Celes Renata
a72f336ad1
Multi-stage evidence-grounded inference architecture replacing the monolithic 9B model extraction pipeline. CPU-first specialist services handle routine extraction while the 9B vLLM model is preserved for semantic adjudication of ambiguous cases. Key components: - Capability-aware inference gateway (OpenAI-compatible + Ollama) - Endpoint registry with DB migrations and REST API - Sentence-aware document segmenter (property tests) - Deterministic financial parsing with offset integrity - Symbol resolution with ambiguity detection - Specialist service (GLiNER2, dynamic batching, K8s deployment) - Company-specific sentiment (FinBERT, calibration) - Retrieval-based novelty and duplicate detection - Confidence calibration pipeline - Deterministic routing engine (property tests) - 9B adjudication layer with VRAM gating - Stock-specific impact model (features, labels, baseline, trained) - Pipeline orchestrator (state machine, queues, leases, feature flags) - Bounded parallelism (async workers, semaphore, load shedding) - Observability (tracing, metrics, alerts) - Compatibility adapter (v3→v2 golden mapping tests) - Shadow/canary promotion framework - Active learning and fine-tuning pipeline Test results: 1,161 tests pass, ruff lint clean. All 282 spec tasks completed.
38 lines
1.1 KiB
Python
38 lines
1.1 KiB
Python
"""Retrieval-based novelty and duplicate detection.
|
|
|
|
Replaces model-generated novelty with deterministic fingerprinting,
|
|
semantic embeddings, and similarity-based scoring against a recent
|
|
history window.
|
|
"""
|
|
|
|
from services.intelligence_pipeline_v3.novelty.embeddings import (
|
|
EmbeddingBackend,
|
|
MockEmbeddingBackend,
|
|
SentenceTransformerBackend,
|
|
cosine_similarity,
|
|
)
|
|
from services.intelligence_pipeline_v3.novelty.fingerprints import (
|
|
compute_exact_fingerprint,
|
|
compute_simhash,
|
|
hamming_distance,
|
|
is_near_duplicate,
|
|
)
|
|
from services.intelligence_pipeline_v3.novelty.index import Match, NoveltyIndex
|
|
from services.intelligence_pipeline_v3.novelty.models import NoveltyResult
|
|
from services.intelligence_pipeline_v3.novelty.scorer import NoveltyScorer
|
|
|
|
__all__ = [
|
|
"EmbeddingBackend",
|
|
"Match",
|
|
"MockEmbeddingBackend",
|
|
"NoveltyIndex",
|
|
"NoveltyResult",
|
|
"NoveltyScorer",
|
|
"SentenceTransformerBackend",
|
|
"compute_exact_fingerprint",
|
|
"compute_simhash",
|
|
"cosine_similarity",
|
|
"hamming_distance",
|
|
"is_near_duplicate",
|
|
]
|