mirror of
https://github.com/meta-llama/llama-stack.git
synced 2025-10-03 19:57:35 +00:00
fix tests, re-record
This commit is contained in:
Ashwin Bharambe
parent
c1818350c8
commit
371de50875
8 changed files with 1677 additions and 5 deletions
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@ -156,6 +156,7 @@ def make_mcp_server(required_auth_token: str | None = None, tools: dict[str, Cal
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:param required_auth_token: Optional auth token required for access
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:param tools: Dictionary of tool_name -> tool_function. If None, uses default tools.
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"""
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import logging
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import threading
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import time
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@ -211,6 +212,7 @@ 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 = logging.getLogger(__name__)
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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 +220,17 @@ 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 +238,36 @@ 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 +275,9 @@ 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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},
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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": "2025-09-27T18:05:56.794187Z",
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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": " assist",
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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": "2025-09-27T18:05:56.837831Z",
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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": " you",
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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": "2025-09-27T18:05:56.879926Z",
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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": " further",
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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": "2025-09-27T18:05:56.92182Z",
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"done": false,
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||||
"done_reason": null,
|
||||
"total_duration": null,
|
||||
"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": "?",
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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": "2025-09-27T18:05:56.963339Z",
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"done": true,
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"done_reason": "stop",
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"total_duration": 492973041,
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"load_duration": 103979375,
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"prompt_eval_count": 482,
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"prompt_eval_duration": 87032041,
|
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"eval_count": 8,
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"eval_duration": 300586375,
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"response": "",
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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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"is_streaming": true
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}
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}
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347
tests/integration/recordings/responses/949d3ad16367.json
Normal file
347
tests/integration/recordings/responses/949d3ad16367.json
Normal file
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@ -0,0 +1,347 @@
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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\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",
|
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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": "2025-09-27T18:05:57.177453Z",
|
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"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": "[",
|
||||
"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,
|
||||
"done_reason": null,
|
||||
"total_duration": null,
|
||||
"load_duration": null,
|
||||
"prompt_eval_count": null,
|
||||
"prompt_eval_duration": null,
|
||||
"eval_count": null,
|
||||
"eval_duration": null,
|
||||
"response": "get",
|
||||
"thinking": null,
|
||||
"context": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "ollama._types.GenerateResponse",
|
||||
"__data__": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"created_at": "2025-09-27T18:05:57.261232Z",
|
||||
"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": "_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,
|
||||
"total_duration": null,
|
||||
"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,
|
||||
"total_duration": null,
|
||||
"load_duration": null,
|
||||
"prompt_eval_count": null,
|
||||
"prompt_eval_duration": null,
|
||||
"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,
|
||||
"load_duration": null,
|
||||
"prompt_eval_count": null,
|
||||
"prompt_eval_duration": null,
|
||||
"eval_count": null,
|
||||
"eval_duration": null,
|
||||
"response": "(",
|
||||
"thinking": null,
|
||||
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185
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}
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{
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],
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"is_streaming": false
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}
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|
|
@ -0,0 +1,96 @@
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{
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"request": {
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"method": "POST",
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"url": "http://0.0.0.0:11434/v1/v1/models",
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"headers": {},
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"body": {},
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"endpoint": "/v1/models",
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"model": ""
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},
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"response": {
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"body": [
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{
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"__data__": {
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"id": "nomic-embed-text:latest",
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{
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"id": "llama3.2:3b-instruct-fp16",
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}
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}
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],
|
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"is_streaming": false
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}
|
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}
|
||||
|
|
@ -31,6 +31,8 @@ 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
|
||||
llama_stack_client.toolgroups.unregister(toolgroup_id=test_toolgroup_id)
|
||||
|
||||
llama_stack_client.toolgroups.register(
|
||||
toolgroup_id=test_toolgroup_id,
|
||||
provider_id="model-context-protocol",
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue