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Add comprehensive tests for CompactifAI provider
- Test basic and streaming completions with proper mocking - Cover authentication, parameter handling, and error scenarios - Test provider detection and async functionality - Verify request headers and response transformation - Follow LiteLLM testing patterns with respx/httpx mocking - Ensure full compatibility with OpenAI-style responses
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Tim Elfrink
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338
tests/llm_translation/test_compactifai.py
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338
tests/llm_translation/test_compactifai.py
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import json
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import os
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import sys
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from unittest.mock import AsyncMock, patch
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from typing import Optional
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sys.path.insert(
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0, os.path.abspath("../..")
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) # Adds the parent directory to the system path
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import httpx
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import pytest
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import respx
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from respx import MockRouter
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import litellm
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from litellm import Choices, Message, ModelResponse
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from base_llm_unit_tests import BaseLLMChatTest
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class TestCompactifAI(BaseLLMChatTest):
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def get_base_completion_call_args(self):
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return {
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"model": "compactifai/llama-2-7b-compressed",
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"messages": [{"role": "user", "content": "Hello"}]
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}
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def get_custom_llm_provider(self):
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return "compactifai"
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# Implement abstract methods to avoid instantiation errors
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def test_tool_call_no_arguments(self):
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# CompactifAI inherits OpenAI tool calling behavior
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pass
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@pytest.mark.respx(base_url="https://api.compactif.ai")
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def test_compactifai_completion_basic():
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"""Test basic CompactifAI completion functionality"""
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mock_response = {
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"id": "chatcmpl-123",
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"object": "chat.completion",
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"created": 1677652288,
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"model": "llama-2-7b-compressed",
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"choices": [
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{
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"index": 0,
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"message": {
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"role": "assistant",
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"content": "Hello! How can I help you today?"
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},
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"finish_reason": "stop"
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}
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],
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"usage": {
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"prompt_tokens": 9,
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"completion_tokens": 12,
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"total_tokens": 21
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}
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}
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with respx.mock() as respx_mock:
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respx_mock.post("https://api.compactif.ai/v1/chat/completions").mock(
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return_value=httpx.Response(200, json=mock_response)
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)
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response = litellm.completion(
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model="compactifai/llama-2-7b-compressed",
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messages=[{"role": "user", "content": "Hello"}],
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api_key="test-key"
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)
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assert response.choices[0].message.content == "Hello! How can I help you today?"
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assert response.model == "compactifai/llama-2-7b-compressed"
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assert response.usage.total_tokens == 21
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@pytest.mark.respx(base_url="https://api.compactif.ai")
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def test_compactifai_completion_streaming():
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"""Test CompactifAI streaming completion"""
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mock_chunks = [
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"data: " + json.dumps({
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"id": "chatcmpl-123",
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"object": "chat.completion.chunk",
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"created": 1677652288,
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"model": "llama-2-7b-compressed",
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"choices": [
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{
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"index": 0,
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"delta": {"content": "Hello"},
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"finish_reason": None
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}
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]
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}) + "\n\n",
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"data: " + json.dumps({
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"id": "chatcmpl-123",
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"object": "chat.completion.chunk",
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"created": 1677652288,
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"model": "llama-2-7b-compressed",
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"choices": [
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{
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"index": 0,
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"delta": {"content": "!"},
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"finish_reason": "stop"
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}
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]
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}) + "\n\n",
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"data: [DONE]\n\n"
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]
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with respx.mock() as respx_mock:
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respx_mock.post("https://api.compactif.ai/v1/chat/completions").mock(
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return_value=httpx.Response(
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200,
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headers={"content-type": "text/plain"},
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content="".join(mock_chunks)
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)
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)
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response = litellm.completion(
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model="compactifai/llama-2-7b-compressed",
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messages=[{"role": "user", "content": "Hello"}],
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api_key="test-key",
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stream=True
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)
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chunks = list(response)
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assert len(chunks) >= 2
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assert chunks[0].choices[0].delta.content == "Hello"
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@pytest.mark.respx(base_url="https://api.compactif.ai")
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def test_compactifai_models_endpoint():
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"""Test CompactifAI models listing"""
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mock_response = {
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"object": "list",
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"data": [
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{
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"id": "llama-2-7b-compressed",
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"object": "model",
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"created": 1677610602,
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"owned_by": "compactifai"
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},
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{
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"id": "mistral-7b-compressed",
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"object": "model",
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"created": 1677610602,
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"owned_by": "compactifai"
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}
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]
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}
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with respx.mock() as respx_mock:
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respx_mock.get("https://api.compactif.ai/v1/models").mock(
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return_value=httpx.Response(200, json=mock_response)
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)
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# This would be tested if litellm had a models() function
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# For now, we'll test that the provider is properly configured
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response = litellm.completion(
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model="compactifai/llama-2-7b-compressed",
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messages=[{"role": "user", "content": "test"}],
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api_key="test-key"
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)
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@pytest.mark.respx(base_url="https://api.compactif.ai")
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def test_compactifai_authentication_error():
