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feat: Add items and title to ToolParameter/ToolParamDefinition (#3003)
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# What does this PR do? <!-- Provide a short summary of what this PR does and why. Link to relevant issues if applicable. --> Add items and title to ToolParameter/ToolParamDefinition. Adding items will resolve the issue that occurs with Gemini LLM when an MCP tool has array-type properties. <!-- If resolving an issue, uncomment and update the line below --> <!-- Closes #[issue-number] --> ## 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.* --> Unite test cases will be added. --------- Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Kai Wu <kaiwu@meta.com> Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
This commit is contained in:
Tami Takamiya
GitHub
parent
1a8d3ed315
commit
65f7b81e98
16 changed files with 1835 additions and 9 deletions
33
docs/static/llama-stack-spec.html
vendored
33
docs/static/llama-stack-spec.html
vendored
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@ -6783,6 +6783,31 @@
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"type": "boolean",
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"default": true
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},
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"items": {
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"oneOf": [
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{
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"type": "null"
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},
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{
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"type": "boolean"
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},
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{
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"type": "number"
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},
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{
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"type": "string"
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},
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{
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"type": "array"
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},
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{
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"type": "object"
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}
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]
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},
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"title": {
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"type": "string"
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},
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"default": {
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"oneOf": [
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{
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@ -7457,6 +7482,14 @@
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"default": true,
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"description": "Whether this parameter is required for tool invocation"
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},
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"items": {
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"type": "object",
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"description": "Type of the elements when parameter_type is array"
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},
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"title": {
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"type": "string",
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"description": "(Optional) Title of the parameter"
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},
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"default": {
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"oneOf": [
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{
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17
docs/static/llama-stack-spec.yaml
vendored
17
docs/static/llama-stack-spec.yaml
vendored
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@ -4866,6 +4866,16 @@ components:
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required:
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type: boolean
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default: true
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items:
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oneOf:
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- type: 'null'
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- type: boolean
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- type: number
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- type: string
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- type: array
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- type: object
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title:
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type: string
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default:
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oneOf:
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- type: 'null'
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@ -5403,6 +5413,13 @@ components:
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default: true
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description: >-
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Whether this parameter is required for tool invocation
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items:
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type: object
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description: >-
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Type of the elements when parameter_type is array
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title:
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type: string
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description: (Optional) Title of the parameter
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default:
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oneOf:
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- type: 'null'
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@ -27,6 +27,8 @@ class ToolParameter(BaseModel):
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:param parameter_type: Type of the parameter (e.g., string, integer)
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:param description: Human-readable description of what the parameter does
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:param required: Whether this parameter is required for tool invocation
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:param items: Type of the elements when parameter_type is array
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:param title: (Optional) Title of the parameter
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:param default: (Optional) Default value for the parameter if not provided
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"""
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@ -34,6 +36,8 @@ class ToolParameter(BaseModel):
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parameter_type: str
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description: str
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required: bool = Field(default=True)
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items: dict | None = None
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title: str | None = None
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default: Any | None = None
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@ -92,6 +92,8 @@ class ToolParamDefinition(BaseModel):
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param_type: str
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description: str | None = None
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required: bool | None = True
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items: Any | None = None
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title: str | None = None
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default: Any | None = None
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@ -798,6 +798,8 @@ class ChatAgent(ShieldRunnerMixin):
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param_type=param.parameter_type,
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description=param.description,
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required=param.required,
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items=param.items,
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title=param.title,
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default=param.default,
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)
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for param in tool_def.parameters
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@ -841,6 +843,8 @@ class ChatAgent(ShieldRunnerMixin):
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param_type=param.parameter_type,
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description=param.description,
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required=param.required,
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items=param.items,
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title=param.title,
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default=param.default,
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)
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for param in tool_def.parameters
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@ -805,6 +805,10 @@ def convert_tooldef_to_openai_tool(tool: ToolDefinition) -> dict:
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properties[param_name].update(description=param.description)
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if param.default:
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properties[param_name].update(default=param.default)
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if param.items:
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properties[param_name].update(items=param.items)
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if param.title:
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properties[param_name].update(title=param.title)
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if param.required:
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required.append(param_name)
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@ -120,6 +120,10 @@ async def list_mcp_tools(endpoint: str, headers: dict[str, str]) -> ListToolDefs
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name=param_name,
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parameter_type=param_schema.get("type", "string"),
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description=param_schema.get("description", ""),
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required="default" not in param_schema,
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items=param_schema.get("items", None),
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title=param_schema.get("title", None),
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default=param_schema.get("default", None),
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)
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)
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tools.append(
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@ -167,6 +167,8 @@ def make_mcp_server(required_auth_token: str | None = None, tools: dict[str, Cal
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from starlette.responses import Response
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from starlette.routing import Mount, Route
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from llama_stack.log import get_logger
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server = FastMCP("FastMCP Test Server", log_level="WARNING")
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tools = tools or default_tools()
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@ -211,6 +213,7 @@ def make_mcp_server(required_auth_token: str | None = None, tools: dict[str, Cal
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return sock.getsockname()[1]
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port = get_open_port()
