Files
ECC/tests/test_claude_provider.py
ThejeshandGitHub fb98726d0a fix(llm/providers/claude): attach cache_control to system block, not top-level (#2515)
* fix(llm/providers/claude): attach cache_control to system block, not top-level

The Anthropic Messages API does not accept `cache_control` as a top-level
request parameter — it is a per-content-block field. Passing it at the top
level raises `TypeError` in the Python SDK (which validates kwargs against
`messages.create()`'s signature) or a `400 unknown_parameter` from the API,
so every ClaudeProvider.generate() call fails.

Move `cache_control: {"type": "ephemeral"}` onto the last system-prompt
block so ephemeral prompt caching still works when a system prompt is
present, and drop it when there isn't one (nothing to cache).

Existing tests didn't catch this because `FakeMessages.create(**_params)`
accepted anything and ignored the kwargs. FakeMessages now records
`last_params`, and two regression tests assert that:
  - `cache_control` never appears as a top-level param, and
  - when a system prompt is set, `cache_control` rides on the last block.

Fixes #2512

* test(claude_provider): split composite isinstance+truthiness assertion (PT018)

Ruff PT018 flagged the combined `isinstance(system, list) and system` check
in `test_generate_does_not_pass_cache_control_as_top_level_param`. Split
it into two focused asserts (`isinstance(system, list)` then `assert system`)
so a failure points at the exact violation instead of a compound condition.

Behavior unchanged; 6/6 tests still pass.

Addresses CodeRabbit review on #2515.
2026-07-17 16:04:32 -04:00

152 lines
5.0 KiB
Python

from types import SimpleNamespace
from typing import Any
import pytest
from llm.core.types import LLMInput, Message, Role
from llm.providers.claude import ClaudeProvider
class FakeMessages:
def __init__(self, response: SimpleNamespace) -> None:
self.response = response
self.last_params: dict[str, Any] = {}
def create(self, **params: object) -> SimpleNamespace:
self.last_params = dict(params)
return self.response
class FakeClient:
def __init__(self, response: SimpleNamespace) -> None:
self.messages = FakeMessages(response)
self.api_key = "test-key"
def make_provider(response: SimpleNamespace) -> ClaudeProvider:
provider = ClaudeProvider(api_key="test-key")
provider.client = FakeClient(response)
return provider
def make_response(content: list[SimpleNamespace], stop_reason: str = "tool_use") -> SimpleNamespace:
return SimpleNamespace(
content=content,
model="claude-test",
usage=SimpleNamespace(input_tokens=3, output_tokens=5),
stop_reason=stop_reason,
)
@pytest.mark.unit
def test_generate_collects_text_and_tool_use_blocks() -> None:
provider = make_provider(
make_response(
[
SimpleNamespace(type="text", text="I will search. "),
SimpleNamespace(type="tool_use", id="toolu_1", name="search", input={"query": "claude"}),
SimpleNamespace(type="text", text="Done."),
]
)
)
output = provider.generate(LLMInput(messages=[Message(role=Role.USER, content="Search")]))
assert output.content == "I will search. Done."
assert output.tool_calls is not None
assert len(output.tool_calls) == 1
assert output.tool_calls[0].id == "toolu_1"
assert output.tool_calls[0].name == "search"
assert output.tool_calls[0].arguments == {"query": "claude"}
@pytest.mark.unit
def test_generate_collects_multiple_tool_use_blocks() -> None:
provider = make_provider(
make_response(
[
SimpleNamespace(type="tool_use", id="toolu_1", name="search", input={"query": "claude"}),
SimpleNamespace(
type="tool_use",
id="toolu_2",
name="read",
input=SimpleNamespace(path="README.md"),
),
]
)
)
output = provider.generate(LLMInput(messages=[Message(role=Role.USER, content="Use tools")]))
assert output.content == ""
assert [call.id for call in output.tool_calls or []] == ["toolu_1", "toolu_2"]
assert (output.tool_calls or [])[1].arguments == {"path": "README.md"}
@pytest.mark.unit
def test_generate_copies_tool_use_dict_arguments() -> None:
raw_arguments: dict[str, Any] = {"query": "claude"}
provider = make_provider(
make_response(
[SimpleNamespace(type="tool_use", id="toolu_1", name="search", input=raw_arguments)]
)
)
output = provider.generate(LLMInput(messages=[Message(role=Role.USER, content="Use tools")]))
raw_arguments["query"] = "mutated"
assert (output.tool_calls or [])[0].arguments == {"query": "claude"}
@pytest.mark.unit
def test_generate_text_only_has_no_tool_calls() -> None:
provider = make_provider(
make_response(
[SimpleNamespace(type="text", text="Hello.")],
stop_reason="end_turn",
)
)
output = provider.generate(LLMInput(messages=[Message(role=Role.USER, content="Hi")]))
assert output.content == "Hello."
assert output.tool_calls is None
@pytest.mark.unit
def test_generate_does_not_pass_cache_control_as_top_level_param() -> None:
# cache_control is a per-content-block field on the Anthropic Messages API,
# not a top-level parameter. Passing it at the top level raises TypeError
# in the Anthropic Python SDK (or a 400 from the API).
provider = make_provider(make_response([SimpleNamespace(type="text", text="ok")]))
provider.generate(
LLMInput(
messages=[
Message(role=Role.SYSTEM, content="system prompt"),
Message(role=Role.USER, content="hi"),
]
)
)
params = provider.client.messages.last_params
assert "cache_control" not in params
# When a system prompt is present, cache_control should ride on the last
# system content block so ephemeral prompt caching still works.
system = params.get("system")
assert isinstance(system, list), "system should be sent as a list of content blocks"
assert system, "system content-block list should not be empty"
assert system[-1].get("cache_control") == {"type": "ephemeral"}
@pytest.mark.unit
def test_generate_without_system_does_not_set_system_or_cache_control() -> None:
provider = make_provider(make_response([SimpleNamespace(type="text", text="ok")]))
provider.generate(LLMInput(messages=[Message(role=Role.USER, content="hi")]))
params = provider.client.messages.last_params
assert "cache_control" not in params
assert "system" not in params