                };
+
+                let mut builder = ::http_client::Request::builder()
+                    .method(method)
+                    .uri(&request.url);
+
+                for (key, value) in &request.headers {
+                    builder = builder.header(key.as_str(), value.as_str());
+                }
+
+                let body = if request.body.is_empty() {
+                    AsyncBody::empty()
+                } else {
+                    AsyncBody::from(request.body.into_bytes())
+                };
+
+                let http_request = builder
+                    .body(body)
+                    .map_err(|e| anyhow::anyhow!("Failed to build request: {}", e))?;
+
+                let mut response = http_client
+                    .send(http_request)
+                    .await
+                    .map_err(|e| anyhow::anyhow!("HTTP request failed: {}", e))?;
+
+                let status = response.status().as_u16();
+                let headers: Vec<(String, String)> = response
+                    .headers()
+                    .iter()
+                    .map(|(k, v)| (k.to_string(), v.to_str().unwrap_or("").to_string()))
+                    .collect();
+
+                let mut body_bytes = Vec::new();
+                futures::AsyncReadExt::read_to_end(response.body_mut(), &mut body_bytes)
+                    .await
+                    .map_err(|e| anyhow::anyhow!("Failed to read response body: {}", e))?;
+
+                let body = String::from_utf8_lossy(&body_bytes).to_string();
+
+                Ok(llm_provider::OauthHttpResponse {
+                    status,
+                    headers,
+                    body,
+                })
+            }
+            .boxed_local()
+        })
+        .await
+        .to_wasmtime_result()
+    }
+
+    async fn oauth_open_browser(&mut self, url: String) -> wasmtime::Result<Result<(), String>> {
+        self.on_main_thread(move |cx| {
+            async move {
+                cx.update(|cx| {
+                    cx.open_url(&url);
+                })?;
+                Ok(())
+            }
+            .boxed_local()
+        })
+        .await
+        .to_wasmtime_result()
+    }
+}

crates/icons/src/icons.rs

@@ -9,7 +9,6 @@ use strum::{EnumIter, EnumString, IntoStaticStr};
 #[strum(serialize_all = "snake_case")]
 pub enum IconName {
     Ai,
-    AiAnthropic,
     AiBedrock,
     AiClaude,
     AiDeepSeek,

crates/language_model/src/language_model.rs

@@ -746,6 +746,11 @@ pub trait LanguageModelProvider: 'static {
     fn icon(&self) -> IconName {
         IconName::ZedAssistant
     }
+    /// Returns the path to an external SVG icon for this provider, if any.
+    /// When present, this takes precedence over `icon()`.
+    fn icon_path(&self) -> Option<SharedString> {
+        None
+    }
     fn default_model(&self, cx: &App) -> Option<Arc<dyn LanguageModel>>;
     fn default_fast_model(&self, cx: &App) -> Option<Arc<dyn LanguageModel>>;
     fn provided_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>>;

crates/language_models/Cargo.toml

@@ -28,6 +28,7 @@ convert_case.workspace = true
 copilot.workspace = true
 credentials_provider.workspace = true
 deepseek = { workspace = true, features = ["schemars"] }
+extension.workspace = true
 fs.workspace = true
 futures.workspace = true
 google_ai = { workspace = true, features = ["schemars"] }

crates/language_models/src/extension.rs

@@ -0,0 +1,34 @@
+use extension::{ExtensionLanguageModelProviderProxy, LanguageModelProviderRegistration};
+use gpui::{App, Entity};
+use language_model::{LanguageModelProviderId, LanguageModelRegistry};
+use std::sync::Arc;
+
+/// Proxy implementation that registers extension-based language model providers
+/// with the LanguageModelRegistry.
+pub struct ExtensionLanguageModelProxy {
+    registry: Entity<LanguageModelRegistry>,
+}
+
+impl ExtensionLanguageModelProxy {
+    pub fn new(registry: Entity<LanguageModelRegistry>) -> Self {
+        Self { registry }
+    }
+}
+
+impl ExtensionLanguageModelProviderProxy for ExtensionLanguageModelProxy {
+    fn register_language_model_provider(
+        &self,
+        provider_id: Arc<str>,
+        register_fn: LanguageModelProviderRegistration,
+        cx: &mut App,
+    ) {
+        let _ = provider_id;
+        register_fn(cx);
+    }
+
+    fn unregister_language_model_provider(&self, provider_id: Arc<str>, cx: &mut App) {
+        self.registry.update(cx, |registry, cx| {
+            registry.unregister_provider(LanguageModelProviderId::from(provider_id), cx);
+        });
+    }
+}

crates/language_models/src/language_models.rs

@@ -1,5 +1,6 @@
 use std::sync::Arc;
 
+use ::extension::ExtensionHostProxy;
 use ::settings::{Settings, SettingsStore};
 use client::{Client, UserStore};
 use collections::HashSet;
@@ -8,11 +9,11 @@ use language_model::{LanguageModelProviderId, LanguageModelRegistry};
 use provider::deepseek::DeepSeekLanguageModelProvider;
 
 mod api_key;
+mod extension;
 pub mod provider;
 mod settings;
 pub mod ui;
 
-use crate::provider::anthropic::AnthropicLanguageModelProvider;
 use crate::provider::bedrock::BedrockLanguageModelProvider;
 use crate::provider::cloud::CloudLanguageModelProvider;
 use crate::provider::copilot_chat::CopilotChatLanguageModelProvider;
@@ -33,6 +34,12 @@ pub fn init(user_store: Entity<UserStore>, client: Arc<Client>, cx: &mut App) {
         register_language_model_providers(registry, user_store, client.clone(), cx);
     });
 
+    // Register the extension language model provider proxy
+    let extension_proxy = ExtensionHostProxy::default_global(cx);
+    extension_proxy.register_language_model_provider_proxy(
+        extension::ExtensionLanguageModelProxy::new(registry.clone()),
+    );
+
     let mut openai_compatible_providers = AllLanguageModelSettings::get_global(cx)
         .openai_compatible
         .keys()
@@ -111,13 +118,6 @@ fn register_language_model_providers(
         )),
         cx,
     );
-    registry.register_provider(
-        Arc::new(AnthropicLanguageModelProvider::new(
-            client.http_client(),
-            cx,
-        )),
-        cx,
-    );
     registry.register_provider(
         Arc::new(OpenAiLanguageModelProvider::new(client.http_client(), cx)),
         cx,

crates/language_models/src/provider.rs

@@ -1,4 +1,3 @@
-pub mod anthropic;
 pub mod bedrock;
 pub mod cloud;
 pub mod copilot_chat;

crates/language_models/src/provider/cloud.rs

@@ -1,5 +1,8 @@
 use ai_onboarding::YoungAccountBanner;
-use anthropic::AnthropicModelMode;
+use anthropic::{
+    AnthropicModelMode, ContentDelta, Event, ResponseContent, ToolResultContent, ToolResultPart,
+    Usage,
+};
 use anyhow::{Context as _, Result, anyhow};
 use chrono::{DateTime, Utc};
 use client::{Client, ModelRequestUsage, UserStore, zed_urls};
@@ -23,8 +26,9 @@ use language_model::{
     LanguageModelCompletionError, LanguageModelCompletionEvent, LanguageModelId, LanguageModelName,
     LanguageModelProvider, LanguageModelProviderId, LanguageModelProviderName,
     LanguageModelProviderState, LanguageModelRequest, LanguageModelToolChoice,
-    LanguageModelToolSchemaFormat, LlmApiToken, ModelRequestLimitReachedError,
-    PaymentRequiredError, RateLimiter, RefreshLlmTokenListener,
+    LanguageModelToolResultContent, LanguageModelToolSchemaFormat, LanguageModelToolUse,
+    LanguageModelToolUseId, LlmApiToken, MessageContent, ModelRequestLimitReachedError,
+    PaymentRequiredError, RateLimiter, RefreshLlmTokenListener, Role, StopReason,
 };
 use release_channel::AppVersion;
 use schemars::JsonSchema;
@@ -42,7 +46,6 @@ use thiserror::Error;
 use ui::{TintColor, prelude::*};
 use util::{ResultExt as _, maybe};
 
-use crate::provider::anthropic::{AnthropicEventMapper, count_anthropic_tokens, into_anthropic};
 use crate::provider::google::{GoogleEventMapper, into_google};
 use crate::provider::open_ai::{OpenAiEventMapper, count_open_ai_tokens, into_open_ai};
 use crate::provider::x_ai::count_xai_tokens;
@@ -1394,3 +1397,434 @@ mod tests {
         }
     }
 }
+
+fn count_anthropic_tokens(
+    request: LanguageModelRequest,
+    cx: &App,
+) -> BoxFuture<'static, Result<u64>> {
+    use gpui::AppContext as _;
+    cx.background_spawn(async move {
+        let messages = request.messages;
+        let mut tokens_from_images = 0;
+        let mut string_messages = Vec::with_capacity(messages.len());
+
+        for message in messages {
+            let mut string_contents = String::new();
+
+            for content in message.content {
+                match content {
+                    MessageContent::Text(text) => {
+                        string_contents.push_str(&text);
+                    }
+                    MessageContent::Thinking { .. } => {}
+                    MessageContent::RedactedThinking(_) => {}
+                    MessageContent::Image(image) => {
+                        tokens_from_images += image.estimate_tokens();
+                    }
+                    MessageContent::ToolUse(_tool_use) => {}
+                    MessageContent::ToolResult(tool_result) => match &tool_result.content {
+                        LanguageModelToolResultContent::Text(text) => {
+                            string_contents.push_str(text);
+                        }
+                        LanguageModelToolResultContent::Image(image) => {
+                            tokens_from_images += image.estimate_tokens();
+                        }
+                    },
+                }
+            }
+
+            if !string_contents.is_empty() {
+                string_messages.push(tiktoken_rs::ChatCompletionRequestMessage {
+                    role: match message.role {
+                        Role::User => "user".into(),
+                        Role::Assistant => "assistant".into(),
+                        Role::System => "system".into(),
+                    },
+                    content: Some(string_contents),
+                    name: None,
+                    function_call: None,
+                });
+            }
+        }
+
+        tiktoken_rs::num_tokens_from_messages("gpt-4", &string_messages)
+            .map(|tokens| (tokens + tokens_from_images) as u64)
+    })
+    .boxed()
+}
+
+fn into_anthropic(
+    request: LanguageModelRequest,
+    model: String,
+    default_temperature: f32,
+    max_output_tokens: u64,
+    mode: AnthropicModelMode,
+) -> anthropic::Request {
+    let mut new_messages: Vec<anthropic::Message> = Vec::new();
+    let mut system_message = String::new();
+
+    for message in request.messages {
+        if message.contents_empty() {
+            continue;
+        }
+
+        match message.role {
+            Role::User | Role::Assistant => {
+                let mut anthropic_message_content: Vec<anthropic::RequestContent> = message
+                    .content
+                    .into_iter()
+                    .filter_map(|content| match content {
+                        MessageContent::Text(text) => {
+                            let text = if text.chars().last().is_some_and(|c| c.is_whitespace()) {
+                                text.trim_end().to_string()
+                            } else {
+                                text
+                            };
+                            if !text.is_empty() {
+                                Some(anthropic::RequestContent::Text {
+                                    text,
+                                    cache_control: None,
+                                })
+                            } else {
+                                None
+                            }
+                        }
+                        MessageContent::Thinking {
+                            text: thinking,
+                            signature,
+                        } => {
+                            if !thinking.is_empty() {
+                                Some(anthropic::RequestContent::Thinking {
+                                    thinking,
+                                    signature: signature.unwrap_or_default(),
+                                    cache_control: None,
+                                })
+                            } else {
+                                None
+                            }
+                        }
+                        MessageContent::RedactedThinking(data) => {
+                            if !data.is_empty() {
+                                Some(anthropic::RequestContent::RedactedThinking { data })
+                            } else {
+                                None
+                            }
+                        }
+                        MessageContent::Image(image) => Some(anthropic::RequestContent::Image {
+                            source: anthropic::ImageSource {
+                                source_type: "base64".to_string(),
+                                media_type: "image/png".to_string(),
+                                data: image.source.to_string(),
+                            },
+                            cache_control: None,
+                        }),
+                        MessageContent::ToolUse(tool_use) => {
+                            Some(anthropic::RequestContent::ToolUse {
+                                id: tool_use.id.to_string(),
+                                name: tool_use.name.to_string(),
+                                input: tool_use.input,
+                                cache_control: None,
+                            })
+                        }
+                        MessageContent::ToolResult(tool_result) => {
+                            Some(anthropic::RequestContent::ToolResult {
+                                tool_use_id: tool_result.tool_use_id.to_string(),
+                                is_error: tool_result.is_error,
+                                content: match tool_result.content {
+                                    LanguageModelToolResultContent::Text(text) => {
+                                        ToolResultContent::Plain(text.to_string())
+                                    }
+                                    LanguageModelToolResultContent::Image(image) => {
+                                        ToolResultContent::Multipart(vec![ToolResultPart::Image {
+                                            source: anthropic::ImageSource {
+                                                source_type: "base64".to_string(),
+                                                media_type: "image/png".to_string(),
+                                                data: image.source.to_string(),
+                                            },
+                                        }])
+                                    }
+                                },
+                                cache_control: None,
+                            })
+                        }
+                    })
+                    .collect();
+                let anthropic_role = match message.role {
+                    Role::User => anthropic::Role::User,
+                    Role::Assistant => anthropic::Role::Assistant,
+                    Role::System => unreachable!("System role should never occur here"),
+                };
+                if let Some(last_message) = new_messages.last_mut()
+                    && last_message.role == anthropic_role
+                {
+                    last_message.content.extend(anthropic_message_content);
+                    continue;
+                }
+
+                if message.cache {
+                    let cache_control_value = Some(anthropic::CacheControl {
+                        cache_type: anthropic::CacheControlType::Ephemeral,
+                    });
+                    for message_content in anthropic_message_content.iter_mut().rev() {
+                        match message_content {
+                            anthropic::RequestContent::RedactedThinking { .. } => {}
+                            anthropic::RequestContent::Text { cache_control, .. }
+                            | anthropic::RequestContent::Thinking { cache_control, .. }
+                            | anthropic::RequestContent::Image { cache_control, .. }
+                            | anthropic::RequestContent::ToolUse { cache_control, .. }
+                            | anthropic::RequestContent::ToolResult { cache_control, .. } => {
+                                *cache_control = cache_control_value;
+                                break;
+                            }
+                        }
+                    }
+                }
+
+                new_messages.push(anthropic::Message {
+                    role: anthropic_role,
+                    content: anthropic_message_content,
+                });
+            }
+            Role::System => {
+                if !system_message.is_empty() {
+                    system_message.push_str("\n\n");
+                }
+                system_message.push_str(&message.string_contents());
+            }
+        }
+    }
+
+    anthropic::Request {
+        model,
+        messages: new_messages,
+        max_tokens: max_output_tokens,
+        system: if system_message.is_empty() {
+            None
+        } else {
+            Some(anthropic::StringOrContents::String(system_message))
+        },
+        thinking: if request.thinking_allowed
+            && let AnthropicModelMode::Thinking { budget_tokens } = mode
+        {
+            Some(anthropic::Thinking::Enabled { budget_tokens })
+        } else {
+            None
+        },
+        tools: request
+            .tools
+            .into_iter()
+            .map(|tool| anthropic::Tool {
+                name: tool.name,
+                description: tool.description,
+                input_schema: tool.input_schema,
+            })
+            .collect(),
+        tool_choice: request.tool_choice.map(|choice| match choice {
+            LanguageModelToolChoice::Auto => anthropic::ToolChoice::Auto,
+            LanguageModelToolChoice::Any => anthropic::ToolChoice::Any,
+            LanguageModelToolChoice::None => anthropic::ToolChoice::None,
+        }),
+        metadata: None,
+        stop_sequences: Vec::new(),
+        temperature: request.temperature.or(Some(default_temperature)),
+        top_k: None,
+        top_p: None,
+    }
+}
+
+struct AnthropicEventMapper {
+    tool_uses_by_index: collections::HashMap<usize, RawToolUse>,
+    usage: Usage,
+    stop_reason: StopReason,
+}
+
+impl AnthropicEventMapper {
+    fn new() -> Self {
+        Self {
+            tool_uses_by_index: collections::HashMap::default(),
+            usage: Usage::default(),
+            stop_reason: StopReason::EndTurn,
+        }
+    }
+
+    fn map_event(
+        &mut self,
+        event: Event,
+    ) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
+        match event {
+            Event::ContentBlockStart {
+                index,
+                content_block,
+            } => match content_block {
+                ResponseContent::Text { text } => {
+                    vec![Ok(LanguageModelCompletionEvent::Text(text))]
+                }
+                ResponseContent::Thinking { thinking } => {
+                    vec![Ok(LanguageModelCompletionEvent::Thinking {
+                        text: thinking,
+                        signature: None,
+                    })]
+                }
+                ResponseContent::RedactedThinking { data } => {
+                    vec![Ok(LanguageModelCompletionEvent::RedactedThinking { data })]
+                }
+                ResponseContent::ToolUse { id, name, .. } => {
+                    self.tool_uses_by_index.insert(
+                        index,
+                        RawToolUse {
+                            id,
+                            name,
+                            input_json: String::new(),
+                        },
+                    );
+                    Vec::new()
+                }
+            },
+            Event::ContentBlockDelta { index, delta } => match delta {
+                ContentDelta::TextDelta { text } => {
+                    vec![Ok(LanguageModelCompletionEvent::Text(text))]
+                }
+                ContentDelta::ThinkingDelta { thinking } => {
+                    vec![Ok(LanguageModelCompletionEvent::Thinking {
+                        text: thinking,
+                        signature: None,
+                    })]
+                }
+                ContentDelta::SignatureDelta { signature } => {
+                    vec![Ok(LanguageModelCompletionEvent::Thinking {
+                        text: "".to_string(),
+                        signature: Some(signature),
+                    })]
+                }
+                ContentDelta::InputJsonDelta { partial_json } => {
+                    if let Some(tool_use) = self.tool_uses_by_index.get_mut(&index) {
+                        tool_use.input_json.push_str(&partial_json);
+
+                        let event = serde_json::from_str::<serde_json::Value>(&tool_use.input_json)
+                            .ok()
+                            .and_then(|input| {
+                                let input_json_roundtripped = serde_json::to_string(&input).ok()?;
+
+                                if !tool_use.input_json.starts_with(&input_json_roundtripped) {
+                                    return None;
+                                }
+
+                                Some(LanguageModelCompletionEvent::ToolUse(
+                                    LanguageModelToolUse {
+                                        id: LanguageModelToolUseId::from(tool_use.id.clone()),
+                                        name: tool_use.name.clone().into(),
+                                        raw_input: tool_use.input_json.clone(),
+                                        input,
+                                        is_input_complete: false,
+                                        thought_signature: None,
+                                    },
+                                ))
+                            });
+
+                        if let Some(event) = event {
+                            vec![Ok(event)]
+                        } else {
+                            Vec::new()
+                        }
+                    } else {
+                        Vec::new()
+                    }
+                }
+            },
+            Event::ContentBlockStop { index } => {
+                if let Some(tool_use) = self.tool_uses_by_index.remove(&index) {
+                    let event_result = match serde_json::from_str(&tool_use.input_json) {
+                        Ok(input) => Ok(LanguageModelCompletionEvent::ToolUse(
+                            LanguageModelToolUse {
+                                id: LanguageModelToolUseId::from(tool_use.id),
+                                name: tool_use.name.into(),
+                                raw_input: tool_use.input_json,
+                                input,
+                                is_input_complete: true,
+                                thought_signature: None,
+                            },
+                        )),
+                        Err(json_parse_err) => {
+                            Ok(LanguageModelCompletionEvent::ToolUseJsonParseError {
+                                id: LanguageModelToolUseId::from(tool_use.id),
+                                tool_name: tool_use.name.into(),
+                                raw_input: tool_use.input_json.into(),
+                                json_parse_error: json_parse_err.to_string(),
+                            })
+                        }
+                    };
+
+                    vec![event_result]
+                } else {
+                    Vec::new()
+                }
+            }
+            Event::MessageStart { message } => {
+                update_anthropic_usage(&mut self.usage, &message.usage);
+                vec![
+                    Ok(LanguageModelCompletionEvent::UsageUpdate(
+                        convert_anthropic_usage(&self.usage),
+                    )),
+                    Ok(LanguageModelCompletionEvent::StartMessage {
+                        message_id: message.id,
+                    }),
+                ]
+            }
+            Event::MessageDelta { delta, usage } => {
+                update_anthropic_usage(&mut self.usage, &usage);
+                if let Some(stop_reason) = delta.stop_reason.as_deref() {
+                    self.stop_reason = match stop_reason {
+                        "end_turn" => StopReason::EndTurn,
+                        "max_tokens" => StopReason::MaxTokens,
+                        "tool_use" => StopReason::ToolUse,
+                        "refusal" => StopReason::Refusal,
+                        _ => {
+                            log::error!("Unexpected anthropic stop_reason: {stop_reason}");
+                            StopReason::EndTurn
+                        }
+                    };
+                }
+                vec![Ok(LanguageModelCompletionEvent::UsageUpdate(
+                    convert_anthropic_usage(&self.usage),
+                ))]
+            }
+            Event::MessageStop => {
+                vec![Ok(LanguageModelCompletionEvent::Stop(self.stop_reason))]
+            }
+            Event::Error { error } => {
+                vec![Err(error.into())]
+            }
+            _ => Vec::new(),
+        }
+    }
+}
+
+struct RawToolUse {
+    id: String,
+    name: String,
+    input_json: String,
+}
+
+fn update_anthropic_usage(usage: &mut Usage, new: &Usage) {
+    if let Some(input_tokens) = new.input_tokens {
+        usage.input_tokens = Some(input_tokens);
+    }
+    if let Some(output_tokens) = new.output_tokens {
+        usage.output_tokens = Some(output_tokens);
+    }
+    if let Some(cache_creation_input_tokens) = new.cache_creation_input_tokens {
+        usage.cache_creation_input_tokens = Some(cache_creation_input_tokens);
+    }
+    if let Some(cache_read_input_tokens) = new.cache_read_input_tokens {
+        usage.cache_read_input_tokens = Some(cache_read_input_tokens);
+    }
+}
+
+fn convert_anthropic_usage(usage: &Usage) -> language_model::TokenUsage {
+    language_model::TokenUsage {
+        input_tokens: usage.input_tokens.unwrap_or(0),
+        output_tokens: usage.output_tokens.unwrap_or(0),
+        cache_creation_input_tokens: usage.cache_creation_input_tokens.unwrap_or(0),
+        cache_read_input_tokens: usage.cache_read_input_tokens.unwrap_or(0),
+    }
+}

