mirror of
https://github.com/meta-llama/llama-stack.git
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fix: Fix max_tool_calls for openai provider and add integration tests for the max_tool_calls feat (#4190)
# Problem
OpenAI gpt-4 returned an error when built-in and mcp calls were skipped
due to max_tool_calls parameter. Following is from the server log:
```
RuntimeError: OpenAI response failed: Error code: 400 - {'error': {'message': "An assistant message with
'tool_calls' must be followed by tool messages responding to each 'tool_call_id'. The following tool_call_ids
did not have response messages: call_Yi9V1QNpN73dJCAgP2Arcjej", 'type': 'invalid_request_error', 'param':
'messages', 'code': None}}
```
# What does this PR do?
- Fixes error returned by openai/gpt when calls were skipped due to
max_tool_calls. We now return a tool message that explicitly mentions
that the call is skipped.
- Adds integration tests as a follow-up to
PR#[4062](https://github.com/llamastack/llama-stack/pull/4062)
<!-- If resolving an issue, uncomment and update the line below -->
Part 2 for issue
#[3563](https://github.com/llamastack/llama-stack/issues/3563)
## Test Plan
<!-- Describe the tests you ran to verify your changes with result
summaries. *Provide clear instructions so the plan can be easily
re-executed.* -->
- Added integration tests
- Added new recordings
---------
Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
This commit is contained in:
Shabana Baig
GitHub
parent
f18870a221
commit
72ea95e2e0
11 changed files with 8386 additions and 168 deletions
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@ -516,169 +516,3 @@ def test_response_with_instructions(openai_client, client_with_models, text_mode
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# Verify instructions from previous response was not carried over to the next response
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assert response_with_instructions2.instructions == instructions2
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@pytest.mark.skip(reason="Tool calling is not reliable.")
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def test_max_tool_calls_with_function_tools(openai_client, client_with_models, text_model_id):
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"""Test handling of max_tool_calls with function tools in responses."""
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if isinstance(client_with_models, LlamaStackAsLibraryClient):
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pytest.skip("OpenAI responses are not supported when testing with library client yet.")
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client = openai_client
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max_tool_calls = 1
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tools = [
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{
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"type": "function",
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"name": "get_weather",
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"description": "Get weather information for a specified location",
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"parameters": {
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"type": "object",
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"properties": {
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"location": {
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"type": "string",
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"description": "The city name (e.g., 'New York', 'London')",
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},
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},
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},
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},
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{
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"type": "function",
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"name": "get_time",
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"description": "Get current time for a specified location",
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"parameters": {
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"type": "object",
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"properties": {
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"location": {
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"type": "string",
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"description": "The city name (e.g., 'New York', 'London')",
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},
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},
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},
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},
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]
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# First create a response that triggers function tools
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response = client.responses.create(
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model=text_model_id,
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input="Can you tell me the weather in Paris and the current time?",
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tools=tools,
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stream=False,
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max_tool_calls=max_tool_calls,
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)
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# Verify we got two function calls and that the max_tool_calls do not affect function tools
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assert len(response.output) == 2
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assert response.output[0].type == "function_call"
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assert response.output[0].name == "get_weather"
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assert response.output[0].status == "completed"
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assert response.output[1].type == "function_call"
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assert response.output[1].name == "get_time"
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assert response.output[0].status == "completed"
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# Verify we have a valid max_tool_calls field
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assert response.max_tool_calls == max_tool_calls
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def test_max_tool_calls_invalid(openai_client, client_with_models, text_model_id):
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"""Test handling of invalid max_tool_calls in responses."""
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if isinstance(client_with_models, LlamaStackAsLibraryClient):
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pytest.skip("OpenAI responses are not supported when testing with library client yet.")
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client = openai_client
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input = "Search for today's top technology news."
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invalid_max_tool_calls = 0
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tools = [
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{"type": "web_search"},
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]
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# Create a response with an invalid max_tool_calls value i.e. 0
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# Handle ValueError from LLS and BadRequestError from OpenAI client
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with pytest.raises((ValueError, BadRequestError)) as excinfo:
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client.responses.create(
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model=text_model_id,
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input=input,
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tools=tools,
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stream=False,
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max_tool_calls=invalid_max_tool_calls,
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)
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error_message = str(excinfo.value)
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assert f"Invalid max_tool_calls={invalid_max_tool_calls}; should be >= 1" in error_message, (
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f"Expected error message about invalid max_tool_calls, got: {error_message}"
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)
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def test_max_tool_calls_with_builtin_tools(openai_client, client_with_models, text_model_id):
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"""Test handling of max_tool_calls with built-in tools in responses."""
