ducoterra
022da8e2bc
Foundation (phase 01, verified): - FastAPI app: /api/health, /api/suggestions, /api/chat (placeholder), static frontend served locally (no CDN) - Postgres 17 + pgvector via db/Containerfile + compose.yaml (podman compose up -d db), Alembic initial migration (documents, chunks with vector(768), query_log) - LLM client targeting https://aipi.reeseapps.com/v1 (turbo/embed); scripts/llm_probe.py verified models + 768-dim embeddings live - Conditional debugpy: imported only when DEBUGPY=1 (attach on demand, :5678); logging config for clean single-line logs - Frontend shell: mobile-first chat + Sources pages, tokens, a11y baselines - Tests: 24 unit+integration (99% coverage on app/), ruff + pyright clean, Playwright smoke E2E (3 tests) against a deterministic mock LLM - Planning: .agent/PLAN.md (architecture + LOCKED decisions), AGENTS.md, 6 user stories, 7 phase files (one story / one phase / one Playwright suite each)
27 lines
935 B
Python
27 lines
935 B
Python
"""Logging configuration.
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Human-readable, timestamped, single-line records on stdout. Every
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request-critical operation (retrieval, LLM calls, imports) logs key=value
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context at INFO level so a user is never left wondering what the system is
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doing — this pairs with the UI's loading/progress feedback (see PLAN §UI/UX).
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"""
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from __future__ import annotations
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import logging
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import sys
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_FORMAT = "%(asctime)s %(levelname)-8s %(name)s :: %(message)s"
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_DATEFMT = "%Y-%m-%d %H:%M:%S"
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def configure_logging(level: str = "INFO") -> None:
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root = logging.getLogger()
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root.setLevel(level.upper())
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handler = logging.StreamHandler(sys.stdout)
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handler.setFormatter(logging.Formatter(_FORMAT, _DATEFMT))
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root.handlers = [handler]
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# Keep third-party noise down while our own loggers stay verbose.
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for noisy in ("httpx", "httpcore", "openai", "urllib3"):
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logging.getLogger(noisy).setLevel(logging.WARNING)
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