alvis
161e654027
Convert ml-serving from isolated MLflow runs to nested traces using mlflow.start_span_no_context(). The recommend endpoint now emits a full span tree: recommend (CHAIN) → build_context (TOOL), agent:* (AGENT) ×N, llm_orchestrator (LLM). Compute and infer endpoints each emit a single span. Supporting changes: - mlflow-skinny>=3.1.0 added to requirements - MLflow configured with --serve-artifacts + mlflow-artifacts:/ default root for cross-container artifact proxy (spans now persist from ml-serving) - --allowed-hosts extended to include mlflow:5000 (SDK includes port in Host) - science_destiny slider wired through prompts.py and recommend endpoint - Config page exposes science/destiny slider (0=data-driven, 100=intuitive) - Tip page shows rationale inline on tap Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
11 lines
178 B
Plaintext
11 lines
178 B
Plaintext
fastapi==0.115.6
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uvicorn[standard]==0.32.1
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pydantic==2.10.4
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numpy>=1.26.0
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httpx>=0.27.0
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anthropic>=0.40.0
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nats-py>=2.9.0
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structlog>=24.1.0
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sentry-sdk>=2.0.0
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mlflow-skinny>=3.1.0
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