litellm-mirror/tests/llm_responses_api_testing/base_responses_api.py

import httpx
import json
import pytest
import sys
from typing import Any, Dict, List
from unittest.mock import MagicMock, Mock, patch
import os
import uuid
import time
import base64

sys.path.insert(
    0, os.path.abspath("../..")
)  # Adds the parent directory to the system path
import litellm
from abc import ABC, abstractmethod

from litellm.integrations.custom_logger import CustomLogger
import json
from litellm.types.utils import StandardLoggingPayload
from litellm.types.llms.openai import (
    ResponseCompletedEvent,
    ResponsesAPIResponse,
    ResponseTextConfig,
    ResponseAPIUsage,
    IncompleteDetails,
)
from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler


def validate_responses_api_response(response, final_chunk: bool = False):
    """
    Validate that a response from litellm.responses() or litellm.aresponses()
    conforms to the expected ResponsesAPIResponse structure.

    Args:
        response: The response object to validate

    Raises:
        AssertionError: If the response doesn't match the expected structure
    """
    # Validate response structure
    print("response=", json.dumps(response, indent=4, default=str))
    assert isinstance(
        response, ResponsesAPIResponse
    ), "Response should be an instance of ResponsesAPIResponse"

    # Required fields
    assert "id" in response and isinstance(
        response["id"], str
    ), "Response should have a string 'id' field"
    assert "created_at" in response and isinstance(
        response["created_at"], (int, float)
    ), "Response should have a numeric 'created_at' field"
    assert "output" in response and isinstance(
        response["output"], list
    ), "Response should have a list 'output' field"
    assert "parallel_tool_calls" in response and isinstance(
        response["parallel_tool_calls"], bool
    ), "Response should have a boolean 'parallel_tool_calls' field"

    # Optional fields with their expected types
    optional_fields = {
        "error": (dict, type(None)),  # error can be dict or None
        "incomplete_details": (IncompleteDetails, type(None)),
        "instructions": (str, type(None)),
        "metadata": dict,
        "model": str,
        "object": str,
        "temperature": (int, float, type(None)),
        "tool_choice": (dict, str),
        "tools": list,
        "top_p": (int, float, type(None)),
        "max_output_tokens": (int, type(None)),
        "previous_response_id": (str, type(None)),
        "reasoning": dict,
        "status": str,
        "text": ResponseTextConfig,
        "truncation": (str, type(None)),
        "usage": ResponseAPIUsage,
        "user": (str, type(None)),
    }
    if final_chunk is False:
        optional_fields["usage"] = type(None)

    for field, expected_type in optional_fields.items():
        if field in response:
            assert isinstance(
                response[field], expected_type
            ), f"Field '{field}' should be of type {expected_type}, but got {type(response[field])}"

    # Check if output has at least one item
    if final_chunk is True:
        assert (
            len(response["output"]) > 0
        ), "Response 'output' field should have at least one item"

    return True  # Return True if validation passes



class BaseResponsesAPITest(ABC):
    """
    Abstract base test class that enforces a common test across all test classes.
    """
    @abstractmethod
    def get_base_completion_call_args(self) -> dict:
        """Must return the base completion call args"""
        pass


    @pytest.mark.parametrize("sync_mode", [True, False])
    @pytest.mark.asyncio
    async def test_basic_openai_responses_api(self, sync_mode):
        litellm._turn_on_debug()
        litellm.set_verbose = True
        base_completion_call_args = self.get_base_completion_call_args()
        if sync_mode:
            response = litellm.responses(
                input="Basic ping", max_output_tokens=20,
                **base_completion_call_args
            )
        else:
            response = await litellm.aresponses(
                input="Basic ping", max_output_tokens=20,
                **base_completion_call_args
            )

        print("litellm response=", json.dumps(response, indent=4, default=str))

        # Use the helper function to validate the response
        validate_responses_api_response(response, final_chunk=True)


    @pytest.mark.parametrize("sync_mode", [True, False])
    @pytest.mark.asyncio
    async def test_basic_openai_responses_api_streaming(self, sync_mode):
        litellm._turn_on_debug()
        base_completion_call_args = self.get_base_completion_call_args()
        collected_content_string = ""
        response_completed_event = None
        if sync_mode:
            response = litellm.responses(
                input="Basic ping",
                stream=True,
                **base_completion_call_args
            )
            for event in response:
                print("litellm response=", json.dumps(event, indent=4, default=str))
                if event.type == "response.output_text.delta":
                    collected_content_string += event.delta
                elif event.type == "response.completed":
                    response_completed_event = event
        else:
            response = await litellm.aresponses(
                input="Basic ping",
                stream=True,
                **base_completion_call_args
            )
            async for event in response:
                print("litellm response=", json.dumps(event, indent=4, default=str))
                if event.type == "response.output_text.delta":
                    collected_content_string += event.delta
                elif event.type == "response.completed":
                    response_completed_event = event

        # assert the delta chunks content had len(collected_content_string) > 0
        # this content is typically rendered on chat ui's
        assert len(collected_content_string) > 0

        # assert the response completed event is not None
        assert response_completed_event is not None

        # assert the response completed event has a response
        assert response_completed_event.response is not None

        # assert the response completed event includes the usage
        assert response_completed_event.response.usage is not None

        # basic test assert the usage seems reasonable
        print("response_completed_event.response.usage=", response_completed_event.response.usage)
        assert response_completed_event.response.usage.input_tokens > 0 and response_completed_event.response.usage.input_tokens < 100
        assert response_completed_event.response.usage.output_tokens > 0 and response_completed_event.response.usage.output_tokens < 1000
        assert response_completed_event.response.usage.total_tokens > 0 and response_completed_event.response.usage.total_tokens < 1000

        # total tokens should be the sum of input and output tokens
        assert response_completed_event.response.usage.total_tokens == response_completed_event.response.usage.input_tokens + response_completed_event.response.usage.output_tokens