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logger = get_logger(__name__, category="tests::mcp")
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# make uvicorn logs be less verbose
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config = uvicorn.Config(app, host="0.0.0.0", port=port, log_level="warning")
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@ -218,10 +221,17 @@ def make_mcp_server(required_auth_token: str | None = None, tools: dict[str, Cal
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app.state.uvicorn_server = server_instance
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def run_server():
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server_instance.run()
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try:
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logger.info(f"Starting MCP server on port {port}")
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server_instance.run()
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logger.info(f"MCP server on port {port} has stopped")
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except Exception as e:
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logger.error(f"MCP server failed to start on port {port}: {e}")
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raise
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# Start the server in a new thread
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server_thread = threading.Thread(target=run_server, daemon=True)
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logger.info(f"Starting MCP server thread on port {port}")
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server_thread.start()
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# Polling until the server is ready
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@ -229,24 +239,36 @@ def make_mcp_server(required_auth_token: str | None = None, tools: dict[str, Cal
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start_time = time.time()
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server_url = f"http://localhost:{port}/sse"
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logger.info(f"Waiting for MCP server to be ready at {server_url}")
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while time.time() - start_time < timeout:
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try:
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response = httpx.get(server_url)
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if response.status_code in [200, 401]:
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logger.info(f"MCP server is ready on port {port} (status: {response.status_code})")
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break
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except httpx.RequestError:
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except httpx.RequestError as e:
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logger.debug(f"Server not ready yet, retrying... ({e})")
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pass
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time.sleep(0.1)
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else:
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# If we exit the loop due to timeout
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logger.error(f"MCP server failed to start within {timeout} seconds on port {port}")
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logger.error(f"Thread alive: {server_thread.is_alive()}")
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if server_thread.is_alive():
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logger.error("Server thread is still running but not responding to HTTP requests")
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try:
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yield {"server_url": server_url}
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finally:
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logger.info(f"Shutting down MCP server on port {port}")
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server_instance.should_exit = True
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time.sleep(0.5)
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# Force shutdown if still running
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if server_thread.is_alive():
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try:
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logger.info("Force shutting down server thread")
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if hasattr(server_instance, "servers") and server_instance.servers:
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for srv in server_instance.servers:
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srv.close()
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@ -254,9 +276,9 @@ def make_mcp_server(required_auth_token: str | None = None, tools: dict[str, Cal
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# Wait for graceful shutdown
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server_thread.join(timeout=3)
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if server_thread.is_alive():
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print("Warning: Server thread still alive after shutdown attempt")
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logger.warning("Server thread still alive after shutdown attempt")
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except Exception as e:
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print(f"Error during server shutdown: {e}")
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logger.error(f"Error during server shutdown: {e}")
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# CRITICAL: Reset SSE global state to prevent event loop contamination
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# Reset the SSE AppStatus singleton that stores anyio.Event objects
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167
tests/integration/recordings/responses/168daab89068.json
Normal file
167
tests/integration/recordings/responses/168daab89068.json
Normal file
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@ -0,0 +1,167 @@
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{
