feat: Intelligence Pipeline v3 — full implementation

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.

services/intelligence_pipeline_v3/novelty/__init__.py

@@ -0,0 +1,37 @@
+"""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",
+]