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
63 lines
2.1 KiB
Markdown
63 lines
2.1 KiB
Markdown
# Trend Accumulation and Escalation
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```mermaid
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flowchart TD
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subgraph Windows["Five Time Windows\nservices/aggregation/worker.py"]
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W1["intraday (12h)"]
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W2["1d (1 day)"]
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W3["7d (7 days)"]
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W4["30d (30 days)"]
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W5["90d (90 days)"]
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end
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W1 & W2 & W3 & W4 & W5 --> SIGNALS
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SIGNALS["Fetch signals per window\nEntity + Macro + Competitive\n→ WeightedSignal[]"]
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SIGNALS --> SENT["weighted_sentiment_average()\nCompute avg sentiment across signals"]
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SENT --> DIR
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subgraph DIR["derive_trend_direction()"]
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D1["avg_sentiment ≥ 0.15 → POSITIVE"]
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D2["avg_sentiment ≤ −0.15 → NEGATIVE"]
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D3["contradiction > 0.10\nAND |avg| < 0.30 → MIXED"]
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D4["otherwise → NEUTRAL"]
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end
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DIR --> CONF
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subgraph CONF["compute_trend_confidence()"]
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C1["Unique source count\ncaps at 15 → 0.8 contribution"]
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C2["Avg extraction credibility"]
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C3["Signal agreement ratio\ndampened by log₂(n+1)/log₂(8)\nsaturates ~7 unique sources"]
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C4["Contradiction penalty\n−0.4 × contradiction_score"]
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C5["confidence = 0.3×count + 0.3×credibility\n+ 0.4×agreement − penalty"]
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end
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CONF --> STRENGTH["trend_strength = |avg_sentiment|\nclamped to [0, 1]"]
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STRENGTH --> ESC
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subgraph ESC["Escalation Path\n(via eligibility thresholds)"]
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direction TB
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E1["NEUTRAL\nconfidence < 0.35\nOR strength < 0.10\nOR direction = neutral"]
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E2["OBSERVE\nstrength < 0.25\nAND confidence < 0.50"]
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E3["MONITOR\nstrength < 0.25\nAND confidence ≥ 0.50"]
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E4["ACT / DEFER\nstrength ≥ 0.25\nAND direction = positive/negative"]
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E1 -->|"More signals\nsame direction"| E2
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E2 -->|"Confidence grows\nmore unique sources"| E3
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E3 -->|"Strength exceeds 0.25\naccumulated evidence"| E4
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end
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ESC --> PERSIST
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subgraph PERSIST["Persistence"]
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P1["trend_windows\n(upserted each cycle)"]
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P2["trend_history\n(time-series snapshots)"]
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P3["trend_evidence\n(per-document rankings)"]
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P4["trend_projections\nservices/aggregation/projection.py"]
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end
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```
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