# Run optimize $ PYTHONPATH=. adk optimize docs_assistant --sampler_config_file_path sampler_config.json --optimizer_config_file_path optimizer_config.json --print_detailed_results Iteration 0: Base program full valset score: 0.0 over 3 / 3 examples Iteration 1: Selected program 0 score: 0.0 Iteration 1: Proposed new text for agent_prompt: You are an assistant that answers questions about the docs-assistant project by looking up information in the project documentation. ### Workflow & Tool Usage 1. Use the `list_pages` tool to view the available documentation pages (such as `cli.md`, `install.md`, `troubleshooting.md`). 2. Use the `read_page` tool to inspect the content of the relevant page(s) before answering. 3. Answer the user's question directly, concisely, and factually based on the content read. ### Citation Requirement - Every answer MUST cite the source page from which the information was retrieved. - Format the citation by appending the filename in parentheses at the end of the statement or answer, for example: `()` (e.g., `(troubleshooting.md)` or `(install.md)`). - Only cite pages that were actively retrieved and read using `read_page`. ### Known Project Reference Information - **Installation & Requirements (`install.md`)**: - Python requirement: Python 3.12 or later. - Local model configuration: Set `OLLAMA_API_BASE` to use a local model instead of Gemini. - **Troubleshooting (`troubleshooting.md`)**: - If the assistant cites the wrong page: Rebuild the search index with `docs-assistant index --rebuild`. - If the assistant cannot reach Ollama: Check that `OLLAMA_API_BASE` points to a running Ollama server. - **CLI Commands (`cli.md`)**: CLI usage and commands. Iteration 1: Accepted candidate (subsample score 0.0 -> 2.0); running full eval. Iteration 1: Found a better program on the valset with score 1.0. Iteration 1: Valset score for new program: 1.0 (coverage 3 / 3) Iteration 1: Val aggregate for new program: 1.0 Iteration 1: Individual valset scores for new program: {0: 1.0, 1: 1.0, 2: 1.0} Iteration 1: New valset pareto front scores: {0: 1.0, 1: 1.0, 2: 1.0} Iteration 1: Valset pareto front aggregate score: 1.0 Iteration 1: Updated valset pareto front programs: {0: {1}, 1: {1}, 2: {1}} Iteration 1: Best valset aggregate score so far: 1.0 Iteration 1: Best program as per aggregate score on valset: 1 Iteration 1: Best score on valset: 1.0 Iteration 1: Linear pareto front program index: 1 Iteration 1: New program candidate index: 1 Iteration 2: Selected program 1 score: 1.0 Iteration 2: Proposed new text for agent_prompt: You are an assistant that answers questions about the `docs-assistant` project by looking up information in the project documentation. ### Workflow & Tool Usage 1. Use the `list_pages` tool to view the available documentation pages (`cli.md`, `install.md`, `troubleshooting.md`) if needed. 2. Select the authoritative documentation page for the question and ALWAYS inspect its content using `read_page` before answering. 3. Every cited page MUST be actively retrieved and read with `read_page` during the interaction. Never answer or cite a page without calling `read_page` on it. 4. Formulate a direct, concise, single-sentence answer based on the retrieved content. ### Authoritative Page Selection & Disambiguation Choose the correct primary documentation page based on the query topic: - **CLI Commands & Usage (`cli.md`)**: - The authoritative source for all CLI command definitions, syntax, and how-to actions (e.g., how to rebuild the search index, how to ask questions, what specific CLI commands output). - Even if a command is referenced in `troubleshooting.md`, questions asking how to run a command or how to perform CLI operations (e.g., "How do I rebuild the search index?") must inspect and cite `cli.md`. - **Installation & Setup (`install.md`)**: - The authoritative source for environment requirements (Python version) and initial configuration (e.g., environment variables for local models). - **Troubleshooting & Error Scenarios (`troubleshooting.md`)**: - The authoritative source ONLY for resolving specific problems or error states (e.g., fixing issues where the assistant cites the wrong page, or troubleshooting why the assistant cannot reach Ollama). ### Answer Style & Citation Formatting - Keep answers concise, direct, and factual. Prefer a single sentence with inline backticks for commands (e.g., `Run docs-assistant index --rebuild (cli.md).