ce8a9ae0e7
Implements an RLM-powered codebase intelligence system that: - Ingests git repositories and chunks code intelligently - Stores chunks in eXist-db for RAG retrieval - Answers natural language queries using LLM synthesis New package xml_pipeline/librarian/ with: - chunker.py: AST-based code chunking (Python, JS/TS, C++) - ingest.py: Git clone + file walking + chunk storage - index.py: Structural index building (files, functions, classes) - query.py: RAG search + LLM synthesis with source citations - primitives.py: XML payloads (LibrarianIngest, LibrarianQuery, etc.) - handler.py: Message handlers for organism integration Also adds GitPython and aiohttp as optional [librarian] dependencies. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
167 lines
3.1 KiB
Python
167 lines
3.1 KiB
Python
"""
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primitives.py — XML payload dataclasses for Premium Librarian.
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These are the message types that flow through the organism's message bus.
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Note: Do NOT use `from __future__ import annotations` here
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as it breaks the xmlify decorator which needs concrete types.
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"""
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from dataclasses import dataclass
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from third_party.xmlable import xmlify
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@xmlify
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@dataclass
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class LibrarianIngest:
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"""
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Request to ingest a codebase into the Premium Librarian.
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Supports git URLs. The library will be cloned, chunked, and stored
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in eXist-db for subsequent querying.
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"""
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git_url: str = ""
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branch: str = "main"
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library_name: str = "" # Optional; derived from URL if empty
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@xmlify
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@dataclass
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class LibrarianIngested:
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"""
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Response after successful codebase ingestion.
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Contains the library_id needed for subsequent queries.
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"""
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library_id: str = ""
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library_name: str = ""
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files_processed: int = 0
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chunks_created: int = 0
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index_built: bool = False
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errors: str = "" # Newline-separated error messages
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@xmlify
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@dataclass
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class LibrarianQuery:
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"""
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Query an ingested library with a natural language question.
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The system will search for relevant code chunks and synthesize
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an answer using the configured LLM.
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"""
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library_id: str = ""
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question: str = ""
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max_chunks: int = 20 # Max chunks to include in context
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model: str = "" # Optional; uses default if empty
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@xmlify
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@dataclass
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class LibrarianAnswer:
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"""
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Response to a library query.
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Contains the synthesized answer and source references.
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"""
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answer: str = ""
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sources: str = "" # XML-formatted source list
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tokens_used: int = 0
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chunks_examined: int = 0
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error: str = ""
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@xmlify
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@dataclass
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class LibrarianList:
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"""
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Request to list all ingested libraries.
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"""
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pass # No parameters needed
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@xmlify
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@dataclass
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class LibraryInfo:
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"""
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Information about a single ingested library.
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"""
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library_id: str = ""
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name: str = ""
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source_url: str = ""
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created_at: str = ""
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total_files: int = 0
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total_chunks: int = 0
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@xmlify
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@dataclass
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class LibrarianLibraries:
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"""
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Response listing all ingested libraries.
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"""
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count: int = 0
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libraries: str = "" # XML-formatted library list
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@xmlify
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@dataclass
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class LibrarianDelete:
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"""
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Request to delete an ingested library.
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"""
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library_id: str = ""
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@xmlify
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@dataclass
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class LibrarianDeleted:
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"""
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Response after library deletion.
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"""
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library_id: str = ""
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success: bool = False
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error: str = ""
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@xmlify
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@dataclass
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class LibrarianGetChunk:
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"""
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Request to retrieve a specific code chunk.
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Useful for examining source code referenced in a query response.
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"""
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library_id: str = ""
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chunk_id: str = ""
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@xmlify
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@dataclass
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class LibrarianChunk:
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"""
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Response with a specific code chunk.
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"""
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chunk_id: str = ""
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file_path: str = ""
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name: str = ""
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chunk_type: str = ""
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language: str = ""
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start_line: int = 0
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end_line: int = 0
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content: str = ""
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docstring: str = ""
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signature: str = ""
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error: str = ""
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