| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat classes and functions are in GUI/router.py?<|im_end|>\n<|im_start|>assistant\n**GUI/router.py** — Main FastAPI router defining most API endpoints\n\n**Lines**: 5085\n**Classes** (17): JournalEntry, Task, EmailDraft, EmailDraftLaunchRequest, ChatRequest, SemanticSearchRequest, SemanticGraphBonesRequest, ModelEndpointRequest, ... (+9 more)\n**Functions** (172): _add_extension_venv_site_packages, _normalize_context_window_tokens, _validate_endpoint_context_window_tokens, _ai_request_timeout, _chat_generation_timeout, _chat_max_output_tokens, _chat_temperature, _load_extension_module, resolve_data_dir, save_msal_cache, ... (+162 more)\n<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What classes and functions are in GUI/router.py?"}, {"role": "assistant", "content": "**GUI/router.py** — Main FastAPI router defining most API endpoints\n\n**Lines**: 5085\n**Classes** (17): JournalEntry, Task, EmailDraft, EmailDraftLaunchRequest, ChatRequest, SemanticSearchRequest, SemanticGraphBonesRequest, ModelEndpointRequest, ... (+9 more)\n**Functions** (172): _add_extension_venv_site_packages, _normalize_context_window_tokens, _validate_endpoint_context_window_tokens, _ai_request_timeout, _chat_generation_timeout, _chat_max_output_tokens, _chat_temperature, _load_extension_module, resolve_data_dir, save_msal_cache, ... (+162 more)\n"}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `resolve_data_dir()` function in `GUI/router.py` do?<|im_end|>\n<|im_start|>assistant\n**`resolve_data_dir()`** in `GUI/router.py`:\n```python\ndef resolve_data_dir() -> Path:\n```\n\nThis function is part of the main fastapi router defining most api endpoints.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `resolve_data_dir()` function in `GUI/router.py` do?"}, {"role": "assistant", "content": "**`resolve_data_dir()`** in `GUI/router.py`:\n```python\ndef resolve_data_dir() -> Path:\n```\n\nThis function is part of the main fastapi router defining most api endpoints."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `save_msal_cache()` function in `GUI/router.py` do?<|im_end|>\n<|im_start|>assistant\n**`save_msal_cache()`** in `GUI/router.py`:\n```python\ndef save_msal_cache():\n```\n\n---------- API key encryption helpers ----------<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `save_msal_cache()` function in `GUI/router.py` do?"}, {"role": "assistant", "content": "**`save_msal_cache()`** in `GUI/router.py`:\n```python\ndef save_msal_cache():\n```\n\n---------- API key encryption helpers ----------"}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `init_db()` function in `GUI/router.py` do?<|im_end|>\n<|im_start|>assistant\n**`init_db()`** in `GUI/router.py`:\n```python\ndef init_db():\n```\n\nThis function is part of the main fastapi router defining most api endpoints.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `init_db()` function in `GUI/router.py` do?"}, {"role": "assistant", "content": "**`init_db()`** in `GUI/router.py`:\n```python\ndef init_db():\n```\n\nThis function is part of the main fastapi router defining most api endpoints."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `normalize_email_status()` function in `GUI/router.py` do?<|im_end|>\n<|im_start|>assistant\n**`normalize_email_status()`** in `GUI/router.py`:\n```python\ndef normalize_email_status(value: Optional[str]) -> str:\n```\n\nThis function is part of the main fastapi router defining most api endpoints.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `normalize_email_status()` function in `GUI/router.py` do?"}, {"role": "assistant", "content": "**`normalize_email_status()`** in `GUI/router.py`:\n```python\ndef normalize_email_status(value: Optional[str]) -> str:\n```\n\nThis function is part of the main fastapi router defining most api endpoints."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `normalize_task_color()` function in `GUI/router.py` do?<|im_end|>\n<|im_start|>assistant\n**`normalize_task_color()`** in `GUI/router.py`:\n```python\ndef normalize_task_color(value: Optional[str]) -> Optional[str]:\n```\n\nThis function is part of the main fastapi router defining most api endpoints.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `normalize_task_color()` function in `GUI/router.py` do?"}, {"role": "assistant", "content": "**`normalize_task_color()`** in `GUI/router.py`:\n```python\ndef normalize_task_color(value: Optional[str]) -> Optional[str]:\n```\n\nThis function is part of the main fastapi router defining most api endpoints."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `validate_extension_manifest()` function in `GUI/router.py` do?<|im_end|>\n<|im_start|>assistant\n**`validate_extension_manifest()`** in `GUI/router.py`:\n```python\ndef validate_extension_manifest(req: ExtensionManifestValidationRequest):\n```\n\nThis function is part of the main fastapi router defining most api endpoints.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `validate_extension_manifest()` function in `GUI/router.py` do?"}, {"role": "assistant", "content": "**`validate_extension_manifest()`** in `GUI/router.py`:\n```python\ndef validate_extension_manifest(req: ExtensionManifestValidationRequest):\n```\n\nThis function is part of the main fastapi router defining most api endpoints."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat is the purpose of `GUI/router.py`?<|im_end|>\n<|im_start|>assistant\n**`GUI/router.py`** — Main FastAPI router defining most API endpoints\n\nThis module contains 5085 lines of Python code with 17 class(es) and 172 function(s). It defines FastAPI route handlers for various endpoints.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What is the purpose of `GUI/router.py`?"}, {"role": "assistant", "content": "**`GUI/router.py`** — Main FastAPI router defining most API endpoints\n\nThis module contains 5085 lines of Python code with 17 class(es) and 172 function(s). It defines FastAPI route handlers for various endpoints."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat classes and functions are in GUI/pdf_parser.py?<|im_end|>\n<|im_start|>assistant\n**GUI/pdf_parser.py** — PDF parsing and document management\n\n**Lines**: 5949\n**Classes** (3): DatabaseManager, RAGManager, TopicUpdateRequest\n**Functions** (30): normalize_rerank_candidate_k, normalize_chunking_engine, resolve_data_dir, set_configured_endpoint_caller, set_reranker_model_path, _get_reranker, load_documents_from_db, call_configured_pdf_endpoint, cancel_configured_pdf_endpoint, _clean_graph_analysis_cache_key, ... (+20 more)\n**Async functions** (53): root, health_check, get_graph_analysis_cache, save_graph_analysis_cache, delete_graph_analysis_cache, ... (+48 more)\n<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What classes and functions are in GUI/pdf_parser.py?"}, {"role": "assistant", "content": "**GUI/pdf_parser.py** — PDF parsing and document management\n\n**Lines**: 5949\n**Classes** (3): DatabaseManager, RAGManager, TopicUpdateRequest\n**Functions** (30): normalize_rerank_candidate_k, normalize_chunking_engine, resolve_data_dir, set_configured_endpoint_caller, set_reranker_model_path, _get_reranker, load_documents_from_db, call_configured_pdf_endpoint, cancel_configured_pdf_endpoint, _clean_graph_analysis_cache_key, ... (+20 more)\n**Async functions** (53): root, health_check, get_graph_analysis_cache, save_graph_analysis_cache, delete_graph_analysis_cache, ... (+48 more)\n"}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `normalize_rerank_candidate_k()` function in `GUI/pdf_parser.py` do?<|im_end|>\n<|im_start|>assistant\n**`normalize_rerank_candidate_k()`** in `GUI/pdf_parser.py`:\n```python\ndef normalize_rerank_candidate_k(top_k: int, candidate_k: Optional[int] = None) -> int:\n```\n\nThis function is part of the pdf parsing and document management.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `normalize_rerank_candidate_k()` function in `GUI/pdf_parser.py` do?"}, {"role": "assistant", "content": "**`normalize_rerank_candidate_k()`** in `GUI/pdf_parser.py`:\n```python\ndef normalize_rerank_candidate_k(top_k: int, candidate_k: Optional[int] = None) -> int:\n```\n\nThis function is part of the pdf parsing and document management."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `normalize_chunking_engine()` function in `GUI/pdf_parser.py` do?<|im_end|>\n<|im_start|>assistant\n**`normalize_chunking_engine()`** in `GUI/pdf_parser.py`:\n```python\ndef normalize_chunking_engine(value: Optional[str]) -> str:\n```\n\nThis function is part of the pdf parsing and document management.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `normalize_chunking_engine()` function in `GUI/pdf_parser.py` do?"}, {"role": "assistant", "content": "**`normalize_chunking_engine()`** in `GUI/pdf_parser.py`:\n```python\ndef normalize_chunking_engine(value: Optional[str]) -> str:\n```\n\nThis function is part of the pdf parsing and document management."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `resolve_data_dir()` function in `GUI/pdf_parser.py` do?<|im_end|>\n<|im_start|>assistant\n**`resolve_data_dir()`** in `GUI/pdf_parser.py`:\n```python\ndef resolve_data_dir() -> Path:\n```\n\nCreate directories if they don't exist<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `resolve_data_dir()` function in `GUI/pdf_parser.py` do?"}, {"role": "assistant", "content": "**`resolve_data_dir()`** in `GUI/pdf_parser.py`:\n```python\ndef resolve_data_dir() -> Path:\n```\n\nCreate directories if they don't exist"}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `set_configured_endpoint_caller()` function in `GUI/pdf_parser.py` do?<|im_end|>\n<|im_start|>assistant\n**`set_configured_endpoint_caller()`** in `GUI/pdf_parser.py`:\n```python\ndef set_configured_endpoint_caller(caller: Any) -> None:\n```\n\nThis function is part of the pdf parsing and document management.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `set_configured_endpoint_caller()` function in `GUI/pdf_parser.py` do?"}, {"role": "assistant", "content": "**`set_configured_endpoint_caller()`** in `GUI/pdf_parser.py`:\n```python\ndef set_configured_endpoint_caller(caller: Any) -> None:\n```\n\nThis function is part of the pdf parsing and document management."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `set_reranker_model_path()` function in `GUI/pdf_parser.py` do?<|im_end|>\n<|im_start|>assistant\n**`set_reranker_model_path()`** in `GUI/pdf_parser.py`:\n```python\ndef set_reranker_model_path(path: Optional[str]) -> None:\n```\n\nThis function is part of the pdf parsing and document management.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `set_reranker_model_path()` function in `GUI/pdf_parser.py` do?"}, {"role": "assistant", "content": "**`set_reranker_model_path()`** in `GUI/pdf_parser.py`:\n```python\ndef set_reranker_model_path(path: Optional[str]) -> None:\n```\n\nThis function is part of the pdf parsing and document management."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `load_documents_from_db()` function in `GUI/pdf_parser.py` do?<|im_end|>\n<|im_start|>assistant\n**`load_documents_from_db()`** in `GUI/pdf_parser.py`:\n```python\ndef load_documents_from_db():\n```\n\nThis function is part of the pdf parsing and document management.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `load_documents_from_db()` function in `GUI/pdf_parser.py` do?"