Celes Renata
88ad1e8d99
- Add scheduler and ingestion unit tests (test_scheduler_unit.py, test_ingestion_unit.py) - Add all 13 app services + dashboard to docker-compose.yml - Add full documentation suite: API reference, Helm reference, Docker deployment guide, 3 architecture diagrams (K8s, Docker Compose, data pipeline), AI agent guide, backup/restore guide, observability/metrics reference, per-service docs - Add intelligence pipeline deep-dive docs with Mermaid diagrams - Update README with documentation index and links - Add specs for comprehensive-quality-docs, intelligence-pipeline-deep-dive, sanitized-pipeline-docs
59 lines
1.7 KiB
Markdown
59 lines
1.7 KiB
Markdown
# Weighted Signal Computation
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```mermaid
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flowchart TD
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DOC["Document Signal Input\n(published_at, source_credibility,\nnovelty_score, extraction_confidence,\nmarket_ctx)"]
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DOC --> GATE
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DOC --> REC
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DOC --> CRED
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DOC --> NOV
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DOC --> MKT
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subgraph GATE["Confidence Gate"]
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G1["extraction_confidence ≥ 0.2?"]
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G1 -->|"Yes"| G2["gate = 1.0"]
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G1 -->|"No"| G3["gate = 0.0\n(signal zeroed out)"]
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end
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subgraph REC["Recency Decay"]
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R1["w = 2^(−age_hours / half_life)"]
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R2["Half-lives per window:\nintraday: 2h\n1d: 12h\n7d: 72h\n30d: 240h\n90d: 720h"]
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R3["Floor: min_recency_weight = 0.01"]
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R1 --- R2
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R1 --- R3
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end
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subgraph CRED["Source Credibility"]
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C1["Clamp to [0.1, 1.0]"]
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C2["Apply exponent\n(default 1.0)"]
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C1 --> C2
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end
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subgraph NOV["Novelty Bonus"]
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N1["bonus = novelty_score × 0.25"]
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N2["Range: [0.0, 0.25]\n(up to 25% boost)"]
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N1 --- N2
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end
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subgraph MKT["Environmental Context Multiplier"]
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M1["Volatility boost\nlog₁₊(excess) × 0.15\ncapped at 0.30"]
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M2["Volume surge boost\nvolume_change > 50% → +0.15"]
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M3["multiplier = 1.0 + boost\n(always ≥ 1.0)"]
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M1 --> M3
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M2 --> M3
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end
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GATE --> FORMULA
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REC --> FORMULA
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CRED --> FORMULA
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NOV --> FORMULA
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MKT --> FORMULA
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FORMULA["combined = gate × recency × credibility\n× (1 + novelty_bonus)\n× market_context_multiplier"]
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FORMULA --> SW["SignalWeight\nservices/aggregation/scoring.py"]
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SW --> WS["WeightedSignal\n{ document_id, weight: SignalWeight,\nsentiment_value, impact_score }"]
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```
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