mirror of
https://github.com/tiennm99/litellm.git
synced 2026-07-04 09:06:17 +00:00
Ishaan Jaff
dc9b058dbd
* Added get responses API (#10234) * test_basic_openai_responses_get_endpoint * transform_get_response_api_request * test_basic_openai_responses_get_endpoint --------- Co-authored-by: Prathamesh Saraf <pratamesh1867@gmail.com>
106 lines
3.2 KiB
Python
106 lines
3.2 KiB
Python
import os
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import sys
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import pytest
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import asyncio
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from typing import Optional
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from unittest.mock import patch, AsyncMock
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sys.path.insert(0, os.path.abspath("../.."))
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import litellm
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from litellm.integrations.custom_logger import CustomLogger
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import json
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from litellm.types.utils import StandardLoggingPayload
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from litellm.types.llms.openai import (
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ResponseCompletedEvent,
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ResponsesAPIResponse,
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ResponseTextConfig,
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ResponseAPIUsage,
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IncompleteDetails,
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)
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import litellm
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from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler
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from base_responses_api import BaseResponsesAPITest
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from openai.types.responses.function_tool import FunctionTool
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class TestAnthropicResponsesAPITest(BaseResponsesAPITest):
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def get_base_completion_call_args(self):
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#litellm._turn_on_debug()
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return {
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"model": "anthropic/claude-3-5-sonnet-latest",
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}
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async def test_basic_openai_responses_delete_endpoint(self, sync_mode=False):
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pass
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async def test_basic_openai_responses_streaming_delete_endpoint(self, sync_mode=False):
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pass
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async def test_basic_openai_responses_get_endpoint(self, sync_mode=False):
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pass
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def test_multiturn_tool_calls():
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# Test streaming response with tools for Anthropic
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litellm._turn_on_debug()
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shell_tool = dict(FunctionTool(
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type="function",
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name="shell",
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description="Runs a shell command, and returns its output.",
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parameters={
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"type": "object",
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"properties": {
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"command": {"type": "array", "items": {"type": "string"}},
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"workdir": {"type": "string", "description": "The working directory for the command."}
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},
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"required": ["command"]
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},
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strict=True
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))
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# Step 1: Initial request with the tool
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response = litellm.responses(
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input=[{
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'role': 'user',
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'content': [
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{'type': 'input_text', 'text': 'make a hello world html file'}
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],
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'type': 'message'
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}],
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model='anthropic/claude-3-7-sonnet-latest',
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instructions='You are a helpful coding assistant.',
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tools=[shell_tool]
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)
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print("response=", response)
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# Step 2: Send the results of the tool call back to the model
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# Get the response ID and tool call ID from the response
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response_id = response.id
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tool_call_id = ""
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for item in response.output:
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if 'type' in item and item['type'] == 'function_call':
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tool_call_id = item['call_id']
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break
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# Use await with asyncio.run for the async function
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follow_up_response = litellm.responses(
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model='anthropic/claude-3-7-sonnet-latest',
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previous_response_id=response_id,
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input=[{
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'type': 'function_call_output',
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'call_id': tool_call_id,
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'output': '{"output":"<html>\\n<head>\\n <title>Hello Page</title>\\n</head>\\n<body>\\n <h1>Hi</h1>\\n <p>Welcome to this simple webpage!</p>\\n</body>\\n</html> > index.html\\n","metadata":{"exit_code":0,"duration_seconds":0}}'
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}],
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tools=[shell_tool]
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)
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print("follow_up_response=", follow_up_response)
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