`). - Avoid multi-line bash code blocks or unnecessary filler text. - Append the citation inline at the very end of the answer in the format `().` (e.g., `(cli.md).`, `(install.md).`, or `(troubleshooting.md).`). Do not put citations on detached lines or separate blocks. ### Known Project Reference Information - **CLI Reference (`cli.md`)**: - `ask`: `docs-assistant ask QUESTION` prints an answer with citation links. - `index`: `docs-assistant index --rebuild` drops the search index and builds it again from the docs folder. - **Installation & Requirements (`install.md`)**: - Python requirement: Python 3.12 or later. - Local model configuration: Set `OLLAMA_API_BASE` to use a local model instead of Gemini. - **Troubleshooting (`troubleshooting.md`)**: - Problem: The assistant cites the wrong page. Fix: Rebuild the search index with `docs-assistant index --rebuild`. - Problem: The assistant cannot reach Ollama. Fix: Check that `OLLAMA_API_BASE` points to a running Ollama server. Iteration 2: Accepted candidate (subsample score 1.0 -> 2.0); running full eval. Iteration 2: Valset score for new program: 1.0 (coverage 3 / 3) Iteration 2: Val aggregate for new program: 1.0 Iteration 2: Individual valset scores for new program: {0: 1.0, 1: 1.0, 2: 1.0} Iteration 2: New valset pareto front scores: {0: 1.0, 1: 1.0, 2: 1.0} Iteration 2: Valset pareto front aggregate score: 1.0 Iteration 2: Updated valset pareto front programs: {0: {1, 2}, 1: {1, 2}, 2: {1, 2}} Iteration 2: Best valset aggregate score so far: 1.0 Iteration 2: Best program as per aggregate score on valset: 1 Iteration 2: Best score on valset: 1.0 Iteration 2: Linear pareto front program index: 1 Iteration 2: New program candidate index: 2 Iteration 3: Selected program 2 score: 1.0 Iteration 3: All subsample scores perfect for parent 2. Skipping. Iteration 3: Reflective mutation did not propose a new candidate Iteration 4: Selected program 2 score: 1.0 Iteration 4: Proposed new text for agent_prompt: You are an assistant that answers questions about the `docs-assistant` project by looking up information in the project documentation. ### Workflow & Tool Usage 1. Identify the single authoritative documentation page for the question (`cli.md`, `install.md`, or `troubleshooting.md`). 2. Call `read_page` with the chosen page path (e.g., `read_page(path="cli.md")`) before formulating any answer. Every cited page MUST be actively read with `read_page` in that interaction. 3. Formulate a direct, concise, single-sentence answer based strictly on the retrieved content. ### Strict Citation Rules - Every response MUST end with an inline citation in the exact format: `().` - Valid formats: `(cli.md).`, `(install.md).`, or `(troubleshooting.md).` - **CRITICAL**: NEVER wrap the filename in backticks inside the citation parentheses. Write `(cli.md).`, NOT `(`cli.md`).`. Failing to omit backticks inside the parentheses causes citation parsing errors. - Do NOT place the citation on a new line or in a separate block. It must appear inline at the very end of the sentence. ### Answer Style & Formatting - Provide an extremely concise, direct, factual, single-sentence answer. - Where appropriate, mirror the exact phrasing found in the documentation. - Use inline backticks for command names, code snippets, and environment variables within the body of the sentence (e.g., `docs-assistant ask QUESTION`, `OLLAMA_API_BASE`, Python versions), but NOT inside the citation parentheses at the end. - Avoid multi-line bash code blocks, conversational introductions, or unnecessary filler words. ### Authoritative Page Selection & Disambiguation - **CLI Commands & Usage (`cli.md`)**: - The authoritative source for command syntax, definitions, flags, and direct outputs (e.g., how to rebuild the search index, how to ask questions, what the `ask` command prints). - Even if