mirror of
https://github.com/headroomlabs-ai/headroom.git
synced 2026-08-10 14:27:00 -04:00
## Description
`CCRResponseHandler._extract_assistant_message` extracts the assistant
message from an upstream response while building the CCR
retrieval-continuation history. The OpenAI branch is not defensive about
an empty or malformed `choices` array:
```python
elif provider == "openai":
message = response.get("choices", [{}])[0].get("message", {})
```
`response.get("choices", [{}])` only falls back to `[{}]` when the key
is **absent**. When `choices` is present but empty (`[]`) or carries a
null first element (`[null]`), this raises on the success path:
- `choices: []` → `[][0]` → `IndexError`
- `choices: [null]` → `None.get(...)` → `AttributeError`
OpenAI-compatible gateways can return those shapes on content-filtered
or usage-only responses. The sibling **Google** branch a few lines below
already guards this (`candidates = response.get("candidates", []); if
candidates: ... else: parts = []`), and so does `ccr/tool_calls.py` (it
checks `isinstance(choices, list)`, non-empty, and
`isinstance(first_choice, dict)`). Only this OpenAI branch was missed.
## Fix
Guard the list and the first element the same way the siblings do:
```python
elif provider == "openai":
choices = response.get("choices")
first = choices[0] if isinstance(choices, list) and choices else {}
message = first.get("message", {}) if isinstance(first, dict) else {}
return {
"role": "assistant",
"content": message.get("content"),
"tool_calls": message.get("tool_calls"),
}
```
A well-formed response is unaffected; an empty/null/absent `choices` now
yields `{"role": "assistant", "content": None, "tool_calls": None}`
instead of raising.
## Type of Change
- [x] Bug fix (non-breaking change that fixes an issue)
- [ ] New feature (non-breaking change that adds functionality)
- [ ] Breaking change (fix or feature that would cause existing
functionality to change)
- [ ] Documentation update
- [ ] Performance improvement
- [ ] Code refactoring (no functional changes)
## Changes Made
- `headroom/ccr/response_handler.py`: guard empty/non-list `choices` and
a non-dict first element in the OpenAI branch of
`_extract_assistant_message`.
- `tests/test_ccr_response_handler.py`: add
`TestExtractAssistantMessageEdgeCases` (empty `choices`, `[null]`,
absent, and the normal case).
- `CHANGELOG.md`: Bug Fixes entry.
## Testing
- [x] Unit tests pass (`pytest`)
- [x] Linting passes (`ruff check .`)
- [x] Type checking passes (`mypy headroom`)
- [x] New tests added for new functionality
- [ ] Manual testing performed
### Test Output
```text
$ uvx ruff@0.15.17 check headroom/ccr/response_handler.py tests/test_ccr_response_handler.py
All checks passed!
$ uvx ruff@0.15.17 format --check headroom/ccr/response_handler.py tests/test_ccr_response_handler.py
2 files already formatted
# Verified against the REAL imported module (headroom.ccr.response_handler is
# light — no ML imports), so this ran locally in the project venv:
$ python -c "from headroom.ccr.response_handler import CCRResponseHandler as H; h=H(); \
assert h._extract_assistant_message({'choices': []}, 'openai') == {'role':'assistant','content':None,'tool_calls':None}"
# (no IndexError; normal case still extracts content/tool_calls)
```
## Real Behavior Proof
- Environment: Windows 11, Python 3.12, project venv (`uv sync --extra
proxy`), `uvx ruff@0.15.17`.
- Exact command / steps: imported the real `CCRResponseHandler` and
called `_extract_assistant_message` with `{"choices": []}`, `{"choices":
[null]}`, `{}` (absent), and a normal `{"choices": [{"message":
{...}}]}`.
- Observed result: the OLD code raised `IndexError` on `[]` and
`AttributeError` on `[null]`; the NEW code returns `{"role":
"assistant", "content": None, "tool_calls": None}` for all three
malformed shapes and still extracts `content`/`tool_calls` from a
well-formed response. Because `response_handler` has no ML imports, this
ran against the actual module, not a replica.
- Not tested: a live CCR retrieval round trip through a gateway that
emits empty choices; the added unit tests drive
`_extract_assistant_message` directly.