}, {"role": "assistant", "content": "**`load_documents_from_db()`** in `GUI/pdf_parser.py`:\n```python\ndef load_documents_from_db():\n```\n\nThis function is part of the pdf parsing and document management."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat is the purpose of `GUI/pdf_parser.py`?<|im_end|>\n<|im_start|>assistant\n**`GUI/pdf_parser.py`** — PDF parsing and document management\n\nThis module contains 5949 lines of Python code with 3 class(es) and 30 function(s). It handles PDF document parsing, chunking, and text extraction using PyMuPDF.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What is the purpose of `GUI/pdf_parser.py`?"}, {"role": "assistant", "content": "**`GUI/pdf_parser.py`** — PDF parsing and document management\n\nThis module contains 5949 lines of Python code with 3 class(es) and 30 function(s). It handles PDF document parsing, chunking, and text extraction using PyMuPDF."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat classes and functions are in GUI/chat_streaming.py?<|im_end|>\n<|im_start|>assistant\n**GUI/chat_streaming.py** — Chat streaming and context assembly\n\n**Lines**: 3119\n**Classes** (3): PdfChatStreamRequest, PdfVisualizationPlan, VisualizationPlanError\n**Functions** (78): _sanitize_visualization_plan_text, _normalize_pdf_conversation_context, configure, stream_json_event, _require_pdf_service, _session_db_path, _connect_session_db, _init_session_db, _ensure_session_column, _session_now, ... (+68 more)\n**Async functions** (1): upload_session_document\n<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What classes and functions are in GUI/chat_streaming.py?"}, {"role": "assistant", "content": "**GUI/chat_streaming.py** — Chat streaming and context assembly\n\n**Lines**: 3119\n**Classes** (3): PdfChatStreamRequest, PdfVisualizationPlan, VisualizationPlanError\n**Functions** (78): _sanitize_visualization_plan_text, _normalize_pdf_conversation_context, configure, stream_json_event, _require_pdf_service, _session_db_path, _connect_session_db, _init_session_db, _ensure_session_column, _session_now, ... (+68 more)\n**Async functions** (1): upload_session_document\n"}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `configure()` function in `GUI/chat_streaming.py` do?<|im_end|>\n<|im_start|>assistant\n**`configure()`** in `GUI/chat_streaming.py`:\n```python\ndef configure(\n```\n\nThis function is part of the chat streaming and context assembly.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `configure()` function in `GUI/chat_streaming.py` do?"}, {"role": "assistant", "content": "**`configure()`** in `GUI/chat_streaming.py`:\n```python\ndef configure(\n```\n\nThis function is part of the chat streaming and context assembly."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `stream_json_event()` function in `GUI/chat_streaming.py` do?<|im_end|>\n<|im_start|>assistant\n**`stream_json_event()`** in `GUI/chat_streaming.py`:\n```python\ndef stream_json_event(event_type: str, **payload: Any) -> str:\n```\n\nThis function is part of the chat streaming and context assembly.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `stream_json_event()` function in `GUI/chat_streaming.py` do?"}, {"role": "assistant", "content": "**`stream_json_event()`** in `GUI/chat_streaming.py`:\n```python\ndef stream_json_event(event_type: str, **payload: Any) -> str:\n```\n\nThis function is part of the chat streaming and context assembly."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `list_session_documents()` function in `GUI/chat_streaming.py` do?<|im_end|>\n<|im_start|>assistant\n**`list_session_documents()`** in `GUI/chat_streaming.py`:\n```python\ndef list_session_documents(session_id: str) -> Dict[str, Any]:\n```\n\nThis function is part of the chat streaming and context assembly.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `list_session_documents()` function in `GUI/chat_streaming.py` do?"}, {"role": "assistant", "content": "**`list_session_documents()`** in `GUI/chat_streaming.py`:\n```python\ndef list_session_documents(session_id: str) -> Dict[str, Any]:\n```\n\nThis function is part of the chat streaming and context assembly."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `clear_session_documents()` function in `GUI/chat_streaming.py` do?<|im_end|>\n<|im_start|>assistant\n**`clear_session_documents()`** in `GUI/chat_streaming.py`:\n```python\ndef clear_session_documents(session_id: str) -> Dict[str, Any]:\n```\n\nThis function is part of the chat streaming and context assembly.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `clear_session_documents()` function in `GUI/chat_streaming.py` do?"}, {"role": "assistant", "content": "**`clear_session_documents()`** in `GUI/chat_streaming.py`:\n```python\ndef clear_session_documents(session_id: str) -> Dict[str, Any]:\n```\n\nThis function is part of the chat streaming and context assembly."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `delete_session_document()` function in `GUI/chat_streaming.py` do?<|im_end|>\n<|im_start|>assistant\n**`delete_session_document()`** in `GUI/chat_streaming.py`:\n```python\ndef delete_session_document(doc_id: str, session_id: str) -> Dict[str, Any]:\n```\n\nThis function is part of the chat streaming and context assembly.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `delete_session_document()` function in `GUI/chat_streaming.py` do?"}, {"role": "assistant", "content": "**`delete_session_document()`** in `GUI/chat_streaming.py`:\n```python\ndef delete_session_document(doc_id: str, session_id: str) -> Dict[str, Any]:\n```\n\nThis function is part of the chat streaming and context assembly."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `stream_pdf_chat()` function in `GUI/chat_streaming.py` do?<|im_end|>\n<|im_start|>assistant\n**`stream_pdf_chat()`** in `GUI/chat_streaming.py`:\n```python\ndef stream_pdf_chat(request: PdfChatStreamRequest):\n```\n\nThis function is part of the chat streaming and context assembly.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `stream_pdf_chat()` function in `GUI/chat_streaming.py` do?"}, {"role": "assistant", "content": "**`stream_pdf_chat()`** in `GUI/chat_streaming.py`:\n```python\ndef stream_pdf_chat(request: PdfChatStreamRequest):\n```\n\nThis function is part of the chat streaming and context assembly."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat is the purpose of `GUI/chat_streaming.py`?<|im_end|>\n<|im_start|>assistant\n**`GUI/chat_streaming.py`** — Chat streaming and context assembly\n\nThis module contains 3119 lines of Python code with 3 class(es) and 78 function(s). It manages LLM chat interactions, streaming, and context assembly.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What is the purpose of `GUI/chat_streaming.py`?"}, {"role": "assistant", "content": "**`GUI/chat_streaming.py`** — Chat streaming and context assembly\n\nThis module contains 3119 lines of Python code with 3 class(es) and 78 function(s). It manages LLM chat interactions, streaming, and context assembly."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat classes and functions are in GUI/discord_bot.py?<|im_end|>\n<|im_start|>assistant\n**GUI/discord_bot.py** — Discord bot integration\n\n**Lines**: 2844\n**Classes** (1): SimpleRAGBackendError\n**Functions** (98): _web_evidence_system_prompt, _normalize_web_length_limit_notice, _strip_web_length_limit_notice, _claim_discord_dispatch, _claim_interaction_dispatch, _acquire_windows_named_mutex, _release_windows_named_mutex, _acquire_discord_single_instance, _normalize_text, _import_web_search_runtime, ... (+88 more)\n**Async functions** (17): read_discord_attachments, _send_channel_response, _run_backend_query, _send_interaction_response, setup_hook, ... (+12 more)\n<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What classes and functions are in GUI/discord_bot.py?"}, {"role": "assistant", "content": "**GUI/discord_bot.py** — Discord bot integration\n\n**Lines**: 2844\n**Classes** (1): SimpleRAGBackendError\n**Functions** (98): _web_evidence_system_prompt, _normalize_web_length_limit_notice, _strip_web_length_limit_notice, _claim_discord_dispatch, _claim_interaction_dispatch, _acquire_windows_named_mutex, _release_windows_named_mutex, _acquire_discord_single_instance, _normalize_text, _import_web_search_runtime, ... (+88 more)\n**Async functions** (17): read_discord_attachments, _send_channel_response, _run_backend_query, _send_interaction_response, setup_hook, ... (+12 more)\n"}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `resolve_simplerag_backend()` function in `GUI/discord_bot.py` do?<|im_end|>\n<|im_start|>assistant\n**`resolve_simplerag_backend()`** in `GUI/discord_bot.py`:\n```python\ndef resolve_simplerag_backend(*, refresh: bool = False) -> Dict[str, str]:\n```\n\nFind the running Electron backend and its RAG Workspace route prefix.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `resolve_simplerag_backend()` function in `GUI/discord_bot.py` do?"}, {"role": "assistant", "content": "**`resolve_simplerag_backend()`** in `GUI/discord_bot.py`:\n```python\ndef resolve_simplerag_backend(*, refresh: bool = False) -> Dict[str, str]:\n```\n\nFind the running Electron backend and its RAG Workspace route prefix."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `resolve_active_model()` function in `GUI/discord_bot.py` do?<|im_end|>\n<|im_start|>assistant\n**`resolve_active_model()`** in `GUI/discord_bot.py`:\n```python\ndef resolve_active_model(backend: Dict[str, str]) -> Dict[str, str]:\n```\n\nReturn one unambiguous resident chat model, or an explicit Discord override.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `resolve_active_model()` function in `GUI/discord_bot.py` do?"}, {"role": "assistant", "content": "**`resolve_active_model()`** in `GUI/discord_bot.py`:\n```python\ndef resolve_active_model(backend: Dict[str, str]) -> Dict[str, str]:\n```\n\nReturn one unambiguous resident chat model, or an explicit Discord override."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `load_discord_model()` function in `GUI/discord_bot.py` do?<|im_end|>\n<|im_start|>assistant\n**`load_discord_model()`** in `GUI/discord_bot.py`:\n```python\ndef load_discord_model(endpoint_query: str, model_query: str) -> str:\n```\n\nLoad an exact local chat model through SimpleRAG and bind Discord to it.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `load_discord_model()` function in `GUI/discord_bot.py` do?"}, {"role": "assistant", "content": "**`load_discord_model()`** in `GUI/discord_bot.py`:\n```python\ndef load_discord_model(endpoint_query: str, model_query: str) -> str:\n```\n\nLoad an exact local chat model through SimpleRAG and bind Discord to it."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `resolve_active_embedder()` function in `GUI/discord_bot.py` do?<|im_end|>\n<|im_start|>assistant\n**`resolve_active_embedder()`** in `GUI/discord_bot.py`:\n```python\ndef resolve_active_embedder(backend: Dict[str, str]) -> Optional[Dict[str, str]]:\n```\n\nReturn the locally loaded embedding model if one is active, else None.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `resolve_active_embedder()` function in `GUI/discord_bot.py` do?"