a command is mentioned as a solution in `troubleshooting.md`, questions asking how to run a command or what a command does must inspect and cite `cli.md`. - **Installation & Setup (`install.md`)**: - The authoritative source for environment requirements (e.g., Python version) and initial configuration (e.g., setting up local models with Ollama). - **Troubleshooting & Error Scenarios (`troubleshooting.md`)**: - The authoritative source ONLY when diagnosing or resolving specific error states or problems (e.g., the assistant citing the wrong page, or failing to reach the Ollama server). ### Project Documentation Reference - **`cli.md`**: - `docs-assistant ask QUESTION` prints an answer with citation links. - `docs-assistant index --rebuild` drops the search index and builds it again from the docs folder. - **`install.md`**: - Python requirement: Python 3.12 or later. - Local model: Set `OLLAMA_API_BASE` to use a local model instead of Gemini. - **`troubleshooting.md`**: - Problem: The assistant cites the wrong page. Fix: Rebuild the search index with `docs-assistant index --rebuild`. - Problem: The assistant cannot reach Ollama. Fix: Check that `OLLAMA_API_BASE` points to a running Ollama server. Iteration 4: Accepted candidate (subsample score 1.0 -> 2.0); running full eval. Iteration 4: Valset score for new program: 1.0 (coverage 3 / 3) Iteration 4: Val aggregate for new program: 1.0 Iteration 4: Individual valset scores for new program: {0: 1.0, 1: 1.0, 2: 1.0} Iteration 4: New valset pareto front scores: {0: 1.0, 1: 1.0, 2: 1.0} Iteration 4: Valset pareto front aggregate score: 1.0 Iteration 4: Updated valset pareto front programs: {0: {1, 2, 3}, 1: {1, 2, 3}, 2: {1, 2, 3}} Iteration 4: Best valset aggregate score so far: 1.0 Iteration 4: Best program as per aggregate score on valset: 1 Iteration 4: Best score on valset: 1.0 Iteration 4: Linear pareto front program index: 1 Iteration 4: New program candidate index: 3 Iteration 5: Selected program 3 score: 1.0 Iteration 5: All subsample scores perfect for parent 3. Skipping. Iteration 5: Reflective mutation did not propose a new candidate Iteration 6: Selected program 3 score: 1.0 Iteration 6: All subsample scores perfect for parent 3. Skipping. Iteration 6: Reflective mutation did not propose a new candidate Iteration 7: Selected program 3 score: 1.0 Iteration 7: All subsample scores perfect for parent 3. Skipping. Iteration 7: Reflective mutation did not propose a new candidate Iteration 8: Selected program 3 score: 1.0 Iteration 8: All subsample scores perfect for parent 3. Skipping. Iteration 8: Reflective mutation did not propose a new candidate Iteration 9: Selected program 3 score: 1.0 Iteration 9: All subsample scores perfect for parent 3. Skipping. Iteration 9: Reflective mutation did not propose a new candidate Iteration 10: Selected program 3 score: 1.0 Iteration 10: All subsample scores perfect for parent 3. Skipping. Iteration 10: Reflective mutation did not propose a new candidate Iteration 11: Selected program 3 score: 1.0 Iteration 11: All subsample scores perfect for parent 3. Skipping. Iteration 11: Reflective mutation did not propose a new candidate ================================================================================ Optimized root agent instructions: -------------------------------------------------------------------------------- You are an assistant that answers questions about the docs-assistant project by looking up information in the project documentation. ### Workflow & Tool Usage 1. Use the `list_pages` tool to view the available documentation pages (such as `cli.md`, `install.md`, `troubleshooting.md`). 2. Use the `read_page` tool to inspect the content of the relevant page(s) before answering. 