751cc25327
## Summary
Two bugs in `agnes describe` surfaced from a real analyst session following the CLAUDE.md agent-rails discovery workflow. Together they break `agnes describe` end-to-end for any analyst (or analyst-AI) who follows the documented form.
### A) CLI parsing
`agnes describe TABLE -n 5` failed with `Missing argument 'TABLE_ID'`. Root cause: the command was registered as a `Typer.Typer` subcommand group via `app.add_typer(describe_app, name="describe")` + `@describe_app.callback(invoke_without_command=True)`, and that pattern mis-parses positional + short-int option in some orderings. Same pattern in `cli/commands/schema.py` works only because schema has no INTEGER short option. Fix: switch to flat `@app.command("describe")`.
### B) Server NaN
`/api/v2/sample/<id>` (called by `agnes describe`) returned HTTP 500 with `ValueError: Out of range float values are not JSON compliant: nan` whenever a row contained NaN. Fix: sanitize NaN/±inf to None before JSON serialization.
## Test plan
- [x] `pytest tests/test_cli_describe*.py` — added regression tests pinning `-n` parsing on either side of the positional.
- [x] `pytest tests/test_api_v2_sample*.py` — added regression test for NaN row → JSON `null` (not 500).
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120 lines
4.3 KiB
TOML
120 lines
4.3 KiB
TOML
[project]
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name = "agnes-the-ai-analyst"
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version = "0.46.5"
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description = "Agnes — AI Data Analyst platform for AI analytical systems"
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requires-python = ">=3.11,<3.14"
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license = "MIT"
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readme = "README.md"
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dependencies = [
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# Core database
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"duckdb>=0.9.0",
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# Web framework (FastAPI)
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"fastapi>=0.115.0",
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"uvicorn[standard]>=0.32.0",
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"python-multipart>=0.0.27",
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"jinja2>=3.1.0",
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"starlette>=0.41.0",
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# Authentication
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"PyJWT>=2.8.0",
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"itsdangerous>=2.1.0",
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"authlib>=1.6.11",
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"argon2-cffi>=23.1.0",
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# HTTP client. `h2` enables HTTP/2 multiplexing for the persistent
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# CLI client used by `agnes pull` (one TCP connection serves N
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# concurrent parquet streams + range chunks). `cli/client.py`
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# gracefully falls back to HTTP/1.1 if h2 is missing, so this
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# extra is for performance, not correctness.
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"httpx>=0.27.0",
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"h2>=4.1.0",
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# CLI
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"typer>=0.12.0",
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"rich>=13.0.0",
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# Configuration
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"python-dotenv>=1.0.0",
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"pyyaml>=6.0",
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# Data processing
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"pandas>=2.0.0",
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"pyarrow>=12.0.0",
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"pytz>=2024.1",
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# SQL parsing — server-side WHERE validator for /api/v2/scan (app/api/where_validator.py)
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# Minimum 30.x — older versions had walk() yielding (node, parent, key)
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# tuples instead of expression nodes, which would silently bypass the
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# WHERE-validator structural checks (isinstance(tuple, exp.Subquery)
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# is always False). 30.x yields nodes directly.
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"sqlglot>=30.0.0",
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# Data source connectors
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"google-cloud-bigquery>=3.0.0",
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"google-cloud-bigquery-storage>=2.0.0",
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# Google Workspace Cloud Identity / Admin SDK (Workspace group membership sync)
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"google-api-python-client>=2.0.0",
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# Profiler visualizations
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"matplotlib>=3.8.0",
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"numpy>=1.24.0",
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# Claude Code marketplace endpoint — pure-Python git server mounted in FastAPI
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"dulwich>=0.22.0",
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"a2wsgi>=1.10.0",
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# In-process TTL cache for marketplace etag (transitively present via
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# google-auth, declared explicitly here because we depend on it directly).
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"cachetools>=5.3.0",
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# Per-IP rate limiting on auth endpoints (#45). In-process counters by
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# default — fine for single-replica deploys. Multi-replica rollouts can
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# swap the storage backend via slowapi's `storage_uri` (Redis, Memcached).
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"slowapi>=0.1.9",
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# LLM provider SDKs — core (not dev) because connectors/llm/*_provider.py
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# is imported by services/{corporate_memory, verification_detector} which
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# the scheduler drives in production. Promoted from [dev] in #176 to fix
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# ModuleNotFoundError boot loops on default Compose deploys.
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"anthropic>=0.30.0",
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"openai>=1.30.0",
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# Keboola Storage API SDK — used by:
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# - `connectors/keboola/client.py` for admin-side bucket / table list
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# (consumed from `app/api/admin.py` discover-and-register, table
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# metadata refresh).
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# Extraction itself uses the lightweight `connectors/keboola/storage_api.py`
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# module (export-async + signed-URL download) which talks to Storage API
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# directly via `requests` — no SDK dependency on the data-path side. The
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# SDK stays for the metadata reads.
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"kbcstorage>=0.9.0",
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]
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[project.optional-dependencies]
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dev = [
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"pytest>=9.0.0",
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"pytest-timeout>=2.0.0",
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"pytest-xdist>=3.0.0",
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"faker>=24.0.0",
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# jsonschema validates the corporate-memory extraction-tool golden fixtures
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# under tests/test_corporate_memory_v1.py (extraction.json, correction.json,
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# confidence_calibration.json). Production code does not depend on it.
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"jsonschema>=4.0.0",
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# FastAPI debug toolbar — gated behind DEBUG=1 env var in app/main.py.
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# Provides per-request panels (headers, routes, timer, profiling, etc.)
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# for local development. Never loaded in production (no DEBUG=1 there).
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"fastapi-debug-toolbar>=0.6.3",
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]
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[project.scripts]
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agnes = "cli.main:_run_with_clean_errors"
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[build-system]
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requires = ["hatchling"]
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build-backend = "hatchling.build"
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[tool.hatch.build.targets.wheel]
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packages = ["app", "src", "connectors", "cli", "services", "config"]
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[tool.ruff]
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line-length = 120
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target-version = "py313"
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[tool.uv]
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dev-dependencies = [
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"pytest>=9.0.0",
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"pytest-timeout>=2.0.0",
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"pytest-xdist>=3.0.0",
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"faker>=24.0.0",
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"anthropic>=0.30.0",
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"openai>=1.30.0",
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"fastapi-debug-toolbar>=0.6.3",
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]
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