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"""Test CompactifAI authentication error handling"""
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mock_error = {
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"error": {
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"message": "Invalid API key provided",
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"type": "invalid_request_error",
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"param": None,
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"code": "invalid_api_key"
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}
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}
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with respx.mock() as respx_mock:
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respx_mock.post("https://api.compactif.ai/v1/chat/completions").mock(
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return_value=httpx.Response(401, json=mock_error)
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)
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with pytest.raises(litellm.AuthenticationError):
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litellm.completion(
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model="compactifai/llama-2-7b-compressed",
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messages=[{"role": "user", "content": "test"}],
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api_key="invalid-key"
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)
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@pytest.mark.respx(base_url="https://api.compactif.ai")
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def test_compactifai_provider_detection():
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"""Test that CompactifAI provider is properly detected from model name"""
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from litellm.utils import get_llm_provider
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model, provider, dynamic_api_key, api_base = get_llm_provider(
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model="compactifai/llama-2-7b-compressed"
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)
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assert provider == "compactifai"
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assert model == "llama-2-7b-compressed"
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@pytest.mark.respx(base_url="https://api.compactif.ai")
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def test_compactifai_with_optional_params():
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"""Test CompactifAI with optional parameters like temperature, max_tokens"""
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mock_response = {
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"id": "chatcmpl-123",
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"object": "chat.completion",
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"created": 1677652288,
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"model": "llama-2-7b-compressed",
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"choices": [
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{
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"index": 0,
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"message": {
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"role": "assistant",
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"content": "This is a test response with custom parameters."
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},
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"finish_reason": "stop"
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}
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],
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"usage": {
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"prompt_tokens": 15,
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"completion_tokens": 20,
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"total_tokens": 35
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}
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}
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with respx.mock() as respx_mock:
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request_mock = respx_mock.post("https://api.compactif.ai/v1/chat/completions").mock(
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return_value=httpx.Response(200, json=mock_response)
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)
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response = litellm.completion(
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model="compactifai/llama-2-7b-compressed",
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messages=[{"role": "user", "content": "Hello with params"}],
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api_key="test-key",
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temperature=0.7,
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max_tokens=100,
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top_p=0.9
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)
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assert response.choices[0].message.content == "This is a test response with custom parameters."
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# Verify the request was made with correct parameters
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assert request_mock.called
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request_data = request_mock.calls[0].request.content
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parsed_data = json.loads(request_data)
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assert parsed_data["temperature"] == 0.7
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assert parsed_data["max_tokens"] == 100
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assert parsed_data["top_p"] == 0.9
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@pytest.mark.respx(base_url="https://api.compactif.ai")
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def test_compactifai_headers_authentication():
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"""Test that CompactifAI request includes proper authorization headers"""
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mock_response = {
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"id": "chatcmpl-123",
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"object": "chat.completion",
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"created": 1677652288,
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"model": "llama-2-7b-compressed",
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"choices": [
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{
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"index": 0,
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"message": {
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"role": "assistant",
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"content": "Test response"
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},
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"finish_reason": "stop"
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}
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],
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"usage": {
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"prompt_tokens": 5,
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"completion_tokens": 10,
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"total_tokens": 15
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}
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}
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with respx.mock() as respx_mock:
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request_mock = respx_mock.post("https://api.compactif.ai/v1/chat/completions").mock(
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return_value=httpx.Response(200, json=mock_response)
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)
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response = litellm.completion(
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model="compactifai/llama-2-7b-compressed",
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messages=[{"role": "user", "content": "Test auth"}],
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api_key="test-api-key-123"
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)
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assert response.choices[0].message.content == "Test response"
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# Verify authorization header was set correctly
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assert request_mock.called
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request_headers = request_mock.calls[0].request.headers
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assert "authorization" in request_headers
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assert request_headers["authorization"] == "Bearer test-api-key-123"
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@pytest.mark.asyncio
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@pytest.mark.respx(base_url="https://api.compactif.ai")
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async def test_compactifai_async_completion():
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"""Test CompactifAI async completion"""
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mock_response = {
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"id": "chatcmpl-123",
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"object": "chat.completion",
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"created": 1677652288,
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"model": "llama-2-7b-compressed",
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"choices": [
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{
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"index": 0,
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"message": {
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"role": "assistant",
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"content": "Async response from CompactifAI"
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},
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"finish_reason": "stop"
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}
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],
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"usage": {
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"prompt_tokens": 8,
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"completion_tokens": 15,
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"total_tokens": 23
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}
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}
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with respx.mock() as respx_mock:
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respx_mock.post("https://api.compactif.ai/v1/chat/completions").mock(
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return_value=httpx.Response(200, json=mock_response)
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)
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response = await litellm.acompletion(
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model="compactifai/llama-2-7b-compressed",
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messages=[{"role": "user", "content": "Async test"}],
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api_key="test-key"
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)
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assert response.choices[0].message.content == "Async response from CompactifAI"
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assert response.usage.total_tokens == 23
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