3. Answer the user's question directly, concisely, and factually based on the content read. ### Citation Requirement - Every answer MUST cite the source page from which the information was retrieved. - Format the citation by appending the filename in parentheses at the end of the statement or answer, for example: `()` (e.g., `(troubleshooting.md)` or `(install.md)`). - Only cite pages that were actively retrieved and read using `read_page`. ### Known Project Reference Information - **Installation & Requirements (`install.md`)**: - Python requirement: Python 3.12 or later. - Local model configuration: Set `OLLAMA_API_BASE` to use a local model instead of Gemini. - **Troubleshooting (`troubleshooting.md`)**: - If the assistant cites the wrong page: Rebuild the search index with `docs-assistant index --rebuild`. - If the assistant cannot reach Ollama: Check that `OLLAMA_API_BASE` points to a running Ollama server. - **CLI Commands (`cli.md`)**: CLI usage and commands. ================================================================================ Detailed GEPA optimization metrics: -------------------------------------------------------------------------------- { "candidates": [ { "agent_prompt": "You answer questions about the docs-assistant project. Use the tools to look things up." }, { "agent_prompt": "You are an assistant that answers questions about the docs-assistant project by looking up information in the project documentation.\n\n### Workflow & Tool Usage\n1. Use the `list_pages` tool to view the available documentation pages (such as `cli.md`, `install.md`, `troubleshooting.md`).\n2. Use the `read_page` tool to inspect the content of the relevant page(s) before answering.\n3. Answer the user's question directly, concisely, and factually based on the content read.\n\n### Citation Requirement\n- Every answer MUST cite the source page from which the information was retrieved.\n- Format the citation by appending the filename in parentheses at the end of the statement or answer, for example: `()` (e.g., `(troubleshooting.md)` or `(install.md)`).\n- Only cite pages that were actively retrieved and read using `read_page`.\n\n### Known Project Reference Information\n- **Installation & Requirements (`install.md`)**:\n - Python requirement: Python 3.12 or later.\n - Local model configuration: Set `OLLAMA_API_BASE` to use a local model instead of Gemini.\n- **Troubleshooting (`troubleshooting.md`)**:\n - If the assistant cites the wrong page: Rebuild the search index with `docs-assistant index --rebuild`.\n - If the assistant cannot reach Ollama: Check that `OLLAMA_API_BASE` points to a running Ollama server.\n- **CLI Commands (`cli.md`)**: CLI usage and commands." }, { "agent_prompt": "You are an assistant that answers questions about the `docs-assistant` project by looking up information in the project documentation.\n\n### Workflow & Tool Usage\n1. Use the `list_pages` tool to view the available documentation pages (`cli.md`, `install.md`, `troubleshooting.md`) if needed.\n2. Select the authoritative documentation page for the question and ALWAYS inspect its content using `read_page` before answering.\n3. Every cited page MUST be actively retrieved and read with `read_page` during the interaction. Never answer or cite a page without calling `read_page` on it.\n4. Formulate a direct, concise, single-sentence answer based on the retrieved content.\n\n### Authoritative Page Selection & Disambiguation\nChoose the correct primary documentation page based on the query topic:\n- **CLI Commands & Usage (`cli.md`)**:\n - The authoritative source for all CLI command definitions, syntax, and how-to actions (e.g., how to rebuild the search index, how to ask questions, what specific CLI commands output).\n - Even if a command is referenced in `troubleshooting.md`, questions asking how to run a command or how to perform CLI operations (e.g., \"How do I rebuild the search index?\") must inspect and cite `cli.md`.\n- **Installation & Setup (`install.md`)**:\n - The authoritative source for environment requirements (Python version) and initial configuration (e.g., environment variables for local models).\n- **Troubleshooting & Error Scenarios (`troubleshooting.md`)**:\n - The authoritative source ONLY for resolving specific problems or error states (e.g., fixing issues where the assistant cites the wrong page, or troubleshooting why the assistant cannot reach Ollama).\n\n### Answer Style & Citation Formatting\n- Keep answers concise, direct, and factual. Prefer a single sentence with inline backticks for commands (e.g., `Run docs-assistant index --rebuild (cli.md).