crates/language_models/src/settings.rs

@@ -4,16 +4,14 @@ use collections::HashMap;
 use settings::RegisterSetting;
 
 use crate::provider::{
-    anthropic::AnthropicSettings, bedrock::AmazonBedrockSettings, cloud::ZedDotDevSettings,
-    deepseek::DeepSeekSettings, google::GoogleSettings, lmstudio::LmStudioSettings,
-    mistral::MistralSettings, ollama::OllamaSettings, open_ai::OpenAiSettings,
-    open_ai_compatible::OpenAiCompatibleSettings, open_router::OpenRouterSettings,
-    vercel::VercelSettings, x_ai::XAiSettings,
+    bedrock::AmazonBedrockSettings, cloud::ZedDotDevSettings, deepseek::DeepSeekSettings,
+    google::GoogleSettings, lmstudio::LmStudioSettings, mistral::MistralSettings,
+    ollama::OllamaSettings, open_ai::OpenAiSettings, open_ai_compatible::OpenAiCompatibleSettings,
+    open_router::OpenRouterSettings, vercel::VercelSettings, x_ai::XAiSettings,
 };
 
 #[derive(Debug, RegisterSetting)]
 pub struct AllLanguageModelSettings {
-    pub anthropic: AnthropicSettings,
     pub bedrock: AmazonBedrockSettings,
     pub deepseek: DeepSeekSettings,
     pub google: GoogleSettings,
@@ -33,7 +31,6 @@ impl settings::Settings for AllLanguageModelSettings {
 
     fn from_settings(content: &settings::SettingsContent) -> Self {
         let language_models = content.language_models.clone().unwrap();
-        let anthropic = language_models.anthropic.unwrap();
         let bedrock = language_models.bedrock.unwrap();
         let deepseek = language_models.deepseek.unwrap();
         let google = language_models.google.unwrap();
@@ -47,10 +44,6 @@ impl settings::Settings for AllLanguageModelSettings {
         let x_ai = language_models.x_ai.unwrap();
         let zed_dot_dev = language_models.zed_dot_dev.unwrap();
         Self {
-            anthropic: AnthropicSettings {
-                api_url: anthropic.api_url.unwrap(),
-                available_models: anthropic.available_models.unwrap_or_default(),
-            },
             bedrock: AmazonBedrockSettings {
                 available_models: bedrock.available_models.unwrap_or_default(),
                 region: bedrock.region,

crates/settings/src/settings_content/agent.rs

@@ -255,7 +255,6 @@ impl JsonSchema for LanguageModelProviderSetting {
                     "type": "string",
                     "enum": [
                         "amazon-bedrock",
-                        "anthropic",
                         "copilot_chat",
                         "deepseek",
                         "google",

crates/settings/src/settings_content/extension.rs

@@ -20,6 +20,12 @@ pub struct ExtensionSettingsContent {
     pub auto_update_extensions: HashMap<Arc<str>, bool>,
     /// The capabilities granted to extensions.
     pub granted_extension_capabilities: Option<Vec<ExtensionCapabilityContent>>,
+    /// Extension language model providers that are allowed to read API keys from
+    /// environment variables. Each entry is a provider ID in the format
+    /// "extension_id:provider_id" (e.g., "openai:openai").
+    ///
+    /// Default: []
+    pub allowed_env_var_providers: Option<Vec<Arc<str>>>,
 }
 
 /// A capability for an extension.

crates/settings/src/settings_content/language_model.rs

@@ -8,7 +8,6 @@ use std::sync::Arc;
 #[with_fallible_options]
 #[derive(Default, Clone, Debug, Serialize, Deserialize, PartialEq, JsonSchema, MergeFrom)]
 pub struct AllLanguageModelSettingsContent {
-    pub anthropic: Option<AnthropicSettingsContent>,
     pub bedrock: Option<AmazonBedrockSettingsContent>,
     pub deepseek: Option<DeepseekSettingsContent>,
     pub google: Option<GoogleSettingsContent>,
@@ -24,35 +23,6 @@ pub struct AllLanguageModelSettingsContent {
     pub zed_dot_dev: Option<ZedDotDevSettingsContent>,
 }
 
-#[with_fallible_options]
-#[derive(Clone, Debug, Serialize, Deserialize, PartialEq, JsonSchema, MergeFrom)]
-pub struct AnthropicSettingsContent {
-    pub api_url: Option<String>,
-    pub available_models: Option<Vec<AnthropicAvailableModel>>,
-}
-
-#[with_fallible_options]
-#[derive(Clone, Debug, PartialEq, Serialize, Deserialize, JsonSchema, MergeFrom)]
-pub struct AnthropicAvailableModel {
-    /// The model's name in the Anthropic API. e.g. claude-3-5-sonnet-latest, claude-3-opus-20240229, etc
-    pub name: String,
-    /// The model's name in Zed's UI, such as in the model selector dropdown menu in the assistant panel.
-    pub display_name: Option<String>,
-    /// The model's context window size.
-    pub max_tokens: u64,
-    /// A model `name` to substitute when calling tools, in case the primary model doesn't support tool calling.
-    pub tool_override: Option<String>,
-    /// Configuration of Anthropic's caching API.
-    pub cache_configuration: Option<LanguageModelCacheConfiguration>,
-    pub max_output_tokens: Option<u64>,
-    #[serde(serialize_with = "crate::serialize_optional_f32_with_two_decimal_places")]
-    pub default_temperature: Option<f32>,
-    #[serde(default)]
-    pub extra_beta_headers: Vec<String>,
-    /// The model's mode (e.g. thinking)
-    pub mode: Option<ModelMode>,
-}
-
 #[with_fallible_options]
 #[derive(Default, Clone, Debug, Serialize, Deserialize, PartialEq, JsonSchema, MergeFrom)]
 pub struct AmazonBedrockSettingsContent {

