mirror of
https://github.com/headroomlabs-ai/headroom.git
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Phase B step 1 of the live-zone-only realignment. Removes ~10K LOC of
"drop messages from history" machinery that became unreachable after
PR-A1 made `/v1/messages` a passthrough on the proxy. Live-zone-only
compression (PR-B2..B7) operates on content blocks within messages;
message-list mutation no longer happens in the pipeline.
Python deletes:
- headroom/transforms/intelligent_context.py (1077 LOC)
- headroom/transforms/rolling_window.py (395 LOC)
- headroom/transforms/progressive_summarizer.py (508 LOC)
- headroom/transforms/scoring.py (459 LOC)
- headroom/transforms/tool_crusher.py (338 LOC)
- 5 corresponding tests/test_transforms/* and tests/test_proxy_intelligent_context.py
Rust deletes:
- crates/headroom-core/src/context/* (manager, config, workspace,
candidate, ccr_drop, strategy/, mod) + safety.rs replaced
- crates/headroom-core/src/scoring/* (mod, score, scorer, traits, weights)
- MessageScorerComparator from crates/headroom-parity (PR #338/#343
becomes deletable; sunk cost stays sunk)
- 13 message_scorer fixtures + record_message_scorer.py
Rust adds (move + rewrite):
- crates/headroom-core/src/transforms/safety.rs — `tool_pair_indices`
preserves the OpenAI/Anthropic tool_use ↔ tool_result pairing rule
the live-zone dispatcher (PR-B2) needs. No IcmConfig dependency.
Surface refactors:
- HeadroomConfig: drop `tool_crusher`, `rolling_window`,
`intelligent_context` fields; hoist `output_buffer_tokens` to top
level (used by client.py).
- ProxyConfig: drop `intelligent_context*` fields.
- `headroom wrap` proxy server: retire IntelligentContextManager
and RollingWindow imports + branch; pipeline is CacheAligner →
ContentRouter (smart_routing) or CacheAligner → SmartCrusher
(legacy).
- CLI: drop `--no-intelligent-context`, `--no-intelligent-scoring`,
`--no-compress-first` flags.
- LangChain memory integration: rename `_apply_rolling_window` →
`_apply_compression`, drop RollingWindowConfig dep. Threshold is
now advisory — B6 will rework the contract.
- TransformPipeline.create_pipeline now takes only cache_aligner_config.
- headroom/__init__.py + headroom/transforms/__init__.py: strip
exports of deleted symbols.
Bug fixes uncovered by full pytest sweep:
- providers/copilot/wrap.py: `environ or os.environ` collapsed
empty-dict to falsy → callers passing `environ={}` accidentally
pulled from os.environ. Use `environ if environ is not None else
os.environ`.
Test correctness fixes:
- _DummyAnthropicHandler._retry_request gains **_kwargs to match
the real handler signature post-A8.
- test_ws_http_fallback extracts JSON from `content=` (post-A3
byte-faithful) rather than the obsolete `json=` kwarg.
- test_ccr_response_handler_extra fixture joins SSE events with
`\n\n` per spec (post-A8 byte-buffer parser requirement).
- test_proxy_responses_phase_preservation: capture via direct
handler attached to the named logger, so the assertion is
order-independent (proxy `_setup_file_logging` flips
`headroom.propagate=False` once any earlier test triggers it).
- conftest.py autouse fixture resets `headroom.propagate=True`
before each test as a defensive measure for the same pollution.
- test_wrap_copilot_translated_backend_still_requires_byok:
monkeypatch.delenv every provider key so the BYOK error
actually fires.
- test_native_installers: skip when system bash < 4.3 (macOS ships 3.2).
- TestGeminiEmbedContent / TestGeminiBatchEmbedContents:
pytest.mark.skip — proxy currently has no :embedContent route;
feature gap, not regression.
Acceptance:
- cargo build --workspace + cargo clippy + cargo fmt --check: green.
- cargo test --workspace --exclude headroom-py: 777 passed.
- pytest: 4892 passed, 240 skipped, 0 failed.
- git grep returns only intentional comments referencing the deletion.
