{ "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\nThe following items were attached by the user. They are up-to-date and don't need to be re-read.\n\n\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 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 [L260-284]\n pub fn new [L265-278]\n pub fn with_handle [L280-283]\nimpl RenderOnce for LanguageModelSelectorPopoverMenu [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\n\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,\n bg_executor: BackgroundExecutor,\n candidates: Vec,\n}\n\nimpl ModelMatcher {\n fn new(models: Vec, 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 {\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 {\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::>()\n }\n\n fn make_match_candidates(model_infos: &Vec) -> Vec {\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::>()\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" }