Files
DocsGPT/application/retriever/retriever_creator.py
T
Alex 4e0c792a6d feat(graphrag): GraphRAGRetriever (PPR local) + register + ClassicRAG fallback
Query-side: composes ClassicRAG (rephrase/budget/fallback). Per source: pgvector entity-name seed -> bounded subgraph -> networkx personalized PageRank (IDF hub down-weight) -> rank graph_node_chunks -> chunk text -> shared token budget; no LLM at query time. Citations derived from chunk metadata (matches ClassicRAG). Falls back to ClassicRAG per-source when no graph rows / unavailable / error (retrieval never breaks). get_chunk_texts queries the co-located documents table by configured table/column names (parameterized). Registered 'graphrag'. Unit G5.
2026-06-23 01:45:14 +01:00

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884 B
Python

from application.retriever.classic_rag import ClassicRAG
from application.retriever.graph_rag import GraphRAGRetriever
from application.retriever.hybrid_rag import HybridRetriever
class RetrieverCreator:
retrievers = {
"classic": ClassicRAG,
"default": ClassicRAG,
"hybrid": HybridRetriever,
"graphrag": GraphRAGRetriever,
}
@classmethod
def create_retriever(cls, type, *args, **kwargs):
retriever_type = (type or "default").lower()
retiever_class = cls.retrievers.get(retriever_type)
if not retiever_class:
raise ValueError(f"No retievers class found for type {type}")
return retiever_class(*args, **kwargs)
@classmethod
def register(cls, key, retriever_class):
"""Register ``retriever_class`` under ``key`` (idempotent)."""
cls.retrievers[key] = retriever_class