## Review Readiness
- [x] I have performed a self-review
- [x] This PR is ready for human review
## Checklist
- [x] My code follows the project's style guidelines
- [x] I have performed a self-review of my code
- [x] I have commented my code, particularly in hard-to-understand areas
- [ ] I have made corresponding changes to the documentation
- [x] My changes generate no new warnings
- [x] I have added tests that prove my fix is effective or that my
feature works
- [x] New and existing unit tests pass locally with my changes
- [x] I have updated the CHANGELOG.md if applicable
## Additional Notes
`headroom/ccr/response_handler.py` is a light module (no ML imports), so
unlike most of my recent PRs I verified the fix by importing the real
class in the project venv (output above), in addition to the added unit
tests. This aligns the OpenAI branch with the already-defensive Google
branch and `ccr/tool_calls.py`.
748 lines
24 KiB
Python
748 lines
24 KiB
Python
"""Tests for CCR response handler.
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These tests verify that:
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1. CCR tool calls are correctly detected in responses
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2. Retrieval execution works for both full and search modes
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3. Continuation flow handles multiple rounds
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4. Provider-specific formats are handled correctly
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5. Streaming buffer detection works
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"""
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import json
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import pytest
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from headroom.cache.compression_store import (
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get_compression_store,
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reset_compression_store,
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)
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from headroom.ccr.response_handler import (
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CCRResponseHandler,
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CCRToolCall,
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CCRToolResult,
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ResponseHandlerConfig,
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StreamingCCRBuffer,
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)
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from headroom.ccr.tool_injection import CCR_TOOL_NAME
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class TestCCRToolCallDetection:
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"""Test detection of CCR tool calls in responses."""
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@pytest.fixture(autouse=True)
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def reset_store(self):
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"""Reset global store before each test."""
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reset_compression_store()
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yield
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reset_compression_store()
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def test_detect_anthropic_ccr_tool_call(self):
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"""Detect CCR tool call in Anthropic format."""
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handler = CCRResponseHandler()
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response = {
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"content": [
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{"type": "text", "text": "Let me retrieve that data."},
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{
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"type": "tool_use",
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"id": "tool_123",
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"name": CCR_TOOL_NAME,
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"input": {"hash": "abc123"},
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},
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]
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}
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assert handler.has_ccr_tool_calls(response, "anthropic")
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def test_detect_openai_ccr_tool_call(self):
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"""Detect CCR tool call in OpenAI format."""
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handler = CCRResponseHandler()
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response = {
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"choices": [
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{
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"message": {
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"role": "assistant",
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"content": "Let me retrieve that data.",
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"tool_calls": [
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{
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"id": "call_123",
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"type": "function",
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"function": {
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"name": CCR_TOOL_NAME,
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"arguments": '{"hash": "abc123"}',
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},
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}
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],
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}
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}
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]
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}
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assert handler.has_ccr_tool_calls(response, "openai")
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def test_no_ccr_tool_call_anthropic(self):
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"""No false positive when no CCR tool call present."""
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handler = CCRResponseHandler()
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response = {
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"content": [
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{"type": "text", "text": "Here is the data."},
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{
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"type": "tool_use",
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"id": "tool_123",
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"name": "some_other_tool",
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"input": {"param": "value"},
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},
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]
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}
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assert not handler.has_ccr_tool_calls(response, "anthropic")
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def test_no_ccr_tool_call_openai(self):
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"""No false positive when no CCR tool call present in OpenAI format."""
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handler = CCRResponseHandler()
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response = {
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"choices": [
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{
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"message": {
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"role": "assistant",
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"content": "Here is the data.",
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"tool_calls": [
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{
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"id": "call_123",
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"type": "function",
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"function": {
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"name": "other_tool",
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"arguments": '{"param": "value"}',
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},
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}
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],
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}
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}
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]
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}
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assert not handler.has_ccr_tool_calls(response, "openai")
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def test_text_only_response(self):
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"""No false positive for text-only responses."""
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handler = CCRResponseHandler()
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response = {"content": [{"type": "text", "text": "Just plain text."}]}
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assert not handler.has_ccr_tool_calls(response, "anthropic")
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def test_empty_response(self):
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"""Handle empty response gracefully."""
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handler = CCRResponseHandler()
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assert not handler.has_ccr_tool_calls({}, "anthropic")
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assert not handler.has_ccr_tool_calls({"content": []}, "anthropic")
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class TestCCRToolCallParsing:
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"""Test parsing of CCR tool calls."""
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def test_parse_anthropic_full_retrieval(self):
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"""Parse full retrieval call from Anthropic format."""
