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.
21 lines
554 B
Python
21 lines
554 B
Python
"""Legacy path deprecation tracking and cleanup management.
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Tracks deprecated components (VLLMClient, v2 prompts, provider branching),
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validates that all consumers have migrated, and provides safe removal
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gating. Removal only proceeds after all downstream consumers read v3.
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"""
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from services.intelligence_pipeline_v3.deprecation.tracker import (
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DeprecationEntry,
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DeprecationStatus,
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DeprecationTracker,
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MigrationReport,
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)
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__all__ = [
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"DeprecationEntry",
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"DeprecationStatus",
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"DeprecationTracker",
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"MigrationReport",
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]
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