mirror of
https://github.com/BerriAI/litellm.git
synced 2026-10-08 03:08:45 +00:00
Add: missing anthropic tool results
This commit is contained in:
Sameer Kankute
parent
dd299c93c2
commit
3c1ffda117
3 changed files with 282 additions and 24 deletions
|
|
@ -719,19 +719,28 @@ class ModelResponseIterator:
|
|||
content_block_start=content_block_start,
|
||||
provider_specific_fields=provider_specific_fields,
|
||||
)
|
||||
elif (
|
||||
content_block_start["content_block"]["type"]
|
||||
== "web_search_tool_result"
|
||||
):
|
||||
# Capture web_search_tool_result for multi-turn reconstruction
|
||||
# The full content comes in content_block_start, not in deltas
|
||||
# See: https://github.com/BerriAI/litellm/issues/17737
|
||||
self.web_search_results.append(
|
||||
content_block_start["content_block"]
|
||||
)
|
||||
provider_specific_fields["web_search_results"] = (
|
||||
self.web_search_results
|
||||
)
|
||||
elif content_block_start["content_block"]["type"].endswith("_tool_result"):
|
||||
# Handle all tool result types (web_search, bash_code_execution, text_editor, etc.)
|
||||
content_type = content_block_start["content_block"]["type"]
|
||||
|
||||
# Special handling for web_search_tool_result for backwards compatibility
|
||||
if content_type == "web_search_tool_result":
|
||||
# Capture web_search_tool_result for multi-turn reconstruction
|
||||
# The full content comes in content_block_start, not in deltas
|
||||
# See: https://github.com/BerriAI/litellm/issues/17737
|
||||
self.web_search_results.append(
|
||||
content_block_start["content_block"]
|
||||
)
|
||||
provider_specific_fields["web_search_results"] = (
|
||||
self.web_search_results
|
||||
)
|
||||
elif content_type != "tool_search_tool_result":
|
||||
# Handle other tool results (code execution, etc.)
|
||||
# Skip tool_search_tool_result as it's internal metadata
|
||||
if not hasattr(self, "tool_results"):
|
||||
self.tool_results = []
|
||||
self.tool_results.append(content_block_start["content_block"])
|
||||
provider_specific_fields["tool_results"] = self.tool_results
|
||||
elif type_chunk == "content_block_stop":
|
||||
ContentBlockStop(**chunk) # type: ignore
|
||||
# check if tool call content block - only for tool_use and server_tool_use blocks
|
||||
|
|
|
|||
|
|
@ -1131,6 +1131,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
|
|||
Optional[str],
|
||||
List[ChatCompletionToolCallChunk],
|
||||
Optional[List[Any]],
|
||||
Optional[List[Any]],
|
||||
]:
|
||||
text_content = ""
|
||||
citations: Optional[List[Any]] = None
|
||||
|
|
@ -1142,6 +1143,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
|
|||
reasoning_content: Optional[str] = None
|
||||
tool_calls: List[ChatCompletionToolCallChunk] = []
|
||||
web_search_results: Optional[List[Any]] = None
|
||||
tool_results: Optional[List[Any]] = None
|
||||
for idx, content in enumerate(completion_response["content"]):
|
||||
if content["type"] == "text":
|
||||
text_content += content["text"]
|
||||
|
|
@ -1152,16 +1154,21 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
|
|||
index=idx,
|
||||
)
|
||||
tool_calls.append(tool_call)
|
||||
## TOOL SEARCH TOOL RESULT (skip - this is metadata about tool discovery)
|
||||
elif content["type"] == "tool_search_tool_result":
|
||||
# This block contains tool_references that were discovered
|
||||
# We don't need to include this in the response as it's internal metadata
|
||||
pass
|
||||
## WEB SEARCH TOOL RESULT - preserve web search results for multi-turn conversations
|
||||
elif content["type"] == "web_search_tool_result":
|
||||
if web_search_results is None:
|
||||
web_search_results = []
|
||||
web_search_results.append(content)