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"request": {
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"method": "POST",
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"url": "http://localhost:11434/api/generate",
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"headers": {},
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"body": {
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"model": "llama3.2:3b-instruct-fp16",
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"raw": true,
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"prompt": "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\nYou are a helpful assistant. You have access to functions, but you should only use them if they are required.\nYou are an expert in composing functions. You are given a question and a set of possible functions.\nBased on the question, you may or may not need to make one function/tool call to achieve the purpose.\n\nIf you decide to invoke any of the function(s), you MUST put it in the format of [func_name1(params_name1=params_value1, params_name2=params_value2...), func_name2(params)]\nIf you decide to invoke a function, you SHOULD NOT include any other text in the response. besides the function call in the above format.\nFor a boolean parameter, be sure to use `True` or `False` (capitalized) for the value.\n\n\nHere is a list of functions in JSON format that you can invoke.\n\n[\n {\n \"name\": \"greet_everyone\",\n \"description\": \"\",\n \"parameters\": {\n \"type\": \"dict\",\n \"required\": [\"url\"],\n \"properties\": {\n \"url\": {\n \"type\": \"string\",\n \"description\": \"\"\n }\n }\n }\n },\n {\n \"name\": \"get_boiling_point\",\n \"description\": \"\n Returns the boiling point of a liquid in Celsius or Fahrenheit.\n\n :param liquid_name: The name of the liquid\n :param celsius: Whether to return the boiling point in Celsius\n :return: The boiling point of the liquid in Celcius or Fahrenheit\n \",\n \"parameters\": {\n \"type\": \"dict\",\n \"required\": [\"liquid_name\"],\n \"properties\": {\n \"liquid_name\": {\n \"type\": \"string\",\n \"description\": \"\"\n },\n \"celsius\": {\n \"type\": \"boolean\",\n \"description\": \"\",\n \"default\": \"True\"\n }\n }\n }\n }\n]\n\nYou can answer general questions or invoke tools when necessary.\nIn addition to tool calls, you should also augment your responses by using the tool outputs.\nYou are a helpful assistant.<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nSay hi to the world. Use tools to do so.<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n[greet_everyone(url=\"world\")]<|eot_id|><|start_header_id|>ipython<|end_header_id|>\n\nHello, world!<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n",
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"options": {
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"temperature": 0.0
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},
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"stream": true
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},
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"endpoint": "/api/generate",
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"model": "llama3.2:3b-instruct-fp16"
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},
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"response": {
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"body": [
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{
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"__type__": "ollama._types.GenerateResponse",
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"__data__": {
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"model": "llama3.2:3b-instruct-fp16",
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"created_at": "2025-09-27T18:05:56.663224Z",
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"done": false,
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"done_reason": null,
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"total_duration": null,
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"load_duration": null,
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"prompt_eval_count": null,
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"prompt_eval_duration": null,
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"eval_count": null,
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"eval_duration": null,
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"response": "How",
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"thinking": null,
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"context": null
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}
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},
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{
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"__type__": "ollama._types.GenerateResponse",
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"__data__": {
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"model": "llama3.2:3b-instruct-fp16",
|
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"created_at": "2025-09-27T18:05:56.706706Z",
|
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"done": false,
|
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"done_reason": null,
|
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"total_duration": null,
|
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"load_duration": null,
|
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"prompt_eval_count": null,
|
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"prompt_eval_duration": null,
|
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"eval_count": null,
|
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"eval_duration": null,
|
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"response": " can",
|
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"thinking": null,
|
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"context": null
|
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}
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},
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{
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"__type__": "ollama._types.GenerateResponse",
|
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"__data__": {