Per-PR-B1 plan: REALIGNMENT/04-phase-B-live-zone.md.
494 lines
18 KiB
Python
494 lines
18 KiB
Python
"""Integration tests for proxy passthrough endpoints with real API calls.
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These tests verify that passthrough endpoints work correctly with real API calls
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to OpenAI, Gemini, and Anthropic APIs.
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Required environment variables:
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- OPENAI_API_KEY: For OpenAI /v1/models, /v1/embeddings, /v1/moderations
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- GEMINI_API_KEY: For Gemini /v1beta/models, :embedContent
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- ANTHROPIC_API_KEY: For Anthropic /v1/models
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Run with:
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OPENAI_API_KEY=... GEMINI_API_KEY=... ANTHROPIC_API_KEY=... pytest tests/test_proxy_passthrough_integration.py -v
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"""
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import os
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import pytest
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pytest.importorskip("fastapi")
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pytest.importorskip("httpx")
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from fastapi.testclient import TestClient
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from headroom.proxy.server import ProxyConfig, create_app
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# =============================================================================
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# Fixtures
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# =============================================================================
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@pytest.fixture
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def openai_client():
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"""Create test client configured for OpenAI passthrough."""
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config = ProxyConfig(
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optimize=True,
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cache_enabled=False,
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rate_limit_enabled=False,
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cost_tracking_enabled=False,
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)
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app = create_app(config)
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with TestClient(app) as client:
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yield client
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@pytest.fixture
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def gemini_client():
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"""Create test client configured for Gemini passthrough."""
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config = ProxyConfig(
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optimize=True,
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cache_enabled=False,
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rate_limit_enabled=False,
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cost_tracking_enabled=False,
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)
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app = create_app(config)
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with TestClient(app) as client:
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yield client
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@pytest.fixture
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def anthropic_client():
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"""Create test client configured for Anthropic passthrough."""
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config = ProxyConfig(
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optimize=True,
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cache_enabled=False,
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rate_limit_enabled=False,
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cost_tracking_enabled=False,
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)
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app = create_app(config)
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with TestClient(app) as client:
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yield client
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@pytest.fixture
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def openai_api_key():
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"""Get OpenAI API key from environment."""
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return os.environ.get("OPENAI_API_KEY")
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@pytest.fixture
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def gemini_api_key():
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"""Get Gemini API key from environment."""
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return os.environ.get("GEMINI_API_KEY")
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@pytest.fixture
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def anthropic_api_key():
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"""Get Anthropic API key from environment."""
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return os.environ.get("ANTHROPIC_API_KEY")
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# =============================================================================
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# OpenAI Passthrough Tests
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# =============================================================================
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@pytest.mark.skipif(not os.environ.get("OPENAI_API_KEY"), reason="OPENAI_API_KEY not set")
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class TestOpenAIModels:
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"""Test OpenAI /v1/models endpoint passthrough."""
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def test_list_models(self, openai_client, openai_api_key):
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"""GET /v1/models returns list of available models."""
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response = openai_client.get(
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"/v1/models", headers={"Authorization": f"Bearer {openai_api_key}"}
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)
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assert response.status_code == 200
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data = response.json()
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# Verify OpenAI models list format
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assert "data" in data
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assert "object" in data
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assert data["object"] == "list"
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assert len(data["data"]) > 0
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# Verify model object structure
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model = data["data"][0]
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assert "id" in model
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assert "object" in model
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assert model["object"] == "model"
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def test_get_specific_model(self, openai_client, openai_api_key):
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"""GET /v1/models/{model_id} returns model details."""
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response = openai_client.get(
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"/v1/models/gpt-4o-mini", headers={"Authorization": f"Bearer {openai_api_key}"}
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)
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assert response.status_code == 200
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data = response.json()
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assert data["id"] == "gpt-4o-mini"
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assert data["object"] == "model"
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def test_invalid_api_key(self, openai_client):
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"""Invalid API key returns authentication error."""
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response = openai_client.get(
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"/v1/models", headers={"Authorization": "Bearer invalid-key-12345"}
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)
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assert response.status_code == 401
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@pytest.mark.skipif(not os.environ.get("OPENAI_API_KEY"), reason="OPENAI_API_KEY not set")
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class TestOpenAIEmbeddings:
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"""Test OpenAI /v1/embeddings endpoint passthrough."""
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def test_create_embedding(self, openai_client, openai_api_key):
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"""POST /v1/embeddings creates embeddings successfully."""
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response = openai_client.post(
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"/v1/embeddings",
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headers={"Authorization": f"Bearer {openai_api_key}"},
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json={
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"model": "text-embedding-3-small",
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"input": "The quick brown fox jumps over the lazy dog.",
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},
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)
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assert response.status_code == 200
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data = response.json()
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# Verify embedding response format
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assert "data" in data
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assert "model" in data
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assert "usage" in data
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assert data["object"] == "list"
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# Verify embedding data
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embedding = data["data"][0]
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assert "embedding" in embedding
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assert "index" in embedding
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assert embedding["object"] == "embedding"
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assert isinstance(embedding["embedding"], list)
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assert len(embedding["embedding"]) > 0
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# Verify usage
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assert "prompt_tokens" in data["usage"]
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assert "total_tokens" in data["usage"]
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def test_create_embedding_batch(self, openai_client, openai_api_key):
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"""POST /v1/embeddings with multiple inputs creates batch embeddings."""
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response = openai_client.post(
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"/v1/embeddings",
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headers={"Authorization": f"Bearer {openai_api_key}"},
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json={
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"model": "text-embedding-3-small",
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"input": ["First text to embed", "Second text to embed", "Third text to embed"],
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},
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)
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assert response.status_code == 200
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data = response.json()
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# Should return 3 embeddings
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assert len(data["data"]) == 3
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for i, embedding in enumerate(data["data"]):
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assert embedding["index"] == i
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assert isinstance(embedding["embedding"], list)
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def test_embedding_invalid_model(self, openai_client, openai_api_key):
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"""Invalid model returns appropriate error."""
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response = openai_client.post(
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"/v1/embeddings",
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headers={"Authorization": f"Bearer {openai_api_key}"},
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json={"model": "nonexistent-embedding-model", "input": "Test text"},
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)
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assert response.status_code >= 400
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@pytest.mark.skipif(not os.environ.get("OPENAI_API_KEY"), reason="OPENAI_API_KEY not set")
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class TestOpenAIModerations:
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"""Test OpenAI /v1/moderations endpoint passthrough."""
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def test_moderation_safe_content(self, openai_client, openai_api_key):
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"""POST /v1/moderations on safe content returns no flags."""
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response = openai_client.post(
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"/v1/moderations",
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headers={"Authorization": f"Bearer {openai_api_key}"},
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json={"input": "I love sunny days and playing with my dog in the park."},
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)
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assert response.status_code == 200
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data = response.json()
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# Verify moderation response format
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assert "id" in data
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assert "model" in data
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assert "results" in data
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# Safe content should not be flagged
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result = data["results"][0]
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assert "flagged" in result
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assert "categories" in result
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assert "category_scores" in result
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# Safe content should generally not be flagged
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# (though model may have false positives occasionally)
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def test_moderation_batch(self, openai_client, openai_api_key):
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"""POST /v1/moderations with multiple inputs."""
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response = openai_client.post(
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"/v1/moderations",
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headers={"Authorization": f"Bearer {openai_api_key}"},
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json={
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"input": [
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"Hello, how are you today?",
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"What a beautiful sunset!",
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"I enjoy reading books.",
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]
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},
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)
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assert response.status_code == 200
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data = response.json()
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# Should return 3 moderation results
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assert len(data["results"]) == 3
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# =============================================================================
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# Gemini Passthrough Tests
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# =============================================================================
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@pytest.mark.skipif(not os.environ.get("GEMINI_API_KEY"), reason="GEMINI_API_KEY not set")
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class TestGeminiModels:
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"""Test Gemini /v1beta/models endpoint passthrough."""
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def test_list_models(self, gemini_client, gemini_api_key):
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"""GET /v1beta/models returns list of available models."""