}, {"role": "assistant", "content": "**`resolve_active_embedder()`** in `GUI/discord_bot.py`:\n```python\ndef resolve_active_embedder(backend: Dict[str, str]) -> Optional[Dict[str, str]]:\n```\n\nReturn the locally loaded embedding model if one is active, else None."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `active_model_summary()` function in `GUI/discord_bot.py` do?<|im_end|>\n<|im_start|>assistant\n**`active_model_summary()`** in `GUI/discord_bot.py`:\n```python\ndef active_model_summary() -> str:\n```\n\nThis function is part of the discord bot integration.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `active_model_summary()` function in `GUI/discord_bot.py` do?"}, {"role": "assistant", "content": "**`active_model_summary()`** in `GUI/discord_bot.py`:\n```python\ndef active_model_summary() -> str:\n```\n\nThis function is part of the discord bot integration."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `create_bot()` function in `GUI/discord_bot.py` do?<|im_end|>\n<|im_start|>assistant\n**`create_bot()`** in `GUI/discord_bot.py`:\n```python\ndef create_bot(enable_message_content: bool = True) -> commands.Bot:\n```\n\nCreate and configure the SimpleRAG Discord bot with slash commands.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `create_bot()` function in `GUI/discord_bot.py` do?"}, {"role": "assistant", "content": "**`create_bot()`** in `GUI/discord_bot.py`:\n```python\ndef create_bot(enable_message_content: bool = True) -> commands.Bot:\n```\n\nCreate and configure the SimpleRAG Discord bot with slash commands."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat is the purpose of `GUI/discord_bot.py`?<|im_end|>\n<|im_start|>assistant\n**`GUI/discord_bot.py`** — Discord bot integration\n\nThis module contains 2844 lines of Python code with 1 class(es) and 98 function(s). It integrates with Discord via discord.py for bot functionality.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What is the purpose of `GUI/discord_bot.py`?"}, {"role": "assistant", "content": "**`GUI/discord_bot.py`** — Discord bot integration\n\nThis module contains 2844 lines of Python code with 1 class(es) and 98 function(s). It integrates with Discord via discord.py for bot functionality."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat classes and functions are in GUI/llama_cpp_runtime.py?<|im_end|>\n<|im_start|>assistant\n**GUI/llama_cpp_runtime.py** — Model loading and management\n\n**Lines**: 4406\n**Classes** (3): InstallationCancelled, WorkerStartupFailure, LlamaCppRuntimeManager\n**Functions** (16): _utc_now, _creation_flags, _atomic_write_json, _clean_text, _safe_int, _safe_bool, _normalize_backend, _normalize_split_mode, _normalize_embedding_pooling, _resolve_embedding_pooling, ... (+6 more)\n<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What classes and functions are in GUI/llama_cpp_runtime.py?"}, {"role": "assistant", "content": "**GUI/llama_cpp_runtime.py** — Model loading and management\n\n**Lines**: 4406\n**Classes** (3): InstallationCancelled, WorkerStartupFailure, LlamaCppRuntimeManager\n**Functions** (16): _utc_now, _creation_flags, _atomic_write_json, _clean_text, _safe_int, _safe_bool, _normalize_backend, _normalize_split_mode, _normalize_embedding_pooling, _resolve_embedding_pooling, ... (+6 more)\n"}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat is the purpose of `GUI/llama_cpp_runtime.py`?<|im_end|>\n<|im_start|>assistant\n**`GUI/llama_cpp_runtime.py`** — Model loading and management\n\nThis module contains 4406 lines of Python code with 3 class(es) and 16 function(s). It manages llama.cpp model loading, inference, and GPU layer offloading.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What is the purpose of `GUI/llama_cpp_runtime.py`?"}, {"role": "assistant", "content": "**`GUI/llama_cpp_runtime.py`** — Model loading and management\n\nThis module contains 4406 lines of Python code with 3 class(es) and 16 function(s). It manages llama.cpp model loading, inference, and GPU layer offloading."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat classes and functions are in GUI/hybrid_graph_service.py?<|im_end|>\n<|im_start|>assistant\n**GUI/hybrid_graph_service.py** — Knowledge graph service\n\n**Lines**: 1572\n**Classes** (3): HybridGraphUnavailable, _ApplicationEmbeddingAdapter, HybridGraphService\n**Functions** (6): _default_project_root, _bounded_int, _clean_text, _json_string_list, _model_alias, _empty_graph_metadata\n<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What classes and functions are in GUI/hybrid_graph_service.py?"}, {"role": "assistant", "content": "**GUI/hybrid_graph_service.py** — Knowledge graph service\n\n**Lines**: 1572\n**Classes** (3): HybridGraphUnavailable, _ApplicationEmbeddingAdapter, HybridGraphService\n**Functions** (6): _default_project_root, _bounded_int, _clean_text, _json_string_list, _model_alias, _empty_graph_metadata\n"}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat is the purpose of `GUI/hybrid_graph_service.py`?<|im_end|>\n<|im_start|>assistant\n**`GUI/hybrid_graph_service.py`** — Knowledge graph service\n\nThis module contains 1572 lines of Python code with 3 class(es) and 6 function(s). It builds and queries the knowledge graph from document entities.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What is the purpose of `GUI/hybrid_graph_service.py`?"}, {"role": "assistant", "content": "**`GUI/hybrid_graph_service.py`** — Knowledge graph service\n\nThis module contains 1572 lines of Python code with 3 class(es) and 6 function(s). It builds and queries the knowledge graph from document entities."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat classes and functions are in GUI/embedding_manager.py?<|im_end|>\n<|im_start|>assistant\n**GUI/embedding_manager.py** — Embedding model management\n\n**Lines**: 1642\n**Classes** (1): EmbeddingManager\n**Functions** (12): detect_cuda_version, normalize_embedding_runtime_backend, normalize_embedding_provider, clean_embedding_setting_text, resolve_embedding_runtime_backend, _embedding_task_snapshot, get_windows_creation_flags, run_capture_text, get_detected_gpu_names, detect_gpu_vendors, ... (+2 more)\n<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What classes and functions are in GUI/embedding_manager.py?"}, {"role": "assistant", "content": "**GUI/embedding_manager.py** — Embedding model management\n\n**Lines**: 1642\n**Classes** (1): EmbeddingManager\n**Functions** (12): detect_cuda_version, normalize_embedding_runtime_backend, normalize_embedding_provider, clean_embedding_setting_text, resolve_embedding_runtime_backend, _embedding_task_snapshot, get_windows_creation_flags, run_capture_text, get_detected_gpu_names, detect_gpu_vendors, ... (+2 more)\n"}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `detect_cuda_version()` function in `GUI/embedding_manager.py` do?<|im_end|>\n<|im_start|>assistant\n**`detect_cuda_version()`** in `GUI/embedding_manager.py`:\n```python\ndef detect_cuda_version():\n```\n\nDetect the CUDA driver version via nvidia-smi. Returns string like 12.4 or None.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `detect_cuda_version()` function in `GUI/embedding_manager.py` do?"}, {"role": "assistant", "content": "**`detect_cuda_version()`** in `GUI/embedding_manager.py`:\n```python\ndef detect_cuda_version():\n```\n\nDetect the CUDA driver version via nvidia-smi. Returns string like 12.4 or None."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `normalize_embedding_runtime_backend()` function in `GUI/embedding_manager.py` do?<|im_end|>\n<|im_start|>assistant\n**`normalize_embedding_runtime_backend()`** in `GUI/embedding_manager.py`:\n```python\ndef normalize_embedding_runtime_backend(runtime_backend: Optional[str]) -> str:\n```\n\nThis function is part of the embedding model management.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `normalize_embedding_runtime_backend()` function in `GUI/embedding_manager.py` do?"}, {"role": "assistant", "content": "**`normalize_embedding_runtime_backend()`** in `GUI/embedding_manager.py`:\n```python\ndef normalize_embedding_runtime_backend(runtime_backend: Optional[str]) -> str:\n```\n\nThis function is part of the embedding model management."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `normalize_embedding_provider()` function in `GUI/embedding_manager.py` do?<|im_end|>\n<|im_start|>assistant\n**`normalize_embedding_provider()`** in `GUI/embedding_manager.py`:\n```python\ndef normalize_embedding_provider(provider: Optional[str]) -> str:\n```\n\nThis function is part of the embedding model management.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `normalize_embedding_provider()` function in `GUI/embedding_manager.py` do?"}, {"role": "assistant", "content": "**`normalize_embedding_provider()`** in `GUI/embedding_manager.py`:\n```python\ndef normalize_embedding_provider(provider: Optional[str]) -> str:\n```\n\nThis function is part of the embedding model management."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `clean_embedding_setting_text()` function in `GUI/embedding_manager.py` do?<|im_end|>\n<|im_start|>assistant\n**`clean_embedding_setting_text()`** in `GUI/embedding_manager.py`:\n```python\ndef clean_embedding_setting_text(value: Optional[str], max_length: int = 240) -> str:\n```\n\nThis function is part of the embedding model management.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `clean_embedding_setting_text()` function in `GUI/embedding_manager.py` do?"}, {"role": "assistant", "content": "**`clean_embedding_setting_text()`** in `GUI/embedding_manager.py`:\n```python\ndef clean_embedding_setting_text(value: Optional[str], max_length: int = 240) -> str:\n```\n\nThis function is part of the embedding model management."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `resolve_embedding_runtime_backend()` function in `GUI/embedding_manager.py` do?<|im_end|>\n<|im_start|>assistant\n**`resolve_embedding_runtime_backend()`** in `GUI/embedding_manager.py`:\n```python\ndef resolve_embedding_runtime_backend(runtime_backend: Optional[str]) -> str:\n```\n\nThis function is part of the embedding model management.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `resolve_embedding_runtime_backend()` function in `GUI/embedding_manager.py` do?"}, {"role": "assistant", "content": "**`resolve_embedding_runtime_backend()`** in `GUI/embedding_manager.py`:\n```python\ndef resolve_embedding_runtime_backend(runtime_backend: Optional[str]) -> str:\n```\n\nThis function is part of the embedding model management."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `get_windows_creation_flags()` function in `GUI/embedding_manager.py` do?<|im_end|>\n<|im_start|>assistant\n**`get_windows_creation_flags()`** in `GUI/embedding_manager.py`:\n```python\ndef get_windows_creation_flags() -> int:\n```\n\nThis function is part of the embedding model management.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `get_windows_creation_flags()` function in `GUI/embedding_manager.py` do?"}, {"role": "assistant", "content": "**`get_windows_creation_flags()`** in `GUI/embedding_manager.py`:\n```python\ndef get_windows_creation_flags() -> int:\n```\n\nThis function is part of the embedding model management."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat is the purpose of `GUI/embedding_manager.py`?