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N. Hariharan
13294c0cf0
detect_backend() picks a cloud provider purely from whichever API key is set
in the environment, and community labeling additionally falls back to claude -p
when the CLI is on PATH. Keys in a developer environment are often there for
other tools, so a bare `graphify extract .` could send uncached documents to a
provider the user did not intend.
Add explicit control without breaking existing auto-detect flows:
- GRAPHIFY_BACKEND=<name> selects a backend explicitly and wins over ambient
keys; GRAPHIFY_BACKEND=none disables every LLM backend, including the label
claude -p fallback. `graphify extract` then keeps the local AST pass and
reports what it held back instead of failing or auto-selecting a provider.
- Auto-detection now reports the exact environment variable that selected the
backend, so sending a corpus to a cloud provider is never a surprise.
- The claude -p labeling fallback is announced, and GRAPHIFY_BACKEND=none opts
out of it (it is otherwise kept: silently downgrading good labels to
"Community N" was the reason it exists).
- extract_files_direct raises a clear error naming GRAPHIFY_BACKEND when the
library caller would otherwise auto-detect a disabled backend.
README data-residency note updated. detect_backend_with_source() now carries the
detection logic and names its source; detect_backend() delegates to it.
Note: this deliberately keeps auto-detection ON by default (the issue's
alternative #2) rather than flipping cloud use to opt-in, which would break
every existing key-less `graphify extract` flow. GRAPHIFY_BACKEND makes the
opt-in switch a one-liner for a follow-up if maintainers prefer it.
(cherry picked from commit 7e2467ea43)
52 lines
2.1 KiB
Python
52 lines
2.1 KiB
Python
"""Backend-detection tests must not depend on the developer's shell (#3481).
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`detect_backend()` reads a dozen environment variables. The autouse fixture in
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conftest.py clears all of them; these tests keep that list complete and prove
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the fixture makes the detection tests immune to ambient keys.
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"""
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import inspect
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import os
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import re
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import subprocess
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import sys
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from pathlib import Path
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from graphify import llm
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ROOT = Path(__file__).resolve().parent.parent
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def test_env_list_covers_every_variable_detect_backend_reads():
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source = (
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inspect.getsource(llm.detect_backend_with_source)
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+ inspect.getsource(llm._resolve_ollama_base_url)
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)
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direct = set(re.findall(r'os\.environ\.get\("([A-Z_]+)"', source))
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builtin_keys = {key for name in llm.BACKENDS for key in llm._backend_env_keys(name)}
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listed = set(llm.backend_detection_env_vars())
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assert direct <= listed, sorted(direct - listed)
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assert builtin_keys <= listed, sorted(builtin_keys - listed)
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# The regression trigger from the report and the two Azure halves are in there.
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assert {"GOOGLE_API_KEY", "GEMINI_API_KEY", "AZURE_OPENAI_ENDPOINT", "OLLAMA_HOST"} <= listed
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def test_autouse_fixture_clears_the_backend_environment():
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for key in llm.backend_detection_env_vars():
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assert key not in os.environ, key
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assert llm.detect_backend() is None
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def test_detection_tests_pass_with_every_backend_variable_exported():
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"""The report's repro: run the detection tests with ambient keys set."""
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env = {**os.environ, **{key: "ambient-dummy" for key in llm.backend_detection_env_vars()}}
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env["AZURE_OPENAI_ENDPOINT"] = "https://example.openai.azure.com"
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env["OLLAMA_BASE_URL"] = "http://localhost:11434/v1"
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env["OLLAMA_HOST"] = "http://localhost:11434"
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result = subprocess.run(
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[sys.executable, "-m", "pytest", "-q", "-p", "no:cacheprovider",
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"tests/test_ollama.py", "tests/test_provider_registry.py", "tests/test_llm_backends.py",
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"-k", "detect_backend"],
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cwd=ROOT, env=env, capture_output=True, text=True, timeout=600,
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)
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assert result.returncode == 0, result.stdout[-3000:] + result.stderr[-1000:]
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