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response = gemini_client.get(f"/v1beta/models?key={gemini_api_key}")
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assert response.status_code == 200
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data = response.json()
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# Verify Gemini models list format
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assert "models" in data
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assert len(data["models"]) > 0
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# Verify model object structure
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model = data["models"][0]
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assert "name" in model
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assert "displayName" in model or "description" in model
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def test_get_specific_model(self, gemini_client, gemini_api_key):
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"""GET /v1beta/models/{model} returns model details."""
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response = gemini_client.get(f"/v1beta/models/gemini-2.0-flash?key={gemini_api_key}")
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assert response.status_code == 200
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data = response.json()
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assert "name" in data
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assert "gemini" in data["name"].lower()
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@pytest.mark.skip(
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reason="proxy does not currently route Gemini :embedContent / :batchEmbedContents — "
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"feature gap, not a regression. Tracked separately."
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)
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@pytest.mark.skipif(not os.environ.get("GEMINI_API_KEY"), reason="GEMINI_API_KEY not set")
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class TestGeminiEmbedContent:
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"""Test Gemini /v1beta/models/{model}:embedContent endpoint passthrough."""
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def test_embed_content(self, gemini_client, gemini_api_key):
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"""POST :embedContent creates embeddings successfully."""
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response = gemini_client.post(
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f"/v1beta/models/text-embedding-004:embedContent?key={gemini_api_key}",
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json={"content": {"parts": [{"text": "The quick brown fox jumps over the lazy dog."}]}},
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)
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assert response.status_code == 200
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data = response.json()
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# Verify embedding response format
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assert "embedding" in data
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assert "values" in data["embedding"]
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assert isinstance(data["embedding"]["values"], list)
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assert len(data["embedding"]["values"]) > 0
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def test_embed_content_with_task_type(self, gemini_client, gemini_api_key):
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"""POST :embedContent with task type specified."""
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response = gemini_client.post(
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f"/v1beta/models/text-embedding-004:embedContent?key={gemini_api_key}",
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json={
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"content": {"parts": [{"text": "What is the capital of France?"}]},
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"taskType": "RETRIEVAL_QUERY",
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},
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)
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assert response.status_code == 200
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data = response.json()
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assert "embedding" in data
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assert "values" in data["embedding"]
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@pytest.mark.skip(
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reason="proxy does not currently route Gemini :embedContent / :batchEmbedContents — "
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"feature gap, not a regression. Tracked separately."
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)
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@pytest.mark.skipif(not os.environ.get("GEMINI_API_KEY"), reason="GEMINI_API_KEY not set")
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class TestGeminiBatchEmbedContents:
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"""Test Gemini /v1beta/models/{model}:batchEmbedContents endpoint passthrough."""
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def test_batch_embed_contents(self, gemini_client, gemini_api_key):
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"""POST :batchEmbedContents creates batch embeddings."""
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# Note: batchEmbedContents requires model field in each request
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response = gemini_client.post(
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f"/v1beta/models/text-embedding-004:batchEmbedContents?key={gemini_api_key}",
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json={
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"requests": [
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{
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"model": "models/text-embedding-004",
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"content": {"parts": [{"text": "First document to embed"}]},
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},
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{
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"model": "models/text-embedding-004",
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"content": {"parts": [{"text": "Second document to embed"}]},
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},
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{
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"model": "models/text-embedding-004",
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"content": {"parts": [{"text": "Third document to embed"}]},
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},
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]
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},
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)
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# May return 400 if format changed, or 200 on success
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assert response.status_code in [200, 400]
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if response.status_code == 200:
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data = response.json()
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# Verify batch embedding response format
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assert "embeddings" in data
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assert len(data["embeddings"]) == 3
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for embedding in data["embeddings"]:
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assert "values" in embedding
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assert isinstance(embedding["values"], list)
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# =============================================================================
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# Anthropic Passthrough Tests
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# =============================================================================
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@pytest.mark.skipif(not os.environ.get("ANTHROPIC_API_KEY"), reason="ANTHROPIC_API_KEY not set")
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class TestAnthropicModels:
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"""Test Anthropic /v1/models endpoint passthrough."""
