Initial commit: Ten31 Signal Engine (ingest, scoring brain, corpus seeds)
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# Ten31 Signal Engine — pilot dependencies, grouped by pipeline layer.
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# Foundation (init-db, seed, spark client) needs only: requests, PyYAML, numpy.
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# --- core / foundation ---
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requests>=2.31
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PyYAML>=6.0
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numpy>=1.26
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# --- ingestion (§4.1) ---
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feedparser>=6.0 # podcast RSS (conditional GET via etag/modified)
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yt-dlp>=2025.1 # YouTube audio (needs a PO-token provider sidecar; see README)
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edgartools>=3.0 # SEC EDGAR filings (sets UA, throttles ≤10 rps)
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# FMP earnings transcripts are plain REST via `requests` (no SDK)
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# --- scheduling + queue (§13.4) ---
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APScheduler>=3.10
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# --- embeddings/vectors (§4.3) — vectors live in Qdrant behind Spark Control ---
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qdrant-client>=1.12
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fastembed>=0.4 # client-side BM25 sparse vectors (Qdrant/bm25, modifier: idf)
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# --- frontier (§4.6), bounded final step ---
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anthropic>=0.40
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# --- eval UI (§4.7 / human eval) ---
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fastapi>=0.110
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uvicorn>=0.29
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