docs/src/configuring-zed.md

@@ -2626,9 +2626,6 @@ These values take in the same options as the root-level settings with the same n
 ```json [settings]
 {
   "language_models": {
-    "anthropic": {
-      "api_url": "https://api.anthropic.com"
-    },
     "google": {
       "api_url": "https://generativelanguage.googleapis.com"
     },

extensions/anthropic/Cargo.lock

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extensions/anthropic/Cargo.toml

@@ -0,0 +1,17 @@
+[package]
+name = "anthropic"
+version = "0.1.0"
+edition = "2021"
+publish = false
+license = "Apache-2.0"
+
+[workspace]
+
+[lib]
+path = "src/anthropic.rs"
+crate-type = ["cdylib"]
+
+[dependencies]
+zed_extension_api = { path = "../../crates/extension_api" }
+serde = { version = "1.0", features = ["derive"] }
+serde_json = "1.0"

extensions/anthropic/extension.toml

@@ -0,0 +1,13 @@
+id = "anthropic"
+name = "Anthropic"
+description = "Anthropic Claude LLM provider for Zed."
+version = "0.1.0"
+schema_version = 1
+authors = ["Zed Team"]
+repository = "https://github.com/zed-industries/zed"
+
+[language_model_providers.anthropic]
+name = "Anthropic"
+
+[language_model_providers.anthropic.auth]
+env_var = "ANTHROPIC_API_KEY"

extensions/anthropic/icons/anthropic.svg

@@ -1,7 +1,7 @@
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+<path d="M11.094 3.09999H8.952L12.858 12.9H15L11.094 3.09999Z" fill="black"/>
+<path d="M4.906 3.09999L1 12.9H3.184L3.98284 10.842H8.06915L8.868 12.9H11.052L7.146 3.09999H4.906ZM4.68928 9.02199L6.026 5.57799L7.3627 9.02199H4.68928Z" fill="black"/>
 </g>
 <defs>
 <clipPath id="clip0_1896_18">

extensions/anthropic/src/anthropic.rs

@@ -0,0 +1,803 @@
+use std::collections::HashMap;
+use std::sync::Mutex;
+
+use serde::{Deserialize, Serialize};
+use zed_extension_api::http_client::{HttpMethod, HttpRequest, HttpResponseStream, RedirectPolicy};
+use zed_extension_api::{self as zed, *};
+
+struct AnthropicProvider {
+    streams: Mutex<HashMap<String, StreamState>>,
+    next_stream_id: Mutex<u64>,
+}
+
+struct StreamState {
+    response_stream: Option<HttpResponseStream>,
+    buffer: String,
+    started: bool,
+    current_tool_use: Option<ToolUseState>,
+    stop_reason: Option<LlmStopReason>,
+    pending_signature: Option<String>,
+}
+
+struct ToolUseState {
+    id: String,
+    name: String,
+    input_json: String,
+}
+
+struct ModelDefinition {
+    real_id: &'static str,
+    display_name: &'static str,
+    max_tokens: u64,
+    max_output_tokens: u64,
+    supports_images: bool,
+    supports_thinking: bool,
+    is_default: bool,
+    is_default_fast: bool,
+}
+
+const MODELS: &[ModelDefinition] = &[
+    ModelDefinition {
+        real_id: "claude-opus-4-5-20251101",
+        display_name: "Claude Opus 4.5",
+        max_tokens: 200_000,
+        max_output_tokens: 8_192,
+        supports_images: true,
+        supports_thinking: false,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        real_id: "claude-opus-4-5-20251101",
+        display_name: "Claude Opus 4.5 Thinking",
+        max_tokens: 200_000,
+        max_output_tokens: 8_192,
+        supports_images: true,
+        supports_thinking: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        real_id: "claude-sonnet-4-5-20250929",
+        display_name: "Claude Sonnet 4.5",
+        max_tokens: 200_000,
+        max_output_tokens: 8_192,
+        supports_images: true,
+        supports_thinking: false,
+        is_default: true,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        real_id: "claude-sonnet-4-5-20250929",
+        display_name: "Claude Sonnet 4.5 Thinking",
+        max_tokens: 200_000,
+        max_output_tokens: 8_192,
+        supports_images: true,
+        supports_thinking: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        real_id: "claude-sonnet-4-20250514",
+        display_name: "Claude Sonnet 4",
+        max_tokens: 200_000,
+        max_output_tokens: 8_192,
+        supports_images: true,
+        supports_thinking: false,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        real_id: "claude-sonnet-4-20250514",
+        display_name: "Claude Sonnet 4 Thinking",
+        max_tokens: 200_000,
+        max_output_tokens: 8_192,
+        supports_images: true,
+        supports_thinking: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        real_id: "claude-haiku-4-5-20251001",
+        display_name: "Claude Haiku 4.5",
+        max_tokens: 200_000,
+        max_output_tokens: 64_000,
+        supports_images: true,
+        supports_thinking: false,
+        is_default: false,
+        is_default_fast: true,
+    },
+    ModelDefinition {
+        real_id: "claude-haiku-4-5-20251001",
+        display_name: "Claude Haiku 4.5 Thinking",
+        max_tokens: 200_000,
+        max_output_tokens: 64_000,
+        supports_images: true,
+        supports_thinking: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        real_id: "claude-3-5-sonnet-latest",
+        display_name: "Claude 3.5 Sonnet",
+        max_tokens: 200_000,
+        max_output_tokens: 8_192,
+        supports_images: true,
+        supports_thinking: false,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        real_id: "claude-3-5-haiku-latest",
+        display_name: "Claude 3.5 Haiku",
+        max_tokens: 200_000,
+        max_output_tokens: 8_192,
+        supports_images: true,
+        supports_thinking: false,
+        is_default: false,
+        is_default_fast: false,
+    },
+];
+
+fn get_model_definition(display_name: &str) -> Option<&'static ModelDefinition> {
+    MODELS.iter().find(|m| m.display_name == display_name)
+}
+
+// Anthropic API Request Types
+
+#[derive(Serialize)]
+struct AnthropicRequest {
+    model: String,
+    max_tokens: u64,
+    messages: Vec<AnthropicMessage>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    system: Option<String>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    thinking: Option<AnthropicThinking>,
+    #[serde(skip_serializing_if = "Vec::is_empty")]
+    tools: Vec<AnthropicTool>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    tool_choice: Option<AnthropicToolChoice>,
+    #[serde(skip_serializing_if = "Vec::is_empty")]
+    stop_sequences: Vec<String>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    temperature: Option<f32>,
+    stream: bool,
+}
+
+#[derive(Serialize)]
+struct AnthropicThinking {
+    #[serde(rename = "type")]
+    thinking_type: String,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    budget_tokens: Option<u32>,
+}
+
+#[derive(Serialize)]
+struct AnthropicMessage {
+    role: String,
+    content: Vec<AnthropicContent>,
+}
+
+#[derive(Serialize, Clone)]
+#[serde(tag = "type")]
+enum AnthropicContent {
+    #[serde(rename = "text")]
+    Text { text: String },
+    #[serde(rename = "thinking")]
+    Thinking { thinking: String, signature: String },
+    #[serde(rename = "redacted_thinking")]
+    RedactedThinking { data: String },
+    #[serde(rename = "image")]
+    Image { source: AnthropicImageSource },
+    #[serde(rename = "tool_use")]
+    ToolUse {
+        id: String,
+        name: String,
+        input: serde_json::Value,
+    },
+    #[serde(rename = "tool_result")]
+    ToolResult {
+        tool_use_id: String,
+        is_error: bool,
+        content: String,
+    },
+}
+
+#[derive(Serialize, Clone)]
+struct AnthropicImageSource {
+    #[serde(rename = "type")]
+    source_type: String,
+    media_type: String,
+    data: String,
+}
+
+#[derive(Serialize)]
+struct AnthropicTool {
+    name: String,
+    description: String,
+    input_schema: serde_json::Value,
+}
+
+#[derive(Serialize)]
+#[serde(tag = "type", rename_all = "lowercase")]
+enum AnthropicToolChoice {
+    Auto,
+    Any,
+    None,
+}
+
+// Anthropic API Response Types
+
+#[derive(Deserialize, Debug)]
+#[serde(tag = "type")]
+#[allow(dead_code)]
+enum AnthropicEvent {
+    #[serde(rename = "message_start")]
+    MessageStart { message: AnthropicMessageResponse },
+    #[serde(rename = "content_block_start")]
+    ContentBlockStart {
+        index: usize,
+        content_block: AnthropicContentBlock,
+    },
+    #[serde(rename = "content_block_delta")]
+    ContentBlockDelta { index: usize, delta: AnthropicDelta },
+    #[serde(rename = "content_block_stop")]
+    ContentBlockStop { index: usize },
+    #[serde(rename = "message_delta")]
+    MessageDelta {
+        delta: AnthropicMessageDelta,
+        usage: AnthropicUsage,
+    },
+    #[serde(rename = "message_stop")]
+    MessageStop,
+    #[serde(rename = "ping")]
+    Ping,
+    #[serde(rename = "error")]
+    Error { error: AnthropicApiError },
+}
+
+#[derive(Deserialize, Debug)]
+struct AnthropicMessageResponse {
+    #[allow(dead_code)]
+    id: String,
+    #[allow(dead_code)]
+    role: String,
+    #[serde(default)]
+    usage: AnthropicUsage,
+}
+
+#[derive(Deserialize, Debug)]
+#[serde(tag = "type")]
+enum AnthropicContentBlock {
+    #[serde(rename = "text")]
+    Text { text: String },
+    #[serde(rename = "thinking")]
+    Thinking { thinking: String },
+    #[serde(rename = "redacted_thinking")]
+    RedactedThinking { data: String },
+    #[serde(rename = "tool_use")]
+    ToolUse { id: String, name: String },
+}
+
+#[derive(Deserialize, Debug)]
+#[serde(tag = "type")]
+enum AnthropicDelta {
+    #[serde(rename = "text_delta")]
+    TextDelta { text: String },
+    #[serde(rename = "thinking_delta")]
+    ThinkingDelta { thinking: String },
+    #[serde(rename = "signature_delta")]
+    SignatureDelta { signature: String },
+    #[serde(rename = "input_json_delta")]
+    InputJsonDelta { partial_json: String },
+}
+
+#[derive(Deserialize, Debug)]
+struct AnthropicMessageDelta {
+    stop_reason: Option<String>,
+}
+
+#[derive(Deserialize, Debug, Default)]
+struct AnthropicUsage {
+    #[serde(default)]
+    input_tokens: Option<u64>,
+    #[serde(default)]
+    output_tokens: Option<u64>,
+    #[serde(default)]
+    cache_creation_input_tokens: Option<u64>,
+    #[serde(default)]
+    cache_read_input_tokens: Option<u64>,
+}
+
+#[derive(Deserialize, Debug)]
+struct AnthropicApiError {
+    #[serde(rename = "type")]
+    #[allow(dead_code)]
+    error_type: String,
+    message: String,
+}
+
+fn convert_request(
+    model_id: &str,
+    request: &LlmCompletionRequest,
+) -> Result<AnthropicRequest, String> {
+    let model_def =
+        get_model_definition(model_id).ok_or_else(|| format!("Unknown model: {}", model_id))?;
+
+    let mut messages: Vec<AnthropicMessage> = Vec::new();
+    let mut system_message = String::new();
+
+    for msg in &request.messages {
+        match msg.role {
+            LlmMessageRole::System => {
+                for content in &msg.content {
+                    if let LlmMessageContent::Text(text) = content {
+                        if !system_message.is_empty() {
+                            system_message.push('\n');
+                        }
+                        system_message.push_str(text);
+                    }
+                }
+            }
+            LlmMessageRole::User => {
+                let mut contents: Vec<AnthropicContent> = Vec::new();
+
+                for content in &msg.content {
+                    match content {
+                        LlmMessageContent::Text(text) => {
+                            if !text.is_empty() {
+                                contents.push(AnthropicContent::Text { text: text.clone() });
+                            }
+                        }
+                        LlmMessageContent::Image(img) => {
+                            contents.push(AnthropicContent::Image {
+                                source: AnthropicImageSource {
+                                    source_type: "base64".to_string(),
+                                    media_type: "image/png".to_string(),
+                                    data: img.source.clone(),
+                                },
+                            });
+                        }
+                        LlmMessageContent::ToolResult(result) => {
+                            let content_text = match &result.content {
+                                LlmToolResultContent::Text(t) => t.clone(),
+                                LlmToolResultContent::Image(_) => "[Image]".to_string(),
+                            };
+                            contents.push(AnthropicContent::ToolResult {
+                                tool_use_id: result.tool_use_id.clone(),
+                                is_error: result.is_error,
+                                content: content_text,
+                            });
+                        }
+                        _ => {}
+                    }
+                }
+
+                if !contents.is_empty() {
+                    messages.push(AnthropicMessage {
+                        role: "user".to_string(),
+                        content: contents,
+                    });
+                }
+            }
+            LlmMessageRole::Assistant => {
+                let mut contents: Vec<AnthropicContent> = Vec::new();
+
+                for content in &msg.content {
+                    match content {
+                        LlmMessageContent::Text(text) => {
+                            if !text.is_empty() {
+                                contents.push(AnthropicContent::Text { text: text.clone() });
+                            }
+                        }
+                        LlmMessageContent::ToolUse(tool_use) => {
+                            let input: serde_json::Value =
+                                serde_json::from_str(&tool_use.input).unwrap_or_default();
+                            contents.push(AnthropicContent::ToolUse {
+                                id: tool_use.id.clone(),
+                                name: tool_use.name.clone(),
+                                input,
+                            });
+                        }
+                        LlmMessageContent::Thinking(thinking) => {
+                            if !thinking.text.is_empty() {
+                                contents.push(AnthropicContent::Thinking {
+                                    thinking: thinking.text.clone(),
+                                    signature: thinking.signature.clone().unwrap_or_default(),
+                                });
+                            }
+                        }
+                        LlmMessageContent::RedactedThinking(data) => {
+                            if !data.is_empty() {
+                                contents.push(AnthropicContent::RedactedThinking {
+                                    data: data.clone(),
+                                });
+                            }
+                        }
+                        _ => {}
+                    }
+                }
+
+                if !contents.is_empty() {
+                    messages.push(AnthropicMessage {
+                        role: "assistant".to_string(),
+                        content: contents,
+                    });
+                }
+            }
+        }
+    }
+
+    let tools: Vec<AnthropicTool> = request
+        .tools
+        .iter()
+        .map(|t| AnthropicTool {
+            name: t.name.clone(),
+            description: t.description.clone(),
+            input_schema: serde_json::from_str(&t.input_schema)
+                .unwrap_or(serde_json::Value::Object(Default::default())),
+        })
+        .collect();
+
+    let tool_choice = request.tool_choice.as_ref().map(|tc| match tc {
+        LlmToolChoice::Auto => AnthropicToolChoice::Auto,
+        LlmToolChoice::Any => AnthropicToolChoice::Any,
+        LlmToolChoice::None => AnthropicToolChoice::None,
+    });
+
+    let thinking = if model_def.supports_thinking && request.thinking_allowed {
+        Some(AnthropicThinking {
+            thinking_type: "enabled".to_string(),
+            budget_tokens: Some(4096),
+        })
+    } else {
+        None
+    };
+
+    Ok(AnthropicRequest {
+        model: model_def.real_id.to_string(),
+        max_tokens: model_def.max_output_tokens,
+        messages,
+        system: if system_message.is_empty() {
+            None
+        } else {
+            Some(system_message)
+        },
+        thinking,
+        tools,
+        tool_choice,
+        stop_sequences: request.stop_sequences.clone(),
+        temperature: request.temperature,
+        stream: true,
+    })
+}
+
+fn parse_sse_line(line: &str) -> Option<AnthropicEvent> {
+    let data = line.strip_prefix("data: ")?;
+    serde_json::from_str(data).ok()
+}
+
+impl zed::Extension for AnthropicProvider {
+    fn new() -> Self {
+        Self {
+            streams: Mutex::new(HashMap::new()),
+            next_stream_id: Mutex::new(0),
+        }
+    }
+
+    fn llm_providers(&self) -> Vec<LlmProviderInfo> {
+        vec![LlmProviderInfo {
+            id: "anthropic".into(),
+            name: "Anthropic".into(),
+            icon: Some("icons/anthropic.svg".into()),
+        }]
+    }
+
+    fn llm_provider_models(&self, _provider_id: &str) -> Result<Vec<LlmModelInfo>, String> {
+        Ok(MODELS
+            .iter()
+            .map(|m| LlmModelInfo {
+                id: m.display_name.to_string(),
+                name: m.display_name.to_string(),
+                max_token_count: m.max_tokens,
+                max_output_tokens: Some(m.max_output_tokens),
+                capabilities: LlmModelCapabilities {
+                    supports_images: m.supports_images,
+                    supports_tools: true,
+                    supports_tool_choice_auto: true,
+                    supports_tool_choice_any: true,
+                    supports_tool_choice_none: true,
+                    supports_thinking: m.supports_thinking,
+                    tool_input_format: LlmToolInputFormat::JsonSchema,
+                },
+                is_default: m.is_default,
+                is_default_fast: m.is_default_fast,
+            })
+            .collect())
+    }
+
+    fn llm_provider_is_authenticated(&self, _provider_id: &str) -> bool {
+        llm_get_credential("anthropic").is_some()
+    }
+
+    fn llm_provider_settings_markdown(&self, _provider_id: &str) -> Option<String> {
+        Some(
+            r#"# Anthropic Setup
+
+Welcome to **Anthropic**! This extension provides access to Claude models.
+
+## Configuration
+
+Enter your Anthropic API key below. You can get your API key at [console.anthropic.com](https://console.anthropic.com/).
+
+## Available Models
+
+| Display Name | Real Model | Context | Output |
+|--------------|------------|---------|--------|
+| Claude Opus 4.5 | claude-opus-4-5 | 200K | 8K |
+| Claude Opus 4.5 Thinking | claude-opus-4-5 | 200K | 8K |
+| Claude Sonnet 4.5 | claude-sonnet-4-5 | 200K | 8K |
+| Claude Sonnet 4.5 Thinking | claude-sonnet-4-5 | 200K | 8K |
+| Claude Sonnet 4 | claude-sonnet-4 | 200K | 8K |
+| Claude Sonnet 4 Thinking | claude-sonnet-4 | 200K | 8K |
+| Claude Haiku 4.5 | claude-haiku-4-5 | 200K | 64K |
+| Claude Haiku 4.5 Thinking | claude-haiku-4-5 | 200K | 64K |
+| Claude 3.5 Sonnet | claude-3-5-sonnet | 200K | 8K |
+| Claude 3.5 Haiku | claude-3-5-haiku | 200K | 8K |
+
+## Features
+
+- ✅ Full streaming support
+- ✅ Tool/function calling
+- ✅ Vision (image inputs)
+- ✅ Extended thinking support
+- ✅ All Claude models
+
+## Pricing
+
+Uses your Anthropic API credits. See [Anthropic pricing](https://www.anthropic.com/pricing) for details.
+"#
+            .to_string(),
+        )
+    }
+
+    fn llm_provider_authenticate(&mut self, _provider_id: &str) -> Result<(), String> {
+        let provided = llm_request_credential(
+            "anthropic",
+            LlmCredentialType::ApiKey,
+            "Anthropic API Key",
+            "sk-ant-...",
+        )?;
+        if provided {
+            Ok(())
+        } else {
+            Err("Authentication cancelled".to_string())
+        }
+    }
+
+    fn llm_provider_reset_credentials(&mut self, _provider_id: &str) -> Result<(), String> {
+        llm_delete_credential("anthropic")
+    }
+
+    fn llm_stream_completion_start(
+        &mut self,
+        _provider_id: &str,
+        model_id: &str,
+        request: &LlmCompletionRequest,
+    ) -> Result<String, String> {
+        let api_key = llm_get_credential("anthropic").ok_or_else(|| {
+            "No API key configured. Please add your Anthropic API key in settings.".to_string()
+        })?;
+
+        let anthropic_request = convert_request(model_id, request)?;
+
+        let body = serde_json::to_vec(&anthropic_request)
+            .map_err(|e| format!("Failed to serialize request: {}", e))?;
+
+        let http_request = HttpRequest {
+            method: HttpMethod::Post,
+            url: "https://api.anthropic.com/v1/messages".to_string(),
+            headers: vec![
+                ("Content-Type".to_string(), "application/json".to_string()),
+                ("x-api-key".to_string(), api_key),
+                ("anthropic-version".to_string(), "2023-06-01".to_string()),
+            ],
+            body: Some(body),
+            redirect_policy: RedirectPolicy::FollowAll,
+        };
+
+        let response_stream = http_request
+            .fetch_stream()
+            .map_err(|e| format!("HTTP request failed: {}", e))?;
+
+        let stream_id = {
+            let mut id_counter = self.next_stream_id.lock().unwrap();
+            let id = format!("anthropic-stream-{}", *id_counter);
+            *id_counter += 1;
+            id
+        };
+
+        self.streams.lock().unwrap().insert(
+            stream_id.clone(),
+            StreamState {
+                response_stream: Some(response_stream),
+                buffer: String::new(),
+                started: false,
+                current_tool_use: None,
+                stop_reason: None,
+                pending_signature: None,
+            },
+        );
+
+        Ok(stream_id)
+    }
+
+    fn llm_stream_completion_next(
+        &mut self,
+        stream_id: &str,
+    ) -> Result<Option<LlmCompletionEvent>, String> {
+        let mut streams = self.streams.lock().unwrap();
+        let state = streams
+            .get_mut(stream_id)
+            .ok_or_else(|| format!("Unknown stream: {}", stream_id))?;
+
+        if !state.started {
+            state.started = true;
+            return Ok(Some(LlmCompletionEvent::Started));
+        }
+
+        let response_stream = state
+            .response_stream
+            .as_mut()
+            .ok_or_else(|| "Stream already closed".to_string())?;
+
+        loop {
+            if let Some(newline_pos) = state.buffer.find('\n') {
+                let line = state.buffer[..newline_pos].to_string();
+                state.buffer = state.buffer[newline_pos + 1..].to_string();
+
+                if line.trim().is_empty() || line.starts_with("event:") {
+                    continue;
+                }
+
+                if let Some(event) = parse_sse_line(&line) {
+                    match event {
+                        AnthropicEvent::MessageStart { message } => {
+                            if let (Some(input), Some(output)) =
+                                (message.usage.input_tokens, message.usage.output_tokens)
+                            {
+                                return Ok(Some(LlmCompletionEvent::Usage(LlmTokenUsage {
+                                    input_tokens: input,
+                                    output_tokens: output,
+                                    cache_creation_input_tokens: message
+                                        .usage
+                                        .cache_creation_input_tokens,
+                                    cache_read_input_tokens: message.usage.cache_read_input_tokens,
+                                })));
+                            }
+                        }
+                        AnthropicEvent::ContentBlockStart { content_block, .. } => {
+                            match content_block {
+                                AnthropicContentBlock::Text { text } => {
+                                    if !text.is_empty() {
+                                        return Ok(Some(LlmCompletionEvent::Text(text)));
+                                    }
+                                }
+                                AnthropicContentBlock::Thinking { thinking } => {
+                                    return Ok(Some(LlmCompletionEvent::Thinking(
+                                        LlmThinkingContent {
+                                            text: thinking,
+                                            signature: None,
+                                        },
+                                    )));
+                                }
+                                AnthropicContentBlock::RedactedThinking { data } => {
+                                    return Ok(Some(LlmCompletionEvent::RedactedThinking(data)));
+                                }
+                                AnthropicContentBlock::ToolUse { id, name } => {
+                                    state.current_tool_use = Some(ToolUseState {
+                                        id,
+                                        name,
+                                        input_json: String::new(),
+                                    });
+                                }
+                            }
+                        }
+                        AnthropicEvent::ContentBlockDelta { delta, .. } => match delta {
+                            AnthropicDelta::TextDelta { text } => {
+                                if !text.is_empty() {
+                                    return Ok(Some(LlmCompletionEvent::Text(text)));
+                                }
+                            }
+                            AnthropicDelta::ThinkingDelta { thinking } => {
+                                return Ok(Some(LlmCompletionEvent::Thinking(
+                                    LlmThinkingContent {
+                                        text: thinking,
+                                        signature: None,
+                                    },
+                                )));
+                            }
+                            AnthropicDelta::SignatureDelta { signature } => {
+                                state.pending_signature = Some(signature.clone());
+                                return Ok(Some(LlmCompletionEvent::Thinking(
+                                    LlmThinkingContent {
+                                        text: String::new(),
+                                        signature: Some(signature),
+                                    },
+                                )));
+                            }
+                            AnthropicDelta::InputJsonDelta { partial_json } => {
+                                if let Some(ref mut tool_use) = state.current_tool_use {
+                                    tool_use.input_json.push_str(&partial_json);
+                                }
+                            }
+                        },
+                        AnthropicEvent::ContentBlockStop { .. } => {
+                            if let Some(tool_use) = state.current_tool_use.take() {
+                                return Ok(Some(LlmCompletionEvent::ToolUse(LlmToolUse {
+                                    id: tool_use.id,
+                                    name: tool_use.name,
+                                    input: tool_use.input_json,
+                                    thought_signature: state.pending_signature.take(),
+                                })));
+                            }
+                        }
+                        AnthropicEvent::MessageDelta { delta, usage } => {
+                            if let Some(reason) = delta.stop_reason {
+                                state.stop_reason = Some(match reason.as_str() {
+                                    "end_turn" => LlmStopReason::EndTurn,
+                                    "max_tokens" => LlmStopReason::MaxTokens,
+                                    "tool_use" => LlmStopReason::ToolUse,
+                                    _ => LlmStopReason::EndTurn,
+                                });
+                            }
+                            if let Some(output) = usage.output_tokens {
+                                return Ok(Some(LlmCompletionEvent::Usage(LlmTokenUsage {
+                                    input_tokens: usage.input_tokens.unwrap_or(0),
+                                    output_tokens: output,
+                                    cache_creation_input_tokens: usage.cache_creation_input_tokens,
+                                    cache_read_input_tokens: usage.cache_read_input_tokens,
+                                })));
+                            }
+                        }
+                        AnthropicEvent::MessageStop => {
+                            if let Some(stop_reason) = state.stop_reason.take() {
+                                return Ok(Some(LlmCompletionEvent::Stop(stop_reason)));
+                            }
+                            return Ok(Some(LlmCompletionEvent::Stop(LlmStopReason::EndTurn)));
+                        }
+                        AnthropicEvent::Ping => {}
+                        AnthropicEvent::Error { error } => {
+                            return Err(format!("API error: {}", error.message));
+                        }
+                    }
+                }
+
+                continue;
+            }
+
+            match response_stream.next_chunk() {
+                Ok(Some(chunk)) => {
+                    let text = String::from_utf8_lossy(&chunk);
+                    state.buffer.push_str(&text);
+                }
+                Ok(None) => {
+                    if let Some(stop_reason) = state.stop_reason.take() {
+                        return Ok(Some(LlmCompletionEvent::Stop(stop_reason)));
+                    }
+                    return Ok(None);
+                }
+                Err(e) => {
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+            }
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+    }
+
+    fn llm_stream_completion_close(&mut self, stream_id: &str) {
+        self.streams.lock().unwrap().remove(stream_id);
+    }
+}
+
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extensions/copilot-chat/Cargo.toml

@@ -0,0 +1,17 @@
+[package]
+name = "copilot-chat"
+version = "0.1.0"
+edition = "2021"
+publish = false
+license = "Apache-2.0"
+
+[workspace]
+
+[lib]
+path = "src/copilot_chat.rs"
+crate-type = ["cdylib"]
+
+[dependencies]
+zed_extension_api = { path = "../../crates/extension_api" }
+serde = { version = "1.0", features = ["derive"] }
+serde_json = "1.0"

extensions/copilot-chat/extension.toml

@@ -0,0 +1,13 @@
+id = "copilot-chat"
+name = "Copilot Chat"
+description = "GitHub Copilot Chat LLM provider for Zed."
+version = "0.1.0"
+schema_version = 1
+authors = ["Zed Team"]
+repository = "https://github.com/zed-industries/zed"
+
+[language_model_providers.copilot-chat]
+name = "Copilot Chat"
+
+[language_model_providers.copilot-chat.auth]
+env_var = "GH_COPILOT_TOKEN"

extensions/copilot-chat/icons/copilot.svg

@@ -0,0 +1,9 @@
+<svg width="16" height="16" viewBox="0 0 16 16" fill="none" xmlns="http://www.w3.org/2000/svg">
+<path fill-rule="evenodd" clip-rule="evenodd" d="M6.44643 8.76593C6.83106 8.76593 7.14286 9.0793 7.14286 9.46588V10.9825C7.14286 11.369 6.83106 11.6824 6.44643 11.6824C6.06181 11.6824 5.75 11.369 5.75 10.9825V9.46588C5.75 9.0793 6.06181 8.76593 6.44643 8.76593Z" fill="black"/>
+<path fill-rule="evenodd" clip-rule="evenodd" d="M9.57168 8.76593C9.95631 8.76593 10.2681 9.0793 10.2681 9.46588V10.9825C10.2681 11.369 9.95631 11.6824 9.57168 11.6824C9.18705 11.6824 8.87524 11.369 8.87524 10.9825V9.46588C8.87524 9.0793 9.18705 8.76593 9.57168 8.76593Z" fill="black"/>
+<path d="M7.99976 4.17853C7.99976 6.67853 5.83695 7.28202 4.30332 7.28202C2.76971 7.28202 2.44604 6.1547 2.44604 4.76409C2.44604 3.37347 3.68929 2.24615 5.2229 2.24615C6.75651 2.24615 7.99976 2.78791 7.99976 4.17853Z" fill="black" fill-opacity="0.5" stroke="black" stroke-width="1.2"/>
+<path d="M8 4.17853C8 6.67853 10.1628 7.28202 11.6965 7.28202C13.2301 7.28202 13.5537 6.1547 13.5537 4.76409C13.5537 3.37347 12.3105 2.24615 10.7769 2.24615C9.24325 2.24615 8 2.78791 8 4.17853Z" fill="black" fill-opacity="0.5" stroke="black" stroke-width="1.2"/>
+<path d="M12.5894 6.875C12.5894 6.875 13.3413 7.35585 13.7144 8.08398C14.0876 8.81212 14.0894 10.4985 13.7144 11.1064C13.3395 11.7143 12.8931 12.1429 11.7637 12.7543C10.6344 13.3657 9.143 13.7321 9.143 13.7321H6.85728C6.85728 13.7321 5.37513 13.4107 4.23656 12.7543C3.09798 12.0978 2.55371 11.6786 2.28585 11.1064C2.01799 10.5342 1.92871 8.85715 2.28585 8.08398C2.64299 7.31081 3.42871 6.875 3.42871 6.875" stroke="black" stroke-width="1.2" stroke-linejoin="round"/>
+<path d="M11.9375 12.6016V7.33636L13.9052 7.99224V10.9255L11.9375 12.6016Z" fill="black" fill-opacity="0.75"/>
+<path d="M4.01793 12.6016V7.33636L2.05029 7.99224V10.9255L4.01793 12.6016Z" fill="black" fill-opacity="0.75"/>
+</svg>

extensions/copilot-chat/src/copilot_chat.rs

@@ -0,0 +1,696 @@
+use std::collections::HashMap;
+use std::sync::Mutex;
+
+use serde::{Deserialize, Serialize};
+use zed_extension_api::http_client::{HttpMethod, HttpRequest, HttpResponseStream, RedirectPolicy};
+use zed_extension_api::{self as zed, *};
+
+struct CopilotChatProvider {
+    streams: Mutex<HashMap<String, StreamState>>,
+    next_stream_id: Mutex<u64>,
+}
+
+struct StreamState {
+    response_stream: Option<HttpResponseStream>,
+    buffer: String,
+    started: bool,
+    tool_calls: HashMap<usize, AccumulatedToolCall>,
+    tool_calls_emitted: bool,
+}
+
+#[derive(Clone, Default)]
+struct AccumulatedToolCall {
+    id: String,
+    name: String,
+    arguments: String,
+}
+
+struct ModelDefinition {
+    id: &'static str,
+    display_name: &'static str,
+    max_tokens: u64,
+    max_output_tokens: Option<u64>,
+    supports_images: bool,
+    is_default: bool,
+    is_default_fast: bool,
+}
+
+const MODELS: &[ModelDefinition] = &[
+    ModelDefinition {
+        id: "gpt-4o",
+        display_name: "GPT-4o",
+        max_tokens: 128_000,
+        max_output_tokens: Some(16_384),
+        supports_images: true,
+        is_default: true,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        id: "gpt-4o-mini",
+        display_name: "GPT-4o Mini",
+        max_tokens: 128_000,
+        max_output_tokens: Some(16_384),
+        supports_images: true,
+        is_default: false,
+        is_default_fast: true,
+    },
+    ModelDefinition {
+        id: "gpt-4.1",
+        display_name: "GPT-4.1",
+        max_tokens: 1_000_000,
+        max_output_tokens: Some(32_768),
+        supports_images: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        id: "o1",
+        display_name: "o1",
+        max_tokens: 200_000,
+        max_output_tokens: Some(100_000),
+        supports_images: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        id: "o3-mini",
+        display_name: "o3-mini",
+        max_tokens: 200_000,
+        max_output_tokens: Some(100_000),
+        supports_images: false,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        id: "claude-3.5-sonnet",
+        display_name: "Claude 3.5 Sonnet",
+        max_tokens: 200_000,
+        max_output_tokens: Some(8_192),
+        supports_images: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        id: "claude-3.7-sonnet",
+        display_name: "Claude 3.7 Sonnet",
+        max_tokens: 200_000,
+        max_output_tokens: Some(8_192),
+        supports_images: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        id: "gemini-2.0-flash-001",
+        display_name: "Gemini 2.0 Flash",
+        max_tokens: 1_000_000,
+        max_output_tokens: Some(8_192),
+        supports_images: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+];
+
+fn get_model_definition(model_id: &str) -> Option<&'static ModelDefinition> {
+    MODELS.iter().find(|m| m.id == model_id)
+}
+
+#[derive(Serialize)]
+struct OpenAiRequest {
+    model: String,
+    messages: Vec<OpenAiMessage>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    max_tokens: Option<u64>,
+    #[serde(skip_serializing_if = "Vec::is_empty")]
+    tools: Vec<OpenAiTool>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    tool_choice: Option<String>,
+    #[serde(skip_serializing_if = "Vec::is_empty")]
+    stop: Vec<String>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    temperature: Option<f32>,
+    stream: bool,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    stream_options: Option<StreamOptions>,
+}
+
+#[derive(Serialize)]
+struct StreamOptions {
+    include_usage: bool,
+}
+
+#[derive(Serialize)]
+struct OpenAiMessage {
+    role: String,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    content: Option<OpenAiContent>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    tool_calls: Option<Vec<OpenAiToolCall>>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    tool_call_id: Option<String>,
+}
+
+#[derive(Serialize, Clone)]
+#[serde(untagged)]
+enum OpenAiContent {
+    Text(String),
+    Parts(Vec<OpenAiContentPart>),
+}
+
+#[derive(Serialize, Clone)]
+#[serde(tag = "type")]
+enum OpenAiContentPart {
+    #[serde(rename = "text")]
+    Text { text: String },
+    #[serde(rename = "image_url")]
+    ImageUrl { image_url: ImageUrl },
+}
+
+#[derive(Serialize, Clone)]
+struct ImageUrl {
+    url: String,
+}
+
+#[derive(Serialize, Clone)]
+struct OpenAiToolCall {
+    id: String,
+    #[serde(rename = "type")]
+    call_type: String,
+    function: OpenAiFunctionCall,
+}
+
+#[derive(Serialize, Clone)]
+struct OpenAiFunctionCall {
+    name: String,
+    arguments: String,
+}
+
+#[derive(Serialize)]
+struct OpenAiTool {
+    #[serde(rename = "type")]
+    tool_type: String,
+    function: OpenAiFunctionDef,
+}
+
+#[derive(Serialize)]
+struct OpenAiFunctionDef {
+    name: String,
+    description: String,
+    parameters: serde_json::Value,
+}
+
+#[derive(Deserialize, Debug)]
+struct OpenAiStreamResponse {
+    choices: Vec<OpenAiStreamChoice>,
+    #[serde(default)]
+    usage: Option<OpenAiUsage>,
+}
+
+#[derive(Deserialize, Debug)]
+struct OpenAiStreamChoice {
+    delta: OpenAiDelta,
+    finish_reason: Option<String>,
+}
+
+#[derive(Deserialize, Debug, Default)]
+struct OpenAiDelta {
+    #[serde(default)]
+    content: Option<String>,
+    #[serde(default)]
+    tool_calls: Option<Vec<OpenAiToolCallDelta>>,
+}
+
+#[derive(Deserialize, Debug)]
+struct OpenAiToolCallDelta {
+    index: usize,
+    #[serde(default)]
+    id: Option<String>,
+    #[serde(default)]
+    function: Option<OpenAiFunctionDelta>,
+}
+
+#[derive(Deserialize, Debug, Default)]
+struct OpenAiFunctionDelta {
+    #[serde(default)]
+    name: Option<String>,
+    #[serde(default)]
+    arguments: Option<String>,
+}
+
+#[derive(Deserialize, Debug)]
+struct OpenAiUsage {
+    prompt_tokens: u64,
+    completion_tokens: u64,
+}
+
+fn convert_request(
+    model_id: &str,
+    request: &LlmCompletionRequest,
+) -> Result<OpenAiRequest, String> {
+    let mut messages: Vec<OpenAiMessage> = Vec::new();
+
+    for msg in &request.messages {
+        match msg.role {
+            LlmMessageRole::System => {
+                let mut text_content = String::new();
+                for content in &msg.content {
+                    if let LlmMessageContent::Text(text) = content {
+                        if !text_content.is_empty() {
+                            text_content.push('\n');
+                        }
+                        text_content.push_str(text);
+                    }
+                }
+                if !text_content.is_empty() {
+                    messages.push(OpenAiMessage {
+                        role: "system".to_string(),
+                        content: Some(OpenAiContent::Text(text_content)),
+                        tool_calls: None,
+                        tool_call_id: None,
+                    });
+                }
+            }
+            LlmMessageRole::User => {
+                let mut parts: Vec<OpenAiContentPart> = Vec::new();
+                let mut tool_result_messages: Vec<OpenAiMessage> = Vec::new();
+
+                for content in &msg.content {
+                    match content {
+                        LlmMessageContent::Text(text) => {
+                            if !text.is_empty() {
+                                parts.push(OpenAiContentPart::Text { text: text.clone() });
+                            }
+                        }
+                        LlmMessageContent::Image(img) => {
+                            let data_url = format!("data:image/png;base64,{}", img.source);
+                            parts.push(OpenAiContentPart::ImageUrl {
+                                image_url: ImageUrl { url: data_url },
+                            });
+                        }
+                        LlmMessageContent::ToolResult(result) => {
+                            let content_text = match &result.content {
+                                LlmToolResultContent::Text(t) => t.clone(),
+                                LlmToolResultContent::Image(_) => "[Image]".to_string(),
+                            };
+                            tool_result_messages.push(OpenAiMessage {
+                                role: "tool".to_string(),
+                                content: Some(OpenAiContent::Text(content_text)),
+                                tool_calls: None,
+                                tool_call_id: Some(result.tool_use_id.clone()),
+                            });
+                        }
+                        _ => {}
+                    }
+                }
+
+                if !parts.is_empty() {
+                    let content = if parts.len() == 1 {
+                        if let OpenAiContentPart::Text { text } = &parts[0] {
+                            OpenAiContent::Text(text.clone())
+                        } else {
+                            OpenAiContent::Parts(parts)
+                        }
+                    } else {
+                        OpenAiContent::Parts(parts)
+                    };
+
+                    messages.push(OpenAiMessage {
+                        role: "user".to_string(),
+                        content: Some(content),
+                        tool_calls: None,
+                        tool_call_id: None,
+                    });
+                }
+
+                messages.extend(tool_result_messages);
+            }
+            LlmMessageRole::Assistant => {
+                let mut text_content = String::new();
+                let mut tool_calls: Vec<OpenAiToolCall> = Vec::new();
+
+                for content in &msg.content {
+                    match content {
+                        LlmMessageContent::Text(text) => {
+                            if !text.is_empty() {
+                                if !text_content.is_empty() {
+                                    text_content.push('\n');
+                                }
+                                text_content.push_str(text);
+                            }
+                        }
+                        LlmMessageContent::ToolUse(tool_use) => {
+                            tool_calls.push(OpenAiToolCall {
+                                id: tool_use.id.clone(),
+                                call_type: "function".to_string(),
+                                function: OpenAiFunctionCall {
+                                    name: tool_use.name.clone(),
+                                    arguments: tool_use.input.clone(),
+                                },
+                            });
+                        }
+                        _ => {}
+                    }
+                }
+
+                messages.push(OpenAiMessage {
+                    role: "assistant".to_string(),
+                    content: if text_content.is_empty() {
+                        None
+                    } else {
+                        Some(OpenAiContent::Text(text_content))
+                    },
+                    tool_calls: if tool_calls.is_empty() {
+                        None
+                    } else {
+                        Some(tool_calls)
+                    },
+                    tool_call_id: None,
+                });
+            }
+        }
+    }
+
+    let tools: Vec<OpenAiTool> = request
+        .tools
+        .iter()
+        .map(|t| OpenAiTool {
+            tool_type: "function".to_string(),
+            function: OpenAiFunctionDef {
+                name: t.name.clone(),
+                description: t.description.clone(),
+                parameters: serde_json::from_str(&t.input_schema)
+                    .unwrap_or(serde_json::Value::Object(Default::default())),
+            },
+        })
+        .collect();
+
+    let tool_choice = request.tool_choice.as_ref().map(|tc| match tc {
+        LlmToolChoice::Auto => "auto".to_string(),
+        LlmToolChoice::Any => "required".to_string(),
+        LlmToolChoice::None => "none".to_string(),
+    });
+
+    let model_def = get_model_definition(model_id);
+    let max_tokens = request
+        .max_tokens
+        .or(model_def.and_then(|m| m.max_output_tokens));
+
+    Ok(OpenAiRequest {
+        model: model_id.to_string(),
+        messages,
+        max_tokens,
+        tools,
+        tool_choice,
+        stop: request.stop_sequences.clone(),
+        temperature: request.temperature,
+        stream: true,
+        stream_options: Some(StreamOptions {
+            include_usage: true,
+        }),
+    })
+}
+
+fn parse_sse_line(line: &str) -> Option<OpenAiStreamResponse> {
+    let data = line.strip_prefix("data: ")?;
+    if data.trim() == "[DONE]" {
+        return None;
+    }
+    serde_json::from_str(data).ok()
+}
+
+impl zed::Extension for CopilotChatProvider {
+    fn new() -> Self {
+        Self {
+            streams: Mutex::new(HashMap::new()),
+            next_stream_id: Mutex::new(0),
+        }
+    }
+
+    fn llm_providers(&self) -> Vec<LlmProviderInfo> {
+        vec![LlmProviderInfo {
+            id: "copilot_chat".into(),
+            name: "Copilot Chat".into(),
+            icon: Some("icons/copilot.svg".into()),
+        }]
+    }
+
+    fn llm_provider_models(&self, _provider_id: &str) -> Result<Vec<LlmModelInfo>, String> {
+        Ok(MODELS
+            .iter()
+            .map(|m| LlmModelInfo {
+                id: m.id.to_string(),
+                name: m.display_name.to_string(),
+                max_token_count: m.max_tokens,
+                max_output_tokens: m.max_output_tokens,
+                capabilities: LlmModelCapabilities {
+                    supports_images: m.supports_images,
+                    supports_tools: true,
+                    supports_tool_choice_auto: true,
+                    supports_tool_choice_any: true,
+                    supports_tool_choice_none: true,
+                    supports_thinking: false,
+                    tool_input_format: LlmToolInputFormat::JsonSchema,
+                },
+                is_default: m.is_default,
+                is_default_fast: m.is_default_fast,
+            })
+            .collect())
+    }
+
+    fn llm_provider_is_authenticated(&self, _provider_id: &str) -> bool {
+        llm_get_credential("copilot_chat").is_some()
+    }
+
+    fn llm_provider_settings_markdown(&self, _provider_id: &str) -> Option<String> {
+        Some(
+            r#"# Copilot Chat Setup
+
+Welcome to **Copilot Chat**! This extension provides access to GitHub Copilot's chat models.
+
+## Configuration
+
+Enter your GitHub Copilot token below. You need an active GitHub Copilot subscription.
+
+To get your token:
+1. Ensure you have a GitHub Copilot subscription
+2. Generate a token from your GitHub Copilot settings
+
+## Available Models
+
+| Model | Context | Output |
+|-------|---------|--------|
+| GPT-4o | 128K | 16K |
+| GPT-4o Mini | 128K | 16K |
+| GPT-4.1 | 1M | 32K |
+| o1 | 200K | 100K |
+| o3-mini | 200K | 100K |
+| Claude 3.5 Sonnet | 200K | 8K |
+| Claude 3.7 Sonnet | 200K | 8K |
+| Gemini 2.0 Flash | 1M | 8K |
+
+## Features
+
+- ✅ Full streaming support
+- ✅ Tool/function calling
+- ✅ Vision (image inputs)
+- ✅ Multiple model providers via Copilot
+
+## Note
+
+This extension requires an active GitHub Copilot subscription.
+"#
+            .to_string(),
+        )
+    }
+
+    fn llm_provider_authenticate(&mut self, _provider_id: &str) -> Result<(), String> {
+        let provided = llm_request_credential(
+            "copilot_chat",
+            LlmCredentialType::ApiKey,
+            "GitHub Copilot Token",
+            "ghu_...",
+        )?;
+        if provided {
+            Ok(())
+        } else {
+            Err("Authentication cancelled".to_string())
+        }
+    }
+
+    fn llm_provider_reset_credentials(&mut self, _provider_id: &str) -> Result<(), String> {
+        llm_delete_credential("copilot_chat")
+    }
+
+    fn llm_stream_completion_start(
+        &mut self,
+        _provider_id: &str,
+        model_id: &str,
+        request: &LlmCompletionRequest,
+    ) -> Result<String, String> {
+        let api_key = llm_get_credential("copilot_chat").ok_or_else(|| {
+            "No token configured. Please add your GitHub Copilot token in settings.".to_string()
+        })?;
+
+        let openai_request = convert_request(model_id, request)?;
+
+        let body = serde_json::to_vec(&openai_request)
+            .map_err(|e| format!("Failed to serialize request: {}", e))?;
+
+        let http_request = HttpRequest {
+            method: HttpMethod::Post,
+            url: "https://api.githubcopilot.com/chat/completions".to_string(),
+            headers: vec![
+                ("Content-Type".to_string(), "application/json".to_string()),
+                ("Authorization".to_string(), format!("Bearer {}", api_key)),
+                (
+                    "Copilot-Integration-Id".to_string(),
+                    "vscode-chat".to_string(),
+                ),
+                ("Editor-Version".to_string(), "Zed/1.0.0".to_string()),
+            ],
+            body: Some(body),
+            redirect_policy: RedirectPolicy::FollowAll,
+        };
+
+        let response_stream = http_request
+            .fetch_stream()
+            .map_err(|e| format!("HTTP request failed: {}", e))?;
+
+        let stream_id = {
+            let mut id_counter = self.next_stream_id.lock().unwrap();
+            let id = format!("copilot-stream-{}", *id_counter);
+            *id_counter += 1;
+            id
+        };
+
+        self.streams.lock().unwrap().insert(
+            stream_id.clone(),
+            StreamState {
+                response_stream: Some(response_stream),
+                buffer: String::new(),
+                started: false,
+                tool_calls: HashMap::new(),
+                tool_calls_emitted: false,
+            },
+        );
+
+        Ok(stream_id)
+    }
+
+    fn llm_stream_completion_next(
+        &mut self,
+        stream_id: &str,
+    ) -> Result<Option<LlmCompletionEvent>, String> {
+        let mut streams = self.streams.lock().unwrap();
+        let state = streams
+            .get_mut(stream_id)
+            .ok_or_else(|| format!("Unknown stream: {}", stream_id))?;
+
+        if !state.started {
+            state.started = true;
+            return Ok(Some(LlmCompletionEvent::Started));
+        }
+
+        let response_stream = state
+            .response_stream
+            .as_mut()
+            .ok_or_else(|| "Stream already closed".to_string())?;
+
+        loop {
+            if let Some(newline_pos) = state.buffer.find('\n') {
+                let line = state.buffer[..newline_pos].to_string();
+                state.buffer = state.buffer[newline_pos + 1..].to_string();
+
+                if line.trim().is_empty() {
+                    continue;
+                }
+
+                if let Some(response) = parse_sse_line(&line) {
+                    if let Some(choice) = response.choices.first() {
+                        if let Some(content) = &choice.delta.content {
+                            if !content.is_empty() {
+                                return Ok(Some(LlmCompletionEvent::Text(content.clone())));
+                            }
+                        }
+
+                        if let Some(tool_calls) = &choice.delta.tool_calls {
+                            for tc in tool_calls {
+                                let entry = state
+                                    .tool_calls
+                                    .entry(tc.index)
+                                    .or_insert_with(AccumulatedToolCall::default);
+
+                                if let Some(id) = &tc.id {
+                                    entry.id = id.clone();
+                                }
+                                if let Some(func) = &tc.function {
+                                    if let Some(name) = &func.name {
+                                        entry.name = name.clone();
+                                    }
+                                    if let Some(args) = &func.arguments {
+                                        entry.arguments.push_str(args);
+                                    }
+                                }
+                            }
+                        }
+
+                        if let Some(finish_reason) = &choice.finish_reason {
+                            if !state.tool_calls.is_empty() && !state.tool_calls_emitted {
+                                state.tool_calls_emitted = true;
+                                let mut tool_calls: Vec<_> = state.tool_calls.drain().collect();
+                                tool_calls.sort_by_key(|(idx, _)| *idx);
+
+                                if let Some((_, tc)) = tool_calls.into_iter().next() {
+                                    return Ok(Some(LlmCompletionEvent::ToolUse(LlmToolUse {
+                                        id: tc.id,
+                                        name: tc.name,
+                                        input: tc.arguments,
+                                        thought_signature: None,
+                                    })));
+                                }
+                            }
+
+                            let stop_reason = match finish_reason.as_str() {
+                                "stop" => LlmStopReason::EndTurn,
+                                "length" => LlmStopReason::MaxTokens,
+                                "tool_calls" => LlmStopReason::ToolUse,
+                                "content_filter" => LlmStopReason::Refusal,
+                                _ => LlmStopReason::EndTurn,
+                            };
+                            return Ok(Some(LlmCompletionEvent::Stop(stop_reason)));
+                        }
+                    }
+
+                    if let Some(usage) = response.usage {
+                        return Ok(Some(LlmCompletionEvent::Usage(LlmTokenUsage {
+                            input_tokens: usage.prompt_tokens,
+                            output_tokens: usage.completion_tokens,
+                            cache_creation_input_tokens: None,
+                            cache_read_input_tokens: None,
+                        })));
+                    }
+                }
+
+                continue;
+            }
+
+            match response_stream.next_chunk() {
+                Ok(Some(chunk)) => {
+                    let text = String::from_utf8_lossy(&chunk);
+                    state.buffer.push_str(&text);
+                }
+                Ok(None) => {
+                    return Ok(None);
+                }
+                Err(e) => {
+                    return Err(format!("Stream error: {}", e));
+                }
+            }
+        }
+    }
+
+    fn llm_stream_completion_close(&mut self, stream_id: &str) {
+        self.streams.lock().unwrap().remove(stream_id);
+    }
+}
+
+zed::register_extension!(CopilotChatProvider);

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extensions/google-ai/Cargo.toml

@@ -0,0 +1,17 @@
+[package]
+name = "google-ai"
+version = "0.1.0"
+edition = "2021"
+publish = false
+license = "Apache-2.0"
+
+[workspace]
+
+[lib]
+path = "src/google_ai.rs"
+crate-type = ["cdylib"]
+
+[dependencies]
+zed_extension_api = { path = "../../crates/extension_api" }
+serde = { version = "1.0", features = ["derive"] }
+serde_json = "1.0"

extensions/google-ai/extension.toml

@@ -0,0 +1,13 @@
+id = "google-ai"
+name = "Google AI"
+description = "Google Gemini LLM provider for Zed."
+version = "0.1.0"
+schema_version = 1
+authors = ["Zed Team"]
+repository = "https://github.com/zed-industries/zed"
+
+[language_model_providers.google-ai]
+name = "Google AI"
+
+[language_model_providers.google-ai.auth]
+env_var = "GEMINI_API_KEY"

extensions/google-ai/icons/google-ai.svg

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+<svg width="16" height="16" viewBox="0 0 16 16" fill="none" xmlns="http://www.w3.org/2000/svg">
+<path d="M7.44 12.27C7.81333 13.1217 8 14.0317 8 15C8 14.0317 8.18083 13.1217 8.5425 12.27C8.91583 11.4183 9.4175 10.6775 10.0475 10.0475C10.6775 9.4175 11.4183 8.92167 12.27 8.56C13.1217 8.18667 14.0317 8 15 8C14.0317 8 13.1217 7.81917 12.27 7.4575C11.4411 7.1001 10.6871 6.5895 10.0475 5.9525C9.4105 5.31293 8.8999 4.55891 8.5425 3.73C8.18083 2.87833 8 1.96833 8 1C8 1.96833 7.81333 2.87833 7.44 3.73C7.07833 4.58167 6.5825 5.3225 5.9525 5.9525C5.31293 6.5895 4.55891 7.1001 3.73 7.4575C2.87833 7.81917 1.96833 8 1 8C1.96833 8 2.87833 8.18667 3.73 8.56C4.58167 8.92167 5.3225 9.4175 5.9525 10.0475C6.5825 10.6775 7.07833 11.4183 7.44 12.27Z" fill="black"/>
+</svg>

extensions/google-ai/src/google_ai.rs

@@ -0,0 +1,840 @@
+use std::collections::HashMap;
+use std::sync::atomic::{AtomicU64, Ordering};
+use std::sync::Mutex;
+
+use serde::{Deserialize, Serialize};
+use zed_extension_api::http_client::{HttpMethod, HttpRequest, HttpResponseStream, RedirectPolicy};
+use zed_extension_api::{self as zed, *};
+
+static TOOL_CALL_COUNTER: AtomicU64 = AtomicU64::new(0);
+
+struct GoogleAiProvider {
+    streams: Mutex<HashMap<String, StreamState>>,
+    next_stream_id: Mutex<u64>,
+}
+
+struct StreamState {
+    response_stream: Option<HttpResponseStream>,
+    buffer: String,
+    started: bool,
+    stop_reason: Option<LlmStopReason>,
+    wants_tool_use: bool,
+}
+
+struct ModelDefinition {
+    real_id: &'static str,
+    display_name: &'static str,
+    max_tokens: u64,
+    max_output_tokens: Option<u64>,
+    supports_images: bool,
+    supports_thinking: bool,
+    is_default: bool,
+    is_default_fast: bool,
+}
+
+const MODELS: &[ModelDefinition] = &[
+    ModelDefinition {
+        real_id: "gemini-2.5-flash-lite",
+        display_name: "Gemini 2.5 Flash-Lite",
+        max_tokens: 1_048_576,
+        max_output_tokens: Some(65_536),
+        supports_images: true,
+        supports_thinking: true,
+        is_default: false,
+        is_default_fast: true,
+    },
+    ModelDefinition {
+        real_id: "gemini-2.5-flash",
+        display_name: "Gemini 2.5 Flash",
+        max_tokens: 1_048_576,
+        max_output_tokens: Some(65_536),
+        supports_images: true,
+        supports_thinking: true,
+        is_default: true,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        real_id: "gemini-2.5-pro",
+        display_name: "Gemini 2.5 Pro",
+        max_tokens: 1_048_576,
+        max_output_tokens: Some(65_536),
+        supports_images: true,
+        supports_thinking: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        real_id: "gemini-3-pro-preview",
+        display_name: "Gemini 3 Pro",
+        max_tokens: 1_048_576,
+        max_output_tokens: Some(65_536),
+        supports_images: true,
+        supports_thinking: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+];
+
+fn get_real_model_id(display_name: &str) -> Option<&'static str> {
+    MODELS
+        .iter()
+        .find(|m| m.display_name == display_name)
+        .map(|m| m.real_id)
+}
+
+fn get_model_supports_thinking(display_name: &str) -> bool {
+    MODELS
+        .iter()
+        .find(|m| m.display_name == display_name)
+        .map(|m| m.supports_thinking)
+        .unwrap_or(false)
+}
+
+/// Adapts a JSON schema to be compatible with Google's API subset.
+/// Google only supports a specific subset of JSON Schema fields.
+/// See: https://ai.google.dev/api/caching#Schema
+fn adapt_schema_for_google(json: &mut serde_json::Value) {
+    adapt_schema_for_google_impl(json, true);
+}
+
+fn adapt_schema_for_google_impl(json: &mut serde_json::Value, is_schema: bool) {
+    if let serde_json::Value::Object(obj) = json {
+        // Google's Schema only supports these fields:
+        // type, format, title, description, nullable, enum, maxItems, minItems,
+        // properties, required, minProperties, maxProperties, minLength, maxLength,
+        // pattern, example, anyOf, propertyOrdering, default, items, minimum, maximum
+        const ALLOWED_KEYS: &[&str] = &[
+            "type",
+            "format",
+            "title",
+            "description",
+            "nullable",
+            "enum",
+            "maxItems",
+            "minItems",
+            "properties",
+            "required",
+            "minProperties",
+            "maxProperties",
+            "minLength",
+            "maxLength",
+            "pattern",
+            "example",
+            "anyOf",
+            "propertyOrdering",
+            "default",
+            "items",
+            "minimum",
+            "maximum",
+        ];
+
+        // Convert oneOf to anyOf before filtering keys
+        if let Some(one_of) = obj.remove("oneOf") {
+            obj.insert("anyOf".to_string(), one_of);
+        }
+
+        // If type is an array (e.g., ["string", "null"]), take just the first type
+        if let Some(type_field) = obj.get_mut("type") {
+            if let serde_json::Value::Array(types) = type_field {
+                if let Some(first_type) = types.first().cloned() {
+                    *type_field = first_type;
+                }
+            }
+        }
+
+        // Only filter keys if this is a schema object, not a properties map
+        if is_schema {
+            obj.retain(|key, _| ALLOWED_KEYS.contains(&key.as_str()));
+        }
+
+        // Recursively process nested values
+        // "properties" contains a map of property names -> schemas
+        // "items" and "anyOf" contain schemas directly
+        for (key, value) in obj.iter_mut() {
+            if key == "properties" {
+                // properties is a map of property_name -> schema
+                if let serde_json::Value::Object(props) = value {
+                    for (_, prop_schema) in props.iter_mut() {
+                        adapt_schema_for_google_impl(prop_schema, true);
+                    }
+                }
+            } else if key == "items" {
+                // items is a schema
+                adapt_schema_for_google_impl(value, true);
+            } else if key == "anyOf" {
+                // anyOf is an array of schemas
+                if let serde_json::Value::Array(arr) = value {
+                    for item in arr.iter_mut() {
+                        adapt_schema_for_google_impl(item, true);
+                    }
+                }
+            }
+        }
+    } else if let serde_json::Value::Array(arr) = json {
+        for item in arr.iter_mut() {
+            adapt_schema_for_google_impl(item, true);
+        }
+    }
+}
+
+#[derive(Serialize)]
+#[serde(rename_all = "camelCase")]
+struct GoogleRequest {
+    contents: Vec<GoogleContent>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    system_instruction: Option<GoogleSystemInstruction>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    generation_config: Option<GoogleGenerationConfig>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    tools: Option<Vec<GoogleTool>>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    tool_config: Option<GoogleToolConfig>,
+}
+
+#[derive(Serialize)]
+#[serde(rename_all = "camelCase")]
+struct GoogleSystemInstruction {
+    parts: Vec<GooglePart>,
+}
+
+#[derive(Serialize, Deserialize, Debug, Clone)]
+#[serde(rename_all = "camelCase")]
+struct GoogleContent {
+    parts: Vec<GooglePart>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    role: Option<String>,
+}
+
+#[derive(Serialize, Deserialize, Debug, Clone)]
+#[serde(untagged)]
+enum GooglePart {
+    Text(GoogleTextPart),
+    InlineData(GoogleInlineDataPart),
+    FunctionCall(GoogleFunctionCallPart),
+    FunctionResponse(GoogleFunctionResponsePart),
+    Thought(GoogleThoughtPart),
+}
+
+#[derive(Serialize, Deserialize, Debug, Clone)]
+#[serde(rename_all = "camelCase")]
+struct GoogleTextPart {
+    text: String,
+}
+
+#[derive(Serialize, Deserialize, Debug, Clone)]
+#[serde(rename_all = "camelCase")]
+struct GoogleInlineDataPart {
+    inline_data: GoogleBlob,
+}
+
+#[derive(Serialize, Deserialize, Debug, Clone)]
+#[serde(rename_all = "camelCase")]
+struct GoogleBlob {
+    mime_type: String,
+    data: String,
+}
+
+#[derive(Serialize, Deserialize, Debug, Clone)]
+#[serde(rename_all = "camelCase")]
+struct GoogleFunctionCallPart {
+    function_call: GoogleFunctionCall,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    thought_signature: Option<String>,
+}
+
+#[derive(Serialize, Deserialize, Debug, Clone)]
+#[serde(rename_all = "camelCase")]
+struct GoogleFunctionCall {
+    name: String,
+    args: serde_json::Value,
+}
+
+#[derive(Serialize, Deserialize, Debug, Clone)]
+#[serde(rename_all = "camelCase")]
+struct GoogleFunctionResponsePart {
+    function_response: GoogleFunctionResponse,
+}
+
+#[derive(Serialize, Deserialize, Debug, Clone)]
+#[serde(rename_all = "camelCase")]
+struct GoogleFunctionResponse {
+    name: String,
+    response: serde_json::Value,
+}
+
+#[derive(Serialize, Deserialize, Debug, Clone)]
+#[serde(rename_all = "camelCase")]
+struct GoogleThoughtPart {
+    thought: bool,
+    thought_signature: String,
+}
+
+#[derive(Serialize)]
+#[serde(rename_all = "camelCase")]
+struct GoogleGenerationConfig {
+    #[serde(skip_serializing_if = "Option::is_none")]
+    candidate_count: Option<usize>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    stop_sequences: Option<Vec<String>>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    max_output_tokens: Option<usize>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    temperature: Option<f64>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    thinking_config: Option<GoogleThinkingConfig>,
+}
+
+#[derive(Serialize)]
+#[serde(rename_all = "camelCase")]
+struct GoogleThinkingConfig {
+    thinking_budget: u32,
+}
+
+#[derive(Serialize)]
+#[serde(rename_all = "camelCase")]
+struct GoogleTool {
+    function_declarations: Vec<GoogleFunctionDeclaration>,
+}
+
+#[derive(Serialize)]
+#[serde(rename_all = "camelCase")]
+struct GoogleFunctionDeclaration {
+    name: String,
+    description: String,
+    parameters: serde_json::Value,
+}
+
+#[derive(Serialize)]
+#[serde(rename_all = "camelCase")]
+struct GoogleToolConfig {
+    function_calling_config: GoogleFunctionCallingConfig,
+}
+
+#[derive(Serialize)]
+#[serde(rename_all = "camelCase")]
+struct GoogleFunctionCallingConfig {
+    mode: String,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    allowed_function_names: Option<Vec<String>>,
+}
+
+#[derive(Deserialize, Debug)]
+#[serde(rename_all = "camelCase")]
+struct GoogleStreamResponse {
+    #[serde(default)]
+    candidates: Vec<GoogleCandidate>,
+    #[serde(default)]
+    usage_metadata: Option<GoogleUsageMetadata>,
+}
+
+#[derive(Deserialize, Debug)]
+#[serde(rename_all = "camelCase")]
+struct GoogleCandidate {
+    #[serde(default)]
+    content: Option<GoogleContent>,
+    #[serde(default)]
+    finish_reason: Option<String>,
+}
+
+#[derive(Deserialize, Debug)]
+#[serde(rename_all = "camelCase")]
+struct GoogleUsageMetadata {
+    #[serde(default)]
+    prompt_token_count: u64,
+    #[serde(default)]
+    candidates_token_count: u64,
+}
+
+fn convert_request(
+    model_id: &str,
+    request: &LlmCompletionRequest,
+) -> Result<(GoogleRequest, String), String> {
+    let real_model_id =
+        get_real_model_id(model_id).ok_or_else(|| format!("Unknown model: {}", model_id))?;
+
+    let supports_thinking = get_model_supports_thinking(model_id);
+
+    let mut contents: Vec<GoogleContent> = Vec::new();
+    let mut system_parts: Vec<GooglePart> = Vec::new();
+
+    for msg in &request.messages {
+        match msg.role {
+            LlmMessageRole::System => {
+                for content in &msg.content {
+                    if let LlmMessageContent::Text(text) = content {
+                        if !text.is_empty() {
+                            system_parts
+                                .push(GooglePart::Text(GoogleTextPart { text: text.clone() }));
+                        }
+                    }
+                }
+            }
+            LlmMessageRole::User => {
+                let mut parts: Vec<GooglePart> = Vec::new();
+
+                for content in &msg.content {
+                    match content {
+                        LlmMessageContent::Text(text) => {
+                            if !text.is_empty() {
+                                parts.push(GooglePart::Text(GoogleTextPart { text: text.clone() }));
+                            }
+                        }
+                        LlmMessageContent::Image(img) => {
+                            parts.push(GooglePart::InlineData(GoogleInlineDataPart {
+                                inline_data: GoogleBlob {
+                                    mime_type: "image/png".to_string(),
+                                    data: img.source.clone(),
+                                },
+                            }));
+                        }
+                        LlmMessageContent::ToolResult(result) => {
+                            let response_value = match &result.content {
+                                LlmToolResultContent::Text(t) => {
+                                    serde_json::json!({ "output": t })
+                                }
+                                LlmToolResultContent::Image(_) => {
+                                    serde_json::json!({ "output": "Tool responded with an image" })
+                                }
+                            };
+                            parts.push(GooglePart::FunctionResponse(GoogleFunctionResponsePart {
+                                function_response: GoogleFunctionResponse {
+                                    name: result.tool_name.clone(),
+                                    response: response_value,
+                                },
+                            }));
+                        }
+                        _ => {}
+                    }
+                }
+
+                if !parts.is_empty() {
+                    contents.push(GoogleContent {
+                        parts,
+                        role: Some("user".to_string()),
+                    });
+                }
+            }
+            LlmMessageRole::Assistant => {
+                let mut parts: Vec<GooglePart> = Vec::new();
+
+                for content in &msg.content {
+                    match content {
+                        LlmMessageContent::Text(text) => {
+                            if !text.is_empty() {
+                                parts.push(GooglePart::Text(GoogleTextPart { text: text.clone() }));
+                            }
+                        }
+                        LlmMessageContent::ToolUse(tool_use) => {
+                            let thought_signature =
+                                tool_use.thought_signature.clone().filter(|s| !s.is_empty());
+
+                            let args: serde_json::Value =
+                                serde_json::from_str(&tool_use.input).unwrap_or_default();
+
+                            parts.push(GooglePart::FunctionCall(GoogleFunctionCallPart {
+                                function_call: GoogleFunctionCall {
+                                    name: tool_use.name.clone(),
+                                    args,
+                                },
+                                thought_signature,
+                            }));
+                        }
+                        LlmMessageContent::Thinking(thinking) => {
+                            if let Some(ref signature) = thinking.signature {
+                                if !signature.is_empty() {
+                                    parts.push(GooglePart::Thought(GoogleThoughtPart {
+                                        thought: true,
+                                        thought_signature: signature.clone(),
+                                    }));
+                                }
+                            }
+                        }
+                        _ => {}
+                    }
+                }
+
+                if !parts.is_empty() {
+                    contents.push(GoogleContent {
+                        parts,
+                        role: Some("model".to_string()),
+                    });
+                }
+            }
+        }
+    }
+
+    let system_instruction = if system_parts.is_empty() {
+        None
+    } else {
+        Some(GoogleSystemInstruction {
+            parts: system_parts,
+        })
+    };
+
+    let tools: Option<Vec<GoogleTool>> = if request.tools.is_empty() {
+        None
+    } else {
+        let declarations: Vec<GoogleFunctionDeclaration> = request
+            .tools
+            .iter()
+            .map(|t| {
+                let mut parameters: serde_json::Value = serde_json::from_str(&t.input_schema)
+                    .unwrap_or(serde_json::Value::Object(Default::default()));
+                adapt_schema_for_google(&mut parameters);
+                GoogleFunctionDeclaration {
+                    name: t.name.clone(),
+                    description: t.description.clone(),
+                    parameters,
+                }
+            })
+            .collect();
+        Some(vec![GoogleTool {
+            function_declarations: declarations,
+        }])
+    };
+
+    let tool_config = request.tool_choice.as_ref().map(|tc| {
+        let mode = match tc {
+            LlmToolChoice::Auto => "AUTO",
+            LlmToolChoice::Any => "ANY",
+            LlmToolChoice::None => "NONE",
+        };
+        GoogleToolConfig {
+            function_calling_config: GoogleFunctionCallingConfig {
+                mode: mode.to_string(),
+                allowed_function_names: None,
+            },
+        }
+    });
+
+    let thinking_config = if supports_thinking && request.thinking_allowed {
+        Some(GoogleThinkingConfig {
+            thinking_budget: 8192,
+        })
+    } else {
+        None
+    };
+
+    let generation_config = Some(GoogleGenerationConfig {
+        candidate_count: Some(1),
+        stop_sequences: if request.stop_sequences.is_empty() {
+            None
+        } else {
+            Some(request.stop_sequences.clone())
+        },
+        max_output_tokens: None,
+        temperature: request.temperature.map(|t| t as f64).or(Some(1.0)),
+        thinking_config,
+    });
+
+    Ok((
+        GoogleRequest {
+            contents,
+            system_instruction,
+            generation_config,
+            tools,
+            tool_config,
+        },
+        real_model_id.to_string(),
+    ))
+}
+
+fn parse_stream_line(line: &str) -> Option<GoogleStreamResponse> {
+    let trimmed = line.trim();
+    if trimmed.is_empty() || trimmed == "[" || trimmed == "]" || trimmed == "," {
+        return None;
+    }
+
+    let json_str = trimmed.strip_prefix("data: ").unwrap_or(trimmed);
+    let json_str = json_str.trim_start_matches(',').trim();
+
+    if json_str.is_empty() {
+        return None;
+    }
+
+    serde_json::from_str(json_str).ok()
+}
+
+impl zed::Extension for GoogleAiProvider {
+    fn new() -> Self {
+        Self {
+            streams: Mutex::new(HashMap::new()),
+            next_stream_id: Mutex::new(0),
+        }
+    }
+
+    fn llm_providers(&self) -> Vec<LlmProviderInfo> {
+        vec![LlmProviderInfo {
+            id: "google-ai".into(),
+            name: "Google AI".into(),
+            icon: Some("icons/google-ai.svg".into()),
+        }]
+    }
+
+    fn llm_provider_models(&self, _provider_id: &str) -> Result<Vec<LlmModelInfo>, String> {
+        Ok(MODELS
+            .iter()
+            .map(|m| LlmModelInfo {
+                id: m.display_name.to_string(),
+                name: m.display_name.to_string(),
+                max_token_count: m.max_tokens,
+                max_output_tokens: m.max_output_tokens,
+                capabilities: LlmModelCapabilities {
+                    supports_images: m.supports_images,
+                    supports_tools: true,
+                    supports_tool_choice_auto: true,
+                    supports_tool_choice_any: true,
+                    supports_tool_choice_none: true,
+                    supports_thinking: m.supports_thinking,
+                    tool_input_format: LlmToolInputFormat::JsonSchema,
+                },
+                is_default: m.is_default,
+                is_default_fast: m.is_default_fast,
+            })
+            .collect())
+    }
+
+    fn llm_provider_is_authenticated(&self, _provider_id: &str) -> bool {
+        llm_get_credential("google-ai").is_some()
+    }
+
+    fn llm_provider_settings_markdown(&self, _provider_id: &str) -> Option<String> {
+        Some(
+            r#"# Google AI Setup
+
+Welcome to **Google AI**! This extension provides access to Google Gemini models.
+
+## Configuration
+
+Enter your Google AI API key below. You can get your API key at [aistudio.google.com/apikey](https://aistudio.google.com/apikey).
+
+## Available Models
+
+| Display Name | Real Model | Context | Output |
+|--------------|------------|---------|--------|
+| Gemini 2.5 Flash-Lite | gemini-2.5-flash-lite | 1M | 65K |
+| Gemini 2.5 Flash | gemini-2.5-flash | 1M | 65K |
+| Gemini 2.5 Pro | gemini-2.5-pro | 1M | 65K |
+| Gemini 3 Pro | gemini-3-pro-preview | 1M | 65K |
+
+## Features
+
+- ✅ Full streaming support
+- ✅ Tool/function calling with thought signatures
+- ✅ Vision (image inputs)
+- ✅ Extended thinking support
+- ✅ All Gemini models
+
+## Pricing
+
+Uses your Google AI API credits. See [Google AI pricing](https://ai.google.dev/pricing) for details.
+"#
+            .to_string(),
+        )
+    }
+
+    fn llm_provider_authenticate(&mut self, _provider_id: &str) -> Result<(), String> {
+        let provided = llm_request_credential(
+            "google-ai",
+            LlmCredentialType::ApiKey,
+            "Google AI API Key",
+            "AIza...",
+        )?;
+        if provided {
+            Ok(())
+        } else {
+            Err("Authentication cancelled".to_string())
+        }
+    }
+
+    fn llm_provider_reset_credentials(&mut self, _provider_id: &str) -> Result<(), String> {
+        llm_delete_credential("google-ai")
+    }
+
+    fn llm_stream_completion_start(
+        &mut self,
+        _provider_id: &str,
+        model_id: &str,
+        request: &LlmCompletionRequest,
+    ) -> Result<String, String> {
+        let api_key = llm_get_credential("google-ai").ok_or_else(|| {
+            "No API key configured. Please add your Google AI API key in settings.".to_string()
+        })?;
+
+        let (google_request, real_model_id) = convert_request(model_id, request)?;
+
+        let body = serde_json::to_vec(&google_request)
+            .map_err(|e| format!("Failed to serialize request: {}", e))?;
+
+        let url = format!(
+            "https://generativelanguage.googleapis.com/v1beta/models/{}:streamGenerateContent?alt=sse&key={}",
+            real_model_id, api_key
+        );
+
+        let http_request = HttpRequest {
+            method: HttpMethod::Post,
+            url,
+            headers: vec![("Content-Type".to_string(), "application/json".to_string())],
+            body: Some(body),
+            redirect_policy: RedirectPolicy::FollowAll,
+        };
+
+        let response_stream = http_request
+            .fetch_stream()
+            .map_err(|e| format!("HTTP request failed: {}", e))?;
+
+        let stream_id = {
+            let mut id_counter = self.next_stream_id.lock().unwrap();
+            let id = format!("google-ai-stream-{}", *id_counter);
+            *id_counter += 1;
+            id
+        };
+
+        self.streams.lock().unwrap().insert(
+            stream_id.clone(),
+            StreamState {
+                response_stream: Some(response_stream),
+                buffer: String::new(),
+                started: false,
+                stop_reason: None,
+                wants_tool_use: false,
+            },
+        );
+
+        Ok(stream_id)
+    }
+
+    fn llm_stream_completion_next(
+        &mut self,
+        stream_id: &str,
+    ) -> Result<Option<LlmCompletionEvent>, String> {
+        let mut streams = self.streams.lock().unwrap();
+        let state = streams
+            .get_mut(stream_id)
+            .ok_or_else(|| format!("Unknown stream: {}", stream_id))?;
+
+        if !state.started {
+            state.started = true;
+            return Ok(Some(LlmCompletionEvent::Started));
+        }
+
+        let response_stream = state
+            .response_stream
+            .as_mut()
+            .ok_or_else(|| "Stream already closed".to_string())?;
+
+        loop {
+            if let Some(newline_pos) = state.buffer.find('\n') {
+                let line = state.buffer[..newline_pos].to_string();
+                state.buffer = state.buffer[newline_pos + 1..].to_string();
+
+                if let Some(response) = parse_stream_line(&line) {
+                    for candidate in response.candidates {
+                        if let Some(finish_reason) = &candidate.finish_reason {
+                            state.stop_reason = Some(match finish_reason.as_str() {
+                                "STOP" => {
+                                    if state.wants_tool_use {
+                                        LlmStopReason::ToolUse
+                                    } else {
+                                        LlmStopReason::EndTurn
+                                    }
+                                }
+                                "MAX_TOKENS" => LlmStopReason::MaxTokens,
+                                "SAFETY" => LlmStopReason::Refusal,
+                                _ => LlmStopReason::EndTurn,
+                            });
+                        }
+
+                        if let Some(content) = candidate.content {
+                            for part in content.parts {
+                                match part {
+                                    GooglePart::Text(text_part) => {
+                                        if !text_part.text.is_empty() {
+                                            return Ok(Some(LlmCompletionEvent::Text(
+                                                text_part.text,
+                                            )));
+                                        }
+                                    }
+                                    GooglePart::FunctionCall(fc_part) => {
+                                        state.wants_tool_use = true;
+                                        let next_tool_id =
+                                            TOOL_CALL_COUNTER.fetch_add(1, Ordering::SeqCst);
+                                        let id = format!(
+                                            "{}-{}",
+                                            fc_part.function_call.name, next_tool_id
+                                        );
+
+                                        let thought_signature =
+                                            fc_part.thought_signature.filter(|s| !s.is_empty());
+
+                                        return Ok(Some(LlmCompletionEvent::ToolUse(LlmToolUse {
+                                            id,
+                                            name: fc_part.function_call.name,
+                                            input: fc_part.function_call.args.to_string(),
+                                            thought_signature,
+                                        })));
+                                    }
+                                    GooglePart::Thought(thought_part) => {
+                                        return Ok(Some(LlmCompletionEvent::Thinking(
+                                            LlmThinkingContent {
+                                                text: "(Encrypted thought)".to_string(),
+                                                signature: Some(thought_part.thought_signature),
+                                            },
+                                        )));
+                                    }
+                                    _ => {}
+                                }
+                            }
+                        }
+                    }
+
+                    if let Some(usage) = response.usage_metadata {
+                        return Ok(Some(LlmCompletionEvent::Usage(LlmTokenUsage {
+                            input_tokens: usage.prompt_token_count,
+                            output_tokens: usage.candidates_token_count,
+                            cache_creation_input_tokens: None,
+                            cache_read_input_tokens: None,
+                        })));
+                    }
+                }
+
+                continue;
+            }
+
+            match response_stream.next_chunk() {
+                Ok(Some(chunk)) => {
+                    let text = String::from_utf8_lossy(&chunk);
+                    state.buffer.push_str(&text);
+                }
+                Ok(None) => {
+                    // Stream ended - check if we have a stop reason
+                    if let Some(stop_reason) = state.stop_reason.take() {
+                        return Ok(Some(LlmCompletionEvent::Stop(stop_reason)));
+                    }
+
+                    // No stop reason - this is unexpected. Check if buffer contains error info
+                    let mut error_msg = String::from("Stream ended unexpectedly.");
+
+                    // Try to parse remaining buffer as potential error response
+                    if !state.buffer.is_empty() {
+                        error_msg.push_str(&format!(
+                            "\nRemaining buffer: {}",
+                            &state.buffer[..state.buffer.len().min(1000)]
+                        ));
+                    }
+
+                    return Err(error_msg);
+                }
+                Err(e) => {
+                    return Err(format!("Stream error: {}", e));
+                }
+            }
+        }
+    }
+
+    fn llm_stream_completion_close(&mut self, stream_id: &str) {
+        self.streams.lock().unwrap().remove(stream_id);
+    }
+}
+
+zed::register_extension!(GoogleAiProvider);

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extensions/open-router/Cargo.toml

@@ -0,0 +1,17 @@
+[package]
+name = "open-router"
+version = "0.1.0"
+edition = "2021"
+publish = false
+license = "Apache-2.0"
+
+[workspace]
+
+[lib]
+path = "src/open_router.rs"
+crate-type = ["cdylib"]
+
+[dependencies]
+zed_extension_api = { path = "../../crates/extension_api" }
+serde = { version = "1.0", features = ["derive"] }
+serde_json = "1.0"

extensions/open-router/extension.toml

@@ -0,0 +1,13 @@
+id = "open-router"
+name = "OpenRouter"
+description = "OpenRouter LLM provider - access multiple AI models through a unified API."
+version = "0.1.0"
+schema_version = 1
+authors = ["Zed Team"]
+repository = "https://github.com/zed-industries/zed"
+
+[language_model_providers.open-router]
+name = "OpenRouter"
+
+[language_model_providers.open-router.auth]
+env_var = "OPENROUTER_API_KEY"

extensions/open-router/icons/open-router.svg

@@ -0,0 +1,8 @@
+<svg width="16" height="16" viewBox="0 0 16 16" fill="none" xmlns="http://www.w3.org/2000/svg">
+<path d="M2.54131 7.78012C2.89456 7.78012 4.25937 7.47507 4.96588 7.07512C5.67239 6.67517 5.67239 6.67517 7.13135 5.63951C8.97897 4.32817 10.2858 4.76729 12.4272 4.76729" fill="black"/>
+<path d="M2.54131 7.78012C2.89456 7.78012 4.25937 7.47507 4.96588 7.07512C5.67239 6.67517 5.67239 6.67517 7.13135 5.63951C8.97897 4.32817 10.2858 4.76729 12.4272 4.76729" stroke="black" stroke-width="2.8125"/>
+<path d="M14.4985 4.7801L10.8793 6.86949V2.6907L14.4985 4.7801Z" fill="black" stroke="black"/>
+<path d="M2.47052 7.78088C2.82377 7.78088 4.18859 8.08593 4.8951 8.48588C5.60161 8.88583 5.6016 8.88583 7.06057 9.92149C8.90819 11.2328 10.2142 10.7937 12.3564 10.7937" fill="black"/>
+<path d="M2.47052 7.78088C2.82377 7.78088 4.18859 8.08593 4.8951 8.48588C5.60161 8.88583 5.6016 8.88583 7.06057 9.92149C8.90819 11.2328 10.2142 10.7937 12.3564 10.7937" stroke="black" stroke-width="2.8125"/>
+<path d="M14.4277 10.7809L10.8085 8.6915V12.8703L14.4277 10.7809Z" fill="black" stroke="black"/>
+</svg>

extensions/open-router/src/open_router.rs

@@ -0,0 +1,830 @@
+use std::collections::HashMap;
+use std::sync::Mutex;
+
+use serde::{Deserialize, Serialize};
+use zed_extension_api::http_client::{HttpMethod, HttpRequest, HttpResponseStream, RedirectPolicy};
+use zed_extension_api::{self as zed, *};
+
+struct OpenRouterProvider {
+    streams: Mutex<HashMap<String, StreamState>>,
+    next_stream_id: Mutex<u64>,
+}
+
+struct StreamState {
+    response_stream: Option<HttpResponseStream>,
+    buffer: String,
+    started: bool,
+    tool_calls: HashMap<usize, AccumulatedToolCall>,
+    tool_calls_emitted: bool,
+}
+
+#[derive(Clone, Default)]
+struct AccumulatedToolCall {
+    id: String,
+    name: String,
+    arguments: String,
+}
+
+struct ModelDefinition {
+    id: &'static str,
+    display_name: &'static str,
+    max_tokens: u64,
+    max_output_tokens: Option<u64>,
+    supports_images: bool,
+    supports_tools: bool,
+    is_default: bool,
+    is_default_fast: bool,
+}
+
+const MODELS: &[ModelDefinition] = &[
+    // Anthropic Models
+    ModelDefinition {
+        id: "anthropic/claude-sonnet-4",
+        display_name: "Claude Sonnet 4",
+        max_tokens: 200_000,
+        max_output_tokens: Some(8_192),
+        supports_images: true,
+        supports_tools: true,
+        is_default: true,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        id: "anthropic/claude-opus-4",
+        display_name: "Claude Opus 4",
+        max_tokens: 200_000,
+        max_output_tokens: Some(8_192),
+        supports_images: true,
+        supports_tools: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        id: "anthropic/claude-haiku-4",
+        display_name: "Claude Haiku 4",
+        max_tokens: 200_000,
+        max_output_tokens: Some(8_192),
+        supports_images: true,
+        supports_tools: true,
+        is_default: false,
+        is_default_fast: true,
+    },
+    ModelDefinition {
+        id: "anthropic/claude-3.5-sonnet",
+        display_name: "Claude 3.5 Sonnet",
+        max_tokens: 200_000,
+        max_output_tokens: Some(8_192),
+        supports_images: true,
+        supports_tools: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+    // OpenAI Models
+    ModelDefinition {
+        id: "openai/gpt-4o",
+        display_name: "GPT-4o",
+        max_tokens: 128_000,
+        max_output_tokens: Some(16_384),
+        supports_images: true,
+        supports_tools: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        id: "openai/gpt-4o-mini",
+        display_name: "GPT-4o Mini",
+        max_tokens: 128_000,
+        max_output_tokens: Some(16_384),
+        supports_images: true,
+        supports_tools: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        id: "openai/o1",
+        display_name: "o1",
+        max_tokens: 200_000,
+        max_output_tokens: Some(100_000),
+        supports_images: true,
+        supports_tools: false,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        id: "openai/o3-mini",
+        display_name: "o3-mini",
+        max_tokens: 200_000,
+        max_output_tokens: Some(100_000),
+        supports_images: false,
+        supports_tools: false,
+        is_default: false,
+        is_default_fast: false,
+    },
+    // Google Models
+    ModelDefinition {
+        id: "google/gemini-2.0-flash-001",
+        display_name: "Gemini 2.0 Flash",
+        max_tokens: 1_000_000,
+        max_output_tokens: Some(8_192),
+        supports_images: true,
+        supports_tools: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        id: "google/gemini-2.5-pro-preview",
+        display_name: "Gemini 2.5 Pro",
+        max_tokens: 1_000_000,
+        max_output_tokens: Some(8_192),
+        supports_images: true,
+        supports_tools: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+    // Meta Models
+    ModelDefinition {
+        id: "meta-llama/llama-3.3-70b-instruct",
+        display_name: "Llama 3.3 70B",
+        max_tokens: 128_000,
+        max_output_tokens: Some(4_096),
+        supports_images: false,
+        supports_tools: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        id: "meta-llama/llama-4-maverick",
+        display_name: "Llama 4 Maverick",
+        max_tokens: 128_000,
+        max_output_tokens: Some(4_096),
+        supports_images: true,
+        supports_tools: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+    // Mistral Models
+    ModelDefinition {
+        id: "mistralai/mistral-large-2411",
+        display_name: "Mistral Large",
+        max_tokens: 128_000,
+        max_output_tokens: Some(4_096),
+        supports_images: false,
+        supports_tools: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        id: "mistralai/codestral-latest",
+        display_name: "Codestral",
+        max_tokens: 32_000,
+        max_output_tokens: Some(4_096),
+        supports_images: false,
+        supports_tools: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+    // DeepSeek Models
+    ModelDefinition {
+        id: "deepseek/deepseek-chat-v3-0324",
+        display_name: "DeepSeek V3",
+        max_tokens: 64_000,
+        max_output_tokens: Some(8_192),
+        supports_images: false,
+        supports_tools: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        id: "deepseek/deepseek-r1",
+        display_name: "DeepSeek R1",
+        max_tokens: 64_000,
+        max_output_tokens: Some(8_192),
+        supports_images: false,
+        supports_tools: false,
+        is_default: false,
+        is_default_fast: false,
+    },
+    // Qwen Models
+    ModelDefinition {
+        id: "qwen/qwen3-235b-a22b",
+        display_name: "Qwen 3 235B",
+        max_tokens: 40_000,
+        max_output_tokens: Some(8_192),
+        supports_images: false,
+        supports_tools: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+];
+
+fn get_model_definition(model_id: &str) -> Option<&'static ModelDefinition> {
+    MODELS.iter().find(|m| m.id == model_id)
+}
+
+#[derive(Serialize)]
+struct OpenRouterRequest {
+    model: String,
+    messages: Vec<OpenRouterMessage>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    max_tokens: Option<u64>,
+    #[serde(skip_serializing_if = "Vec::is_empty")]
+    tools: Vec<OpenRouterTool>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    tool_choice: Option<String>,
+    #[serde(skip_serializing_if = "Vec::is_empty")]
+    stop: Vec<String>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    temperature: Option<f32>,
+    stream: bool,
+}
+
+#[derive(Serialize)]
+struct OpenRouterMessage {
+    role: String,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    content: Option<OpenRouterContent>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    tool_calls: Option<Vec<OpenRouterToolCall>>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    tool_call_id: Option<String>,
+}
+
+#[derive(Serialize, Clone)]
+#[serde(untagged)]
+enum OpenRouterContent {
+    Text(String),
+    Parts(Vec<OpenRouterContentPart>),
+}
+
+#[derive(Serialize, Clone)]
+#[serde(tag = "type")]
+enum OpenRouterContentPart {
+    #[serde(rename = "text")]
+    Text { text: String },
+    #[serde(rename = "image_url")]
+    ImageUrl { image_url: ImageUrl },
+}
+
+#[derive(Serialize, Clone)]
+struct ImageUrl {
+    url: String,
+}
+
+#[derive(Serialize, Clone)]
+struct OpenRouterToolCall {
+    id: String,
+    #[serde(rename = "type")]
+    call_type: String,
+    function: OpenRouterFunctionCall,
+}
+
+#[derive(Serialize, Clone)]
+struct OpenRouterFunctionCall {
+    name: String,
+    arguments: String,
+}
+
+#[derive(Serialize)]
+struct OpenRouterTool {
+    #[serde(rename = "type")]
+    tool_type: String,
+    function: OpenRouterFunctionDef,
+}
+
+#[derive(Serialize)]
+struct OpenRouterFunctionDef {
+    name: String,
+    description: String,
+    parameters: serde_json::Value,
+}
+
+#[derive(Deserialize, Debug)]
+struct OpenRouterStreamResponse {
+    choices: Vec<OpenRouterStreamChoice>,
+    #[serde(default)]
+    usage: Option<OpenRouterUsage>,
+}
+
+#[derive(Deserialize, Debug)]
+struct OpenRouterStreamChoice {
+    delta: OpenRouterDelta,
+    finish_reason: Option<String>,
+}
+
+#[derive(Deserialize, Debug, Default)]
+struct OpenRouterDelta {
+    #[serde(default)]
+    content: Option<String>,
+    #[serde(default)]
+    tool_calls: Option<Vec<OpenRouterToolCallDelta>>,
+}
+
+#[derive(Deserialize, Debug)]
+struct OpenRouterToolCallDelta {
+    index: usize,
+    #[serde(default)]
+    id: Option<String>,
+    #[serde(default)]
+    function: Option<OpenRouterFunctionDelta>,
+}
+
+#[derive(Deserialize, Debug, Default)]
+struct OpenRouterFunctionDelta {
+    #[serde(default)]
+    name: Option<String>,
+    #[serde(default)]
+    arguments: Option<String>,
+}
+
+#[derive(Deserialize, Debug)]
+struct OpenRouterUsage {
+    prompt_tokens: u64,
+    completion_tokens: u64,
+}
+
+fn convert_request(
+    model_id: &str,
+    request: &LlmCompletionRequest,
+) -> Result<OpenRouterRequest, String> {
+    let mut messages: Vec<OpenRouterMessage> = Vec::new();
+
+    for msg in &request.messages {
+        match msg.role {
+            LlmMessageRole::System => {
+                let mut text_content = String::new();
+                for content in &msg.content {
+                    if let LlmMessageContent::Text(text) = content {
+                        if !text_content.is_empty() {
+                            text_content.push('\n');
+                        }
+                        text_content.push_str(text);
+                    }
+                }
+                if !text_content.is_empty() {
+                    messages.push(OpenRouterMessage {
+                        role: "system".to_string(),
+                        content: Some(OpenRouterContent::Text(text_content)),
+                        tool_calls: None,
+                        tool_call_id: None,
+                    });
+                }
+            }
+            LlmMessageRole::User => {
+                let mut parts: Vec<OpenRouterContentPart> = Vec::new();
+                let mut tool_result_messages: Vec<OpenRouterMessage> = Vec::new();
+
+                for content in &msg.content {
+                    match content {
+                        LlmMessageContent::Text(text) => {
+                            if !text.is_empty() {
+                                parts.push(OpenRouterContentPart::Text { text: text.clone() });
+                            }
+                        }
+                        LlmMessageContent::Image(img) => {
+                            let data_url = format!("data:image/png;base64,{}", img.source);
+                            parts.push(OpenRouterContentPart::ImageUrl {
+                                image_url: ImageUrl { url: data_url },
+                            });
+                        }
+                        LlmMessageContent::ToolResult(result) => {
+                            let content_text = match &result.content {
+                                LlmToolResultContent::Text(t) => t.clone(),
+                                LlmToolResultContent::Image(_) => "[Image]".to_string(),
+                            };
+                            tool_result_messages.push(OpenRouterMessage {
+                                role: "tool".to_string(),
+                                content: Some(OpenRouterContent::Text(content_text)),
+                                tool_calls: None,
+                                tool_call_id: Some(result.tool_use_id.clone()),
+                            });
+                        }
+                        _ => {}
+                    }
+                }
+
+                if !parts.is_empty() {
+                    let content = if parts.len() == 1 {
+                        if let OpenRouterContentPart::Text { text } = &parts[0] {
+                            OpenRouterContent::Text(text.clone())
+                        } else {
+                            OpenRouterContent::Parts(parts)
+                        }
+                    } else {
+                        OpenRouterContent::Parts(parts)
+                    };
+
+                    messages.push(OpenRouterMessage {
+                        role: "user".to_string(),
+                        content: Some(content),
+                        tool_calls: None,
+                        tool_call_id: None,
+                    });
+                }
+
+                messages.extend(tool_result_messages);
+            }
+            LlmMessageRole::Assistant => {
+                let mut text_content = String::new();
+                let mut tool_calls: Vec<OpenRouterToolCall> = Vec::new();
+
+                for content in &msg.content {
+                    match content {
+                        LlmMessageContent::Text(text) => {
+                            if !text.is_empty() {
+                                if !text_content.is_empty() {
+                                    text_content.push('\n');
+                                }
+                                text_content.push_str(text);
+                            }
+                        }
+                        LlmMessageContent::ToolUse(tool_use) => {
+                            tool_calls.push(OpenRouterToolCall {
+                                id: tool_use.id.clone(),
+                                call_type: "function".to_string(),
+                                function: OpenRouterFunctionCall {
+                                    name: tool_use.name.clone(),
+                                    arguments: tool_use.input.clone(),
+                                },
+                            });
+                        }
+                        _ => {}
+                    }
+                }
+
+                messages.push(OpenRouterMessage {
+                    role: "assistant".to_string(),
+                    content: if text_content.is_empty() {
+                        None
+                    } else {
+                        Some(OpenRouterContent::Text(text_content))
+                    },
+                    tool_calls: if tool_calls.is_empty() {
+                        None
+                    } else {
+                        Some(tool_calls)
+                    },
+                    tool_call_id: None,
+                });
+            }
+        }
+    }
+
+    let model_def = get_model_definition(model_id);
+    let supports_tools = model_def.map(|m| m.supports_tools).unwrap_or(true);
+
+    let tools: Vec<OpenRouterTool> = if supports_tools {
+        request
+            .tools
+            .iter()
+            .map(|t| OpenRouterTool {
+                tool_type: "function".to_string(),
+                function: OpenRouterFunctionDef {
+                    name: t.name.clone(),
+                    description: t.description.clone(),
+                    parameters: serde_json::from_str(&t.input_schema)
+                        .unwrap_or(serde_json::Value::Object(Default::default())),
+                },
+            })
+            .collect()
+    } else {
+        Vec::new()
+    };
+
+    let tool_choice = if supports_tools {
+        request.tool_choice.as_ref().map(|tc| match tc {
+            LlmToolChoice::Auto => "auto".to_string(),
+            LlmToolChoice::Any => "required".to_string(),
+            LlmToolChoice::None => "none".to_string(),
+        })
+    } else {
+        None
+    };
+
+    let max_tokens = request
+        .max_tokens
+        .or(model_def.and_then(|m| m.max_output_tokens));
+
+    Ok(OpenRouterRequest {
+        model: model_id.to_string(),
+        messages,
+        max_tokens,
+        tools,
+        tool_choice,
+        stop: request.stop_sequences.clone(),
+        temperature: request.temperature,
+        stream: true,
+    })
+}
+
+fn parse_sse_line(line: &str) -> Option<OpenRouterStreamResponse> {
+    let data = line.strip_prefix("data: ")?;
+    if data.trim() == "[DONE]" {
+        return None;
+    }
+    serde_json::from_str(data).ok()
+}
+
+impl zed::Extension for OpenRouterProvider {
+    fn new() -> Self {
+        Self {
+            streams: Mutex::new(HashMap::new()),
+            next_stream_id: Mutex::new(0),
+        }
+    }
+
+    fn llm_providers(&self) -> Vec<LlmProviderInfo> {
+        vec![LlmProviderInfo {
+            id: "open_router".into(),
+            name: "OpenRouter".into(),
+            icon: Some("icons/open-router.svg".into()),
+        }]
+    }
+
+    fn llm_provider_models(&self, _provider_id: &str) -> Result<Vec<LlmModelInfo>, String> {
+        Ok(MODELS
+            .iter()
+            .map(|m| LlmModelInfo {
+                id: m.id.to_string(),
+                name: m.display_name.to_string(),
+                max_token_count: m.max_tokens,
+                max_output_tokens: m.max_output_tokens,
+                capabilities: LlmModelCapabilities {
+                    supports_images: m.supports_images,
+                    supports_tools: m.supports_tools,
+                    supports_tool_choice_auto: m.supports_tools,
+                    supports_tool_choice_any: m.supports_tools,
+                    supports_tool_choice_none: m.supports_tools,
+                    supports_thinking: false,
+                    tool_input_format: LlmToolInputFormat::JsonSchema,
+                },
+                is_default: m.is_default,
+                is_default_fast: m.is_default_fast,
+            })
+            .collect())
+    }
+
+    fn llm_provider_is_authenticated(&self, _provider_id: &str) -> bool {
+        llm_get_credential("open_router").is_some()
+    }
+
+    fn llm_provider_settings_markdown(&self, _provider_id: &str) -> Option<String> {
+        Some(
+            r#"# OpenRouter Setup
+
+Welcome to **OpenRouter**! Access multiple AI models through a single API.
+
+## Configuration
+
+Enter your OpenRouter API key below. Get your API key at [openrouter.ai/keys](https://openrouter.ai/keys).
+
+## Available Models
+
+### Anthropic
+| Model | Context | Output |
+|-------|---------|--------|
+| Claude Sonnet 4 | 200K | 8K |
+| Claude Opus 4 | 200K | 8K |
+| Claude Haiku 4 | 200K | 8K |
+| Claude 3.5 Sonnet | 200K | 8K |
+
+### OpenAI
+| Model | Context | Output |
+|-------|---------|--------|
+| GPT-4o | 128K | 16K |
+| GPT-4o Mini | 128K | 16K |
+| o1 | 200K | 100K |
+| o3-mini | 200K | 100K |
+
+### Google
+| Model | Context | Output |
+|-------|---------|--------|
+| Gemini 2.0 Flash | 1M | 8K |
+| Gemini 2.5 Pro | 1M | 8K |
+
+### Meta
+| Model | Context | Output |
+|-------|---------|--------|
+| Llama 3.3 70B | 128K | 4K |
+| Llama 4 Maverick | 128K | 4K |
+
+### Mistral
+| Model | Context | Output |
+|-------|---------|--------|
+| Mistral Large | 128K | 4K |
+| Codestral | 32K | 4K |
+
+### DeepSeek
+| Model | Context | Output |
+|-------|---------|--------|
+| DeepSeek V3 | 64K | 8K |
+| DeepSeek R1 | 64K | 8K |
+
+### Qwen
+| Model | Context | Output |
+|-------|---------|--------|
+| Qwen 3 235B | 40K | 8K |
+
+## Features
+
+- ✅ Full streaming support
+- ✅ Tool/function calling (model dependent)
+- ✅ Vision (model dependent)
+- ✅ Access to 200+ models
+- ✅ Unified billing
+
+## Pricing
+
+Pay-per-use based on model. See [openrouter.ai/models](https://openrouter.ai/models) for pricing.
+"#
+            .to_string(),
+        )
+    }
+
+    fn llm_provider_authenticate(&mut self, _provider_id: &str) -> Result<(), String> {
+        let provided = llm_request_credential(
+            "open_router",
+            LlmCredentialType::ApiKey,
+            "OpenRouter API Key",
+            "sk-or-v1-...",
+        )?;
+        if provided {
+            Ok(())
+        } else {
+            Err("Authentication cancelled".to_string())
+        }
+    }
+
+    fn llm_provider_reset_credentials(&mut self, _provider_id: &str) -> Result<(), String> {
+        llm_delete_credential("open_router")
+    }
+
+    fn llm_stream_completion_start(
+        &mut self,
+        _provider_id: &str,
+        model_id: &str,
+        request: &LlmCompletionRequest,
+    ) -> Result<String, String> {
+        let api_key = llm_get_credential("open_router").ok_or_else(|| {
+            "No API key configured. Please add your OpenRouter API key in settings.".to_string()
+        })?;
+
+        let openrouter_request = convert_request(model_id, request)?;
+
+        let body = serde_json::to_vec(&openrouter_request)
+            .map_err(|e| format!("Failed to serialize request: {}", e))?;
+
+        let http_request = HttpRequest {
+            method: HttpMethod::Post,
+            url: "https://openrouter.ai/api/v1/chat/completions".to_string(),
+            headers: vec![
+                ("Content-Type".to_string(), "application/json".to_string()),
+                ("Authorization".to_string(), format!("Bearer {}", api_key)),
+                ("HTTP-Referer".to_string(), "https://zed.dev".to_string()),
+                ("X-Title".to_string(), "Zed Editor".to_string()),
+            ],
+            body: Some(body),
+            redirect_policy: RedirectPolicy::FollowAll,
+        };
+
+        let response_stream = http_request
+            .fetch_stream()
+            .map_err(|e| format!("HTTP request failed: {}", e))?;
+
+        let stream_id = {
+            let mut id_counter = self.next_stream_id.lock().unwrap();
+            let id = format!("openrouter-stream-{}", *id_counter);
+            *id_counter += 1;
+            id
+        };
+
+        self.streams.lock().unwrap().insert(
+            stream_id.clone(),
+            StreamState {
+                response_stream: Some(response_stream),
+                buffer: String::new(),
+                started: false,
+                tool_calls: HashMap::new(),
+                tool_calls_emitted: false,
+            },
+        );
+
+        Ok(stream_id)
+    }
+
+    fn llm_stream_completion_next(
+        &mut self,
+        stream_id: &str,
+    ) -> Result<Option<LlmCompletionEvent>, String> {
+        let mut streams = self.streams.lock().unwrap();
+        let state = streams
+            .get_mut(stream_id)
+            .ok_or_else(|| format!("Unknown stream: {}", stream_id))?;
+
+        if !state.started {
+            state.started = true;
+            return Ok(Some(LlmCompletionEvent::Started));
+        }
+
+        let response_stream = state
+            .response_stream
+            .as_mut()
+            .ok_or_else(|| "Stream already closed".to_string())?;
+
+        loop {
+            if let Some(newline_pos) = state.buffer.find('\n') {
+                let line = state.buffer[..newline_pos].to_string();
+                state.buffer = state.buffer[newline_pos + 1..].to_string();
+
+                if line.trim().is_empty() {
+                    continue;
+                }
+
+                if let Some(response) = parse_sse_line(&line) {
+                    if let Some(choice) = response.choices.first() {
+                        if let Some(content) = &choice.delta.content {
+                            if !content.is_empty() {
+                                return Ok(Some(LlmCompletionEvent::Text(content.clone())));
+                            }
+                        }
+
+                        if let Some(tool_calls) = &choice.delta.tool_calls {
+                            for tc in tool_calls {
+                                let entry = state
+                                    .tool_calls
+                                    .entry(tc.index)
+                                    .or_insert_with(AccumulatedToolCall::default);
+
+                                if let Some(id) = &tc.id {
+                                    entry.id = id.clone();
+                                }
+                                if let Some(func) = &tc.function {
+                                    if let Some(name) = &func.name {
+                                        entry.name = name.clone();
+                                    }
+                                    if let Some(args) = &func.arguments {
+                                        entry.arguments.push_str(args);
+                                    }
+                                }
+                            }
+                        }
+
+                        if let Some(finish_reason) = &choice.finish_reason {
+                            if !state.tool_calls.is_empty() && !state.tool_calls_emitted {
+                                state.tool_calls_emitted = true;
+                                let mut tool_calls: Vec<_> = state.tool_calls.drain().collect();
+                                tool_calls.sort_by_key(|(idx, _)| *idx);
+
+                                if let Some((_, tc)) = tool_calls.into_iter().next() {
+                                    return Ok(Some(LlmCompletionEvent::ToolUse(LlmToolUse {
+                                        id: tc.id,
+                                        name: tc.name,
+                                        input: tc.arguments,
+                                        thought_signature: None,
+                                    })));
+                                }
+                            }
+
+                            let stop_reason = match finish_reason.as_str() {
+                                "stop" => LlmStopReason::EndTurn,
+                                "length" => LlmStopReason::MaxTokens,
+                                "tool_calls" => LlmStopReason::ToolUse,
+                                "content_filter" => LlmStopReason::Refusal,
+                                _ => LlmStopReason::EndTurn,
+                            };
+                            return Ok(Some(LlmCompletionEvent::Stop(stop_reason)));
+                        }
+                    }
+
+                    if let Some(usage) = response.usage {
+                        return Ok(Some(LlmCompletionEvent::Usage(LlmTokenUsage {
+                            input_tokens: usage.prompt_tokens,
+                            output_tokens: usage.completion_tokens,
+                            cache_creation_input_tokens: None,
+                            cache_read_input_tokens: None,
+                        })));
+                    }
+                }
+
+                continue;
+            }
+
+            match response_stream.next_chunk() {
+                Ok(Some(chunk)) => {
+                    let text = String::from_utf8_lossy(&chunk);
+                    state.buffer.push_str(&text);
+                }
+                Ok(None) => {
+                    return Ok(None);
+                }
+                Err(e) => {
+                    return Err(format!("Stream error: {}", e));
+                }
+            }
+        }
+    }
+
+    fn llm_stream_completion_close(&mut self, stream_id: &str) {
+        self.streams.lock().unwrap().remove(stream_id);
+    }
+}
+
+zed::register_extension!(OpenRouterProvider);

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+[[package]]
+name = "zerotrie"
+version = "0.2.3"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "2a59c17a5562d507e4b54960e8569ebee33bee890c70aa3fe7b97e85a9fd7851"
+dependencies = [
+ "displaydoc",
+ "yoke",
+ "zerofrom",
+]
+
+[[package]]
+name = "zerovec"
+version = "0.11.5"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "6c28719294829477f525be0186d13efa9a3c602f7ec202ca9e353d310fb9a002"
+dependencies = [
+ "yoke",
+ "zerofrom",
+ "zerovec-derive",
+]
+
+[[package]]
+name = "zerovec-derive"
+version = "0.11.2"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "eadce39539ca5cb3985590102671f2567e659fca9666581ad3411d59207951f3"
+dependencies = [
+ "proc-macro2",
+ "quote",
+ "syn",
+]

extensions/openai/Cargo.toml

@@ -0,0 +1,17 @@
+[package]
+name = "openai"
+version = "0.1.0"
+edition = "2021"
+publish = false
+license = "Apache-2.0"
+
+[workspace]
+
+[lib]
+path = "src/openai.rs"
+crate-type = ["cdylib"]
+
+[dependencies]
+zed_extension_api = { path = "../../crates/extension_api" }
+serde = { version = "1.0", features = ["derive"] }
+serde_json = "1.0"

extensions/openai/extension.toml

@@ -0,0 +1,13 @@
+id = "openai"
+name = "OpenAI"
+description = "OpenAI GPT LLM provider for Zed."
+version = "0.1.0"
+schema_version = 1
+authors = ["Zed Team"]
+repository = "https://github.com/zed-industries/zed"
+
+[language_model_providers.openai]
+name = "OpenAI"
+
+[language_model_providers.openai.auth]
+env_var = "OPENAI_API_KEY"

extensions/openai/icons/openai.svg

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+</svg>

extensions/openai/src/openai.rs

@@ -0,0 +1,727 @@
+use std::collections::HashMap;
+use std::sync::Mutex;
+
+use serde::{Deserialize, Serialize};
+use zed_extension_api::http_client::{HttpMethod, HttpRequest, HttpResponseStream, RedirectPolicy};
+use zed_extension_api::{self as zed, *};
+
+struct OpenAiProvider {
+    streams: Mutex<HashMap<String, StreamState>>,
+    next_stream_id: Mutex<u64>,
+}
+
+struct StreamState {
+    response_stream: Option<HttpResponseStream>,
+    buffer: String,
+    started: bool,
+    tool_calls: HashMap<usize, AccumulatedToolCall>,
+    tool_calls_emitted: bool,
+}
+
+#[derive(Clone, Default)]
+struct AccumulatedToolCall {
+    id: String,
+    name: String,
+    arguments: String,
+}
+
+struct ModelDefinition {
+    real_id: &'static str,
+    display_name: &'static str,
+    max_tokens: u64,
+    max_output_tokens: Option<u64>,
+    supports_images: bool,
+    is_default: bool,
+    is_default_fast: bool,
+}
+
+const MODELS: &[ModelDefinition] = &[
+    ModelDefinition {
+        real_id: "gpt-4o",
+        display_name: "GPT-4o",
+        max_tokens: 128_000,
+        max_output_tokens: Some(16_384),
+        supports_images: true,
+        is_default: true,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        real_id: "gpt-4o-mini",
+        display_name: "GPT-4o-mini",
+        max_tokens: 128_000,
+        max_output_tokens: Some(16_384),
+        supports_images: true,
+        is_default: false,
+        is_default_fast: true,
+    },
+    ModelDefinition {
+        real_id: "gpt-4.1",
+        display_name: "GPT-4.1",
+        max_tokens: 1_047_576,
+        max_output_tokens: Some(32_768),
+        supports_images: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        real_id: "gpt-4.1-mini",
+        display_name: "GPT-4.1-mini",
+        max_tokens: 1_047_576,
+        max_output_tokens: Some(32_768),
+        supports_images: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        real_id: "gpt-4.1-nano",
+        display_name: "GPT-4.1-nano",
+        max_tokens: 1_047_576,
+        max_output_tokens: Some(32_768),
+        supports_images: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        real_id: "gpt-5",
+        display_name: "GPT-5",
+        max_tokens: 272_000,
+        max_output_tokens: Some(32_768),
+        supports_images: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        real_id: "gpt-5-mini",
+        display_name: "GPT-5-mini",
+        max_tokens: 272_000,
+        max_output_tokens: Some(32_768),
+        supports_images: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        real_id: "o1",
+        display_name: "o1",
+        max_tokens: 200_000,
+        max_output_tokens: Some(100_000),
+        supports_images: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        real_id: "o3",
+        display_name: "o3",
+        max_tokens: 200_000,
+        max_output_tokens: Some(100_000),
+        supports_images: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        real_id: "o3-mini",
+        display_name: "o3-mini",
+        max_tokens: 200_000,
+        max_output_tokens: Some(100_000),
+        supports_images: false,
+        is_default: false,
+        is_default_fast: false,
+    },
+    ModelDefinition {
+        real_id: "o4-mini",
+        display_name: "o4-mini",
+        max_tokens: 200_000,
+        max_output_tokens: Some(100_000),
+        supports_images: true,
+        is_default: false,
+        is_default_fast: false,
+    },
+];
+
+fn get_real_model_id(display_name: &str) -> Option<&'static str> {
+    MODELS
+        .iter()
+        .find(|m| m.display_name == display_name)
+        .map(|m| m.real_id)
+}
+
+#[derive(Serialize)]
+struct OpenAiRequest {
+    model: String,
+    messages: Vec<OpenAiMessage>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    tools: Option<Vec<OpenAiTool>>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    tool_choice: Option<String>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    temperature: Option<f32>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    max_tokens: Option<u64>,
+    #[serde(skip_serializing_if = "Vec::is_empty")]
+    stop: Vec<String>,
+    stream: bool,
+    stream_options: Option<StreamOptions>,
+}
+
+#[derive(Serialize)]
+struct StreamOptions {
+    include_usage: bool,
+}
+
+#[derive(Serialize)]
+#[serde(tag = "role")]
+enum OpenAiMessage {
+    #[serde(rename = "system")]
+    System { content: String },
+    #[serde(rename = "user")]
+    User { content: Vec<OpenAiContentPart> },
+    #[serde(rename = "assistant")]
+    Assistant {
+        #[serde(skip_serializing_if = "Option::is_none")]
+        content: Option<String>,
+        #[serde(skip_serializing_if = "Option::is_none")]
+        tool_calls: Option<Vec<OpenAiToolCall>>,
+    },
+    #[serde(rename = "tool")]
+    Tool {
+        tool_call_id: String,
+        content: String,
+    },
+}
+
+#[derive(Serialize)]
+#[serde(tag = "type")]
+enum OpenAiContentPart {
+    #[serde(rename = "text")]
+    Text { text: String },
+    #[serde(rename = "image_url")]
+    ImageUrl { image_url: ImageUrl },
+}
+
+#[derive(Serialize)]
+struct ImageUrl {
+    url: String,
+}
+
+#[derive(Serialize, Deserialize, Clone)]
+struct OpenAiToolCall {
+    id: String,
+    #[serde(rename = "type")]
+    call_type: String,
+    function: OpenAiFunctionCall,
+}
+
+#[derive(Serialize, Deserialize, Clone)]
+struct OpenAiFunctionCall {
+    name: String,
+    arguments: String,
+}
+
+#[derive(Serialize)]
+struct OpenAiTool {
+    #[serde(rename = "type")]
+    tool_type: String,
+    function: OpenAiFunctionDef,
+}
+
+#[derive(Serialize)]
+struct OpenAiFunctionDef {
+    name: String,
+    description: String,
+    parameters: serde_json::Value,
+}
+
+#[derive(Deserialize, Debug)]
+struct OpenAiStreamEvent {
+    choices: Vec<OpenAiChoice>,
+    #[serde(default)]
+    usage: Option<OpenAiUsage>,
+}
+
+#[derive(Deserialize, Debug)]
+struct OpenAiChoice {
+    delta: OpenAiDelta,
+    finish_reason: Option<String>,
+}
+
+#[derive(Deserialize, Debug, Default)]
+struct OpenAiDelta {
+    #[serde(default)]
+    content: Option<String>,
+    #[serde(default)]
+    tool_calls: Option<Vec<OpenAiToolCallDelta>>,
+}
+
+#[derive(Deserialize, Debug)]
+struct OpenAiToolCallDelta {
+    index: usize,
+    #[serde(default)]
+    id: Option<String>,
+    #[serde(default)]
+    function: Option<OpenAiFunctionDelta>,
+}
+
+#[derive(Deserialize, Debug)]
+struct OpenAiFunctionDelta {
+    #[serde(default)]
+    name: Option<String>,
+    #[serde(default)]
+    arguments: Option<String>,
+}
+
+#[derive(Deserialize, Debug)]
+struct OpenAiUsage {
+    prompt_tokens: u64,
+    completion_tokens: u64,
+}
+
+#[allow(dead_code)]
+#[derive(Deserialize, Debug)]
+struct OpenAiError {
+    error: OpenAiErrorDetail,
+}
+
+#[allow(dead_code)]
+#[derive(Deserialize, Debug)]
+struct OpenAiErrorDetail {
+    message: String,
+}
+
+fn convert_request(
+    model_id: &str,
+    request: &LlmCompletionRequest,
+) -> Result<OpenAiRequest, String> {
+    let real_model_id =
+        get_real_model_id(model_id).ok_or_else(|| format!("Unknown model: {}", model_id))?;
+
+    let mut messages = Vec::new();
+
+    for msg in &request.messages {
+        match msg.role {
+            LlmMessageRole::System => {
+                let text: String = msg
+                    .content
+                    .iter()
+                    .filter_map(|c| match c {
+                        LlmMessageContent::Text(t) => Some(t.as_str()),
+                        _ => None,
+                    })
+                    .collect::<Vec<_>>()
+                    .join("\n");
+                if !text.is_empty() {
+                    messages.push(OpenAiMessage::System { content: text });
+                }
+            }
+            LlmMessageRole::User => {
+                let parts: Vec<OpenAiContentPart> = msg
+                    .content
+                    .iter()
+                    .filter_map(|c| match c {
+                        LlmMessageContent::Text(t) => {
+                            Some(OpenAiContentPart::Text { text: t.clone() })
+                        }
+                        LlmMessageContent::Image(img) => Some(OpenAiContentPart::ImageUrl {
+                            image_url: ImageUrl {
+                                url: format!("data:image/png;base64,{}", img.source),
+                            },
+                        }),
+                        LlmMessageContent::ToolResult(_) => None,
+                        _ => None,
+                    })
+                    .collect();
+
+                for content in &msg.content {
+                    if let LlmMessageContent::ToolResult(result) = content {
+                        let content_text = match &result.content {
+                            LlmToolResultContent::Text(t) => t.clone(),
+                            LlmToolResultContent::Image(_) => "[Image]".to_string(),
+                        };
+                        messages.push(OpenAiMessage::Tool {
+                            tool_call_id: result.tool_use_id.clone(),
+                            content: content_text,
+                        });
+                    }
+                }
+
+                if !parts.is_empty() {
+                    messages.push(OpenAiMessage::User { content: parts });
+                }
+            }
+            LlmMessageRole::Assistant => {
+                let mut content_text: Option<String> = None;
+                let mut tool_calls: Vec<OpenAiToolCall> = Vec::new();
+
+                for c in &msg.content {
+                    match c {
+                        LlmMessageContent::Text(t) => {
+                            content_text = Some(t.clone());
+                        }
+                        LlmMessageContent::ToolUse(tool_use) => {
+                            tool_calls.push(OpenAiToolCall {
+                                id: tool_use.id.clone(),
+                                call_type: "function".to_string(),
+                                function: OpenAiFunctionCall {
+                                    name: tool_use.name.clone(),
+                                    arguments: tool_use.input.clone(),
+                                },
+                            });
+                        }
+                        _ => {}
+                    }
+                }
+
+                messages.push(OpenAiMessage::Assistant {
+                    content: content_text,
+                    tool_calls: if tool_calls.is_empty() {
+                        None
+                    } else {
+                        Some(tool_calls)
+                    },
+                });
+            }
+        }
+    }
+
+    let tools: Option<Vec<OpenAiTool>> = if request.tools.is_empty() {
+        None
+    } else {
+        Some(
+            request
+                .tools
+                .iter()
+                .map(|t| OpenAiTool {
+                    tool_type: "function".to_string(),
+                    function: OpenAiFunctionDef {
+                        name: t.name.clone(),
+                        description: t.description.clone(),
+                        parameters: serde_json::from_str(&t.input_schema)
+                            .unwrap_or(serde_json::Value::Object(Default::default())),
+                    },
+                })
+                .collect(),
+        )
+    };
+
+    let tool_choice = request.tool_choice.as_ref().map(|tc| match tc {
+        LlmToolChoice::Auto => "auto".to_string(),
+        LlmToolChoice::Any => "required".to_string(),
+        LlmToolChoice::None => "none".to_string(),
+    });
+
+    Ok(OpenAiRequest {
+        model: real_model_id.to_string(),
+        messages,
+        tools,
+        tool_choice,
+        temperature: request.temperature,
+        max_tokens: request.max_tokens,
+        stop: request.stop_sequences.clone(),
+        stream: true,
+        stream_options: Some(StreamOptions {
+            include_usage: true,
+        }),
+    })
+}
+
+fn parse_sse_line(line: &str) -> Option<OpenAiStreamEvent> {
+    if let Some(data) = line.strip_prefix("data: ") {
+        if data == "[DONE]" {
+            return None;
+        }
+        serde_json::from_str(data).ok()
+    } else {
+        None
+    }
+}
+
+impl zed::Extension for OpenAiProvider {
+    fn new() -> Self {
+        Self {
+            streams: Mutex::new(HashMap::new()),
+            next_stream_id: Mutex::new(0),
+        }
+    }
+
+    fn llm_providers(&self) -> Vec<LlmProviderInfo> {
+        vec![LlmProviderInfo {
+            id: "openai".into(),
+            name: "OpenAI".into(),
+            icon: Some("icons/openai.svg".into()),
+        }]
+    }
+
+    fn llm_provider_models(&self, _provider_id: &str) -> Result<Vec<LlmModelInfo>, String> {
+        Ok(MODELS
+            .iter()
+            .map(|m| LlmModelInfo {
+                id: m.display_name.to_string(),
+                name: m.display_name.to_string(),
+                max_token_count: m.max_tokens,
+                max_output_tokens: m.max_output_tokens,
+                capabilities: LlmModelCapabilities {
+                    supports_images: m.supports_images,
+                    supports_tools: true,
+                    supports_tool_choice_auto: true,
+                    supports_tool_choice_any: true,
+                    supports_tool_choice_none: true,
+                    supports_thinking: false,
+                    tool_input_format: LlmToolInputFormat::JsonSchema,
+                },
+                is_default: m.is_default,
+                is_default_fast: m.is_default_fast,
+            })
+            .collect())
+    }
+
+    fn llm_provider_is_authenticated(&self, _provider_id: &str) -> bool {
+        llm_get_credential("openai").is_some()
+    }
+
+    fn llm_provider_settings_markdown(&self, _provider_id: &str) -> Option<String> {
+        Some(
+            r#"# OpenAI Setup
+
+Welcome to **OpenAI**! This extension provides access to OpenAI GPT models.
+
+## Configuration
+
+Enter your OpenAI API key below. You can find your API key at [platform.openai.com/api-keys](https://platform.openai.com/api-keys).
+
+## Available Models
+
+| Display Name | Real Model | Context | Output |
+|--------------|------------|---------|--------|
+| GPT-4o | gpt-4o | 128K | 16K |
+| GPT-4o-mini | gpt-4o-mini | 128K | 16K |
+| GPT-4.1 | gpt-4.1 | 1M | 32K |
+| GPT-4.1-mini | gpt-4.1-mini | 1M | 32K |
+| GPT-5 | gpt-5 | 272K | 32K |
+| GPT-5-mini | gpt-5-mini | 272K | 32K |
+| o1 | o1 | 200K | 100K |
+| o3 | o3 | 200K | 100K |
+| o3-mini | o3-mini | 200K | 100K |
+
+## Features
+
+- ✅ Full streaming support
+- ✅ Tool/function calling
+- ✅ Vision (image inputs)
+- ✅ All OpenAI models
+
+## Pricing
+
+Uses your OpenAI API credits. See [OpenAI pricing](https://openai.com/pricing) for details.
+"#
+            .to_string(),
+        )
+    }
+
+    fn llm_provider_authenticate(&mut self, _provider_id: &str) -> Result<(), String> {
+        let provided = llm_request_credential(
+            "openai",
+            LlmCredentialType::ApiKey,
+            "OpenAI API Key",
+            "sk-...",
+        )?;
+        if provided {
+            Ok(())
+        } else {
+            Err("Authentication cancelled".to_string())
+        }
+    }
+
+    fn llm_provider_reset_credentials(&mut self, _provider_id: &str) -> Result<(), String> {
+        llm_delete_credential("openai")
+    }
+
+    fn llm_stream_completion_start(
+        &mut self,
+        _provider_id: &str,
+        model_id: &str,
+        request: &LlmCompletionRequest,
+    ) -> Result<String, String> {
+        let api_key = llm_get_credential("openai").ok_or_else(|| {
+            "No API key configured. Please add your OpenAI API key in settings.".to_string()
+        })?;
+
+        let openai_request = convert_request(model_id, request)?;
+
+        let body = serde_json::to_vec(&openai_request)
+            .map_err(|e| format!("Failed to serialize request: {}", e))?;
+
+        let http_request = HttpRequest {
+            method: HttpMethod::Post,
+            url: "https://api.openai.com/v1/chat/completions".to_string(),
+            headers: vec![
+                ("Content-Type".to_string(), "application/json".to_string()),
+                ("Authorization".to_string(), format!("Bearer {}", api_key)),
+            ],
+            body: Some(body),
+            redirect_policy: RedirectPolicy::FollowAll,
+        };
+
+        let response_stream = http_request
+            .fetch_stream()
+            .map_err(|e| format!("HTTP request failed: {}", e))?;
+
+        let stream_id = {
+            let mut id_counter = self.next_stream_id.lock().unwrap();
+            let id = format!("openai-stream-{}", *id_counter);
+            *id_counter += 1;
+            id
+        };
+
+        self.streams.lock().unwrap().insert(
+            stream_id.clone(),
+            StreamState {
+                response_stream: Some(response_stream),
+                buffer: String::new(),
+                started: false,
+                tool_calls: HashMap::new(),
+                tool_calls_emitted: false,
+            },
+        );
+
+        Ok(stream_id)
+    }
+
+    fn llm_stream_completion_next(
+        &mut self,
+        stream_id: &str,
+    ) -> Result<Option<LlmCompletionEvent>, String> {
+        let mut streams = self.streams.lock().unwrap();
+        let state = streams
+            .get_mut(stream_id)
+            .ok_or_else(|| format!("Unknown stream: {}", stream_id))?;
+
+        if !state.started {
+            state.started = true;
+            return Ok(Some(LlmCompletionEvent::Started));
+        }
+
+        let response_stream = state
+            .response_stream
+            .as_mut()
+            .ok_or_else(|| "Stream already closed".to_string())?;
+
+        loop {
+            if let Some(newline_pos) = state.buffer.find('\n') {
+                let line = state.buffer[..newline_pos].trim().to_string();
+                state.buffer = state.buffer[newline_pos + 1..].to_string();
+
+                if line.is_empty() {
+                    continue;
+                }
+
+                if let Some(event) = parse_sse_line(&line) {
+                    if let Some(choice) = event.choices.first() {
+                        if let Some(tool_calls) = &choice.delta.tool_calls {
+                            for tc in tool_calls {
+                                let entry = state.tool_calls.entry(tc.index).or_default();
+
+                                if let Some(id) = &tc.id {
+                                    entry.id = id.clone();
+                                }
+
+                                if let Some(func) = &tc.function {
+                                    if let Some(name) = &func.name {
+                                        entry.name = name.clone();
+                                    }
+                                    if let Some(args) = &func.arguments {
+                                        entry.arguments.push_str(args);
+                                    }
+                                }
+                            }
+                        }
+
+                        if let Some(reason) = &choice.finish_reason {
+                            if reason == "tool_calls" && !state.tool_calls_emitted {
+                                state.tool_calls_emitted = true;
+                                if let Some((&index, _)) = state.tool_calls.iter().next() {
+                                    if let Some(tool_call) = state.tool_calls.remove(&index) {
+                                        return Ok(Some(LlmCompletionEvent::ToolUse(LlmToolUse {
+                                            id: tool_call.id,
+                                            name: tool_call.name,
+                                            input: tool_call.arguments,
+                                            thought_signature: None,
+                                        })));
+                                    }
+                                }
+                            }
+
+                            let stop_reason = match reason.as_str() {
+                                "stop" => LlmStopReason::EndTurn,
+                                "length" => LlmStopReason::MaxTokens,
+                                "tool_calls" => LlmStopReason::ToolUse,
+                                "content_filter" => LlmStopReason::Refusal,
+                                _ => LlmStopReason::EndTurn,
+                            };
+
+                            if let Some(usage) = event.usage {
+                                return Ok(Some(LlmCompletionEvent::Usage(LlmTokenUsage {
+                                    input_tokens: usage.prompt_tokens,
+                                    output_tokens: usage.completion_tokens,
+                                    cache_creation_input_tokens: None,
+                                    cache_read_input_tokens: None,
+                                })));
+                            }
+
+                            return Ok(Some(LlmCompletionEvent::Stop(stop_reason)));
+                        }
+
+                        if let Some(content) = &choice.delta.content {
+                            if !content.is_empty() {
+                                return Ok(Some(LlmCompletionEvent::Text(content.clone())));
+                            }
+                        }
+                    }
+
+                    if event.choices.is_empty() {
+                        if let Some(usage) = event.usage {
+                            return Ok(Some(LlmCompletionEvent::Usage(LlmTokenUsage {
+                                input_tokens: usage.prompt_tokens,
+                                output_tokens: usage.completion_tokens,
+                                cache_creation_input_tokens: None,
+                                cache_read_input_tokens: None,
+                            })));
+                        }
+                    }
+                }
+
+                continue;
+            }
+
+            match response_stream.next_chunk() {
+                Ok(Some(chunk)) => {
+                    let text = String::from_utf8_lossy(&chunk);
+                    state.buffer.push_str(&text);
+                }
+                Ok(None) => {
+                    if !state.tool_calls.is_empty() && !state.tool_calls_emitted {
+                        state.tool_calls_emitted = true;
+                        let keys: Vec<usize> = state.tool_calls.keys().copied().collect();
+                        if let Some(&key) = keys.first() {
+                            if let Some(tool_call) = state.tool_calls.remove(&key) {
+                                return Ok(Some(LlmCompletionEvent::ToolUse(LlmToolUse {
+                                    id: tool_call.id,
+                                    name: tool_call.name,
+                                    input: tool_call.arguments,
+                                    thought_signature: None,
+                                })));
+                            }
+                        }
+                    }
+                    return Ok(None);
+                }
+                Err(e) => {
+                    return Err(format!("Stream error: {}", e));
+                }
+            }
+        }
+    }
+
+    fn llm_stream_completion_close(&mut self, stream_id: &str) {
+        self.streams.lock().unwrap().remove(stream_id);
+    }
+}
+
+zed::register_extension!(OpenAiProvider);