112 lines
4.4 KiB
Python
112 lines
4.4 KiB
Python
from __future__ import annotations
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from qdrant_client import QdrantClient
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from adapters.embedding import (
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BedrockCohereQueryEmbedder,
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LocalHashQueryEmbedder,
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SectionOnlyQueryEmbedder,
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)
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from adapters.postgres import PostgresTraceRepository
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from adapters.qdrant import QdrantParentStore, QdrantRetriever
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from config import Settings
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from rag.answer import GroundedAnswerService
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from rag.artifacts import load_aliases
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from rag.conversation import DeterministicSummariser, InMemoryConversationStore
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from rag.conversational import ConversationalLoopService
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from rag.metrics import NullMetrics
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from rag.routing import CatalogDrugResolver, QueryRoutingService
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from rag.sections import SectionResolver
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from rag.service import EvidencePolicy, RetrievalService
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def _build_metrics(settings: Settings):
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"""A Prometheus exporter, or None when the package or the flag is absent.
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Missing `prometheus_client` degrades to no metrics rather than to a service
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that will not start: observability is not a precondition for answering.
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"""
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if not settings.metrics_enabled:
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return None
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try:
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from adapters.prometheus import PrometheusMetrics
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return PrometheusMetrics()
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except ImportError:
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return None
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def _build_generator(settings: Settings):
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if settings.answer_provider == "disabled":
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return None
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if settings.answer_provider == "stub":
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from adapters.bedrock_claude import StubAnswerGenerator
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return StubAnswerGenerator(
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"Câu trả lời mẫu, không gọi nhà cung cấp nào. [1]"
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)
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if settings.answer_provider == "bedrock-claude":
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from adapters.bedrock_claude import BedrockClaudeAnswerGenerator
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return BedrockClaudeAnswerGenerator(
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region=settings.aws_region, model_id=settings.answer_model_id
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)
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raise ValueError(
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"Unknown ANSWER_PROVIDER. Supported values: disabled (default), "
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"stub (local, no cloud), bedrock-claude"
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)
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def build_runtime(settings: Settings):
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metrics = _build_metrics(settings)
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if settings.embedding_provider == "disabled":
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return None, None, PostgresTraceRepository(settings.postgres_dsn), metrics
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if settings.embedding_provider not in ("section-only", "local-smoke", "cohere-v4"):
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raise ValueError(
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"No production query embedder is configured. Supported values: "
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"EMBEDDING_PROVIDER=section-only (default; section route only), "
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"local-smoke (plumbing only) or cohere-v4"
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)
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client = QdrantClient(
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url=settings.qdrant_url,
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api_key=settings.qdrant_api_key,
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timeout=30,
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)
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# A collection built with one model and queried with another returns hits
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# and raises nothing; the results are just meaningless. Keep this in step
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# with `model_id` in the collection's manifest.
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if settings.embedding_provider == "cohere-v4":
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embedder = BedrockCohereQueryEmbedder(
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settings.embedding_dimensions, region=settings.aws_region
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)
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elif settings.embedding_provider == "local-smoke":
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embedder = LocalHashQueryEmbedder(settings.embedding_dimensions)
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else:
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embedder = SectionOnlyQueryEmbedder(settings.embedding_dimensions)
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section_resolver = SectionResolver()
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resolver = CatalogDrugResolver(load_aliases(settings.entities_path))
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retrieval = RetrievalService(
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QdrantRetriever(client, settings.qdrant_collection, embedder),
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QdrantParentStore(client, settings.qdrant_collection),
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EvidencePolicy(minimum_score=settings.evidence_minimum_score),
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section_resolver=section_resolver,
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)
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routing = QueryRoutingService(retrieval, resolver)
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answers = GroundedAnswerService(
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routing, generator=_build_generator(settings), metrics=metrics or NullMetrics()
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)
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# The conversational layer reuses the same resolvers and the safe answer
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# engine, adding only turn understanding, follow-up inheritance and the
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# clarify/refine loop around it. InMemory store for now; a Postgres-backed
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# store is the persistence follow-up.
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conversational = ConversationalLoopService(
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answers=answers,
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resolver=resolver,
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section_resolver=section_resolver,
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store=InMemoryConversationStore(),
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summariser=DeterministicSummariser(),
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metrics=metrics or NullMetrics(),
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)
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return answers, conversational, PostgresTraceRepository(settings.postgres_dsn), metrics
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