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if isinstance(client_with_models, LlamaStackAsLibraryClient):
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pytest.skip("OpenAI responses are not supported when testing with library client yet.")
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client = openai_client
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input = "Search for today's top technology and a positive news story. You MUST make exactly two separate web search calls."
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max_tool_calls = [1, 5]
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tools = [
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{"type": "web_search"},
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]
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# First create a response that triggers web_search tools without max_tool_calls
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response = client.responses.create(
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model=text_model_id,
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input=input,
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tools=tools,
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stream=False,
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)
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# Verify we got two web search calls followed by a message
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assert len(response.output) == 3
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assert response.output[0].type == "web_search_call"
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assert response.output[0].status == "completed"
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assert response.output[1].type == "web_search_call"
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assert response.output[1].status == "completed"
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assert response.output[2].type == "message"
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assert response.output[2].status == "completed"
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assert response.output[2].role == "assistant"
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# Next create a response that triggers web_search tools with max_tool_calls set to 1
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response_2 = client.responses.create(
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model=text_model_id,
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input=input,
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tools=tools,
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stream=False,
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max_tool_calls=max_tool_calls[0],
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)
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# Verify we got one web search tool call followed by a message
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assert len(response_2.output) == 2
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assert response_2.output[0].type == "web_search_call"
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assert response_2.output[0].status == "completed"
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assert response_2.output[1].type == "message"
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assert response_2.output[1].status == "completed"
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assert response_2.output[1].role == "assistant"
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# Verify we have a valid max_tool_calls field
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assert response_2.max_tool_calls == max_tool_calls[0]
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# Finally create a response that triggers web_search tools with max_tool_calls set to 5
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response_3 = client.responses.create(
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model=text_model_id,
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input=input,
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tools=tools,
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stream=False,
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max_tool_calls=max_tool_calls[1],
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)
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# Verify we got two web search calls followed by a message
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assert len(response_3.output) == 3
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assert response_3.output[0].type == "web_search_call"
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assert response_3.output[0].status == "completed"
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assert response_3.output[1].type == "web_search_call"
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assert response_3.output[1].status == "completed"
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assert response_3.output[2].type == "message"
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assert response_3.output[2].status == "completed"
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assert response_3.output[2].role == "assistant"
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# Verify we have a valid max_tool_calls field
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assert response_3.max_tool_calls == max_tool_calls[1]
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@ -0,0 +1,773 @@
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{
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"test_id": "tests/integration/responses/test_tool_responses.py::test_max_tool_calls_with_mcp_tools[client_with_models-txt=openai/gpt-4o]",
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"request": {
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"method": "POST",
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"url": "https://api.openai.com/v1/v1/chat/completions",
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"headers": {},
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"body": {
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"model": "gpt-4o",
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"messages": [
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{
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"role": "user",
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"content": "Get the experiment ID for 'boiling_point' and get the user ID for 'charlie'"
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}
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],
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"stream": true,
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"stream_options": {
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"include_usage": true
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},
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"tools": [
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{
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"type": "function",
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"function": {
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"name": "get_user_id",
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"description": "\n Get the user ID for a given username. This ID is needed for other operations.\n\n :param username: The username to look up\n :return: The user ID for the username\n ",
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"parameters": {
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"properties": {
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"username": {
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"title": "Username",
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"type": "string"
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}
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},
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"required": [
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"username"
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],
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"title": "get_user_idArguments",
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"type": "object"
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}
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}
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},
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{
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"type": "function",
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"function": {
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"name": "get_user_permissions",
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"description": "\n Get the permissions for a user ID. Requires a valid user ID from get_user_id.\n\n :param user_id: The user ID to check permissions for\n :return: The permissions for the user\n ",
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"parameters": {
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"properties": {
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"user_id": {
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"title": "User Id",
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"type": "string"
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}
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},
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"required": [
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"user_id"
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],
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"title": "get_user_permissionsArguments",
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"type": "object"
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}
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}
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},
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{
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"type": "function",
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"function": {
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"name": "check_file_access",
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"description": "\n Check if a user can access a specific file. Requires a valid user ID.\n\n :param user_id: The user ID to check access for\n :param filename: The filename to check access to\n :return: Whether the user can access the file (yes/no)\n ",
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"parameters": {
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"properties": {
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"user_id": {
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"title": "User Id",
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"type": "string"
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},
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"filename": {
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"title": "Filename",
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"type": "string"
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}
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},
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"required": [
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"user_id",
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"filename"
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],
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"title": "check_file_accessArguments",
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"type": "object"
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}
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}
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},
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{
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"type": "function",
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"function": {
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"name": "get_experiment_id",
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"description": "\n Get the experiment ID for a given experiment name. This ID is needed to get results.\n\n :param experiment_name: The name of the experiment\n :return: The experiment ID\n ",
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"parameters": {
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"properties": {
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"experiment_name": {
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"title": "Experiment Name",
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"type": "string"
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}
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},
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"required": [
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"experiment_name"
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],
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"title": "get_experiment_idArguments",
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"type": "object"
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}
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}
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},
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{
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"type": "function",
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"function": {
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"name": "get_experiment_results",
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"description": "\n Get the results for an experiment ID. Requires a valid experiment ID from get_experiment_id.\n\n :param experiment_id: The experiment ID to get results for\n :return: The experiment results\n ",
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"parameters": {
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"properties": {
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"experiment_id": {
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"title": "Experiment Id",
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"type": "string"
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}
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},
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"required": [
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"experiment_id"
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],
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"title": "get_experiment_resultsArguments",
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"type": "object"
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}
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}
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}
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]
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},
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"endpoint": "/v1/chat/completions",
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"model": "gpt-4o"
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},
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"response": {
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"body": [
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{
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"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
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"function_call": null,
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"refusal": null,
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"role": "assistant",
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"tool_calls": null
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},
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"finish_reason": null,
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"index": 0,
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"logprobs": null
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}
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],
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"created": 0,
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"model": "gpt-4o-2024-08-06",
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"object": "chat.completion.chunk",
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"service_tier": "default",
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"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
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"id": "rec-1997dc007d20",
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|
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{
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"id": null,
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},
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}
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]
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},
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"finish_reason": null,
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"index": 0,
|
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"logprobs": null
|
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}
|
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],