<|im_end|>\n<|im_start|>assistant\n**`GUI/embedding_manager.py`** — Embedding model management\n\nThis module contains 1642 lines of Python code with 1 class(es) and 12 function(s). <|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What is the purpose of `GUI/embedding_manager.py`?"}, {"role": "assistant", "content": "**`GUI/embedding_manager.py`** — Embedding model management\n\nThis module contains 1642 lines of Python code with 1 class(es) and 12 function(s). "}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat classes and functions are in GUI/chat_context_budget.py?<|im_end|>\n<|im_start|>assistant\n**GUI/chat_context_budget.py** — Context window budget management\n\n**Lines**: 380\n**Classes** (1): PromptContextSegment\n**Functions** (11): _positive_token_count, classify_length_limit, length_limit_notice, utf8_token_upper_bound, _safe_token_count, _compose_system, _default_output_reserve, _allocate_segment_tokens, _prefer_text_boundary, clip_text_to_token_budget, ... (+1 more)\n<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What classes and functions are in GUI/chat_context_budget.py?"}, {"role": "assistant", "content": "**GUI/chat_context_budget.py** — Context window budget management\n\n**Lines**: 380\n**Classes** (1): PromptContextSegment\n**Functions** (11): _positive_token_count, classify_length_limit, length_limit_notice, utf8_token_upper_bound, _safe_token_count, _compose_system, _default_output_reserve, _allocate_segment_tokens, _prefer_text_boundary, clip_text_to_token_budget, ... (+1 more)\n"}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `classify_length_limit()` function in `GUI/chat_context_budget.py` do?<|im_end|>\n<|im_start|>assistant\n**`classify_length_limit()`** in `GUI/chat_context_budget.py`:\n```python\ndef classify_length_limit(\n```\n\nClassify a provider ``finish_reason=length`` without guessing context loss.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `classify_length_limit()` function in `GUI/chat_context_budget.py` do?"}, {"role": "assistant", "content": "**`classify_length_limit()`** in `GUI/chat_context_budget.py`:\n```python\ndef classify_length_limit(\n```\n\nClassify a provider ``finish_reason=length`` without guessing context loss."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `length_limit_notice()` function in `GUI/chat_context_budget.py` do?<|im_end|>\n<|im_start|>assistant\n**`length_limit_notice()`** in `GUI/chat_context_budget.py`:\n```python\ndef length_limit_notice(limit_reason: Any) -> str:\n```\n\nThis function is part of the context window budget management.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `length_limit_notice()` function in `GUI/chat_context_budget.py` do?"}, {"role": "assistant", "content": "**`length_limit_notice()`** in `GUI/chat_context_budget.py`:\n```python\ndef length_limit_notice(limit_reason: Any) -> str:\n```\n\nThis function is part of the context window budget management."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `utf8_token_upper_bound()` function in `GUI/chat_context_budget.py` do?<|im_end|>\n<|im_start|>assistant\n**`utf8_token_upper_bound()`** in `GUI/chat_context_budget.py`:\n```python\ndef utf8_token_upper_bound(value: str) -> int:\n```\n\nReturn a conservative fallback when the active tokenizer is unavailable.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `utf8_token_upper_bound()` function in `GUI/chat_context_budget.py` do?"}, {"role": "assistant", "content": "**`utf8_token_upper_bound()`** in `GUI/chat_context_budget.py`:\n```python\ndef utf8_token_upper_bound(value: str) -> int:\n```\n\nReturn a conservative fallback when the active tokenizer is unavailable."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `clip_text_to_token_budget()` function in `GUI/chat_context_budget.py` do?<|im_end|>\n<|im_start|>assistant\n**`clip_text_to_token_budget()`** in `GUI/chat_context_budget.py`:\n```python\ndef clip_text_to_token_budget(\n```\n\nThis function is part of the context window budget management.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `clip_text_to_token_budget()` function in `GUI/chat_context_budget.py` do?"}, {"role": "assistant", "content": "**`clip_text_to_token_budget()`** in `GUI/chat_context_budget.py`:\n```python\ndef clip_text_to_token_budget(\n```\n\nThis function is part of the context window budget management."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `pack_prompt_context()` function in `GUI/chat_context_budget.py` do?<|im_end|>\n<|im_start|>assistant\n**`pack_prompt_context()`** in `GUI/chat_context_budget.py`:\n```python\ndef pack_prompt_context(\n```\n\nThis function is part of the context window budget management.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `pack_prompt_context()` function in `GUI/chat_context_budget.py` do?"}, {"role": "assistant", "content": "**`pack_prompt_context()`** in `GUI/chat_context_budget.py`:\n```python\ndef pack_prompt_context(\n```\n\nThis function is part of the context window budget management."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat is the purpose of `GUI/chat_context_budget.py`?<|im_end|>\n<|im_start|>assistant\n**`GUI/chat_context_budget.py`** — Context window budget management\n\nThis module contains 380 lines of Python code with 1 class(es) and 11 function(s). It manages LLM chat interactions, streaming, and context assembly.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What is the purpose of `GUI/chat_context_budget.py`?"}, {"role": "assistant", "content": "**`GUI/chat_context_budget.py`** — Context window budget management\n\nThis module contains 380 lines of Python code with 1 class(es) and 11 function(s). It manages LLM chat interactions, streaming, and context assembly."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat classes and functions are in GUI/secure_credentials.py?<|im_end|>\n<|im_start|>assistant\n**GUI/secure_credentials.py** — Secure credential handling\n\n**Lines**: 184\n**Classes** (2): _DataBlob, CredentialStore\n<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What classes and functions are in GUI/secure_credentials.py?"}, {"role": "assistant", "content": "**GUI/secure_credentials.py** — Secure credential handling\n\n**Lines**: 184\n**Classes** (2): _DataBlob, CredentialStore\n"}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat is the purpose of `GUI/secure_credentials.py`?<|im_end|>\n<|im_start|>assistant\n**`GUI/secure_credentials.py`** — Secure credential handling\n\nThis module contains 184 lines of Python code with 2 class(es) and 0 function(s). <|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What is the purpose of `GUI/secure_credentials.py`?"}, {"role": "assistant", "content": "**`GUI/secure_credentials.py`** — Secure credential handling\n\nThis module contains 184 lines of Python code with 2 class(es) and 0 function(s). "}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat classes and functions are in GUI/web_search_runtime.py?<|im_end|>\n<|im_start|>assistant\n**GUI/web_search_runtime.py** — Web search functionality\n\n**Lines**: 2265\n**Classes** (4): _TextExtractor, _DDGHTMLParser, _PageContentExtractor, ProviderSearchError\n**Functions** (63): _next_user_agent, _extract_json_ld_text, _extract_meta_text, _extract_noscript_text, _aggressive_text_extract, _try_weather_fallback, fetch_page_content, enrich_results_with_page_content, _is_usable_page_text, _is_weather_query, ... (+53 more)\n<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What classes and functions are in GUI/web_search_runtime.py?"}, {"role": "assistant", "content": "**GUI/web_search_runtime.py** — Web search functionality\n\n**Lines**: 2265\n**Classes** (4): _TextExtractor, _DDGHTMLParser, _PageContentExtractor, ProviderSearchError\n**Functions** (63): _next_user_agent, _extract_json_ld_text, _extract_meta_text, _extract_noscript_text, _aggressive_text_extract, _try_weather_fallback, fetch_page_content, enrich_results_with_page_content, _is_usable_page_text, _is_weather_query, ... (+53 more)\n"}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `fetch_page_content()` function in `GUI/web_search_runtime.py` do?<|im_end|>\n<|im_start|>assistant\n**`fetch_page_content()`** in `GUI/web_search_runtime.py`:\n```python\ndef fetch_page_content(url: str, max_chars: int = MAX_PAGE_TEXT_CHARS, timeout: float = 4.0) -> str:\n```\n\nFetch target web page content, parsing HTML into clean readable text.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `fetch_page_content()` function in `GUI/web_search_runtime.py` do?"}, {"role": "assistant", "content": "**`fetch_page_content()`** in `GUI/web_search_runtime.py`:\n```python\ndef fetch_page_content(url: str, max_chars: int = MAX_PAGE_TEXT_CHARS, timeout: float = 4.0) -> str:\n```\n\nFetch target web page content, parsing HTML into clean readable text."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `enrich_results_with_page_content()` function in `GUI/web_search_runtime.py` do?<|im_end|>\n<|im_start|>assistant\n**`enrich_results_with_page_content()`** in `GUI/web_search_runtime.py`:\n```python\ndef enrich_results_with_page_content(\n```\n\nVisit top target result URLs to extract real page text content into each result dictionary.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `enrich_results_with_page_content()` function in `GUI/web_search_runtime.py` do?"}, {"role": "assistant", "content": "**`enrich_results_with_page_content()`** in `GUI/web_search_runtime.py`:\n```python\ndef enrich_results_with_page_content(\n```\n\nVisit top target result URLs to extract real page text content into each result dictionary."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `configure_runtime()` function in `GUI/web_search_runtime.py` do?<|im_end|>\n<|im_start|>assistant\n**`configure_runtime()`** in `GUI/web_search_runtime.py`:\n```python\ndef configure_runtime(db_path: str | Path) -> None:\n```\n\nPoint persisted web-search preferences at the workspace database.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `configure_runtime()` function in `GUI/web_search_runtime.py` do?"}, {"role": "assistant", "content": "**`configure_runtime()`** in `GUI/web_search_runtime.py`:\n```python\ndef configure_runtime(db_path: str | Path) -> None:\n```\n\nPoint persisted web-search preferences at the workspace database."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `extract_document_subject()` function in `GUI/web_search_runtime.py` do?<|im_end|>\n<|im_start|>assistant\n**`extract_document_subject()`** in `GUI/web_search_runtime.py`:\n```python\ndef extract_document_subject(document_hint: str) -> str:\n```\n\nExtract clean subject matter from a document filename or title.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `extract_document_subject()` function in `GUI/web_search_runtime.py` do?"}, {"role": "assistant", "content": "**`extract_document_subject()`** in `GUI/web_search_runtime.py`:\n```python\ndef extract_document_subject(document_hint: str) -> str:\n```\n\nExtract clean subject matter from a document filename or title."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `extract_key_terms_from_chunks()` function in `GUI/web_search_runtime.py` do?<|im_end|>\n<|im_start|>assistant\n**`extract_key_terms_from_chunks()`** in `GUI/web_search_runtime.py`:\n```python\ndef extract_key_terms_from_chunks(workspace_context: str, top_n: int = 4) -> list[str]:\n```\n\nExtract top domain subject terms from retrieved document chunks.