Semantic Kernel 1.45.0: our test log

# Install with uv (cold, no cache)
uv venv -q -p 3.13 work/py/semantic-kernel && VIRTUAL_ENV=work/py/semantic-kernel uv pip install --no-cache -q semantic-kernel

# Install with pip (cold, no cache)
uv venv -q --seed -p 3.13 work/pip/semantic-kernel && work/pip/semantic-kernel/bin/pip install --no-cache-dir -q semantic-kernel

# Task command (all trials)
OTEL_SDK_DISABLED=true work/py/semantic-kernel/bin/python tasks/semantic_kernel_agent.py

from common import *
import asyncio
from openai import AsyncOpenAI
from semantic_kernel import Kernel
from semantic_kernel.connectors.ai.open_ai import OpenAIChatCompletion, OpenAIChatPromptExecutionSettings
from semantic_kernel.connectors.ai.function_choice_behavior import FunctionChoiceBehavior
from semantic_kernel.contents import ChatHistory
from semantic_kernel.functions import kernel_function
class P:
    @kernel_function(name="add_numbers", description="Add two integers and return the sum.")
    def add_numbers(self, a: int, b: int) -> int:
        return add_numbers(a, b)
k = Kernel()
svc = OpenAIChatCompletion(ai_model_id=MODEL, async_client=AsyncOpenAI(base_url=BASE, api_key=KEY), service_id="chat")
k.add_service(svc); k.add_plugin(P(), "math")
s = OpenAIChatPromptExecutionSettings(function_choice_behavior=FunctionChoiceBehavior.Auto(), temperature=0)
h = ChatHistory(); h.add_user_message(TASK)
async def main():
    return await svc.get_chat_message_content(chat_history=h, settings=s, kernel=k)
report(asyncio.run(main()))

import json, os
BASE = "http://127.0.0.1:11434/v1"
MODEL = os.environ.get("MODEL", "qwen2.5-3b")
KEY = "ollama"
TASK = "Use the add_numbers tool to compute 17 + 25, then tell me the result."
CALLS = []
def add_numbers(a: int, b: int) -> int:
    """Add two integers and return the sum."""
    CALLS.append((a, b))
    return int(a) + int(b)
def report(final):
    ok = any({int(x), int(y)} == {17, 25} for x, y in CALLS) and "42" in str(final)
    print("RESULT_JSON " + json.dumps({"calls": CALLS, "final": str(final)[:300], "ok": ok}))

RESULT_JSON {"calls": [], "final": "", "ok": false}

REQ {"model":"qwen2.5-3b","stream":false,"messages":[{"role":"user","content":"Use the add_numbers tool to compute 17 + 25, then tell me the result."}],"temperature":0.0,"tool_choice":"auto","tools":[{"type":"function","function":{"name":"math-add_numbers","description":"Add two integers and return the sum.","parameters":{"type":"object","properties":{"a":{"type":"integer"},"b":{"type":"integer"}},"required":["a","b"]}}}]}
RES {"id":"chatcmpl-336","object":"chat.completion","model":"qwen2.5-3b","choices":[{"index":0,"message":{"role":"assistant","content":""},"finish_reason":"stop"}],"usage":{"prompt_tokens":159,"completion_tokens":28,"total_tokens":187}}

tool=add_numbers      -> {"role": "assistant", "content": "", "tool_calls": [{"function": {"name": "add_numbers", "arguments": "{\"a\":17,\"b\":25}"}}]}
tool=math-add_numbers -> {"role": "assistant", "content": ""}
# prompt changed to say "math-add_numbers tool":
tool=math-add_numbers -> {"role": "assistant", "content": "", "tool_calls": [{"function": {"name": "math-add_numbers", "arguments": "{\"a\":17,\"b\":25}"}}]}

# 1. Serve any local model that supports tool calling behind an OpenAI-compatible endpoint, registered as qwen2.5-3b:
#    http://127.0.0.1:11434/v1  (we used Ollama with a Qwen2.5-3B-Instruct Q4_K_M GGUF)
uv venv -p 3.13 .venv && VIRTUAL_ENV=.venv uv pip install semantic-kernel
# 2. Save common.py (above) and the task script next to each other, then:
.venv/bin/python semantic_kernel_agent.py