|
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"model": "llama3.2:3b-instruct-fp16",
|
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"created_at": "2025-09-27T18:05:56.751075Z",
|
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"done": false,
|
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"done_reason": null,
|
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"total_duration": null,
|
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"load_duration": null,
|
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"prompt_eval_count": null,
|
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"prompt_eval_duration": null,
|
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"eval_count": null,
|
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"eval_duration": null,
|
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"response": " I",
|
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"thinking": null,
|
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"context": null
|
||||
}
|
||||
},
|
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{
|
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"__type__": "ollama._types.GenerateResponse",
|
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"__data__": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"created_at": "2025-09-27T18:05:56.794187Z",
|
||||
"done": false,
|
||||
"done_reason": null,
|
||||
"total_duration": null,
|
||||
"load_duration": null,
|
||||
"prompt_eval_count": null,
|
||||
"prompt_eval_duration": null,
|
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"eval_count": null,
|
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"eval_duration": null,
|
||||
"response": " assist",
|
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"thinking": null,
|
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"context": null
|
||||
}
|
||||
},
|
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{
|
||||
"__type__": "ollama._types.GenerateResponse",
|
||||
"__data__": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"created_at": "2025-09-27T18:05:56.837831Z",
|
||||
"done": false,
|
||||
"done_reason": null,
|
||||
"total_duration": null,
|
||||
"load_duration": null,
|
||||
"prompt_eval_count": null,
|
||||
"prompt_eval_duration": null,
|
||||
"eval_count": null,
|
||||
"eval_duration": null,
|
||||
"response": " you",
|
||||
"thinking": null,
|
||||
"context": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "ollama._types.GenerateResponse",
|
||||
"__data__": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"created_at": "2025-09-27T18:05:56.879926Z",
|
||||
"done": false,
|
||||
"done_reason": null,
|
||||
"total_duration": null,
|
||||
"load_duration": null,
|
||||
"prompt_eval_count": null,
|
||||
"prompt_eval_duration": null,
|
||||
"eval_count": null,
|
||||
"eval_duration": null,
|
||||
"response": " further",
|
||||
"thinking": null,
|
||||
"context": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "ollama._types.GenerateResponse",
|
||||
"__data__": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"created_at": "2025-09-27T18:05:56.92182Z",
|
||||
"done": false,
|
||||
"done_reason": null,
|
||||
"total_duration": null,
|
||||
"load_duration": null,
|
||||
"prompt_eval_count": null,
|
||||
"prompt_eval_duration": null,
|
||||
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|
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|
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{
|
||||
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|
||||
"__data__": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"created_at": "2025-09-27T18:05:56.963339Z",
|
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"done": true,
|
||||
"done_reason": "stop",
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|
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|
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"is_streaming": true
|
||||
}
|
||||
}
|
||||
347
tests/integration/recordings/responses/949d3ad16367.json
Normal file
347
tests/integration/recordings/responses/949d3ad16367.json
Normal file
|
|
@ -0,0 +1,347 @@
|
|||
{
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "http://localhost:11434/api/generate",
|
||||
"headers": {},
|
||||
"body": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"raw": true,
|
||||
"prompt": "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\nYou are a helpful assistant. You have access to functions, but you should only use them if they are required.\nYou are an expert in composing functions. You are given a question and a set of possible functions.\nBased on the question, you may or may not need to make one function/tool call to achieve the purpose.\n\nIf you decide to invoke any of the function(s), you MUST put it in the format of [func_name1(params_name1=params_value1, params_name2=params_value2...), func_name2(params)]\nIf you decide to invoke a function, you SHOULD NOT include any other text in the response. besides the function call in the above format.\nFor a boolean parameter, be sure to use `True` or `False` (capitalized) for the value.\n\n\nHere is a list of functions in JSON format that you can invoke.\n\n[\n {\n \"name\": \"greet_everyone\",\n \"description\": \"\",\n \"parameters\": {\n \"type\": \"dict\",\n \"required\": [\"url\"],\n \"properties\": {\n \"url\": {\n \"type\": \"string\",\n \"description\": \"\"\n }\n }\n }\n },\n {\n \"name\": \"get_boiling_point\",\n \"description\": \"\n Returns the boiling point of a liquid in Celsius or Fahrenheit.\n\n :param liquid_name: The name of the liquid\n :param celsius: Whether to return the boiling point in Celsius\n :return: The boiling point of the liquid in Celcius or Fahrenheit\n \",\n \"parameters\": {\n \"type\": \"dict\",\n \"required\": [\"liquid_name\"],\n \"properties\": {\n \"liquid_name\": {\n \"type\": \"string\",\n \"description\": \"\"\n },\n \"celsius\": {\n \"type\": \"boolean\",\n \"description\": \"\",\n \"default\": \"True\"\n }\n }\n }\n }\n]\n\nYou can answer general questions or invoke tools when necessary.\nIn addition to tool calls, you should also augment your responses by using the tool outputs.\nYou are a helpful assistant.<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nSay hi to the world. Use tools to do so.<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n[greet_everyone(url=\"world\")]<|eot_id|><|start_header_id|>ipython<|end_header_id|>\n\nHello, world!<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\nHow can I assist you further?<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nWhat is the boiling point of polyjuice? Use tools to answer.<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n",
|
||||
"options": {
|
||||
"temperature": 0.0
|
||||
},
|
||||
"stream": true
|
||||
},
|
||||
"endpoint": "/api/generate",
|
||||
"model": "llama3.2:3b-instruct-fp16"
|
||||
},
|
||||
"response": {
|
||||
"body": [
|
||||
{
|
||||
"__type__": "ollama._types.GenerateResponse",
|
||||
"__data__": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"created_at": "2025-09-27T18:05:57.177453Z",
|
||||
"done": false,
|
||||
"done_reason": null,
|
||||
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|
||||
"load_duration": null,
|
||||
"prompt_eval_count": null,
|
||||
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|
||||
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|
||||
"eval_duration": null,
|
||||
"response": "[",
|
||||
"thinking": null,
|
||||
"context": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "ollama._types.GenerateResponse",
|
||||
"__data__": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"created_at": "2025-09-27T18:05:57.220271Z",
|
||||
"done": false,
|
||||
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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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|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "ollama._types.GenerateResponse",
|
||||
"__data__": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"created_at": "2025-09-27T18:05:57.261232Z",
|
||||
"done": false,
|
||||
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||||
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||||
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||||
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||||
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||||
"eval_duration": null,
|
||||
"response": "_bo",
|
||||
"thinking": null,
|
||||
"context": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "ollama._types.GenerateResponse",
|
||||
"__data__": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"created_at": "2025-09-27T18:05:57.302818Z",
|
||||
"done": false,
|
||||
"done_reason": null,
|
||||
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|
||||
"load_duration": null,
|
||||
"prompt_eval_count": null,
|
||||
"prompt_eval_duration": null,
|
||||
"eval_count": null,
|
||||
"eval_duration": null,
|
||||
"response": "iling",
|
||||
"thinking": null,
|
||||
"context": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "ollama._types.GenerateResponse",
|
||||
"__data__": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"created_at": "2025-09-27T18:05:57.344343Z",
|
||||
"done": false,
|
||||
"done_reason": null,
|
||||
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|
||||
"load_duration": null,
|
||||
"prompt_eval_count": null,
|
||||
"prompt_eval_duration": null,
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||||
"eval_count": null,
|
||||
"eval_duration": null,
|
||||
"response": "_point",
|
||||
"thinking": null,
|
||||
"context": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "ollama._types.GenerateResponse",
|
||||
"__data__": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"created_at": "2025-09-27T18:05:57.386025Z",
|
||||
"done": false,
|
||||
"done_reason": null,
|
||||
"total_duration": null,
|
||||
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|
||||
"prompt_eval_count": null,
|
||||
"prompt_eval_duration": null,
|
||||
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|
||||
"eval_duration": null,
|
||||
"response": "(",
|
||||
"thinking": null,
|
||||
"context": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "ollama._types.GenerateResponse",
|
||||
"__data__": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"created_at": "2025-09-27T18:05:57.42778Z",
|
||||
"done": false,
|
||||
"done_reason": null,
|
||||
"total_duration": null,
|
||||
"load_duration": null,
|
||||
"prompt_eval_count": null,
|
||||
"prompt_eval_duration": null,
|
||||
"eval_count": null,
|
||||
"eval_duration": null,
|
||||
"response": "liquid",
|
||||
"thinking": null,
|
||||
"context": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "ollama._types.GenerateResponse",
|
||||
"__data__": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"created_at": "2025-09-27T18:05:57.469673Z",
|
||||
"done": false,
|
||||
"done_reason": null,
|
||||
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|
||||
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||||
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|
||||
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||||
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|
||||
"response": "_name",
|
||||
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|
||||
"context": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "ollama._types.GenerateResponse",
|
||||
"__data__": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"created_at": "2025-09-27T18:05:57.512543Z",
|
||||
"done": false,
|
||||
"done_reason": null,
|
||||
"total_duration": null,
|
||||
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|
||||
"prompt_eval_count": null,
|
||||
"prompt_eval_duration": null,
|
||||
"eval_count": null,
|
||||
"eval_duration": null,
|
||||
"response": "='",
|
||||
"thinking": null,
|
||||
"context": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "ollama._types.GenerateResponse",
|
||||
"__data__": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"created_at": "2025-09-27T18:05:57.554479Z",
|
||||
"done": false,
|
||||
"done_reason": null,
|
||||
"total_duration": null,
|
||||
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|
||||
"prompt_eval_count": null,
|
||||
"prompt_eval_duration": null,
|
||||
"eval_count": null,
|
||||
"eval_duration": null,
|
||||
"response": "poly",
|
||||
"thinking": null,
|
||||
"context": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "ollama._types.GenerateResponse",
|
||||
"__data__": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"created_at": "2025-09-27T18:05:57.597092Z",
|
||||
"done": false,
|
||||
"done_reason": null,
|
||||
"total_duration": null,
|
||||
"load_duration": null,
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||||
"prompt_eval_count": null,
|
||||
"prompt_eval_duration": null,
|
||||
"eval_count": null,
|
||||
"eval_duration": null,
|
||||
"response": "ju",
|
||||
"thinking": null,
|
||||
"context": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "ollama._types.GenerateResponse",
|
||||
"__data__": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"created_at": "2025-09-27T18:05:57.639581Z",
|
||||
"done": false,
|
||||
"done_reason": null,
|
||||
"total_duration": null,
|
||||
"load_duration": null,
|
||||
"prompt_eval_count": null,
|
||||
"prompt_eval_duration": null,
|
||||
"eval_count": null,
|
||||
"eval_duration": null,
|
||||
"response": "ice",
|
||||
"thinking": null,
|
||||
"context": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "ollama._types.GenerateResponse",
|
||||
"__data__": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"created_at": "2025-09-27T18:05:57.683223Z",
|
||||
"done": false,
|
||||
"done_reason": null,
|
||||
"total_duration": null,
|
||||
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|
||||
"prompt_eval_count": null,
|
||||
"prompt_eval_duration": null,
|
||||
"eval_count": null,
|
||||
"eval_duration": null,
|
||||
"response": "',",
|
||||
"thinking": null,
|
||||
"context": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "ollama._types.GenerateResponse",
|
||||
"__data__": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"created_at": "2025-09-27T18:05:57.72556Z",
|
||||
"done": false,
|
||||
"done_reason": null,
|
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|
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|
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|
||||
"response": " c",
|
||||
"thinking": null,
|
||||
"context": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "ollama._types.GenerateResponse",
|
||||
"__data__": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"created_at": "2025-09-27T18:05:57.768012Z",
|
||||
"done": false,
|
||||
"done_reason": null,
|
||||
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|
||||
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|
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|
||||
"prompt_eval_duration": null,
|
||||
"eval_count": null,
|
||||
"eval_duration": null,
|
||||
"response": "elsius",
|
||||
"thinking": null,
|
||||
"context": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "ollama._types.GenerateResponse",
|
||||
"__data__": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"created_at": "2025-09-27T18:05:57.8098Z",
|
||||
"done": false,
|
||||
"done_reason": null,
|
||||
"total_duration": null,
|
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|
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||||
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|
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|
||||
"eval_duration": null,
|
||||
"response": "=True",
|
||||
"thinking": null,
|
||||
"context": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "ollama._types.GenerateResponse",
|
||||
"__data__": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"created_at": "2025-09-27T18:05:57.851578Z",
|
||||
"done": false,
|
||||
"done_reason": null,
|
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"total_duration": null,
|
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"load_duration": null,
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"prompt_eval_count": null,
|
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|
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"eval_count": null,
|
||||
"eval_duration": null,
|
||||
"response": ")]",
|
||||
"thinking": null,
|
||||
"context": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "ollama._types.GenerateResponse",
|
||||
"__data__": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"created_at": "2025-09-27T18:05:57.893693Z",
|
||||
"done": true,
|
||||
"done_reason": "stop",
|
||||
"total_duration": 885274541,
|
||||
"load_duration": 99578333,
|
||||
"prompt_eval_count": 514,
|
||||
"prompt_eval_duration": 67915875,
|
||||
"eval_count": 18,
|
||||
"eval_duration": 717086791,
|
||||
"response": "",
|
||||
"thinking": null,
|
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"context": null
|
||||
}
|
||||
}
|
||||
],
|
||||
"is_streaming": true
|
||||
}
|
||||
}
|
||||
|
|
@ -11,7 +11,27 @@
|
|||
"body": {
|
||||
"__type__": "ollama._types.ProcessResponse",
|
||||
"__data__": {
|
||||
"models": []
|
||||
"models": [
|
||||
{
|
||||
"model": "llama3.2:3b",
|
||||
"name": "llama3.2:3b",
|
||||
"digest": "a80c4f17acd55265feec403c7aef86be0c25983ab279d83f3bcd3abbcb5b8b72",
|
||||
"expires_at": "2025-09-27T11:54:56.718552-07:00",
|
||||
"size": 3367856128,
|
||||
"size_vram": 3367856128,
|
||||
"details": {
|
||||
"parent_model": "",
|
||||
"format": "gguf",
|
||||
"family": "llama",
|
||||
"families": [
|
||||
"llama"
|
||||
],
|
||||
"parameter_size": "3.2B",
|
||||
"quantization_level": "Q4_K_M"
|
||||
},
|
||||
"context_length": 4096
|
||||
}
|
||||
]
|
||||
}
|
||||
},
|
||||
"is_streaming": false
|
||||
|
|
|
|||
185
tests/integration/recordings/responses/e61266e87842.json
Normal file
185
tests/integration/recordings/responses/e61266e87842.json
Normal file
|
|
@ -0,0 +1,185 @@
|
|||
{
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "http://localhost:11434/api/generate",
|
||||
"headers": {},
|
||||
"body": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"raw": true,
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"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "whisper-1",
|
||||
"created": 1677532384,
|
||||
"object": "model",
|
||||
"owned_by": "openai-internal"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "text-embedding-ada-002",
|
||||
"created": 1671217299,
|
||||
"object": "model",
|
||||
"owned_by": "openai-internal"
|
||||
}
|
||||
}
|
||||
],
|
||||
"is_streaming": false
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,96 @@
|
|||
{
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "http://0.0.0.0:11434/v1/v1/models",
|
||||
"headers": {},
|
||||
"body": {},
|
||||
"endpoint": "/v1/models",
|
||||
"model": ""
|
||||
},
|
||||
"response": {
|
||||
"body": [
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "nomic-embed-text:latest",
|
||||
"created": 1756922046,
|
||||
"object": "model",
|
||||
"owned_by": "library"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "all-minilm:l6-v2",
|
||||
"created": 1756919946,
|
||||
"object": "model",
|
||||
"owned_by": "library"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "llama3.2-vision:11b",
|
||||
"created": 1753926302,
|
||||
"object": "model",
|
||||
"owned_by": "library"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "llama3.2-vision:latest",
|
||||
"created": 1753845527,
|
||||
"object": "model",
|
||||
"owned_by": "library"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "llama-guard3:1b",
|
||||
"created": 1753479584,
|
||||
"object": "model",
|
||||
"owned_by": "library"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "llama3.2:1b",
|
||||
"created": 1752814944,
|
||||
"object": "model",
|
||||
"owned_by": "library"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "all-minilm:latest",
|
||||
"created": 1748994610,
|
||||
"object": "model",
|
||||
"owned_by": "library"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "llama3.2:3b",
|
||||
"created": 1746123323,
|
||||
"object": "model",
|
||||
"owned_by": "library"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "llama3.2:3b-instruct-fp16",
|
||||
"created": 1746052428,
|
||||
"object": "model",
|
||||
"owned_by": "library"
|
||||
}
|
||||
}
|
||||
],
|
||||
"is_streaming": false
|
||||
}
|
||||
}
|
||||
|
|
@ -31,6 +31,11 @@ def test_mcp_invocation(llama_stack_client, text_model_id, mcp_server):
|
|||
uri = mcp_server["server_url"]
|
||||
|
||||
# registering should not raise an error anymore even if you don't specify the auth token
|
||||
try:
|
||||
llama_stack_client.toolgroups.unregister(toolgroup_id=test_toolgroup_id)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
llama_stack_client.toolgroups.register(
|
||||
toolgroup_id=test_toolgroup_id,
|
||||
provider_id="model-context-protocol",
|
||||
|
|
|
|||
|
|
@ -16,9 +16,11 @@ from llama_stack.apis.agents import (
|
|||
)
|
||||
from llama_stack.apis.common.responses import PaginatedResponse
|
||||
from llama_stack.apis.inference import Inference
|
||||
from llama_stack.apis.resource import ResourceType
|
||||
from llama_stack.apis.safety import Safety
|
||||
from llama_stack.apis.tools import ToolGroups, ToolRuntime
|
||||
from llama_stack.apis.tools import ListToolsResponse, Tool, ToolGroups, ToolParameter, ToolRuntime
|
||||
from llama_stack.apis.vector_io import VectorIO
|
||||
from llama_stack.providers.inline.agents.meta_reference.agent_instance import ChatAgent
|
||||
from llama_stack.providers.inline.agents.meta_reference.agents import MetaReferenceAgentsImpl
|
||||
from llama_stack.providers.inline.agents.meta_reference.config import MetaReferenceAgentsImplConfig
|
||||
from llama_stack.providers.inline.agents.meta_reference.persistence import AgentInfo
|
||||
|
|
@ -75,11 +77,11 @@ def sample_agent_config():
|
|||
},
|
||||
input_shields=["string"],
|
||||
output_shields=["string"],
|
||||
toolgroups=["string"],
|
||||
toolgroups=["mcp::my_mcp_server"],
|
||||
client_tools=[
|
||||
{
|
||||
"name": "string",
|
||||
"description": "string",
|
||||
"name": "client_tool",
|
||||
"description": "Client Tool",
|
||||
"parameters": [
|
||||
{
|
||||
"name": "string",
|
||||
|
|
@ -226,3 +228,83 @@ async def test_delete_agent(agents_impl, sample_agent_config):
|
|||
# Verify the agent was deleted
|
||||
with pytest.raises(ValueError):
|
||||
await agents_impl.get_agent(agent_id)
|
||||
|
||||
|
||||
async def test__initialize_tools(agents_impl, sample_agent_config):
|
||||
# Mock tool_groups_api.list_tools()
|
||||
agents_impl.tool_groups_api.list_tools.return_value = ListToolsResponse(
|
||||
data=[
|
||||
Tool(
|
||||
identifier="story_maker",
|
||||
provider_id="model-context-protocol",
|
||||
type=ResourceType.tool,
|
||||
toolgroup_id="mcp::my_mcp_server",
|
||||
description="Make a story",
|
||||
parameters=[
|
||||
ToolParameter(
|
||||
name="story_title",
|
||||
parameter_type="string",
|
||||
description="Title of the story",
|
||||
required=True,
|
||||
title="Story Title",
|
||||
),
|
||||
ToolParameter(
|
||||
name="input_words",
|
||||
parameter_type="array",
|
||||
description="Input words",
|
||||
required=False,
|
||||
items={"type": "string"},
|
||||
title="Input Words",
|
||||
default=[],
|
||||
),
|
||||
],
|
||||
)
|
||||
]
|
||||
)
|
||||
|
||||
create_response = await agents_impl.create_agent(sample_agent_config)
|
||||
agent_id = create_response.agent_id
|
||||
|
||||
# Get an instance of ChatAgent
|
||||
chat_agent = await agents_impl._get_agent_impl(agent_id)
|
||||
assert chat_agent is not None
|
||||
assert isinstance(chat_agent, ChatAgent)
|
||||
|
||||
# Initialize tool definitions
|
||||
await chat_agent._initialize_tools()
|
||||
assert len(chat_agent.tool_defs) == 2
|
||||
|
||||
# Verify the first tool, which is a client tool
|
||||
first_tool = chat_agent.tool_defs[0]
|
||||
assert first_tool.tool_name == "client_tool"
|
||||
assert first_tool.description == "Client Tool"
|
||||
|
||||
# Verify the second tool, which is an MCP tool that has an array-type property
|
||||
second_tool = chat_agent.tool_defs[1]
|
||||
assert second_tool.tool_name == "story_maker"
|
||||
assert second_tool.description == "Make a story"
|
||||
|
||||
parameters = second_tool.parameters
|
||||
assert len(parameters) == 2
|
||||
|
||||
# Verify a string property
|
||||
story_title = parameters.get("story_title")
|
||||
assert story_title is not None
|
||||
assert story_title.param_type == "string"
|
||||
assert story_title.description == "Title of the story"
|
||||
assert story_title.required
|
||||
assert story_title.items is None
|
||||
assert story_title.title == "Story Title"
|
||||
assert story_title.default is None
|
||||
|
||||
# Verify an array property
|
||||
input_words = parameters.get("input_words")
|
||||
assert input_words is not None
|
||||
assert input_words.param_type == "array"
|
||||
assert input_words.description == "Input words"
|
||||
assert not input_words.required
|
||||
assert input_words.items is not None
|
||||
assert len(input_words.items) == 1
|
||||
assert input_words.items.get("type") == "string"
|
||||
assert input_words.title == "Input Words"
|
||||
assert input_words.default == []
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue