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# What does this PR do?
Fixes error:
```
[ERROR] Error executing endpoint route='/v1/openai/v1/responses'
method='post': Error code: 400 - {'error': {'message': "Invalid schema for function 'pods_exec': In context=('properties', 'command'), array
schema missing items.", 'type': 'invalid_request_error', 'param': 'tools[7].function.parameters', 'code': 'invalid_function_parameters'}}
```
From script:
```
#!/usr/bin/env python3
"""
Script to test Responses API with kubernetes-mcp-server.
This script:
1. Connects to the llama stack server
2. Uses the Responses API with MCP tools
3. Asks for the list of Kubernetes namespaces using the kubernetes-mcp-server
"""
import json
from openai import OpenAI
# Connect to the llama stack server
base_url = "http://localhost:8321/v1/openai/v1"
client = OpenAI(base_url=base_url, api_key="fake")
# Define the MCP tool pointing to the kubernetes-mcp-server
# The kubernetes-mcp-server is running on port 3000 with SSE endpoint at /sse
mcp_server_url = "http://localhost:3000/sse"
tools = [
{
"type": "mcp",
"server_label": "k8s",
"server_url": mcp_server_url,
}
]
# Create a response request asking for k8s namespaces
print("Sending request to list Kubernetes namespaces...")
print(f"Using MCP server at: {mcp_server_url}")
print("Available tools will be listed automatically by the MCP server.")
print()
response = client.responses.create(
# model="meta-llama/Llama-3.2-3B-Instruct", # Using the vllm model
model="openai/gpt-4o",
input="what are all the Kubernetes namespaces? Use tool call to `namespaces_list`. make sure to adhere to the tool calling format.",
tools=tools,
stream=False,
)
print("\n" + "=" * 80)
print("RESPONSE OUTPUT:")
print("=" * 80)
# Print the output
for i, output in enumerate(response.output):
print(f"\n[Output {i + 1}] Type: {output.type}")
if output.type == "mcp_list_tools":
print(f" Server: {output.server_label}")
print(f" Tools available: {[t.name for t in output.tools]}")
elif output.type == "mcp_call":
print(f" Tool called: {output.name}")
print(f" Arguments: {output.arguments}")
print(f" Result: {output.output}")
if output.error:
print(f" Error: {output.error}")
elif output.type == "message":
print(f" Role: {output.role}")
print(f" Content: {output.content}")
print("\n" + "=" * 80)
print("FINAL RESPONSE TEXT:")
print("=" * 80)
print(response.output_text)
```
## Test Plan
new unit tests
script now runs successfully
|
||
|---|---|---|
| .. | ||
| cli | ||
| distribution | ||
| files | ||
| models | ||
| prompts/prompts | ||
| providers | ||
| rag | ||
| registry | ||
| server | ||
| utils | ||
| __init__.py | ||
| conftest.py | ||
| fixtures.py | ||
| README.md | ||
Llama Stack Unit Tests
Unit Tests
Unit tests verify individual components and functions in isolation. They are fast, reliable, and don't require external services.
Prerequisites
- Python Environment: Ensure you have Python 3.12+ installed
- uv Package Manager: Install
uvif not already installed
You can run the unit tests by running:
./scripts/unit-tests.sh [PYTEST_ARGS]
Any additional arguments are passed to pytest. For example, you can specify a test directory, a specific test file, or any pytest flags (e.g., -vvv for verbosity). If no test directory is specified, it defaults to "tests/unit", e.g:
./scripts/unit-tests.sh tests/unit/registry/test_registry.py -vvv
If you'd like to run for a non-default version of Python (currently 3.12), pass PYTHON_VERSION variable as follows:
source .venv/bin/activate
PYTHON_VERSION=3.13 ./scripts/unit-tests.sh
Test Configuration
- Test Discovery: Tests are automatically discovered in the
tests/unit/directory - Async Support: Tests use
--asyncio-mode=autofor automatic async test handling - Coverage: Tests generate coverage reports in
htmlcov/directory - Python Version: Defaults to Python 3.12, but can be overridden with
PYTHON_VERSIONenvironment variable
Coverage Reports
After running tests, you can view coverage reports:
# Open HTML coverage report in browser
open htmlcov/index.html # macOS
xdg-open htmlcov/index.html # Linux
start htmlcov/index.html # Windows