{  "completion_mode": "normal",  "cumulative_token_usage": {    "cache_creation_input_tokens": 18383,    "cache_read_input_tokens": 97250,    "input_tokens": 45,    "output_tokens": 776  },  "detailed_summary_state": "NotGenerated",  "exceeded_window_error": null,  "initial_project_snapshot": {    "timestamp": "2025-05-08T14:31:16.701157512Z",    "unsaved_buffer_paths": [],    "worktree_snapshots": [      {        "git_state": {          "current_branch": null,          "diff": "diff --git a/crates/language_model_selector/src/language_model_selector.rs b/crates/language_model_selector/src/language_model_selector.rs\nindex 6775bee98a..e25c9e1415 100644\n--- a/crates/language_model_selector/src/language_model_selector.rs\n+++ b/crates/language_model_selector/src/language_model_selector.rs\n@@ -410,7 +410,8 @@ impl ModelMatcher {\n     }\n \n     pub fn is_match(self: &Self, info: &ModelInfo) -> bool {\n-        self.matched_ids.contains(&info.model.id().0)\n+        let q = (info.model.provider_id(), info.model.id());\n+        self.matched_models.contains(&q)\n     }\n }\n \n",          "head_sha": "9245656485e58a5d6d717d82209bc8c57cb9c539",          "remote_url": "git@github.com:zed-industries/zed.git"        },        "worktree_path": "/home/silver/develop/zed"      }    ]  },  "messages": [    {      "context": "\n<context>\nThe following items were attached by the user. They are up-to-date and don't need to be re-read.\n\n<files>\n```rs zed/crates/language_model_selector/src/language_model_selector.rs\nconst TRY_ZED_PRO_URL [L28]\ntype OnModelChanged [L30]\ntype GetActiveModel [L31]\npub struct LanguageModelSelector [L33-37]\n picker [L34]\n _authenticate_all_providers_task [L35]\n _subscriptions [L36]\nimpl LanguageModelSelector [L39-231]\n pub fn new [L40-81]\n fn handle_language_model_registry_event [L83-104]\n fn authenticate_all_providers [L110-154]\n fn all_models [L156-204]\n pub fn active_model [L206-208]\n fn get_active_model_index [L210-230]\nimpl EventEmitter<DismissEvent> for LanguageModelSelector [L233]\nimpl Focusable for LanguageModelSelector [L235-239]\n fn focus_handle [L236-238]\nimpl Render for LanguageModelSelector [L241-245]\n fn render [L242-244]\npub struct LanguageModelSelectorPopoverMenu [L248-258]\n language_model_selector [L253]\n trigger [L254]\n tooltip [L255]\n handle [L256]\n anchor [L257]\nimpl LanguageModelSelectorPopoverMenu<T, TT> [L260-284]\n pub fn new [L265-278]\n pub fn with_handle [L280-283]\nimpl RenderOnce for LanguageModelSelectorPopoverMenu<T, TT> [L286-304]\n fn render [L291-303]\nstruct ModelInfo [L307-310]\n model [L308]\n icon [L309]\npub struct LanguageModelPickerDelegate [L312-319]\n language_model_selector [L313]\n on_model_changed [L314]\n get_active_model [L315]\n all_models [L316]\n filtered_entries [L317]\n selected_index [L318]\nstruct GroupedModels [L321-324]\n recommended [L322]\n other [L323]\nimpl GroupedModels [L326-385]\n pub fn new [L327-342]\n fn entries [L344-370]\n fn model_infos [L372-384]\nenum LanguageModelPickerEntry [L387-390]\n Model [L388]\n Separator [L389]\nstruct ModelMatcher [L392-396]\n models [L393]\n bg_executor [L394]\n candidates [L395]\nimpl ModelMatcher [L398-452]\n fn new [L399-406]\n pub fn fuzzy_search [L408-424]\n pub fn exact_search [L426-438]\n fn make_match_candidates [L440-451]\nimpl PickerDelegate for LanguageModelPickerDelegate [L454-693]\n type ListItem [L455]\n fn match_count [L457-459]\n fn selected_index [L461-463]\n fn set_selected_index [L465-468]\n fn can_select [L470-480]\n fn placeholder_text [L482-484]\n fn update_matches [L486-546]\n fn confirm [L548-560]\n fn dismissed [L562-566]\n fn render_match [L568-636]\n fn render_footer [L638-692]\n\nShowing symbols 1-71 (total symbols: 71)\n\n```\n</files>\n</context>\n",      "creases": [        {          "end": 140,          "icon_path": "icons/file_icons/rust.svg",          "label": "language_model_selector.rs",          "start": 38        }      ],      "id": 0,      "role": "user",      "segments": [        {          "text": "I recently introduced fuzzy search in [@language_model_selector.rs](@file:zed/crates/language_model_selector/src/language_model_selector.rs). Can you write unit-test that check it? You can find a test list of models on images. ",          "type": "text"        }      ],      "tool_results": [],      "tool_uses": []    },    {      "context": "",      "creases": [],      "id": 1,      "role": "assistant",      "segments": [        {          "text": "I'll help you write unit tests for the fuzzy search functionality in the language model selector. I see that you want to test the fuzzy search with the models shown in the images - both Claude models (3, 3.5, 3.7) and GPT models (GPT-3.5, GPT-4, GPT-4o, etc.).\n\nLet's start by examining the code structure to understand how the fuzzy search works.",          "type": "text"        }      ],      "tool_results": [        {          "content": "zed/crates/language_model_selector/Cargo.toml\nzed/crates/language_model_selector/LICENSE-GPL\nzed/crates/language_model_selector/src\n",          "is_error": false,          "output": null,          "tool_use_id": "toolu_01FvYMtHs763GL1wA5mpTpqn"        }      ],      "tool_uses": [        {          "id": "toolu_01FvYMtHs763GL1wA5mpTpqn",          "input": {            "path": "zed/crates/language_model_selector"          },          "name": "list_directory"        }      ]    },    {      "context": "",      "creases": [],      "id": 2,      "role": "assistant",      "segments": [        {          "text": "Let's look at the structure of the tests directory or see if there are existing tests:",          "type": "text"        }      ],      "tool_results": [        {          "content": "zed/crates/language_model_selector/src/language_model_selector.rs\n",          "is_error": false,          "output": null,          "tool_use_id": "toolu_01KSLDsLLrf7tgixB1sge3cm"        }      ],      "tool_uses": [        {          "id": "toolu_01KSLDsLLrf7tgixB1sge3cm",          "input": {            "path": "zed/crates/language_model_selector/src"          },          "name": "list_directory"        }      ]    },    {      "context": "",      "creases": [],      "id": 3,      "role": "assistant",      "segments": [        {          "text": "Let's check the Cargo.toml to understand the dependencies:",          "type": "text"        }      ],      "tool_results": [        {          "content": "[package]\nname = \"language_model_selector\"\nversion = \"0.1.0\"\nedition.workspace = true\npublish.workspace = true\nlicense = \"GPL-3.0-or-later\"\n\n[lints]\nworkspace = true\n\n[lib]\npath = \"src/language_model_selector.rs\"\n\n[dependencies]\ncollections.workspace = true\nfeature_flags.workspace = true\nfuzzy.workspace = true\ngpui.workspace = true\nlanguage_model.workspace = true\nlog.workspace = true\npicker.workspace = true\nproto.workspace = true\nui.workspace = true\n\nzed_actions.workspace = true\n",          "is_error": false,          "output": null,          "tool_use_id": "toolu_019Je2MLfJhpJr93g5igoRAH"        }      ],      "tool_uses": [        {          "id": "toolu_019Je2MLfJhpJr93g5igoRAH",          "input": {            "path": "zed/crates/language_model_selector/Cargo.toml"          },          "name": "read_file"        }      ]    },    {      "context": "",      "creases": [],      "id": 4,      "role": "assistant",      "segments": [        {          "text": "Now let's look at the fuzzy search implementation in detail:",          "type": "text"        }      ],      "tool_results": [        {          "content": "struct ModelMatcher {\n    models: Vec<ModelInfo>,\n    bg_executor: BackgroundExecutor,\n    candidates: Vec<StringMatchCandidate>,\n}\n\nimpl ModelMatcher {\n    fn new(models: Vec<ModelInfo>, bg_executor: BackgroundExecutor) -> ModelMatcher {\n        let candidates = Self::make_match_candidates(&models);\n        Self {\n            models,\n            bg_executor,\n            candidates,\n        }\n    }\n\n    pub fn fuzzy_search(&self, query: &str) -> Vec<ModelInfo> {\n        let matches = self.bg_executor.block(match_strings(\n            &self.candidates,\n            &query,\n            false,\n            100,\n            &Default::default(),\n            self.bg_executor.clone(),\n        ));\n\n        let matched_models: Vec<_> = matches\n            .into_iter()\n            .map(|m| self.models[m.candidate_id].clone())\n            .collect();\n\n        matched_models\n    }\n\n    pub fn exact_search(&self, query: &str) -> Vec<ModelInfo> {\n        self.models\n            .iter()\n            .filter(|m| {\n                m.model\n                    .name()\n                    .0\n                    .to_lowercase()\n                    .contains(&query.to_lowercase())\n            })\n            .cloned()\n            .collect::<Vec<_>>()\n    }\n\n    fn make_match_candidates(model_infos: &Vec<ModelInfo>) -> Vec<StringMatchCandidate> {\n        model_infos\n            .iter()\n            .enumerate()\n            .map(|(index, model)| {\n                StringMatchCandidate::new(\n                    index,\n                    &format!(\"{}/{}\", &model.model.provider_id().0, &model.model.name().0),\n                )\n            })\n            .collect::<Vec<_>>()\n    }\n}",          "is_error": false,          "output": null,          "tool_use_id": "toolu_01GpKFEn6hYrXGiS5yBF3urk"        }      ],      "tool_uses": [        {          "id": "toolu_01GpKFEn6hYrXGiS5yBF3urk",          "input": {            "end_line": 452,            "path": "zed/crates/language_model_selector/src/language_model_selector.rs",            "start_line": 392          },          "name": "read_file"        }      ]    },    {      "context": "",      "creases": [],      "id": 5,      "role": "assistant",      "segments": [        {          "text": "Let's now check if there's an existing test module:",          "type": "text"        }      ],      "tool_results": [        {          "content": "No matches found",          "is_error": false,          "output": null,          "tool_use_id": "toolu_01RZAvFvpMq16Dwh6d6cnVzy"        }      ],      "tool_uses": [        {          "id": "toolu_01RZAvFvpMq16Dwh6d6cnVzy",          "input": {            "include_pattern": "zed/crates/language_model_selector/**/*.rs",            "regex": "mod tests"          },          "name": "grep"        }      ]    },    {      "context": "",      "creases": [],      "id": 6,      "role": "assistant",      "segments": [        {          "text": "Now I'll create a test module for the ModelMatcher's fuzzy search functionality. Let's create this test module:",          "type": "text"        }      ],      "tool_results": [],      "tool_uses": []    }  ],  "model": {    "model": "claude-3-7-sonnet-latest",    "provider": "zed.dev"  },  "profile": "Write",  "request_token_usage": [    {      "cache_creation_input_tokens": 9581,      "input_tokens": 4,      "output_tokens": 5    },    {      "cache_creation_input_tokens": 204,      "cache_read_input_tokens": 9581,      "input_tokens": 6,      "output_tokens": 5    },    {      "cache_creation_input_tokens": 104,      "cache_read_input_tokens": 9785,      "input_tokens": 6,      "output_tokens": 5    },    {      "cache_creation_input_tokens": 239,      "cache_read_input_tokens": 9889,      "input_tokens": 6,      "output_tokens": 5    },    {      "cache_creation_input_tokens": 569,      "cache_read_input_tokens": 10128,      "input_tokens": 5,      "output_tokens": 5    },    {      "cache_creation_input_tokens": 87,      "cache_read_input_tokens": 10697,      "input_tokens": 5,      "output_tokens": 2    },    {      "cache_creation_input_tokens": 7355,      "cache_read_input_tokens": 10784,      "input_tokens": 5,      "output_tokens": 3    }  ],  "summary": "Fuzzy Search Testing Language Model Selector",  "updated_at": "2025-05-08T18:20:34.205405751Z",  "version": "0.2.0"}