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"created": 0,
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1634
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"object": "chat.completion.chunk",
|
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"service_tier": "default",
|
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"system_fingerprint": "fp_b1442291a8",
|
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"usage": null,
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"obfuscation": "LQo"
|
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}
|
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},
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{
|
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"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
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"__data__": {
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"id": "rec-d073f434d28c",
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"choices": [
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{
|
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"delta": {
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"function_call": null,
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"refusal": null,
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"role": null,
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"tool_calls": [
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{
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"index": 1,
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"id": "call_8xkOmOgJpV77n5W2dSx6ytW6",
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"function": {
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"arguments": "",
|
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"name": "get_time"
|
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},
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"type": "function"
|
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}
|
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]
|
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},
|
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"finish_reason": null,
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"index": 0,
|
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"logprobs": null
|
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}
|
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],
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"created": 0,
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"model": "gpt-4o-2024-08-06",
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"object": "chat.completion.chunk",
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"service_tier": "default",
|
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"system_fingerprint": "fp_b1442291a8",
|
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"usage": null,
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"obfuscation": "eltoncGlxI8Go"
|
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}
|
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},
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{
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"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
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"__data__": {
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"id": "rec-d073f434d28c",
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"choices": [
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{
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"delta": {
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"content": null,
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"function_call": null,
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"refusal": null,
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"role": null,
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"tool_calls": [
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{
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"index": 1,
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"id": null,
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"function": {
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"arguments": "{\"lo",
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"name": null
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},
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"type": null
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}
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]
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},
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"finish_reason": null,
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"index": 0,
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"logprobs": null
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}
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],
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"created": 0,
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"model": "gpt-4o-2024-08-06",
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"object": "chat.completion.chunk",
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"service_tier": "default",
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"system_fingerprint": "fp_b1442291a8",
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"usage": null,
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"obfuscation": "S"
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}
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},
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{
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"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
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"__data__": {
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"id": "rec-d073f434d28c",
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"choices": [
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{
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"delta": {
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"content": null,
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"function_call": null,
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"refusal": null,
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"role": null,
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"tool_calls": [
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{
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"index": 1,
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"id": null,
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"function": {
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"arguments": "catio",
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"name": null
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},
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"type": null
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}
|
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]
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},
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"finish_reason": null,
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"index": 0,
|
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"logprobs": null
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}
|
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],
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"created": 0,
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"model": "gpt-4o-2024-08-06",
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"object": "chat.completion.chunk",
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"service_tier": "default",
|
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"system_fingerprint": "fp_b1442291a8",
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"usage": null,
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"obfuscation": "N"
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}
|
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},
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{
|
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"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
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"__data__": {
|
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"id": "rec-d073f434d28c",
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"choices": [
|
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{
|
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"delta": {
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"content": null,
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"function_call": null,
