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https://github.com/trustgraph-ai/trustgraph.git
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01cc8dbc64
Replace the three-prompt LLM scoring pipeline (kg-edge-scoring, kg-edge-reasoning, kg-edge-selection) with a cross-encoder reranker service backed by FlashRank. The new hop_and_filter() method performs iterative graph traversal with semantic scoring at each hop, replacing the previous follow_edges/get_subgraph approach. - Add reranker service (trustgraph-base client/service, FlashRank processor) - Add gateway dispatch for reranker via API and WebSocket - Rewrite GraphRAG pipeline: hop_and_filter() with per-hop cross-encoder scoring - Remove kg_prompt() and edge_score_limit from prompt client - Update provenance: add tg:EdgeSelection type, tg:concept, tg:score predicates - Update CLIs (tg-invoke-graph-rag, tg-show-explain-trace) for new metadata - Add tg-invoke-reranker CLI tool - Add tech spec and UX developer guidance - Update all unit and integration tests |
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| .. | ||
| __init__.py | ||
| agent_client.py | ||
| base.py | ||
| config_client.py | ||
| document_embeddings_client.py | ||
| document_rag_client.py | ||
| embeddings_client.py | ||
| graph_embeddings_client.py | ||
| graph_rag_client.py | ||
| llm_client.py | ||
| prompt_client.py | ||
| row_embeddings_client.py | ||
| triples_query_client.py | ||