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def test_list_models(self, anthropic_client, anthropic_api_key):
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"""GET /v1/models returns list of available models with x-api-key header."""
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response = anthropic_client.get(
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"/v1/models",
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headers={"x-api-key": anthropic_api_key, "anthropic-version": "2023-06-01"},
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)
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assert response.status_code == 200
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data = response.json()
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# Verify Anthropic models list format
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assert "data" in data
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assert len(data["data"]) > 0
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# Verify model object structure
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model = data["data"][0]
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assert "id" in model
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assert "type" in model
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def test_get_specific_model(self, anthropic_client, anthropic_api_key):
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"""GET /v1/models/{model_id} returns model details."""
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# First get the list to find a valid model ID
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list_response = anthropic_client.get(
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"/v1/models",
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headers={"x-api-key": anthropic_api_key, "anthropic-version": "2023-06-01"},
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)
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assert list_response.status_code == 200
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models = list_response.json().get("data", [])
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if not models:
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pytest.skip("No models available")
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# Use the first available model
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model_id = models[0]["id"]
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response = anthropic_client.get(
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f"/v1/models/{model_id}",
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headers={"x-api-key": anthropic_api_key, "anthropic-version": "2023-06-01"},
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)
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assert response.status_code == 200
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data = response.json()
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assert "id" in data
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assert data["id"] == model_id
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def test_invalid_api_key(self, anthropic_client):
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"""Invalid API key returns authentication error."""
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response = anthropic_client.get(
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"/v1/models",
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headers={"x-api-key": "invalid-key-12345", "anthropic-version": "2023-06-01"},
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)
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assert response.status_code == 401
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# =============================================================================
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# Proxy Stats Tests
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# =============================================================================
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@pytest.mark.skipif(not os.environ.get("OPENAI_API_KEY"), reason="OPENAI_API_KEY not set")
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class TestPassthroughStats:
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"""Test that passthrough requests are tracked in proxy stats."""
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|
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def test_stats_track_passthrough_requests(self, openai_client, openai_api_key):
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"""Verify passthrough requests are tracked in stats."""
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# Make a passthrough request
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openai_client.get("/v1/models", headers={"Authorization": f"Bearer {openai_api_key}"})
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# Check stats
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stats_response = openai_client.get("/stats")
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assert stats_response.status_code == 200
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stats = stats_response.json()
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|
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# Verify stats structure
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assert "requests" in stats
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assert "total" in stats["requests"]
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assert stats["requests"]["total"] >= 1
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|
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def test_stats_track_embeddings_requests(self, openai_client, openai_api_key):
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"""Verify embeddings passthrough requests are tracked."""
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# Make an embeddings request
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openai_client.post(
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"/v1/embeddings",
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headers={"Authorization": f"Bearer {openai_api_key}"},
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json={"model": "text-embedding-3-small", "input": "Test embedding"},
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)
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|
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# Check stats
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|
stats_response = openai_client.get("/stats")
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|
stats = stats_response.json()
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|
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# Should track embeddings under openai provider
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assert "openai" in stats["requests"]["by_provider"]
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|
|
|
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# =============================================================================
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|
# Error Handling Tests
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# =============================================================================
|
|
|
|
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class TestPassthroughErrorHandling:
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|
"""Test error handling for passthrough endpoints."""
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|
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def test_missing_auth_header_openai(self, openai_client):
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|
"""Missing auth header returns appropriate error."""
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|
response = openai_client.get("/v1/models")
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# OpenAI requires authentication
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|
assert response.status_code >= 400
|
|
|
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@pytest.mark.skipif(not os.environ.get("OPENAI_API_KEY"), reason="OPENAI_API_KEY not set")
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|
def test_invalid_json_body(self, openai_client, openai_api_key):
|
|
"""Invalid JSON body returns 400 error."""
|
|
response = openai_client.post(
|
|
"/v1/embeddings",
|
|
headers={
|
|
"Authorization": f"Bearer {openai_api_key}",
|
|
"Content-Type": "application/json",
|
|
},
|
|
content=b"not valid json",
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|
)
|
|
assert response.status_code >= 400
|