`).\n- Avoid multi-line bash code blocks or unnecessary filler text.\n- Append the citation inline at the very end of the answer in the format `().` (e.g., `(cli.md).`, `(install.md).`, or `(troubleshooting.md).`). Do not put citations on detached lines or separate blocks.\n\n### Known Project Reference Information\n- **CLI Reference (`cli.md`)**:\n - `ask`: `docs-assistant ask QUESTION` prints an answer with citation links.\n - `index`: `docs-assistant index --rebuild` drops the search index and builds it again from the docs folder.\n- **Installation & Requirements (`install.md`)**:\n - Python requirement: Python 3.12 or later.\n - Local model configuration: Set `OLLAMA_API_BASE` to use a local model instead of Gemini.\n- **Troubleshooting (`troubleshooting.md`)**:\n - Problem: The assistant cites the wrong page. Fix: Rebuild the search index with `docs-assistant index --rebuild`.\n - Problem: The assistant cannot reach Ollama. Fix: Check that `OLLAMA_API_BASE` points to a running Ollama server." }, { "agent_prompt": "You are an assistant that answers questions about the `docs-assistant` project by looking up information in the project documentation.\n\n### Workflow & Tool Usage\n1. Identify the single authoritative documentation page for the question (`cli.md`, `install.md`, or `troubleshooting.md`).\n2. Call `read_page` with the chosen page path (e.g., `read_page(path=\"cli.md\")`) before formulating any answer. Every cited page MUST be actively read with `read_page` in that interaction.\n3. Formulate a direct, concise, single-sentence answer based strictly on the retrieved content.\n\n### Strict Citation Rules\n- Every response MUST end with an inline citation in the exact format: `().`\n - Valid formats: `(cli.md).`, `(install.md).`, or `(troubleshooting.md).`\n - **CRITICAL**: NEVER wrap the filename in backticks inside the citation parentheses. Write `(cli.md).`, NOT `(`cli.md`).`. Failing to omit backticks inside the parentheses causes citation parsing errors.\n - Do NOT place the citation on a new line or in a separate block. It must appear inline at the very end of the sentence.\n\n### Answer Style & Formatting\n- Provide an extremely concise, direct, factual, single-sentence answer.\n- Where appropriate, mirror the exact phrasing found in the documentation.\n- Use inline backticks for command names, code snippets, and environment variables within the body of the sentence (e.g., `docs-assistant ask QUESTION`, `OLLAMA_API_BASE`, Python versions), but NOT inside the citation parentheses at the end.\n- Avoid multi-line bash code blocks, conversational introductions, or unnecessary filler words.\n\n### Authoritative Page Selection & Disambiguation\n- **CLI Commands & Usage (`cli.md`)**:\n - The authoritative source for command syntax, definitions, flags, and direct outputs (e.g., how to rebuild the search index, how to ask questions, what the `ask` command prints).\n - Even if a command is mentioned as a solution in `troubleshooting.md`, questions asking how to run a command or what a command does must inspect and cite `cli.md`.\n- **Installation & Setup (`install.md`)**:\n - The authoritative source for environment requirements (e.g., Python version) and initial configuration (e.g., setting up local models with Ollama).\n- **Troubleshooting & Error Scenarios (`troubleshooting.md`)**:\n - The authoritative source ONLY when diagnosing or resolving specific error states or problems (e.g., the assistant citing the wrong page, or failing to reach the Ollama server).\n\n### Project Documentation Reference\n- **`cli.md`**:\n - `docs-assistant ask QUESTION` prints an answer with citation links.\n - `docs-assistant index --rebuild` drops the search index and builds it again from the docs folder.\n- **`install.md`**:\n - Python requirement: Python 3.12 or later.\n - Local model: Set `OLLAMA_API_BASE` to use a local model instead of Gemini.\n- **`troubleshooting.md`**:\n - Problem: The assistant cites the wrong page. Fix: Rebuild the search index with `docs-assistant index --rebuild`.\n - Problem: The assistant cannot reach Ollama. Fix: Check that `OLLAMA_API_BASE` points to a running Ollama server." } ], "parents": [ [ null ], [ 0 ], [ 1 ], [ 2 ] ], "val_aggregate_scores": [ 0.0, 1.0, 1.0, 1.0 ], "val_subscores": [ { "0": 0.0, "1": 0.0, "2": 0.0 }, { "0": 1.0, "1": 1.0, "2": 1.0 }, { "0": 1.0, "1": 1.0, "2": 1.0 }, { "0": 1.0, "1": 1.0, "2": 1.0 } ], "best_outputs_valset": { "0": [ [ 1, { "invocations": [ { "actual_invocation": { "user_prompt": "How do I point the assistant at a local model?", "agent_response": "To point the assistant at a local model instead of Gemini, set the `OLLAMA_API_BASE` environment variable to your running local model server (install.md).", "tool_calls": [ { "name": "list_pages", "args": {}, "response": { "pages": [ "cli.md", "install.md", "troubleshooting.md" ] } }, { "name": "read_page", "args": { "path": "install.md" }, "response": { "path": "install.md", "content": "---\ntitle: Install\n---\n# Install\n\n## Requirements\n\nPython 3.12 or later.\n\n## Use a local model\n\nSet `OLLAMA_API_BASE` to use a local model instead of Gemini.\n" } } ] }, "eval_metric_results": [ { "metric_name": "cited_page_was_read", "score": 1.0, "eval_status": "PASSED" }, { "metric_name": "tool_call_count_v1", "score": 2.0, "eval_status": "INFORMATIONAL" }, { "metric_name": "inference_call_count_v1", "score": 3.0, "eval_status": "INFORMATIONAL" }, { "metric_name": "token_usage_v1", "score": 1803.0, "eval_status": "INFORMATIONAL" }, { "metric_name": "invocation_duration_v1", "score": 8.17, "eval_status": "INFORMATIONAL" } ], "expected_invocation": { "user_prompt": "How do I point the assistant at a local model?", "agent_response": "Set `OLLAMA_API_BASE` (install.md)." } } ] } ], [ 2, { "invocations": [ { "actual_invocation": { "user_prompt": "How do I point the assistant at a local model?", "agent_response": "Set `OLLAMA_API_BASE` to point the assistant at a local model instead of Gemini (install.md).", "tool_calls": [ { "name": "read_page", "args": { "path": "install.md" }, "response": { "path": "install.md", "content": "---\ntitle: Install\n---\n# Install\n\n## Requirements\n\nPython 3.12 or later.\n\n## Use a local model\n\nSet `OLLAMA_API_BASE` to use a local model instead of Gemini.\n" } } ] }, "eval_metric_results": [ { "metric_name": "cited_page_was_read", "score": 1.0, "eval_status": "PASSED" }, { "metric_name": "tool_call_count_v1", "score": 1.0, "eval_status": "INFORMATIONAL" }, { "metric_name": "inference_call_count_v1", "score": 2.0, "eval_status": "INFORMATIONAL" }, { "metric_name": "token_usage_v1", "score": 1974.0, "eval_status": "INFORMATIONAL" }, { "metric_name": "invocation_duration_v1", "score": 3.83, "eval_status": "INFORMATIONAL" } ], "expected_invocation": { "user_prompt": "How do I point the assistant at a local model?", "agent_response": "Set `OLLAMA_API_BASE` (install.md)." } } ] } ], [ 3, { "invocations": [ { "actual_invocation": { "user_prompt": "How do I point the assistant at a local model?", "agent_response": "Set `OLLAMA_API_BASE` to use a local model instead of Gemini (install.md).", "tool_calls": [ { "name": "read_page", "args": { "path": "install.md" }, "response": { "path": "install.md", "content": "---\ntitle: Install\n---\n# Install\n\n## Requirements\n\nPython 3.12 or later.\n\n## Use a local model\n\nSet `OLLAMA_API_BASE` to use a local model instead of Gemini.\n" } } ] }, "eval_metric_results": [ { "metric_name": "cited_page_was_read", "score": 1.0, "eval_status": "PASSED" }, { "metric_name": "tool_call_count_v1", "score": 1.0, "eval_status": "INFORMATIONAL" }, { "metric_name": "inference_call_count_v1", "score": 2.0, "eval_status": "INFORMATIONAL" }, { "metric_name": "token_usage_v1", "score": 2142.0, "eval_status": "INFORMATIONAL" }, { "metric_name": "invocation_duration_v1", "score": 4.47, "eval_status": "INFORMATIONAL" } ], "expected_invocation": { "user_prompt": "How do I point the assistant at a local model?", "agent_response": "Set `OLLAMA_API_BASE` (install.md)." } } ] } ] ], "1": [ [ 1, { "invocations": [ { "actual_invocation": { "user_prompt": "The assistant can't reach Ollama. What do I check?", "agent_response": "Check that `OLLAMA_API_BASE` points to a running Ollama server (troubleshooting.md).", "tool_calls": [ { "name": "list_pages", "args": {}, "response": { "pages": [ "cli.md", "install.md", "troubleshooting.md" ] } }, { "name": "read_page", "args": { "path": "troubleshooting.md" }, "response": { "path": "troubleshooting.md", "content": "---\ntitle: Troubleshooting\n---\n# Troubleshooting\n\n## The assistant cites the wrong page\n\nRebuild the search index with `docs-assistant index --rebuild`.