|
||||
## TOOL RESULTS - handle all tool result types (code execution, etc.)
|
||||
elif content["type"].endswith("_tool_result"):
|
||||
# Skip tool_search_tool_result as it's internal metadata
|
||||
if content["type"] == "tool_search_tool_result":
|
||||
continue
|
||||
# Handle web_search_tool_result separately for backwards compatibility
|
||||
if content["type"] == "web_search_tool_result":
|
||||
if web_search_results is None:
|
||||
web_search_results = []
|
||||
web_search_results.append(content)
|
||||
else:
|
||||
# All other tool results (bash_code_execution_tool_result, text_editor_code_execution_tool_result, etc.)
|
||||
if tool_results is None:
|
||||
tool_results = []
|
||||
tool_results.append(content)
|
||||
elif content.get("thinking", None) is not None:
|
||||
if thinking_blocks is None:
|
||||
thinking_blocks = []
|
||||
|
|
@ -1193,7 +1200,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
|
|||
if thinking_content is not None:
|
||||
reasoning_content += thinking_content
|
||||
|
||||
return text_content, citations, thinking_blocks, reasoning_content, tool_calls, web_search_results
|
||||
return text_content, citations, thinking_blocks, reasoning_content, tool_calls, web_search_results, tool_results
|
||||
|
||||
def calculate_usage(
|
||||
self,
|
||||
|
|
@ -1335,6 +1342,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
|
|||
reasoning_content,
|
||||
tool_calls,
|
||||
web_search_results,
|
||||
tool_results,
|
||||
) = self.extract_response_content(completion_response=completion_response)
|
||||
|
||||
if (
|
||||
|
|
@ -1358,6 +1366,8 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
|
|||
provider_specific_fields["context_management"] = context_management
|
||||
if web_search_results is not None:
|
||||
provider_specific_fields["web_search_results"] = web_search_results
|
||||
if tool_results is not None:
|
||||
provider_specific_fields["tool_results"] = tool_results
|
||||
if container is not None:
|
||||
provider_specific_fields["container"] = container
|
||||
|
||||
|
|
|
|||
|
|
@ -1812,3 +1812,242 @@ def test_calculate_usage_completion_tokens_details_with_reasoning():
|
|||
expected_text_tokens = 500 - usage.completion_tokens_details.reasoning_tokens
|
||||
assert usage.completion_tokens_details.text_tokens == expected_text_tokens
|
||||
assert usage.completion_tokens == 500
|
||||
|
||||
|
||||
def test_code_execution_tool_results_extraction():
|
||||
"""
|
||||
Test that code execution tool results (bash_code_execution_tool_result,
|
||||
text_editor_code_execution_tool_result) are properly extracted and exposed
|
||||
in provider_specific_fields.
|
||||
|
||||
Related to: https://github.com/BerriAI/litellm/issues/xxxxx
|
||||
"""
|
||||
import httpx
|
||||
from litellm.types.utils import ModelResponse
|
||||
|
||||
config = AnthropicConfig()
|
||||
|
||||
# Mock Anthropic response with code execution tool results
|
||||
mock_anthropic_response = {
|
||||
"id": "msg_01XYZ",
|
||||
"type": "message",
|
||||
"role": "assistant",
|
||||
"model": "claude-sonnet-4-5-20250929",
|
||||
"content": [
|
||||
{
|
||||
"type": "text",
|
||||
"text": "I'll calculate that for you."
|
||||
},
|
||||
{
|
||||
"type": "server_tool_use",
|
||||
"id": "srvtoolu_01ABC",
|
||||
"name": "bash_code_execution",
|
||||
"input": {
|
||||
"command": "python3 << 'EOF'\nprint(2 + 2)\nEOF\n"
|
||||
}
|
||||
},
|
||||
{
|
||||
"type": "bash_code_execution_tool_result",
|
||||
"tool_use_id": "srvtoolu_01ABC",
|
||||
"content": {
|
||||
"type": "bash_code_execution_result",
|
||||
"stdout": "4\n",
|
||||
"stderr": "",
|
||||
"return_code": 0
|
||||
}
|
||||
},
|
||||
{
|
||||
"type": "server_tool_use",
|
||||
"id": "srvtoolu_01DEF",
|
||||
"name": "text_editor_code_execution",
|
||||
"input": {
|
||||
"command": "create",
|
||||
"path": "test.txt",
|
||||
"file_text": "Hello"
|
||||
}
|
||||
},
|
||||
{
|
||||
"type": "text_editor_code_execution_tool_result",
|
||||
"tool_use_id": "srvtoolu_01DEF",
|
||||
"content": {
|
||||
"type": "text_editor_code_execution_result",
|
||||
"is_file_update": False
|
||||
}
|
||||
},
|
||||
{
|
||||
"type": "text",
|
||||
"text": "Done!"
