120 lines
4.4 KiB
Python
120 lines
4.4 KiB
Python
from unittest.mock import Mock, patch
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import pytest
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from google.generativeai import GenerationConfig
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from google.generativeai.types import content_types
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from mem0.configs.llms.base import BaseLlmConfig
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from mem0.llms.gemini import GeminiLLM
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@pytest.fixture
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def mock_gemini_client():
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with patch("mem0.llms.gemini.GenerativeModel") as mock_gemini:
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mock_client = Mock()
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mock_gemini.return_value = mock_client
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yield mock_client
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def test_generate_response_without_tools(mock_gemini_client: Mock):
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config = BaseLlmConfig(model="gemini-1.5-flash-latest", temperature=0.7, max_tokens=100, top_p=1.0)
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llm = GeminiLLM(config)
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messages = [
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{"role": "system", "content": "You are a helpful assistant."},
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{"role": "user", "content": "Hello, how are you?"},
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]
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mock_part = Mock(text="I'm doing well, thank you for asking!")
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mock_content = Mock(parts=[mock_part])
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mock_message = Mock(content=mock_content)
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mock_response = Mock(candidates=[mock_message])
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mock_gemini_client.generate_content.return_value = mock_response
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response = llm.generate_response(messages)
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mock_gemini_client.generate_content.assert_called_once_with(
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contents=[
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{"parts": "THIS IS A SYSTEM PROMPT. YOU MUST OBEY THIS: You are a helpful assistant.", "role": "user"},
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{"parts": "Hello, how are you?", "role": "user"},
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],
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generation_config=GenerationConfig(temperature=0.7, max_output_tokens=100, top_p=1.0),
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tools=None,
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tool_config=content_types.to_tool_config(
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{"function_calling_config": {"mode": "auto", "allowed_function_names": None}}
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),
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)
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assert response == "I'm doing well, thank you for asking!"
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def test_generate_response_with_tools(mock_gemini_client: Mock):
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config = BaseLlmConfig(model="gemini-1.5-flash-latest", temperature=0.7, max_tokens=100, top_p=1.0)
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llm = GeminiLLM(config)
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messages = [
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{"role": "system", "content": "You are a helpful assistant."},
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{"role": "user", "content": "Add a new memory: Today is a sunny day."},
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]
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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": "add_memory",
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"description": "Add a memory",
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"parameters": {
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"type": "object",
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"properties": {"data": {"type": "string", "description": "Data to add to memory"}},
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"required": ["data"],
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},
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},
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}
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]
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mock_tool_call = Mock()
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mock_tool_call.name = "add_memory"
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mock_tool_call.args = {"data": "Today is a sunny day."}
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mock_part = Mock()
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mock_part.function_call = mock_tool_call
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mock_part.text = "I've added the memory for you."
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mock_content = Mock()
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mock_content.parts = [mock_part]
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mock_message = Mock()
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mock_message.content = mock_content
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mock_response = Mock(candidates=[mock_message])
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mock_gemini_client.generate_content.return_value = mock_response
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response = llm.generate_response(messages, tools=tools)
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mock_gemini_client.generate_content.assert_called_once_with(
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contents=[
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{"parts": "THIS IS A SYSTEM PROMPT. YOU MUST OBEY THIS: You are a helpful assistant.", "role": "user"},
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{"parts": "Add a new memory: Today is a sunny day.", "role": "user"},
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],
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generation_config=GenerationConfig(temperature=0.7, max_output_tokens=100, top_p=1.0),
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tools=[
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{
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"function_declarations": [
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{
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"name": "add_memory",
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"description": "Add a memory",
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"parameters": {
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"type": "object",
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"properties": {"data": {"type": "string", "description": "Data to add to memory"}},
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"required": ["data"],
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},
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}
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]
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}
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],
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tool_config=content_types.to_tool_config(
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{"function_calling_config": {"mode": "auto", "allowed_function_names": None}}
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),
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)
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assert response["content"] == "I've added the memory for you."
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assert len(response["tool_calls"]) == 1
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assert response["tool_calls"][0]["name"] == "add_memory"
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assert response["tool_calls"][0]["arguments"] == {"data": "Today is a sunny day."}
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