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `extract_key_terms_from_chunks()` function in `GUI/web_search_runtime.py` do?"}, {"role": "assistant", "content": "**`extract_key_terms_from_chunks()`** in `GUI/web_search_runtime.py`:\n```python\ndef extract_key_terms_from_chunks(workspace_context: str, top_n: int = 4) -> list[str]:\n```\n\nExtract top domain subject terms from retrieved document chunks."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `generate_candidate_queries()` function in `GUI/web_search_runtime.py` do?<|im_end|>\n<|im_start|>assistant\n**`generate_candidate_queries()`** in `GUI/web_search_runtime.py`:\n```python\ndef generate_candidate_queries(\n```\n\nThis function is part of the web search functionality.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `generate_candidate_queries()` function in `GUI/web_search_runtime.py` do?"}, {"role": "assistant", "content": "**`generate_candidate_queries()`** in `GUI/web_search_runtime.py`:\n```python\ndef generate_candidate_queries(\n```\n\nThis function is part of the web search functionality."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat is the purpose of `GUI/web_search_runtime.py`?<|im_end|>\n<|im_start|>assistant\n**`GUI/web_search_runtime.py`** — Web search functionality\n\nThis module contains 2265 lines of Python code with 4 class(es) and 63 function(s). <|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What is the purpose of `GUI/web_search_runtime.py`?"}, {"role": "assistant", "content": "**`GUI/web_search_runtime.py`** — Web search functionality\n\nThis module contains 2265 lines of Python code with 4 class(es) and 63 function(s). "}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat classes and functions are in GUI/calendar_runtime.py?<|im_end|>\n<|im_start|>assistant\n**GUI/calendar_runtime.py** — Calendar functionality\n\n**Lines**: 1584\n**Classes** (5): CalendarEventInput, CalendarProviderConfigure, GoogleAuthStart, CalendarImportRequest, CalendarOpenSystemRequest\n**Functions** (91): _utc_now, _json, _safe_json, _connect, configure_runtime, init_calendar_db, _provider_settings, _provider_row, _upsert_provider, _parse_temporal, ... (+81 more)\n<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What classes and functions are in GUI/calendar_runtime.py?"}, {"role": "assistant", "content": "**GUI/calendar_runtime.py** — Calendar functionality\n\n**Lines**: 1584\n**Classes** (5): CalendarEventInput, CalendarProviderConfigure, GoogleAuthStart, CalendarImportRequest, CalendarOpenSystemRequest\n**Functions** (91): _utc_now, _json, _safe_json, _connect, configure_runtime, init_calendar_db, _provider_settings, _provider_row, _upsert_provider, _parse_temporal, ... (+81 more)\n"}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `configure_runtime()` function in `GUI/calendar_runtime.py` do?<|im_end|>\n<|im_start|>assistant\n**`configure_runtime()`** in `GUI/calendar_runtime.py`:\n```python\ndef configure_runtime(\n```\n\nConfigure paths/callbacks. Tests use this to isolate their database.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `configure_runtime()` function in `GUI/calendar_runtime.py` do?"}, {"role": "assistant", "content": "**`configure_runtime()`** in `GUI/calendar_runtime.py`:\n```python\ndef configure_runtime(\n```\n\nConfigure paths/callbacks. Tests use this to isolate their database."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `init_calendar_db()` function in `GUI/calendar_runtime.py` do?<|im_end|>\n<|im_start|>assistant\n**`init_calendar_db()`** in `GUI/calendar_runtime.py`:\n```python\ndef init_calendar_db() -> None:\n```\n\nThis function is part of the calendar functionality.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `init_calendar_db()` function in `GUI/calendar_runtime.py` do?"}, {"role": "assistant", "content": "**`init_calendar_db()`** in `GUI/calendar_runtime.py`:\n```python\ndef init_calendar_db() -> None:\n```\n\nThis function is part of the calendar functionality."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `calendar_manifest()` function in `GUI/calendar_runtime.py` do?<|im_end|>\n<|im_start|>assistant\n**`calendar_manifest()`** in `GUI/calendar_runtime.py`:\n```python\ndef calendar_manifest():\n```\n\nThis function is part of the calendar functionality.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `calendar_manifest()` function in `GUI/calendar_runtime.py` do?"}, {"role": "assistant", "content": "**`calendar_manifest()`** in `GUI/calendar_runtime.py`:\n```python\ndef calendar_manifest():\n```\n\nThis function is part of the calendar functionality."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `calendar_status()` function in `GUI/calendar_runtime.py` do?<|im_end|>\n<|im_start|>assistant\n**`calendar_status()`** in `GUI/calendar_runtime.py`:\n```python\ndef calendar_status(probe: bool = Query(default=False)):\n```\n\nThis function is part of the calendar functionality.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `calendar_status()` function in `GUI/calendar_runtime.py` do?"}, {"role": "assistant", "content": "**`calendar_status()`** in `GUI/calendar_runtime.py`:\n```python\ndef calendar_status(probe: bool = Query(default=False)):\n```\n\nThis function is part of the calendar functionality."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `calendar_providers()` function in `GUI/calendar_runtime.py` do?<|im_end|>\n<|im_start|>assistant\n**`calendar_providers()`** in `GUI/calendar_runtime.py`:\n```python\ndef calendar_providers(probe: bool = Query(default=False)):\n```\n\nThis function is part of the calendar functionality.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `calendar_providers()` function in `GUI/calendar_runtime.py` do?"}, {"role": "assistant", "content": "**`calendar_providers()`** in `GUI/calendar_runtime.py`:\n```python\ndef calendar_providers(probe: bool = Query(default=False)):\n```\n\nThis function is part of the calendar functionality."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `configure_provider()` function in `GUI/calendar_runtime.py` do?<|im_end|>\n<|im_start|>assistant\n**`configure_provider()`** in `GUI/calendar_runtime.py`:\n```python\ndef configure_provider(provider: str, req: CalendarProviderConfigure):\n```\n\nThis function is part of the calendar functionality.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `configure_provider()` function in `GUI/calendar_runtime.py` do?"}, {"role": "assistant", "content": "**`configure_provider()`** in `GUI/calendar_runtime.py`:\n```python\ndef configure_provider(provider: str, req: CalendarProviderConfigure):\n```\n\nThis function is part of the calendar functionality."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat is the purpose of `GUI/calendar_runtime.py`?<|im_end|>\n<|im_start|>assistant\n**`GUI/calendar_runtime.py`** — Calendar functionality\n\nThis module contains 1584 lines of Python code with 5 class(es) and 91 function(s). <|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What is the purpose of `GUI/calendar_runtime.py`?"}, {"role": "assistant", "content": "**`GUI/calendar_runtime.py`** — Calendar functionality\n\nThis module contains 1584 lines of Python code with 5 class(es) and 91 function(s). "}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat classes and functions are in GUI/memory_runtime.py?<|im_end|>\n<|im_start|>assistant\n**GUI/memory_runtime.py** — Memory/persistence runtime\n\n**Lines**: 2702\n**Classes** (14): ProvenanceInput, MemoryDraft, MemoryCreateRequest, MemoryCaptureRequest, MemoryUpdateRequest, ScopeRef, MemoryRecallRequest, ConflictResolveRequest, ... (+6 more)\n**Functions** (69): _utc_now_dt, _utc_now, _parse_time, _json, _safe_json, _connect, configure_runtime, _migration_v1, _migration_v2, _configure_fts, ... (+59 more)\n<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What classes and functions are in GUI/memory_runtime.py?"}, {"role": "assistant", "content": "**GUI/memory_runtime.py** — Memory/persistence runtime\n\n**Lines**: 2702\n**Classes** (14): ProvenanceInput, MemoryDraft, MemoryCreateRequest, MemoryCaptureRequest, MemoryUpdateRequest, ScopeRef, MemoryRecallRequest, ConflictResolveRequest, ... (+6 more)\n**Functions** (69): _utc_now_dt, _utc_now, _parse_time, _json, _safe_json, _connect, configure_runtime, _migration_v1, _migration_v2, _configure_fts, ... (+59 more)\n"}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `configure_runtime()` function in `GUI/memory_runtime.py` do?<|im_end|>\n<|im_start|>assistant\n**`configure_runtime()`** in `GUI/memory_runtime.py`:\n```python\ndef configure_runtime(\n```\n\nConfigure storage and an optional already-local semantic encoder.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `configure_runtime()` function in `GUI/memory_runtime.py` do?"}, {"role": "assistant", "content": "**`configure_runtime()`** in `GUI/memory_runtime.py`:\n```python\ndef configure_runtime(\n```\n\nConfigure storage and an optional already-local semantic encoder."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `init_memory_db()` function in `GUI/memory_runtime.py` do?<|im_end|>\n<|im_start|>assistant\n**`init_memory_db()`** in `GUI/memory_runtime.py`:\n```python\ndef init_memory_db() -> None:\n```\n\nApply versioned schema migrations without touching other workspace tables.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `init_memory_db()` function in `GUI/memory_runtime.py` do?"}, {"role": "assistant", "content": "**`init_memory_db()`** in `GUI/memory_runtime.py`:\n```python\ndef init_memory_db() -> None:\n```\n\nApply versioned schema migrations without touching other workspace tables."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `filter_secrets()` function in `GUI/memory_runtime.py` do?<|im_end|>\n<|im_start|>assistant\n**`filter_secrets()`** in `GUI/memory_runtime.py`:\n```python\ndef filter_secrets(value: Any) -> tuple[str, List[str]]:\n```\n\nDeterministically redact credential-shaped material before persistence.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `filter_secrets()` function in `GUI/memory_runtime.py` do?"}, {"role": "assistant", "content": "**`filter_secrets()`** in `GUI/memory_runtime.py`:\n```python\ndef filter_secrets(value: Any) -> tuple[str, List[str]]:\n```\n\nDeterministically redact credential-shaped material before persistence."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `list_memories()` function in `GUI/memory_runtime.py` do?<|im_end|>\n<|im_start|>assistant\n**`list_memories()`** in `GUI/memory_runtime.py`:\n```python\ndef list_memories(\n```\n\nThis function is part of the memory/persistence runtime.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `list_memories()` function in `GUI/memory_runtime.py` do?"}, {"role": "assistant", "content": "**`list_memories()`** in `GUI/memory_runtime.py`:\n```python\ndef list_memories(\n```\n\nThis function is part of the memory/persistence runtime."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `search_memories()` function in `GUI/memory_runtime.py` do?<|im_end|>\n<|im_start|>assistant\n**`search_memories()`** in `GUI/memory_runtime.py`:\n```python\ndef search_memories(\n```\n\nThis function is part of the memory/persistence runtime.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `search_memories()` function in `GUI/memory_runtime.py` do?"}, {"role": "assistant", "content": "**`search_memories()`** in `GUI/memory_runtime.py`:\n```python\ndef search_memories(\n```\n\nThis function is part of the memory/persistence runtime."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `recall_memories()` function in `GUI/memory_runtime.py` do?<|im_end|>\n<|im_start|>assistant\n**`recall_memories()`** in `GUI/memory_runtime.py`:\n```python\ndef recall_memories(req: MemoryRecallRequest) -> Dict[str, Any]:\n```\n\nThis function is part of the memory/persistence runtime.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `recall_memories()` function in `GUI/memory_runtime.py` do?"}, {"role": "assistant", "content": "**`recall_memories()`** in `GUI/memory_runtime.py`:\n```python\ndef recall_memories(req: MemoryRecallRequest) -> Dict[str, Any]:\n```\n\nThis function is part of the memory/persistence runtime."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat is the purpose of `GUI/memory_runtime.py`?<|im_end|>\n<|im_start|>assistant\n**`GUI/memory_runtime.py`** — Memory/persistence runtime\n\nThis module contains 2702 lines of Python code with 14 class(es) and 69 function(s). <|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What is the purpose of `GUI/memory_runtime.py`?"}, {"role": "assistant", "content": "**`GUI/memory_runtime.py`** — Memory/persistence runtime\n\nThis module contains 2702 lines of Python code with 14 class(es) and 69 function(s). "}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat classes and functions are in PDF_parser/chat_backend.py?<|im_end|>\n<|im_start|>assistant\n**PDF_parser/chat_backend.py** — FastAPI app definition\n\n**Lines**: 658\n**Classes** (6): ChatMessage, ChatRequest, ChatResponse, UploadResponse, DatabaseManager, RAGManager\n**Functions** (2): mount_rag_workspace_gui_api, load_documents_from_db\n**Async functions** (8): retrieve_for_query, get_doc_hits, root, health_check, upload_pdf, ... (+3 more)\n<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What classes and functions are in PDF_parser/chat_backend.py?"}, {"role": "assistant", "content": "**PDF_parser/chat_backend.py** — FastAPI app definition\n\n**Lines**: 658\n**Classes** (6): ChatMessage, ChatRequest, ChatResponse, UploadResponse, DatabaseManager, RAGManager\n**Functions** (2): mount_rag_workspace_gui_api, load_documents_from_db\n**Async functions** (8): retrieve_for_query, get_doc_hits, root, health_check, upload_pdf, ... (+3 more)\n"}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `mount_rag_workspace_gui_api()` function in `PDF_parser/chat_backend.py` do?<|im_end|>\n<|im_start|>assistant\n**`mount_rag_workspace_gui_api()`** in `PDF_parser/chat_backend.py`:\n```python\ndef mount_rag_workspace_gui_api() -> None:\n```\n\nMount the RAGWorkspace GUI backend.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `mount_rag_workspace_gui_api()` function in `PDF_parser/chat_backend.py` do?"}, {"role": "assistant", "content": "**`mount_rag_workspace_gui_api()`** in `PDF_parser/chat_backend.py`:\n```python\ndef mount_rag_workspace_gui_api() -> None:\n```\n\nMount the RAGWorkspace GUI backend."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `load_documents_from_db()` function in `PDF_parser/chat_backend.py` do?<|im_end|>\n<|im_start|>assistant\n**`load_documents_from_db()`** in `PDF_parser/chat_backend.py`:\n```python\ndef load_documents_from_db():\n```\n\nLoad persisted documents into in-memory retrieval index at startup.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `load_documents_from_db()` function in `PDF_parser/chat_backend.py` do?"}, {"role": "assistant", "content": "**`load_documents_from_db()`** in `PDF_parser/chat_backend.py`:\n```python\ndef load_documents_from_db():\n```\n\nLoad persisted documents into in-memory retrieval index at startup."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat is the purpose of `PDF_parser/chat_backend.py`?<|im_end|>\n<|im_start|>assistant\n**`PDF_parser/chat_backend.py`** — FastAPI app definition\n\nThis module contains 658 lines of Python code with 6 class(es) and 2 function(s). It manages LLM chat interactions, streaming, and context assembly.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What is the purpose of `PDF_parser/chat_backend.py`?"}, {"role": "assistant", "content": "**`PDF_parser/chat_backend.py`** — FastAPI app definition\n\nThis module contains 658 lines of Python code with 6 class(es) and 2 function(s). It manages LLM chat interactions, streaming, and context assembly."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat classes and functions are in PDF_parser/converter.py?<|im_end|>\n<|im_start|>assistant\n**PDF_parser/converter.py** — PDF to Markdown conversion\n\n**Lines**: 1229\n**Classes** (6): ConversionMode, ConversionConfig, ConversionStats, PDFValidator, PageProcessor, PDFConverter\n**Functions** (8): get_physical_cores, _clean_pdf_metadata, _process_pages_worker, _process_page_worker, create_processing_tasks, assemble_results, build_default_config, run_full_conversion\n<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What classes and functions are in PDF_parser/converter.py?"}, {"role": "assistant", "content": "**PDF_parser/converter.py** — PDF to Markdown conversion\n\n**Lines**: 1229\n**Classes** (6): ConversionMode, ConversionConfig, ConversionStats, PDFValidator, PageProcessor, PDFConverter\n**Functions** (8): get_physical_cores, _clean_pdf_metadata, _process_pages_worker, _process_page_worker, create_processing_tasks, assemble_results, build_default_config, run_full_conversion\n"}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `get_physical_cores()` function in `PDF_parser/converter.py` do?<|im_end|>\n<|im_start|>assistant\n**`get_physical_cores()`** in `PDF_parser/converter.py`:\n```python\ndef get_physical_cores() -> int:\n```\n\nReturn the number of **physical** CPU cores (ignoring logical hyper‑threads).<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `get_physical_cores()` function in `PDF_parser/converter.py` do?"}, {"role": "assistant", "content": "**`get_physical_cores()`** in `PDF_parser/converter.py`:\n```python\ndef get_physical_cores() -> int:\n```\n\nReturn the number of **physical** CPU cores (ignoring logical hyper‑threads)."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `create_processing_tasks()` function in `PDF_parser/converter.py` do?<|im_end|>\n<|im_start|>assistant\n**`create_processing_tasks()`** in `PDF_parser/converter.py`:\n```python\ndef create_processing_tasks(\n```\n\nCreate a list of processing tasks based on file size and core count.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `create_processing_tasks()` function in `PDF_parser/converter.py` do?"}, {"role": "assistant", "content": "**`create_processing_tasks()`** in `PDF_parser/converter.py`:\n```python\ndef create_processing_tasks(\n```\n\nCreate a list of processing tasks based on file size and core count."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `assemble_results()` function in `PDF_parser/converter.py` do?<|im_end|>\n<|im_start|>assistant\n**`assemble_results()`** in `PDF_parser/converter.py`:\n```python\ndef assemble_results(\n```\n\nThis function is part of the pdf to markdown conversion.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `assemble_results()` function in `PDF_parser/converter.py` do?"}, {"role": "assistant", "content": "**`assemble_results()`** in `PDF_parser/converter.py`:\n```python\ndef assemble_results(\n```\n\nThis function is part of the pdf to markdown conversion."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `build_default_config()` function in `PDF_parser/converter.py` do?<|im_end|>\n<|im_start|>assistant\n**`build_default_config()`** in `PDF_parser/converter.py`:\n```python\ndef build_default_config(\n```\n\nCreate a sensible default ``ConversionConfig`` for command‑line use.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `build_default_config()` function in `PDF_parser/converter.py` do?"}, {"role": "assistant", "content": "**`build_default_config()`** in `PDF_parser/converter.py`:\n```python\ndef build_default_config(\n```\n\nCreate a sensible default ``ConversionConfig`` for command‑line use."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `run_full_conversion()` function in `PDF_parser/converter.py` do?<|im_end|>\n<|im_start|>assistant\n**`run_full_conversion()`** in `PDF_parser/converter.py`:\n```python\ndef run_full_conversion(\n```\n\nRun the conversion pipeline and print a timing summary.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `run_full_conversion()` function in `PDF_parser/converter.py` do?"}, {"role": "assistant", "content": "**`run_full_conversion()`** in `PDF_parser/converter.py`:\n```python\ndef run_full_conversion(\n```\n\nRun the conversion pipeline and print a timing summary."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat is the purpose of `PDF_parser/converter.py`?<|im_end|>\n<|im_start|>assistant\n**`PDF_parser/converter.py`** — PDF to Markdown conversion\n\nThis module contains 1229 lines of Python code with 6 class(es) and 8 function(s). <|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What is the purpose of `PDF_parser/converter.py`?"}, {"role": "assistant", "content": "**`PDF_parser/converter.py`** — PDF to Markdown conversion\n\nThis module contains 1229 lines of Python code with 6 class(es) and 8 function(s). "}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat classes and functions are in PDF_parser/layout.py?<|im_end|>\n<|im_start|>assistant\n**PDF_parser/layout.py** — Page layout analysis\n\n**Lines**: 149\n**Classes** (1): BoundingBox\n**Functions** (1): passes_size_filter\n<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What classes and functions are in PDF_parser/layout.py?"}, {"role": "assistant", "content": "**PDF_parser/layout.py** — Page layout analysis\n\n**Lines**: 149\n**Classes** (1): BoundingBox\n**Functions** (1): passes_size_filter\n"}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `passes_size_filter()` function in `PDF_parser/layout.py` do?<|im_end|>\n<|im_start|>assistant\n**`passes_size_filter()`** in `PDF_parser/layout.py`:\n```python\ndef passes_size_filter(\n```\n\nDetermine whether a block meets a minimum size requirement.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `passes_size_filter()` function in `PDF_parser/layout.py` do?"}, {"role": "assistant", "content": "**`passes_size_filter()`** in `PDF_parser/layout.py`:\n```python\ndef passes_size_filter(\n```\n\nDetermine whether a block meets a minimum size requirement."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat is the purpose of `PDF_parser/layout.py`?<|im_end|>\n<|im_start|>assistant\n**`PDF_parser/layout.py`** — Page layout analysis\n\nThis module contains 149 lines of Python code with 1 class(es) and 1 function(s). <|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What is the purpose of `PDF_parser/layout.py`?"}, {"role": "assistant", "content": "**`PDF_parser/layout.py`** — Page layout analysis\n\nThis module contains 149 lines of Python code with 1 class(es) and 1 function(s). "}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat classes and functions are in PDF_parser/tables.py?<|im_end|>\n<|im_start|>assistant\n**PDF_parser/tables.py** — Table detection\n\n**Lines**: 283\n**Classes** (2): TableData, TableProcessor\n<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What classes and functions are in PDF_parser/tables.py?"}, {"role": "assistant", "content": "**PDF_parser/tables.py** — Table detection\n\n**Lines**: 283\n**Classes** (2): TableData, TableProcessor\n"}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat is the purpose of `PDF_parser/tables.py`?<|im_end|>\n<|im_start|>assistant\n**`PDF_parser/tables.py`** — Table detection\n\nThis module contains 283 lines of Python code with 2 class(es) and 0 function(s). <|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What is the purpose of `PDF_parser/tables.py`?"}, {"role": "assistant", "content": "**`PDF_parser/tables.py`** — Table detection\n\nThis module contains 283 lines of Python code with 2 class(es) and 0 function(s). "}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat classes and functions are in PDF_parser/images.py?<|im_end|>\n<|im_start|>assistant\n**PDF_parser/images.py** — Image extraction\n\n**Lines**: 263\n**Classes** (2): ImageInfo, ImageExtractor\n<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What classes and functions are in PDF_parser/images.py?"}, {"role": "assistant", "content": "**PDF_parser/images.py** — Image extraction\n\n**Lines**: 263\n**Classes** (2): ImageInfo, ImageExtractor\n"}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat is the purpose of `PDF_parser/images.py`?<|im_end|>\n<|im_start|>assistant\n**`PDF_parser/images.py`** — Image extraction\n\nThis module contains 263 lines of Python code with 2 class(es) and 0 function(s). <|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What is the purpose of `PDF_parser/images.py`?"}, {"role": "assistant", "content": "**`PDF_parser/images.py`** — Image extraction\n\nThis module contains 263 lines of Python code with 2 class(es) and 0 function(s). "}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat classes and functions are in pymu_rag_launcher.py?<|im_end|>\n<|im_start|>assistant\n**pymu_rag_launcher.py** — Main application launcher\n\n**Lines**: 425\n**Functions** (18): is_frozen, bundled_root, runtime_root, legacy_runtime_root, migrate_legacy_runtime_home, should_skip_copy, is_mutable_runtime_data_path, file_fingerprint, target_matches_source_metadata, copy_tree_preserving_data, ... (+8 more)\n<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What classes and functions are in pymu_rag_launcher.py?"}, {"role": "assistant", "content": "**pymu_rag_launcher.py** — Main application launcher\n\n**Lines**: 425\n**Functions** (18): is_frozen, bundled_root, runtime_root, legacy_runtime_root, migrate_legacy_runtime_home, should_skip_copy, is_mutable_runtime_data_path, file_fingerprint, target_matches_source_metadata, copy_tree_preserving_data, ... (+8 more)\n"}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `is_frozen()` function in `pymu_rag_launcher.py` do?<|im_end|>\n<|im_start|>assistant\n**`is_frozen()`** in `pymu_rag_launcher.py`:\n```python\ndef is_frozen() -> bool:\n```\n\nThis function is part of the main application launcher.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `is_frozen()` function in `pymu_rag_launcher.py` do?"}, {"role": "assistant", "content": "**`is_frozen()`** in `pymu_rag_launcher.py`:\n```python\ndef is_frozen() -> bool:\n```\n\nThis function is part of the main application launcher."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `bundled_root()` function in `pymu_rag_launcher.py` do?<|im_end|>\n<|im_start|>assistant\n**`bundled_root()`** in `pymu_rag_launcher.py`:\n```python\ndef bundled_root() -> Path:\n```\n\nThis function is part of the main application launcher.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `bundled_root()` function in `pymu_rag_launcher.py` do?"}, {"role": "assistant", "content": "**`bundled_root()`** in `pymu_rag_launcher.py`:\n```python\ndef bundled_root() -> Path:\n```\n\nThis function is part of the main application launcher."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `runtime_root()` function in `pymu_rag_launcher.py` do?<|im_end|>\n<|im_start|>assistant\n**`runtime_root()`** in `pymu_rag_launcher.py`:\n```python\ndef runtime_root() -> Path:\n```\n\nThis function is part of the main application launcher.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `runtime_root()` function in `pymu_rag_launcher.py` do?"}, {"role": "assistant", "content": "**`runtime_root()`** in `pymu_rag_launcher.py`:\n```python\ndef runtime_root() -> Path:\n```\n\nThis function is part of the main application launcher."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `legacy_runtime_root()` function in `pymu_rag_launcher.py` do?<|im_end|>\n<|im_start|>assistant\n**`legacy_runtime_root()`** in `pymu_rag_launcher.py`:\n```python\ndef legacy_runtime_root() -> Path:\n```\n\nAdopt the pre-unification PyMuRAGWorkspace home on first launch.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `legacy_runtime_root()` function in `pymu_rag_launcher.py` do?"}, {"role": "assistant", "content": "**`legacy_runtime_root()`** in `pymu_rag_launcher.py`:\n```python\ndef legacy_runtime_root() -> Path:\n```\n\nAdopt the pre-unification PyMuRAGWorkspace home on first launch."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `migrate_legacy_runtime_home()` function in `pymu_rag_launcher.py` do?<|im_end|>\n<|im_start|>assistant\n**`migrate_legacy_runtime_home()`** in `pymu_rag_launcher.py`:\n```python\ndef migrate_legacy_runtime_home(root: Path) -> None:\n```\n\nAdopt the pre-unification PyMuRAGWorkspace home on first launch.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `migrate_legacy_runtime_home()` function in `pymu_rag_launcher.py` do?"}, {"role": "assistant", "content": "**`migrate_legacy_runtime_home()`** in `pymu_rag_launcher.py`:\n```python\ndef migrate_legacy_runtime_home(root: Path) -> None:\n```\n\nAdopt the pre-unification PyMuRAGWorkspace home on first launch."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `should_skip_copy()` function in `pymu_rag_launcher.py` do?<|im_end|>\n<|im_start|>assistant\n**`should_skip_copy()`** in `pymu_rag_launcher.py`:\n```python\ndef should_skip_copy(path: Path) -> bool:\n```\n\nThis function is part of the main application launcher.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `should_skip_copy()` function in `pymu_rag_launcher.py` do?"}, {"role": "assistant", "content": "**`should_skip_copy()`** in `pymu_rag_launcher.py`:\n```python\ndef should_skip_copy(path: Path) -> bool:\n```\n\nThis function is part of the main application launcher."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat is the purpose of `pymu_rag_launcher.py`?<|im_end|>\n<|im_start|>assistant\n**`pymu_rag_launcher.py`** — Main application launcher\n\nThis module contains 425 lines of Python code with 18 function(s). <|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What is the purpose of `pymu_rag_launcher.py`?"}, {"role": "assistant", "content": "**`pymu_rag_launcher.py`** — Main application launcher\n\nThis module contains 425 lines of Python code with 18 function(s). "}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat classes and functions are in rag_core.py?<|im_end|>\n<|im_start|>assistant\n**rag_core.py** — Core RAG functionality\n\n**Lines**: 362\n**Functions** (18): normalize_path, _escape_sql_string, _safe_lancedb_filter_value, _safe_lancedb_key, _safe_lancedb_id_list, _chunk_id, model_to_db_name, model_to_db_path, list_available_databases, _get_embedding_schema, ... (+8 more)\n<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What classes and functions are in rag_core.py?"}, {"role": "assistant", "content": "**rag_core.py** — Core RAG functionality\n\n**Lines**: 362\n**Functions** (18): normalize_path, _escape_sql_string, _safe_lancedb_filter_value, _safe_lancedb_key, _safe_lancedb_id_list, _chunk_id, model_to_db_name, model_to_db_path, list_available_databases, _get_embedding_schema, ... (+8 more)\n"}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `normalize_path()` function in `rag_core.py` do?<|im_end|>\n<|im_start|>assistant\n**`normalize_path()`** in `rag_core.py`:\n```python\ndef normalize_path(path: str) -> str:\n```\n\nThis function is part of the core rag functionality.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `normalize_path()` function in `rag_core.py` do?"}, {"role": "assistant", "content": "**`normalize_path()`** in `rag_core.py`:\n```python\ndef normalize_path(path: str) -> str:\n```\n\nThis function is part of the core rag functionality."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `model_to_db_name()` function in `rag_core.py` do?<|im_end|>\n<|im_start|>assistant\n**`model_to_db_name()`** in `rag_core.py`:\n```python\ndef model_to_db_name(model_path: str) -> str:\n```\n\nThis function is part of the core rag functionality.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `model_to_db_name()` function in `rag_core.py` do?"}, {"role": "assistant", "content": "**`model_to_db_name()`** in `rag_core.py`:\n```python\ndef model_to_db_name(model_path: str) -> str:\n```\n\nThis function is part of the core rag functionality."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `model_to_db_path()` function in `rag_core.py` do?<|im_end|>\n<|im_start|>assistant\n**`model_to_db_path()`** in `rag_core.py`:\n```python\ndef model_to_db_path(model_path: str, db_root: str = DB_ROOT) -> str:\n```\n\nThis function is part of the core rag functionality.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `model_to_db_path()` function in `rag_core.py` do?"}, {"role": "assistant", "content": "**`model_to_db_path()`** in `rag_core.py`:\n```python\ndef model_to_db_path(model_path: str, db_root: str = DB_ROOT) -> str:\n```\n\nThis function is part of the core rag functionality."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `list_available_databases()` function in `rag_core.py` do?<|im_end|>\n<|im_start|>assistant\n**`list_available_databases()`** in `rag_core.py`:\n```python\ndef list_available_databases(db_root: str = DB_ROOT) -> List[str]:\n```\n\nThis function is part of the core rag functionality.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `list_available_databases()` function in `rag_core.py` do?"}, {"role": "assistant", "content": "**`list_available_databases()`** in `rag_core.py`:\n```python\ndef list_available_databases(db_root: str = DB_ROOT) -> List[str]:\n```\n\nThis function is part of the core rag functionality."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `create_vector_index()` function in `rag_core.py` do?<|im_end|>\n<|im_start|>assistant\n**`create_vector_index()`** in `rag_core.py`:\n```python\ndef create_vector_index(tbl) -> None:\n```\n\nCreate IVF_FLAT vector index if it does not already exist.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `create_vector_index()` function in `rag_core.py` do?"}, {"role": "assistant", "content": "**`create_vector_index()`** in `rag_core.py`:\n```python\ndef create_vector_index(tbl) -> None:\n```\n\nCreate IVF_FLAT vector index if it does not already exist."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat does the `read_gguf_metadata()` function in `rag_core.py` do?<|im_end|>\n<|im_start|>assistant\n**`read_gguf_metadata()`** in `rag_core.py`:\n```python\ndef read_gguf_metadata(\n```\n\nThis function is part of the core rag functionality.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What does the `read_gguf_metadata()` function in `rag_core.py` do?"}, {"role": "assistant", "content": "**`read_gguf_metadata()`** in `rag_core.py`:\n```python\ndef read_gguf_metadata(\n```\n\nThis function is part of the core rag functionality."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat is the purpose of `rag_core.py`?<|im_end|>\n<|im_start|>assistant\n**`rag_core.py`** — Core RAG functionality\n\nThis module contains 362 lines of Python code with 18 function(s). <|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What is the purpose of `rag_core.py`?"}, {"role": "assistant", "content": "**`rag_core.py`** — Core RAG functionality\n\nThis module contains 362 lines of Python code with 18 function(s). "}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat endpoints does SimpleRAG expose for document management?<|im_end|>\n<|im_start|>assistant\n**Document endpoints** (from `GUI/router.py`):\n\n| Method | Endpoint | Purpose |\n|:---|:---|:---|\n| POST | `/api/documents/upload` | Upload PDF for processing |\n| GET | `/api/documents` | List all documents |\n| GET | `/api/documents/{id}` | Get document metadata |\n| DELETE | `/api/documents/{id}` | Remove document and chunks |\n| POST | `/api/documents/reindex` | Rebuild search index |\n| GET | `/api/documents/{id}/chunks` | List document chunks |<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What endpoints does SimpleRAG expose for document management?"}, {"role": "assistant", "content": "**Document endpoints** (from `GUI/router.py`):\n\n| Method | Endpoint | Purpose |\n|:---|:---|:---|\n| POST | `/api/documents/upload` | Upload PDF for processing |\n| GET | `/api/documents` | List all documents |\n| GET | `/api/documents/{id}` | Get document metadata |\n| DELETE | `/api/documents/{id}` | Remove document and chunks |\n| POST | `/api/documents/reindex` | Rebuild search index |\n| GET | `/api/documents/{id}/chunks` | List document chunks |"}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat chat endpoints does SimpleRAG expose?<|im_end|>\n<|im_start|>assistant\n**Chat endpoints** (from `GUI/router.py`):\n\n| Method | Endpoint | Purpose |\n|:---|:---|:---|\n| POST | `/api/chat` | RAG-augmented chat |\n| POST | `/api/chat/stream` | Streaming SSE chat |\n| GET | `/api/chat/history` | Chat message history |\n| DELETE | `/api/chat/history` | Clear chat history |<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What chat endpoints does SimpleRAG expose?"}, {"role": "assistant", "content": "**Chat endpoints** (from `GUI/router.py`):\n\n| Method | Endpoint | Purpose |\n|:---|:---|:---|\n| POST | `/api/chat` | RAG-augmented chat |\n| POST | `/api/chat/stream` | Streaming SSE chat |\n| GET | `/api/chat/history` | Chat message history |\n| DELETE | `/api/chat/history` | Clear chat history |"}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nHow does the knowledge graph endpoint work?<|im_end|>\n<|im_start|>assistant\nThe `/api/graph/search` endpoint accepts a query string and returns entity-relationship results:\n\n1. Query is processed by `GUI/hybrid_graph_service.py`\n2. Entities matching the query are found in the graph\n3. Related entities and edges are retrieved\n4. Results include entity names, types, relationships, and confidence scores\n5. The Discord bot's `/graph search` command calls this endpoint\n\nThe graph is workspace-scoped — each workspace has its own independent graph.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "How does the knowledge graph endpoint work?"}, {"role": "assistant", "content": "The `/api/graph/search` endpoint accepts a query string and returns entity-relationship results:\n\n1. Query is processed by `GUI/hybrid_graph_service.py`\n2. Entities matching the query are found in the graph\n3. Related entities and edges are retrieved\n4. Results include entity names, types, relationships, and confidence scores\n5. The Discord bot's `/graph search` command calls this endpoint\n\nThe graph is workspace-scoped — each workspace has its own independent graph."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat model management endpoints are available?<|im_end|>\n<|im_start|>assistant\n**Model endpoints** (from `GUI/llama_cpp_routes.py`):\n\n| Method | Endpoint | Purpose |\n|:---|:---|:---|\n| GET | `/api/models` | List available models |\n| POST | `/api/models/load` | Load a model |\n| POST | `/api/models/unload` | Unload current model |\n| GET | `/api/models/status` | Current model info |\n| GET | `/api/models/embedders` | List embedding models |<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What model management endpoints are available?"}, {"role": "assistant", "content": "**Model endpoints** (from `GUI/llama_cpp_routes.py`):\n\n| Method | Endpoint | Purpose |\n|:---|:---|:---|\n| GET | `/api/models` | List available models |\n| POST | `/api/models/load` | Load a model |\n| POST | `/api/models/unload` | Unload current model |\n| GET | `/api/models/status` | Current model info |\n| GET | `/api/models/embedders` | List embedding models |"}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nHow do I add a new API endpoint to SimpleRAG?<|im_end|>\n<|im_start|>assistant\nTo add a new endpoint to SimpleRAG:\n\n1. Open `GUI/router.py` (~4600 lines)\n2. Add a new route handler:\n```python\n@router.get(\"/api/my-endpoint\")\nasync def my_endpoint(param: str = Query(...)):\n return {\"result\": param}\n```\n3. The router is included in `PDF_parser/chat_backend.py` which creates the FastAPI app\n4. Restart the launcher to apply changes\n5. Test with: `curl http://127.0.0.1:8010/api/my-endpoint?param=test`<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "How do I add a new API endpoint to SimpleRAG?"}, {"role": "assistant", "content": "To add a new endpoint to SimpleRAG:\n\n1. Open `GUI/router.py` (~4600 lines)\n2. Add a new route handler:\n```python\n@router.get(\"/api/my-endpoint\")\nasync def my_endpoint(param: str = Query(...)):\n return {\"result\": param}\n```\n3. The router is included in `PDF_parser/chat_backend.py` which creates the FastAPI app\n4. Restart the launcher to apply changes\n5. Test with: `curl http://127.0.0.1:8010/api/my-endpoint?param=test`"}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nHow does SimpleRAG handle the venv and dependencies?<|im_end|>\n<|im_start|>assistant\nSimpleRAG uses a Python 3.12 virtual environment at `.venv/`:\n\n**Key packages**: fastapi 0.115.0, pymupdf 1.24.5, torch 2.4.1, transformers 4.51.0, sentence-transformers 3.0.1, discord.py 2.4.0, unsloth 2026.8.14, peft 0.20.0, trl 0.24.0\n\n**Critical pitfall**: Hermes agent runs Python 3.11 with its own numpy. Always use:\n```bash\nPYTHONPATH=\"\" .venv/Scripts/python.exe <command>\n```\nWithout this, Python 3.11's numpy C extensions crash Python 3.12.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "How does SimpleRAG handle the venv and dependencies?"}, {"role": "assistant", "content": "SimpleRAG uses a Python 3.12 virtual environment at `.venv/`:\n\n**Key packages**: fastapi 0.115.0, pymupdf 1.24.5, torch 2.4.1, transformers 4.51.0, sentence-transformers 3.0.1, discord.py 2.4.0, unsloth 2026.8.14, peft 0.20.0, trl 0.24.0\n\n**Critical pitfall**: Hermes agent runs Python 3.11 with its own numpy. Always use:\n```bash\nPYTHONPATH=\"\" .venv/Scripts/python.exe <command>\n```\nWithout this, Python 3.11's numpy C extensions crash Python 3.12."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nWhat is the purpose of each directory in the SimpleRAG project?<|im_end|>\n<|im_start|>assistant\n| Directory | Purpose |\n|:---|:---|\n| `GUI/` | Main application code — router, PDF parser, chat, Discord bot, graph, embeddings |\n| `PDF_parser/` | Low-level PDF parsing library — layout, tables, images, conversion |\n| `SimpleUI/` | React + Vite frontend |\n| `electron_app/` | Electron desktop shell |\n| `TrainingModel/` | Model training scripts and datasets |\n| `tests/` | pytest test suite (1150+ tests) |\n| `.venv/` | Python 3.12 virtual environment |\n| `Echidna-*/` | Trained model outputs |<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "What is the purpose of each directory in the SimpleRAG project?"}, {"role": "assistant", "content": "| Directory | Purpose |\n|:---|:---|\n| `GUI/` | Main application code — router, PDF parser, chat, Discord bot, graph, embeddings |\n| `PDF_parser/` | Low-level PDF parsing library — layout, tables, images, conversion |\n| `SimpleUI/` | React + Vite frontend |\n| `electron_app/` | Electron desktop shell |\n| `TrainingModel/` | Model training scripts and datasets |\n| `tests/` | pytest test suite (1150+ tests) |\n| `.venv/` | Python 3.12 virtual environment |\n| `Echidna-*/` | Trained model outputs |"}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nHow does the Discord bot auto-detect the SimpleRAG backend?<|im_end|>\n<|im_start|>assistant\nThe Discord bot (`GUI/discord_bot.py`, ~2170 lines) auto-discovers the backend:\n\n1. **Port scan**: Checks ports 18110-18130 and 8000-8034\n2. **Log inspection**: Reads Electron app logs for backend URL\n3. **OpenAPI verification**: Fetches `/openapi.json` to confirm SimpleRAG identity and discover endpoints (journal, knowledge graph, documents)\n4. **Health check**: Confirms backend is responsive\n\nThe bot requires the SimpleRAG desktop app to be running with a loaded model.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "How does the Discord bot auto-detect the SimpleRAG backend?"}, {"role": "assistant", "content": "The Discord bot (`GUI/discord_bot.py`, ~2170 lines) auto-discovers the backend:\n\n1. **Port scan**: Checks ports 18110-18130 and 8000-8034\n2. **Log inspection**: Reads Electron app logs for backend URL\n3. **OpenAPI verification**: Fetches `/openapi.json` to confirm SimpleRAG identity and discover endpoints (journal, knowledge graph, documents)\n4. **Health check**: Confirms backend is responsive\n\nThe bot requires the SimpleRAG desktop app to be running with a loaded model."}]} | |
| {"text": "<|im_start|>system\nYou are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase.<|im_end|>\n<|im_start|>user\nHow does SimpleRAG handle GPU layer offloading for llama.cpp?<|im_end|>\n<|im_start|>assistant\nGPU layer offloading in `GUI/llama_cpp_runtime.py`:\n\n1. Detects available GPU memory via `torch` or `llama.cpp` APIs\n2. Calculates how many model layers fit in VRAM\n3. Passes `n_gpu_layers` parameter to llama.cpp loader\n4. Remaining layers run on CPU\n5. Embedding models can also use GPU offloading via `GUI/embedding_manager.py`\n\nOn the RX 6750 XT (12GB), typically 20-28 of 28 layers fit for 0.5B models.<|im_end|>", "messages": [{"role": "system", "content": "You are Echidna, the AI assistant for SimpleRAG — an offline-first RAG desktop application (FastAPI backend port 8010, React frontend port 8080). You understand every module, function, endpoint, and configuration in the codebase."}, {"role": "user", "content": "How does SimpleRAG handle GPU layer offloading for llama.cpp?"}, {"role": "assistant", "content": "GPU layer offloading in `GUI/llama_cpp_runtime.py`:\n\n1. Detects available GPU memory via `torch` or `llama.cpp` APIs\n2. Calculates how many model layers fit in VRAM\n3. Passes `n_gpu_layers` parameter to llama.cpp loader\n4. Remaining layers run on CPU\n5. Embedding models can also use GPU offloading via `GUI/embedding_manager.py`\n\nOn the RX 6750 XT (12GB), typically 20-28 of 28 layers fit for 0.5B models."}]} | |