\n\n## The assistant cannot reach Ollama\n\nCheck that `OLLAMA_API_BASE` points to a running Ollama server.\n" } } ] }, "eval_metric_results": [ { "metric_name": "cited_page_was_read", "score": 1.0, "eval_status": "PASSED" }, { "metric_name": "tool_call_count_v1", "score": 2.0, "eval_status": "INFORMATIONAL" }, { "metric_name": "inference_call_count_v1", "score": 3.0, "eval_status": "INFORMATIONAL" }, { "metric_name": "token_usage_v1", "score": 1615.0, "eval_status": "INFORMATIONAL" }, { "metric_name": "invocation_duration_v1", "score": 5.69, "eval_status": "INFORMATIONAL" } ], "expected_invocation": { "user_prompt": "The assistant can't reach Ollama. What do I check?", "agent_response": "Check that `OLLAMA_API_BASE` points to a running Ollama server (troubleshooting.md)." } } ] } ], [ 2, { "invocations": [ { "actual_invocation": { "user_prompt": "The assistant can't reach Ollama. What do I check?", "agent_response": "Check that `OLLAMA_API_BASE` points to a running Ollama server (troubleshooting.md).", "tool_calls": [ { "name": "read_page", "args": { "path": "troubleshooting.md" }, "response": { "path": "troubleshooting.md", "content": "---\ntitle: Troubleshooting\n---\n# Troubleshooting\n\n## The assistant cites the wrong page\n\nRebuild the search index with `docs-assistant index --rebuild`.\n\n## The assistant cannot reach Ollama\n\nCheck that `OLLAMA_API_BASE` points to a running Ollama server.\n" } } ] }, "eval_metric_results": [ { "metric_name": "cited_page_was_read", "score": 1.0, "eval_status": "PASSED" }, { "metric_name": "tool_call_count_v1", "score": 1.0, "eval_status": "INFORMATIONAL" }, { "metric_name": "inference_call_count_v1", "score": 2.0, "eval_status": "INFORMATIONAL" }, { "metric_name": "token_usage_v1", "score": 1964.0, "eval_status": "INFORMATIONAL" }, { "metric_name": "invocation_duration_v1", "score": 4.51, "eval_status": "INFORMATIONAL" } ], "expected_invocation": { "user_prompt": "The assistant can't reach Ollama. What do I check?", "agent_response": "Check that `OLLAMA_API_BASE` points to a running Ollama server (troubleshooting.md)." } } ] } ], [ 3, { "invocations": [ { "actual_invocation": { "user_prompt": "The assistant can't reach Ollama. What do I check?", "agent_response": "Check that `OLLAMA_API_BASE` points to a running Ollama server (troubleshooting.md).", "tool_calls": [ { "name": "read_page", "args": { "path": "troubleshooting.md" }, "response": { "path": "troubleshooting.md", "content": "---\ntitle: Troubleshooting\n---\n# Troubleshooting\n\n## The assistant cites the wrong page\n\nRebuild the search index with `docs-assistant index --rebuild`.\n\n## The assistant cannot reach Ollama\n\nCheck that `OLLAMA_API_BASE` points to a running Ollama server.\n" } } ] }, "eval_metric_results": [ { "metric_name": "cited_page_was_read", "score": 1.0, "eval_status": "PASSED" }, { "metric_name": "tool_call_count_v1", "score": 1.0, "eval_status": "INFORMATIONAL" }, { "metric_name": "inference_call_count_v1", "score": 2.0, "eval_status": "INFORMATIONAL" }, { "metric_name": "token_usage_v1", "score": 2078.0, "eval_status": "INFORMATIONAL" }, { "metric_name": "invocation_duration_v1", "score": 3.48, "eval_status": "INFORMATIONAL" } ], "expected_invocation": { "user_prompt": "The assistant can't reach Ollama. What do I check?", "agent_response": "Check that `OLLAMA_API_BASE` points to a running Ollama server (troubleshooting.md)." } } ] } ] ], "2": [ [ 1, { "invocations": [ { "actual_invocation": { "user_prompt": "What command drops the search index?", "agent_response": "The command that drops the search index and builds it again is `docs-assistant index --rebuild` (cli.md).", "tool_calls": [ { "name": "list_pages", "args": {}, "response": { "pages": [ "cli.md", "install.md", "troubleshooting.md" ] } }, { "name": "read_page", "args": { "path": "cli.md" }, "response": { "path": "cli.md", "content": "---\ntitle: CLI reference\n---\n# CLI reference\n\n## ask\n\n`docs-assistant ask QUESTION` prints an answer with citation links.\n\n## index\n\n`docs-assistant index --rebuild` drops the search index and builds it again from the docs folder.\n" } } ] }, "eval_metric_results": [ { "metric_name": "cited_page_was_read", "score": 1.0, "eval_status": "PASSED" }, { "metric_name": "tool_call_count_v1", "score": 2.0, "eval_status": "INFORMATIONAL" }, { "metric_name": "inference_call_count_v1", "score": 3.0, "eval_status": "INFORMATIONAL" }, { "metric_name": "token_usage_v1", "score": 1587.0, "eval_status": "INFORMATIONAL" }, { "metric_name": "invocation_duration_v1", "score": 3.89, "eval_status": "INFORMATIONAL" } ], "expected_invocation": { "user_prompt": "What command drops the search index?", "agent_response": "`docs-assistant index --rebuild` drops the search index and builds it again (cli.md)." } } ] } ], [ 2, { "invocations": [ { "actual_invocation": { "user_prompt": "What command drops the search index?", "agent_response": "Run `docs-assistant index --rebuild` to drop the search index and build it again from the docs folder (cli.md).", "tool_calls": [ { "name": "read_page", "args": { "path": "cli.md" }, "response": { "path": "cli.md", "content": "---\ntitle: CLI reference\n---\n# CLI reference\n\n## ask\n\n`docs-assistant ask QUESTION` prints an answer with citation links.\n\n## index\n\n`docs-assistant index --rebuild` drops the search index and builds it again from the docs folder.\n" } } ] }, "eval_metric_results": [ { "metric_name": "cited_page_was_read", "score": 1.0, "eval_status": "PASSED" }, { "metric_name": "tool_call_count_v1", "score": 1.0, "eval_status": "INFORMATIONAL" }, { "metric_name": "inference_call_count_v1", "score": 2.0, "eval_status": "INFORMATIONAL" }, { "metric_name": "token_usage_v1", "score": 1746.0, "eval_status": "INFORMATIONAL" }, { "metric_name": "invocation_duration_v1", "score": 3.22, "eval_status": "INFORMATIONAL" } ], "expected_invocation": { "user_prompt": "What command drops the search index?", "agent_response": "`docs-assistant index --rebuild` drops the search index and builds it again (cli.md)." } } ] } ], [ 3, { "invocations": [ { "actual_invocation": { "user_prompt": "What command drops the search index?", "agent_response": "The command `docs-assistant index --rebuild` drops the search index and builds it again from the docs folder (cli.md).", "tool_calls": [ { "name": "read_page", "args": { "path": "cli.md" }, "response": { "path": "cli.md", "content": "---\ntitle: CLI reference\n---\n# CLI reference\n\n## ask\n\n`docs-assistant ask QUESTION` prints an answer with citation links.\n\n## index\n\n`docs-assistant index --rebuild` drops the search index and builds it again from the docs folder.\n" } } ] }, "eval_metric_results": [ { "metric_name": "cited_page_was_read", "score": 1.0, "eval_status": "PASSED" }, { "metric_name": "tool_call_count_v1", "score": 1.0, "eval_status": "INFORMATIONAL" }, { "metric_name": "inference_call_count_v1", "score": 2.0, "eval_status": "INFORMATIONAL" }, { "metric_name": "token_usage_v1", "score": 2023.0, "eval_status": "INFORMATIONAL" }, { "metric_name": "invocation_duration_v1", "score": 3.69, "eval_status": "INFORMATIONAL" } ], "expected_invocation": { "user_prompt": "What command drops the search index?", "agent_response": "`docs-assistant index --rebuild` drops the search index and builds it again (cli.md)." } } ] } ] ] }, "per_val_instance_best_candidates": { "0": [ 1, 2, 3 ], "1": [ 1, 2, 3 ], "2": [ 1, 2, 3 ] }, "val_aggregate_subscores": null, "per_objective_best_candidates": null, "objective_pareto_front": null, "discovery_eval_counts": [ 0, 7, 14, 23 ], "total_metric_calls": 40, "num_full_val_evals": 4, "run_dir": null, "seed": 0, "_str_candidate_key": null, "best_idx": 1, "validation_schema_version": 2 } ================================================================================