|
||||
}
|
||||
],
|
||||
"stop_reason": "stop",
|
||||
"stop_sequence": None,
|
||||
"usage": {
|
||||
"input_tokens": 100,
|
||||
"output_tokens": 50
|
||||
}
|
||||
}
|
||||
|
||||
# Create mock HTTP response
|
||||
mock_raw_response = MagicMock(spec=httpx.Response)
|
||||
mock_raw_response.json.return_value = mock_anthropic_response
|
||||
mock_raw_response.status_code = 200
|
||||
mock_raw_response.headers = {}
|
||||
|
||||
model_response = ModelResponse()
|
||||
|
||||
transformed_response = config.transform_parsed_response(
|
||||
completion_response=mock_anthropic_response,
|
||||
raw_response=mock_raw_response,
|
||||
model_response=model_response,
|
||||
json_mode=False,
|
||||
prefix_prompt=None,
|
||||
)
|
||||
|
||||
# Verify tool calls are present
|
||||
assert transformed_response.choices[0].message.tool_calls is not None
|
||||
assert len(transformed_response.choices[0].message.tool_calls) == 2
|
||||
|
||||
# Verify first tool call
|
||||
assert transformed_response.choices[0].message.tool_calls[0].id == "srvtoolu_01ABC"
|
||||
assert transformed_response.choices[0].message.tool_calls[0].function.name == "bash_code_execution"
|
||||
|
||||
# Verify second tool call
|
||||
assert transformed_response.choices[0].message.tool_calls[1].id == "srvtoolu_01DEF"
|
||||
assert transformed_response.choices[0].message.tool_calls[1].function.name == "text_editor_code_execution"
|
||||
|
||||
# Verify tool results are in provider_specific_fields
|
||||
provider_fields = transformed_response.choices[0].message.provider_specific_fields
|
||||
assert provider_fields is not None
|
||||
assert "tool_results" in provider_fields
|
||||
assert provider_fields["tool_results"] is not None
|
||||
assert len(provider_fields["tool_results"]) == 2
|
||||
|
||||
# Verify bash_code_execution_tool_result
|
||||
bash_result = provider_fields["tool_results"][0]
|
||||
assert bash_result["type"] == "bash_code_execution_tool_result"
|
||||
assert bash_result["tool_use_id"] == "srvtoolu_01ABC"
|
||||
assert bash_result["content"]["stdout"] == "4\n"
|
||||
assert bash_result["content"]["return_code"] == 0
|
||||
|
||||
# Verify text_editor_code_execution_tool_result
|
||||
editor_result = provider_fields["tool_results"][1]
|
||||
assert editor_result["type"] == "text_editor_code_execution_tool_result"
|
||||
assert editor_result["tool_use_id"] == "srvtoolu_01DEF"
|
||||
assert editor_result["content"]["is_file_update"] is False
|
||||
|
||||
# Verify text content is properly concatenated
|
||||
assert "I'll calculate that for you." in transformed_response.choices[0].message.content
|
||||
assert "Done!" in transformed_response.choices[0].message.content
|
||||
|
||||
|
||||
def test_tool_search_tool_result_not_in_tool_results():
|
||||
"""
|
||||
Test that tool_search_tool_result is NOT included in tool_results
|
||||
since it's internal metadata, not actual tool execution results.
|
||||
"""
|
||||
import httpx
|
||||
from litellm.types.utils import ModelResponse
|
||||
|
||||
config = AnthropicConfig()
|
||||
|
||||
mock_anthropic_response = {
|
||||
"id": "msg_01XYZ",
|
||||
"type": "message",
|
||||
"role": "assistant",
|
||||
"model": "claude-sonnet-4-5-20250929",
|
||||
"content": [
|
||||
{
|
||||
"type": "text",
|
||||
"text": "Found tools."
|
||||
},
|
||||
{
|
||||
"type": "tool_search_tool_result",
|
||||
"tool_references": ["tool1", "tool2"]
|
||||
}
|
||||
],
|
||||
"stop_reason": "stop",
|
||||
"stop_sequence": None,
|
||||
"usage": {
|
||||
"input_tokens": 100,
|
||||
"output_tokens": 50
|
||||
}
|
||||
}
|
||||
|
||||
mock_raw_response = MagicMock(spec=httpx.Response)
|
||||
mock_raw_response.json.return_value = mock_anthropic_response
|
||||
mock_raw_response.status_code = 200
|
||||
mock_raw_response.headers = {}
|
||||
|
||||
model_response = ModelResponse()
|
||||
|
||||
transformed_response = config.transform_parsed_response(
|
||||
completion_response=mock_anthropic_response,
|
||||
raw_response=mock_raw_response,
|
||||
model_response=model_response,
|
||||
json_mode=False,
|
||||
prefix_prompt=None,
|
||||
)
|
||||
|
||||
# Verify tool_search_tool_result is NOT in tool_results
|
||||
provider_fields = transformed_response.choices[0].message.provider_specific_fields
|
||||
assert provider_fields.get("tool_results") is None
|
||||
|
||||
|
||||
def test_web_search_tool_result_backwards_compatibility():
|
||||
"""
|
||||
Test that web_search_tool_result continues to be stored in web_search_results
|
||||
for backwards compatibility, not in tool_results.
|
||||
"""
|
||||
import httpx
|
||||
from litellm.types.utils import ModelResponse
|
||||
|
||||
config = AnthropicConfig()
|
||||
|
||||
mock_anthropic_response = {
|
||||
"id": "msg_01XYZ",
|
||||
"type": "message",
|
||||
"role": "assistant",
|
||||
"model": "claude-sonnet-4-5-20250929",
|
||||
"content": [
|
||||
{
|
||||
"type": "text",
|
||||
"text": "Here are the results."
|
||||
},
|
||||
{
|
||||
"type": "web_search_tool_result",
|
||||
"search_query": "test query",
|
||||
"results": [{"title": "Result 1", "url": "https://example.com"}]
|
||||
}
|
||||
],
|
||||
"stop_reason": "stop",
|
||||
"stop_sequence": None,
|
||||
"usage": {
|
||||
"input_tokens": 100,
|
||||
"output_tokens": 50
|
||||
}
|
||||
}
|
||||
|
||||
mock_raw_response = MagicMock(spec=httpx.Response)
|
||||
mock_raw_response.json.return_value = mock_anthropic_response
|
||||
mock_raw_response.status_code = 200
|
||||
mock_raw_response.headers = {}
|
||||
|
||||
model_response = ModelResponse()
|
||||
|
||||
transformed_response = config.transform_parsed_response(
|
||||
completion_response=mock_anthropic_response,
|
||||
raw_response=mock_raw_response,
|
||||
model_response=model_response,
|
||||
json_mode=False,
|
||||
prefix_prompt=None,
|
||||
)
|
||||
|
||||
# Verify web_search_tool_result is in web_search_results (not tool_results)
|
||||
provider_fields = transformed_response.choices[0].message.provider_specific_fields
|
||||
assert "web_search_results" in provider_fields
|
||||
assert provider_fields["web_search_results"] is not None
|
||||
assert len(provider_fields["web_search_results"]) == 1
|
||||
assert provider_fields["web_search_results"][0]["type"] == "web_search_tool_result"
|
||||
|
||||
# Should NOT be in tool_results
|
||||
assert provider_fields.get("tool_results") is None
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue