mirror of
https://github.com/invariantlabs-ai/invariant-gateway.git
synced 2026-05-18 21:28:07 +02:00
238 lines
8.1 KiB
Python
238 lines
8.1 KiB
Python
"""Test the chat completions gateway calls with tool calling and processing response."""
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import json
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import os
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import sys
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import time
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import uuid
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# Add integration folder (parent) to sys.path
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sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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from utils import get_open_ai_client
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import pytest
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import requests
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# Pytest plugins
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pytest_plugins = ("pytest_asyncio",)
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@pytest.mark.skipif(not os.getenv("OPENAI_API_KEY"), reason="No OPENAI_API_KEY set")
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@pytest.mark.parametrize("push_to_explorer", [False, True])
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async def test_chat_completion_with_tool_call_without_streaming(
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explorer_api_url, gateway_url, push_to_explorer
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):
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"""
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Test the chat completions gateway calls with tool calling and response processing
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without streaming.
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"""
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dataset_name = f"test-dataset-open-ai-{uuid.uuid4()}"
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client = get_open_ai_client(gateway_url, push_to_explorer, dataset_name)
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chat_response = client.chat.completions.create(
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model="gpt-4o",
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messages=[{"role": "user", "content": "What is the weather in New York?"}],
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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_weather",
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"parameters": {
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"type": "object",
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"properties": {"location": {"type": "string"}},
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"required": ["location"],
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},
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},
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}
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],
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)
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assert chat_response.choices[0].message.role == "assistant"
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# Extract tool call
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assert len(chat_response.choices[0].message.tool_calls) == 1
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tool_call = chat_response.choices[0].message.tool_calls[0]
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assert tool_call.function.name == "get_weather"
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assert (
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"New York" in tool_call.function.arguments
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and "location" in tool_call.function.arguments
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)
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# Mock response of tool call
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tool_result = "The temperature in New York is 15°C and it is raining."
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history = [
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{"role": "user", "content": "What is the weather in New York?"},
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{
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"role": "assistant",
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"tool_calls": [
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{
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"function": {
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"arguments": tool_call.function.arguments,
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"name": tool_call.function.name,
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},
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"id": tool_call.id,
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"type": tool_call.type,
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}
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],
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},
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{
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"role": "tool",
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"tool_call_id": tool_call.id,
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"tool_name": "get_weather",
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"content": tool_result,
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},
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]
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# Send mock response back to OpenAI with history of chat
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chat_response_final = client.chat.completions.create(
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model="gpt-4o",
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messages=history,
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)
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assert "15°C" in chat_response_final.choices[0].message.content
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if push_to_explorer:
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# Wait for the trace to be saved
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# This is needed because the trace is saved asynchronously
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time.sleep(2)
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# Fetch the trace ids for the dataset
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traces_response = requests.get(
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f"{explorer_api_url}/api/v1/dataset/byuser/developer/{dataset_name}/traces",
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timeout=5,
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)
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traces = traces_response.json()
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assert len(traces) == 1
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trace_id = traces[0]["id"]
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# Fetch the trace
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trace_response = requests.get(
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f"{explorer_api_url}/api/v1/trace/{trace_id}",
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timeout=5,
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)
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trace = trace_response.json()
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for message in trace["messages"]:
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message.pop("annotations", None)
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# Verify the trace messages
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expected_messages = history + [
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{
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"role": "assistant",
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"content": chat_response_final.choices[0].message.content,
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}
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]
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expected_messages[1]["tool_calls"][0]["function"]["arguments"] = json.loads(
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expected_messages[1]["tool_calls"][0]["function"]["arguments"]
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)
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assert trace["messages"][:2] == expected_messages[:2]
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assert "15°C" in trace["messages"][2]["content"]
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assert trace["messages"][2]["role"] == "tool"
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@pytest.mark.skipif(not os.getenv("OPENAI_API_KEY"), reason="No OPENAI_API_KEY set")
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@pytest.mark.parametrize("push_to_explorer", [False, True])
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async def test_chat_completion_with_tool_call_with_streaming(
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explorer_api_url, gateway_url, push_to_explorer
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):
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"""
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Test the chat completions gateway calls with tool calling and response processing
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while streaming.
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"""
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dataset_name = f"test-dataset-open-ai-{uuid.uuid4()}"
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client = get_open_ai_client(gateway_url, push_to_explorer, dataset_name)
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chat_response = client.chat.completions.create(
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model="gpt-4o",
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messages=[{"role": "user", "content": "What is the weather in New York?"}],
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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_weather",
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"parameters": {
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"type": "object",
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"properties": {"location": {"type": "string"}},
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"required": ["location"],
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},
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},
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}
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],
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stream=True,
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)
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tool_call = {"function": {}}
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for chunk in chat_response:
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if chunk.choices and chunk.choices[0].delta.tool_calls:
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partial_tool_call = chunk.choices[0].delta.tool_calls[0]
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tool_call.setdefault("id", partial_tool_call.id)
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tool_call.setdefault("type", partial_tool_call.type)
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tool_call["function"].setdefault("name", partial_tool_call.function.name)
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tool_call["function"].setdefault("arguments", "")
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tool_call["function"]["arguments"] += partial_tool_call.function.arguments
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assert tool_call["function"]["name"] == "get_weather"
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assert tool_call["function"]["arguments"] == '{"location":"New York"}'
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# Mock response of tool call
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tool_result = "The temperature in New York is 15°C and it is raining."
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history = [
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{"role": "user", "content": "What is the weather in New York?"},
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{
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"role": "assistant",
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"tool_calls": [
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{
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"function": {
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"arguments": tool_call["function"]["arguments"],
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"name": tool_call["function"]["name"],
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},
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"id": tool_call["id"],
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"type": tool_call["type"],
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}
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],
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},
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{
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"role": "tool",
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"tool_call_id": tool_call["id"],
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"tool_name": "get_weather",
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"content": tool_result,
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},
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]
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# Send mock response back to OpenAI with history of chat
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chat_response_final = client.chat.completions.create(
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model="gpt-4o", messages=history, stream=True
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)
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final_response = {"role": "assistant", "content": ""}
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for chunk in chat_response_final:
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if chunk.choices and chunk.choices[0].delta.content:
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final_response["content"] += chunk.choices[0].delta.content
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if push_to_explorer:
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# Wait for the trace to be saved
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# This is needed because the trace is saved asynchronously
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time.sleep(2)
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# Fetch the trace ids for the dataset
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traces_response = requests.get(
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f"{explorer_api_url}/api/v1/dataset/byuser/developer/{dataset_name}/traces",
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timeout=5,
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)
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traces = traces_response.json()
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assert len(traces) == 1
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trace_id = traces[0]["id"]
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# Fetch the trace
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trace_response = requests.get(
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f"{explorer_api_url}/api/v1/trace/{trace_id}",
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timeout=5,
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)
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trace = trace_response.json()
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# Verify the trace messages
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expected_messages = history + [final_response]
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expected_messages[1]["tool_calls"][0]["function"]["arguments"] = json.loads(
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expected_messages[1]["tool_calls"][0]["function"]["arguments"]
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)
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assert trace["messages"][:2] == expected_messages[:2]
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assert "15°C" in trace["messages"][2]["content"]
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assert trace["messages"][2]["role"] == "tool"
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