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"refusal": null,
|
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"role": null,
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"tool_calls": [
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{
|
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"index": 1,
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"id": null,
|
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"function": {
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"arguments": "n\": \"P",
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"name": null
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},
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"type": null
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}
|
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]
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},
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"finish_reason": null,
|
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"index": 0,
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"logprobs": null
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}
|
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],
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"created": 0,
|
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"model": "gpt-4o-2024-08-06",
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"object": "chat.completion.chunk",
|
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"service_tier": "default",
|
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"system_fingerprint": "fp_b1442291a8",
|
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"usage": null,
|
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"obfuscation": "2bTn1MaAXYFoVK"
|
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}
|
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},
|
||||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-d073f434d28c",
|
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"choices": [
|
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{
|
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"delta": {
|
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"content": null,
|
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"function_call": null,
|
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"refusal": null,
|
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"role": null,
|
||||
"tool_calls": [
|
||||
{
|
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"index": 1,
|
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"id": null,
|
||||
"function": {
|
||||
"arguments": "aris",
|
||||
"name": null
|
||||
},
|
||||
"type": null
|
||||
}
|
||||
]
|
||||
},
|
||||
"finish_reason": null,
|
||||
"index": 0,
|
||||
"logprobs": null
|
||||
}
|
||||
],
|
||||
"created": 0,
|
||||
"model": "gpt-4o-2024-08-06",
|
||||
"object": "chat.completion.chunk",
|
||||
"service_tier": "default",
|
||||
"system_fingerprint": "fp_b1442291a8",
|
||||
"usage": null,
|
||||
"obfuscation": "VF"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-d073f434d28c",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
"content": null,
|
||||
"function_call": null,
|
||||
"refusal": null,
|
||||
"role": null,
|
||||
"tool_calls": [
|
||||
{
|
||||
"index": 1,
|
||||
"id": null,
|
||||
"function": {
|
||||
"arguments": "\"}",
|
||||
"name": null
|
||||
},
|
||||
"type": null
|
||||
}
|
||||
]
|
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},
|
||||
"finish_reason": null,
|
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"index": 0,
|
||||
"logprobs": null
|
||||
}
|
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],
|
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"created": 0,
|
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"model": "gpt-4o-2024-08-06",
|
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"object": "chat.completion.chunk",
|
||||
"service_tier": "default",
|
||||
"system_fingerprint": "fp_b1442291a8",
|
||||
"usage": null,
|
||||
"obfuscation": "BHi"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
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"id": "rec-d073f434d28c",
|
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"choices": [
|
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{
|
||||
"delta": {
|
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"content": null,
|
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"function_call": null,
|
||||
"refusal": null,
|
||||
"role": null,
|
||||
"tool_calls": null
|
||||
},
|
||||
"finish_reason": "tool_calls",
|
||||
"index": 0,
|
||||
"logprobs": null
|
||||
}
|
||||
],
|
||||
"created": 0,
|
||||
"model": "gpt-4o-2024-08-06",
|
||||
"object": "chat.completion.chunk",
|
||||
"service_tier": "default",
|
||||
"system_fingerprint": "fp_b1442291a8",
|
||||
"usage": null,
|
||||
"obfuscation": "WaYG"
|
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}
|
||||
},
|
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{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
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"__data__": {
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"id": "rec-d073f434d28c",
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"choices": [],
|
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"created": 0,
|
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"model": "gpt-4o-2024-08-06",
|
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"object": "chat.completion.chunk",
|
||||
"service_tier": "default",
|
||||
"system_fingerprint": "fp_b1442291a8",
|
||||
"usage": {
|
||||
"completion_tokens": 44,
|
||||
"prompt_tokens": 110,
|
||||
"total_tokens": 154,
|
||||
"completion_tokens_details": {
|
||||
"accepted_prediction_tokens": 0,
|
||||
"audio_tokens": 0,
|
||||
"reasoning_tokens": 0,
|
||||
"rejected_prediction_tokens": 0
|
||||
},
|
||||
"prompt_tokens_details": {
|
||||
"audio_tokens": 0,
|
||||
"cached_tokens": 0
|
||||
}
|
||||
},
|
||||
"obfuscation": "aevj6ZWLqfCK6"
|
||||
}
|
||||
}
|
||||
],
|
||||
"is_streaming": true
|
||||
},
|
||||
"id_normalization_mapping": {}
|
||||
}
|
||||
1661
tests/integration/responses/recordings/e3e2e64c57bb36f2a6ba5f68410d0b947d35c870ff825f06d8997a84dca1f5bf.json
generated
Normal file
1661
tests/integration/responses/recordings/e3e2e64c57bb36f2a6ba5f68410d0b947d35c870ff825f06d8997a84dca1f5bf.json
generated
Normal file
File diff suppressed because it is too large
Load diff
|
|
@ -600,3 +600,155 @@ def test_response_streaming_multi_turn_tool_execution(responses_client, text_mod
|
|||
assert expected_output.lower() in final_response.output_text.lower(), (
|
||||
f"Expected '{expected_output}' to appear in response: {final_response.output_text}"
|
||||
)
|
||||
|
||||
|
||||
def test_max_tool_calls_with_function_tools(responses_client, text_model_id):
|
||||
"""Test handling of max_tool_calls with function tools in responses."""
|
||||
|
||||
max_tool_calls = 1
|
||||
tools = [
|
||||
{
|
||||
"type": "function",
|
||||
"name": "get_weather",
|
||||
"description": "Get weather information for a specified location",
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"location": {
|
||||
"type": "string",
|
||||
"description": "The city name (e.g., 'New York', 'London')",
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
{
|
||||
"type": "function",
|
||||
"name": "get_time",
|
||||
"description": "Get current time for a specified location",
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"location": {
|
||||
"type": "string",
|
||||
"description": "The city name (e.g., 'New York', 'London')",
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
]
|
||||
|
||||
response = responses_client.responses.create(
|
||||
model=text_model_id,
|
||||
input="Can you tell me the weather in Paris and the current time?",
|
||||
tools=tools,
|
||||
stream=False,
|
||||
max_tool_calls=max_tool_calls,
|
||||
)
|
||||
|
||||
# Verify we got two function calls and that the max_tool_calls does not affect function tools
|
||||
assert len(response.output) == 2
|
||||
assert response.output[0].type == "function_call"
|
||||
assert response.output[0].name == "get_weather"
|
||||
assert response.output[0].status == "completed"
|
||||
assert response.output[1].type == "function_call"
|
||||
assert response.output[1].name == "get_time"
|
||||
assert response.output[1].status == "completed"
|
||||
|
||||
# Verify we have a valid max_tool_calls field
|
||||
assert response.max_tool_calls == max_tool_calls
|
||||
|
||||
|
||||
def test_max_tool_calls_invalid(responses_client, text_model_id):
|
||||
"""Test handling of invalid max_tool_calls in responses."""
|
||||
|
||||
input = "Search for today's top technology news."
|
||||
invalid_max_tool_calls = 0
|
||||
tools = [
|
||||
{"type": "web_search"},
|
||||
]
|
||||
|
||||
# Create a response with an invalid max_tool_calls value i.e. 0
|
||||
# Handle ValueError from LLS and BadRequestError from OpenAI client
|
||||
with pytest.raises((ValueError, llama_stack_client.BadRequestError, openai.BadRequestError)) as excinfo:
|
||||
responses_client.responses.create(
|
||||
model=text_model_id,
|
||||
input=input,
|
||||
tools=tools,
|
||||
stream=False,
|
||||
max_tool_calls=invalid_max_tool_calls,
|
||||
)
|
||||
|
||||
error_message = str(excinfo.value)
|
||||
assert f"Invalid max_tool_calls={invalid_max_tool_calls}; should be >= 1" in error_message, (
|
||||
f"Expected error message about invalid max_tool_calls, got: {error_message}"
|
||||
)
|
||||
|
||||
|
||||
def test_max_tool_calls_with_mcp_tools(responses_client, text_model_id):
|
||||
"""Test handling of max_tool_calls with mcp tools in responses."""
|
||||
|
||||
with make_mcp_server(tools=dependency_tools()) as mcp_server_info:
|
||||
input = "Get the experiment ID for 'boiling_point' and get the user ID for 'charlie'"
|
||||
max_tool_calls = [1, 5]
|
||||
tools = [
|
||||
{"type": "mcp", "server_label": "localmcp", "server_url": mcp_server_info["server_url"]},
|
||||
]
|
||||
|
||||
# First create a response that triggers mcp tools without max_tool_calls
|
||||
response = responses_client.responses.create(
|
||||
model=text_model_id,
|
||||
input=input,
|
||||
tools=tools,
|
||||
stream=False,
|
||||
)
|
||||
|
||||
# Verify we got two mcp tool calls followed by a message
|
||||
assert len(response.output) == 4
|
||||
mcp_list_tools = [output for output in response.output if output.type == "mcp_list_tools"]
|
||||
mcp_calls = [output for output in response.output if output.type == "mcp_call"]
|
||||
message_outputs = [output for output in response.output if output.type == "message"]
|
||||
assert len(mcp_list_tools) == 1
|
||||
assert len(mcp_calls) == 2, f"Expected two mcp calls, got {len(mcp_calls)}"
|
||||
assert len(message_outputs) == 1, f"Expected one message output, got {len(message_outputs)}"
|
||||
|
||||
# Next create a response that triggers mcp tools with max_tool_calls set to 1
|
||||
response_2 = responses_client.responses.create(
|
||||
model=text_model_id,
|
||||
input=input,
|
||||
tools=tools,
|
||||
stream=False,
|
||||
max_tool_calls=max_tool_calls[0],
|
||||
)
|
||||
|
||||
# Verify we got one mcp tool call followed by a message
|
||||
assert len(response_2.output) == 3
|
||||
mcp_list_tools = [output for output in response_2.output if output.type == "mcp_list_tools"]
|
||||
mcp_calls = [output for output in response_2.output if output.type == "mcp_call"]
|
||||
message_outputs = [output for output in response_2.output if output.type == "message"]
|
||||
assert len(mcp_list_tools) == 1
|
||||
assert len(mcp_calls) == 1, f"Expected one mcp call, got {len(mcp_calls)}"
|
||||
assert len(message_outputs) == 1, f"Expected one message output, got {len(message_outputs)}"
|
||||
|
||||
# Verify we have a valid max_tool_calls field
|
||||
assert response_2.max_tool_calls == max_tool_calls[0]
|
||||
|
||||
# Finally create a response that triggers mcp tools with max_tool_calls set to 5
|
||||
response_3 = responses_client.responses.create(
|
||||
model=text_model_id,
|
||||
input=input,
|
||||
tools=tools,
|
||||
stream=False,
|
||||
max_tool_calls=max_tool_calls[1],
|
||||
)
|
||||
|
||||
# Verify we got two mcp tool calls followed by a message
|
||||
assert len(response_3.output) == 4
|
||||
mcp_list_tools = [output for output in response_3.output if output.type == "mcp_list_tools"]
|
||||
mcp_calls = [output for output in response_3.output if output.type == "mcp_call"]
|
||||
message_outputs = [output for output in response_3.output if output.type == "message"]
|
||||
assert len(mcp_list_tools) == 1
|
||||
assert len(mcp_calls) == 2, f"Expected two mcp calls, got {len(mcp_calls)}"
|
||||
assert len(message_outputs) == 1, f"Expected one message output, got {len(message_outputs)}"
|
||||
|
||||
# Verify we have a valid max_tool_calls field
|
||||
assert response_3.max_tool_calls == max_tool_calls[1]
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue