ZacharyZhang-NY
0ee99e271d
Real-models implementation: multimodal ingestion, Context Cartridge memory, sparse + Qwen embedding retrieval, Cache Fabric, Qwen runtime adapters, verifier contracts, Visual HashHop proofs, BF16 LoRA fine-tuning, and a local dashboard. Verified by a 15-check PRD proof suite on the live model.
69 lines
2.5 KiB
Python
69 lines
2.5 KiB
Python
from __future__ import annotations
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import hashlib
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from .config import Settings, get_settings
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from .db import Database
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from .schemas import CitationReport, CompiledContext
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class EvidenceGraphService:
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def __init__(self, settings: Settings | None = None, database: Database | None = None) -> None:
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self.settings = settings or get_settings()
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self.db = database or Database(self.settings)
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def record_answer(
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self,
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question: str,
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answer: str,
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report: CitationReport,
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context: CompiledContext,
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) -> str:
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claim_id = claim_node_id(question, answer)
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hit_by_id = {hit.atom.atom_id: hit for hit in context.hits}
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edges: list[dict[str, object]] = []
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for atom_id in report.cited_atom_ids:
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hit = hit_by_id.get(atom_id)
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edges.append(
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{
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"from_atom_id": claim_id,
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"to_atom_id": atom_id,
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"relation": "cites",
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"confidence": report.confidence,
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"metadata": {
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"question": question,
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"answer_sha256": hashlib.sha256(answer.encode("utf-8")).hexdigest(),
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"cache_trace_id": context.cache_trace_id,
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"final_score": hit.final_score if hit else None,
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},
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}
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)
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for atom_id in report.missing_atom_ids:
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edges.append(
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{
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"from_atom_id": claim_id,
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"to_atom_id": atom_id,
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"relation": "missing_citation",
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"confidence": 0.0,
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"metadata": {"question": question, "cache_trace_id": context.cache_trace_id},
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}
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)
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for note in report.contradiction_notes:
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note_id = "contradiction_" + hashlib.sha256(note.encode("utf-8")).hexdigest()[:16]
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edges.append(
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{
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"from_atom_id": claim_id,
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"to_atom_id": note_id,
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"relation": "contradiction_note",
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"confidence": report.confidence,
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"metadata": {"note": note, "question": question},
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}
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)
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self.db.write_evidence_edges(edges)
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return claim_id
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def claim_node_id(question: str, answer: str) -> str:
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digest = hashlib.sha256(f"{question}\n{answer}".encode("utf-8")).hexdigest()[:20]
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return f"claim_{digest}"
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