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handler = CCRResponseHandler()
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response = {
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"content": [
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{
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"type": "tool_use",
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"id": "tool_123",
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"name": CCR_TOOL_NAME,
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"input": {"hash": "abc123def456abc123def456"},
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}
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]
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}
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ccr_calls, other_calls = handler._parse_ccr_tool_calls(response, "anthropic")
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assert len(ccr_calls) == 1
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assert ccr_calls[0].tool_call_id == "tool_123"
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assert ccr_calls[0].hash_key == "abc123def456abc123def456"
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assert not hasattr(ccr_calls[0], "query")
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assert len(other_calls) == 0
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def test_parse_anthropic_retrieval_ignores_query(self):
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"""Retrieval parses the hash; any legacy ``query`` input is ignored."""
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handler = CCRResponseHandler()
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response = {
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"content": [
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{
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"type": "tool_use",
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"id": "tool_456",
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"name": CCR_TOOL_NAME,
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"input": {"hash": "def456abc123def456abc123", "query": "authentication error"},
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}
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]
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}
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ccr_calls, other_calls = handler._parse_ccr_tool_calls(response, "anthropic")
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assert len(ccr_calls) == 1
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assert ccr_calls[0].hash_key == "def456abc123def456abc123"
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assert not hasattr(ccr_calls[0], "query")
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def test_parse_mixed_tool_calls(self):
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"""Parse response with both CCR and other tool calls."""
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handler = CCRResponseHandler()
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response = {
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"content": [
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{
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"type": "tool_use",
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"id": "tool_1",
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"name": CCR_TOOL_NAME,
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"input": {"hash": "abc123def456abc123def456"},
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},
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{
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"type": "tool_use",
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"id": "tool_2",
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"name": "read_file",
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"input": {"path": "/etc/config"},
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},
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]
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}
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ccr_calls, other_calls = handler._parse_ccr_tool_calls(response, "anthropic")
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assert len(ccr_calls) == 1
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assert len(other_calls) == 1
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assert other_calls[0]["name"] == "read_file"
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class TestCCRRetrievalExecution:
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"""Test CCR retrieval execution."""
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@pytest.fixture(autouse=True)
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def reset_store(self):
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"""Reset global store before each test."""
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reset_compression_store()
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yield
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reset_compression_store()
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def test_full_retrieval_success(self):
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"""Successfully retrieve full content."""
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store = get_compression_store()
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original = json.dumps([{"id": i} for i in range(100)])
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compressed = json.dumps([{"id": i} for i in range(10)])
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hash_key = store.store(
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original=original,
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compressed=compressed,
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original_item_count=100,
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compressed_item_count=10,
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)
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handler = CCRResponseHandler()
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call = CCRToolCall(tool_call_id="test_id", hash_key=hash_key)
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result = handler._execute_retrieval(call)
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assert result.success
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assert result.items_retrieved == 100
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# Check content structure
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content = json.loads(result.content)
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assert content["hash"] == hash_key
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assert "original_content" in content
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def test_retrieval_returns_full_content_for_cached_hash(self):
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"""Retrieval always returns the full original content (never empty)."""
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store = get_compression_store()
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items = [
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{"id": 1, "text": "Python programming language tutorial"},
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{"id": 2, "text": "JavaScript web development framework"},
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{"id": 3, "text": "Python data science machine learning"},
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{"id": 4, "text": "Ruby programming language basics"},
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{"id": 5, "text": "Python web framework django flask"},
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]
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original = json.dumps(items)
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compressed = json.dumps(items[:1])
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hash_key = store.store(
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original=original,
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compressed=compressed,
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original_item_count=5,
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compressed_item_count=1,
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)
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handler = CCRResponseHandler()
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call = CCRToolCall(tool_call_id="test_id", hash_key=hash_key)
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result = handler._execute_retrieval(call)
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assert result.success
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assert result.items_retrieved == 5
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content = json.loads(result.content)
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assert content["hash"] == hash_key
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# Full content is always returned — the complete original round-trips.
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assert json.loads(content["original_content"]) == items
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def test_retrieval_nonexistent_hash(self):
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"""Handle retrieval of nonexistent hash."""
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handler = CCRResponseHandler()
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call = CCRToolCall(tool_call_id="test_id", hash_key="nonexistent123")
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result = handler._execute_retrieval(call)
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assert not result.success
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assert result.items_retrieved == 0
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content = json.loads(result.content)
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assert "error" in content
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class TestCCRToolResultMessage:
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"""Test tool result message creation."""
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def test_anthropic_tool_result_format(self):
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"""Create tool result message in Anthropic format."""
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handler = CCRResponseHandler()
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results = [
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CCRToolResult(
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tool_call_id="tool_123",
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content='{"data": "retrieved"}',
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success=True,
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items_retrieved=10,
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)
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]
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message = handler._create_tool_result_message(results, "anthropic")
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assert message["role"] == "user"
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assert len(message["content"]) == 1
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assert message["content"][0]["type"] == "tool_result"
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assert message["content"][0]["tool_use_id"] == "tool_123"
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def test_openai_tool_result_format(self):
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"""Create tool result messages in OpenAI format."""
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handler = CCRResponseHandler()
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results = [
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CCRToolResult(
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tool_call_id="call_123",
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content='{"data": "retrieved"}',
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success=True,
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),
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CCRToolResult(
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tool_call_id="call_456",
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content='{"data": "more data"}',
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success=True,
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),
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]
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message = handler._create_tool_result_message(results, "openai")
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assert "_openai_tool_results" in message
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assert len(message["_openai_tool_results"]) == 2
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assert message["_openai_tool_results"][0]["role"] == "tool"
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class TestCCRResponseHandling:
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"""Test the full response handling flow."""
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@pytest.fixture(autouse=True)
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def reset_store(self):
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"""Reset global store before each test."""
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reset_compression_store()
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yield
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reset_compression_store()
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@pytest.mark.asyncio
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async def test_handle_response_no_ccr(self):
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"""Handle response with no CCR calls (pass-through)."""
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handler = CCRResponseHandler()
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response = {"content": [{"type": "text", "text": "Just text."}]}
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async def mock_api_call(messages, tools):
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return {"content": [{"type": "text", "text": "Response"}]}
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result = await handler.handle_response(response, [], None, mock_api_call, "anthropic")
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# Should return original response unchanged
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assert result == response
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@pytest.mark.asyncio
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async def test_handle_response_with_ccr(self):
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"""Handle response containing CCR tool call."""
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store = get_compression_store()
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original = json.dumps([{"id": i} for i in range(50)])
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hash_key = store.store(
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original=original,
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compressed="[]",
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original_item_count=50,
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)
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handler = CCRResponseHandler()
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# Initial response with CCR tool call
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initial_response = {
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"content": [
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{"type": "text", "text": "Let me get that data."},
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{
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"type": "tool_use",
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"id": "tool_123",
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"name": CCR_TOOL_NAME,
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"input": {"hash": hash_key},
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},
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]
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}
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# Final response after tool result
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final_response = {"content": [{"type": "text", "text": "Here is all 50 items of data."}]}
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call_count = 0
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async def mock_api_call(messages, tools):
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nonlocal call_count
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call_count += 1
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return final_response
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result = await handler.handle_response(
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initial_response,
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[{"role": "user", "content": "Get me the data"}],
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None,
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mock_api_call,
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"anthropic",
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)
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# Should have made continuation call
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assert call_count == 1
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# Should return final response
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assert result == final_response
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@pytest.mark.asyncio
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async def test_handle_response_max_rounds(self):
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"""Respects max retrieval rounds limit."""
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store = get_compression_store()
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hash_key = store.store(original="[1,2,3]", compressed="[]")
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config = ResponseHandlerConfig(max_retrieval_rounds=2)
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handler = CCRResponseHandler(config)
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# Response that always has CCR tool call (simulating infinite loop)
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ccr_response = {
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"content": [
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{
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"type": "tool_use",
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"id": "tool_123",
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"name": CCR_TOOL_NAME,
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"input": {"hash": hash_key},
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}
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]
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}
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call_count = 0
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async def mock_api_call(messages, tools):
|
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nonlocal call_count
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call_count += 1
|
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return ccr_response
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await handler.handle_response(ccr_response, [], None, mock_api_call, "anthropic")
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|
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# Should stop after max rounds
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assert call_count == 2
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@pytest.mark.asyncio
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async def test_handle_response_disabled(self):
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"""Disabled handler returns response unchanged."""
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config = ResponseHandlerConfig(enabled=False)
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handler = CCRResponseHandler(config)
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response = {
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"content": [
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{
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"type": "tool_use",
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"id": "tool_123",
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"name": CCR_TOOL_NAME,
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"input": {"hash": "abc123"},
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}
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]
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}
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async def mock_api_call(messages, tools):
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raise AssertionError("Should not be called")
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result = await handler.handle_response(response, [], None, mock_api_call, "anthropic")
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assert result == response
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@pytest.mark.asyncio
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async def test_handle_response_mixed_tools_skips_ccr(self):
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"""When CCR and non-CCR tools are called together, skip CCR.
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Building a valid continuation is impossible without results for the
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non-CCR tools (Anthropic requires every tool_use to have a
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tool_result). Skipping CCR avoids a wasted 400 API call and returns
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the original response immediately so the client can resolve all
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tool calls itself.
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"""
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store = get_compression_store()
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hash_key = store.store(original="[1,2,3]", compressed="[]")
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handler = CCRResponseHandler()
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mixed_response = {
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"content": [
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{
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"type": "tool_use",
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"id": "ccr_call",
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"name": CCR_TOOL_NAME,
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"input": {"hash": hash_key},
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},
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{
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"type": "tool_use",
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"id": "user_call",
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"name": "read_file",
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"input": {"path": "/etc/config"},
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},
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]
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}
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api_call_count = 0
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async def mock_api_call(messages, tools):
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nonlocal api_call_count
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api_call_count += 1
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return {"content": [{"type": "text", "text": "continuation"}]}
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result = await handler.handle_response(mixed_response, [], None, mock_api_call, "anthropic")
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# CCR skipped — no continuation call made (avoids the 400 API round-trip)
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assert api_call_count == 0, "should not attempt continuation with mixed tools"
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# Original response returned unchanged so client can handle all tool calls
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assert result is mixed_response
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class TestCCRResponseHandlerStats:
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"""Test handler statistics."""
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@pytest.fixture(autouse=True)
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def reset_store(self):
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"""Reset global store before each test."""
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reset_compression_store()
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yield
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reset_compression_store()
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@pytest.mark.asyncio
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async def test_retrieval_count_tracking(self):
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"""Track total retrieval count."""
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store = get_compression_store()
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hash_key = store.store(original="[1,2,3]", compressed="[]")
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handler = CCRResponseHandler()
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initial_response = {
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"content": [
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{
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"type": "tool_use",
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"id": "tool_123",
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"name": CCR_TOOL_NAME,
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"input": {"hash": hash_key},
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}
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]
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}
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final_response = {"content": [{"type": "text", "text": "Done"}]}
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async def mock_api_call(messages, tools):
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return final_response
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await handler.handle_response(initial_response, [], None, mock_api_call, "anthropic")
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stats = handler.get_stats()
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assert stats["total_retrievals"] == 1
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class TestStreamingCCRBuffer:
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"""Test streaming buffer for CCR detection."""
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def test_buffer_accumulation(self):
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"""Buffer accumulates chunks."""
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buffer = StreamingCCRBuffer()
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buffer.add_chunk(b"part1")
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buffer.add_chunk(b"part2")
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buffer.add_chunk(b"part3")
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assert buffer.get_accumulated() == b"part1part2part3"
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def test_detect_ccr_tool_in_stream(self):
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"""Detect CCR tool call in streaming chunks."""
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buffer = StreamingCCRBuffer()
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# Simulate streaming response with tool_use
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chunk1 = b'{"type":"content_block_start","content_block":{"type":"tool_use"'
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chunk2 = f',"name":"{CCR_TOOL_NAME}"'.encode()
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detected = buffer.add_chunk(chunk1)
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assert not detected # Not complete yet
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detected = buffer.add_chunk(chunk2)
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assert detected # Now detected
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assert buffer.detected_ccr
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def test_no_false_positive_detection(self):
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"""No false positive for non-CCR tool calls."""
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buffer = StreamingCCRBuffer()
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chunk = b'{"type":"content_block_start","content_block":{"type":"tool_use","name":"other_tool"}}'
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detected = buffer.add_chunk(chunk)
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assert not detected
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assert not buffer.detected_ccr
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def test_buffer_clear(self):
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"""Buffer clears state correctly."""
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buffer = StreamingCCRBuffer()
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buffer.add_chunk(b"data")
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buffer.detected_ccr = True
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buffer.clear()
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assert buffer.get_accumulated() == b""
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assert not buffer.detected_ccr
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class TestResponseHandlerConfig:
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"""Test response handler configuration."""
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def test_default_config(self):
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"""Default config values."""
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config = ResponseHandlerConfig()
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assert config.enabled is True
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assert config.max_retrieval_rounds == 3
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assert config.strip_ccr_from_response is True
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assert config.continuation_timeout_ms == 120000
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def test_custom_config(self):
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"""Custom config values."""
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config = ResponseHandlerConfig(
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enabled=False,
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max_retrieval_rounds=5,
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)
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assert config.enabled is False
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assert config.max_retrieval_rounds == 5
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|
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class TestCCRToolCallDataClass:
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"""Test CCRToolCall dataclass."""
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def test_full_retrieval_call(self):
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"""Create full retrieval call."""
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call = CCRToolCall(
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tool_call_id="test_123",
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hash_key="abc123",
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)
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assert call.tool_call_id == "test_123"
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assert call.hash_key == "abc123"
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assert not hasattr(call, "query")
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|
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|
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class TestCCRToolResultDataClass:
|
|
"""Test CCRToolResult dataclass."""
|
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|
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def test_successful_result(self):
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"""Create successful result."""
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result = CCRToolResult(
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tool_call_id="test_123",
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content='{"data": "content"}',
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success=True,
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items_retrieved=50,
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)
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assert result.success
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assert result.items_retrieved == 50
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assert not hasattr(result, "was_search")
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def test_failed_result(self):
|
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"""Create failed result."""
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result = CCRToolResult(
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tool_call_id="test_789",
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content='{"error": "not found"}',
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success=False,
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)
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assert not result.success
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assert result.items_retrieved == 0
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|
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class TestExtractAssistantMessage:
|
|
"""Test extraction of assistant messages from responses."""
|
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|
|
def test_extract_anthropic_message(self):
|
|
"""Extract assistant message from Anthropic response."""
|
|
handler = CCRResponseHandler()
|
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|
|
response = {
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"content": [
|
|
{"type": "text", "text": "Hello"},
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{"type": "tool_use", "id": "123", "name": "test", "input": {}},
|
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]
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}
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message = handler._extract_assistant_message(response, "anthropic")
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assert message["role"] == "assistant"
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assert message["content"] == response["content"]
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def test_extract_openai_message(self):
|
|
"""Extract assistant message from OpenAI response."""
|
|
handler = CCRResponseHandler()
|
|
|
|
response = {
|
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"choices": [
|
|
{
|
|
"message": {
|
|
"role": "assistant",
|
|
"content": "Hello",
|
|
"tool_calls": [{"id": "123"}],
|
|
}
|
|
}
|
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]
|
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}
|
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|
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message = handler._extract_assistant_message(response, "openai")
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|
assert message["role"] == "assistant"
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|
assert message["content"] == "Hello"
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|
assert message["tool_calls"] == [{"id": "123"}]
|
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|
|
|
|
class TestExtractAssistantMessageEdgeCases:
|
|
"""Regression: `_extract_assistant_message` must not crash on an empty or
|
|
malformed OpenAI `choices` array (OpenAI-compatible gateways can send
|
|
`choices: []` or `[null]` on content-filtered / usage-only responses)."""
|
|
|
|
def test_openai_empty_choices_does_not_crash(self):
|
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handler = CCRResponseHandler()
|
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msg = handler._extract_assistant_message({"choices": []}, "openai")
|
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assert msg == {"role": "assistant", "content": None, "tool_calls": None}
|
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|
def test_openai_null_first_choice_does_not_crash(self):
|
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handler = CCRResponseHandler()
|
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msg = handler._extract_assistant_message({"choices": [None]}, "openai")
|
|
assert msg == {"role": "assistant", "content": None, "tool_calls": None}
|
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|
|
def test_openai_absent_choices_does_not_crash(self):
|
|
handler = CCRResponseHandler()
|
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msg = handler._extract_assistant_message({}, "openai")
|
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assert msg == {"role": "assistant", "content": None, "tool_calls": None}
|
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def test_openai_normal_choice_still_extracts(self):
|
|
handler = CCRResponseHandler()
|
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resp = {"choices": [{"message": {"content": "hi", "tool_calls": [{"id": "1"}]}}]}
|
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msg = handler._extract_assistant_message(resp, "openai")
|
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assert msg == {"role": "assistant", "content": "hi", "tool_calls": [{"id": "1"}]}
|