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dc893fb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 | """Test cases for LLM wrapper client."""
import asyncio
from pathlib import Path
import pytest
import yaml
from mini_agent.llm import LLMClient
from mini_agent.schema import LLMProvider, Message
@pytest.mark.asyncio
async def test_wrapper_anthropic_provider():
"""Test LLM wrapper with Anthropic provider."""
print("\n=== Testing LLM Wrapper (Anthropic Provider) ===")
# Load config
config_path = Path("mini_agent/config/config.yaml")
with open(config_path, encoding="utf-8") as f:
config = yaml.safe_load(f)
# Create client with Anthropic provider
client = LLMClient(
api_key=config["api_key"],
provider=LLMProvider.ANTHROPIC,
api_base=config.get("api_base"),
model=config.get("model"),
)
assert client.provider == LLMProvider.ANTHROPIC
# Simple messages
messages = [
Message(role="system", content="You are a helpful assistant."),
Message(role="user", content="Say 'Hello, Mini Agent!' and nothing else."),
]
try:
response = await client.generate(messages=messages)
print(f"Response: {response.content}")
print(f"Finish reason: {response.finish_reason}")
assert response.content, "Response content is empty"
assert "Hello" in response.content or "hello" in response.content, (
f"Response doesn't contain 'Hello': {response.content}"
)
print("✅ Anthropic provider test passed")
return True
except Exception as e:
print(f"❌ Anthropic provider test failed: {e}")
import traceback
traceback.print_exc()
return False
@pytest.mark.asyncio
async def test_wrapper_openai_provider():
"""Test LLM wrapper with OpenAI provider."""
print("\n=== Testing LLM Wrapper (OpenAI Provider) ===")
# Load config
config_path = Path("mini_agent/config/config.yaml")
with open(config_path, encoding="utf-8") as f:
config = yaml.safe_load(f)
# Create client with OpenAI provider
client = LLMClient(
api_key=config["api_key"],
provider=LLMProvider.OPENAI,
model=config.get("model"),
)
assert client.provider == LLMProvider.OPENAI
# Simple messages
messages = [
Message(role="system", content="You are a helpful assistant."),
Message(role="user", content="Say 'Hello, Mini Agent!' and nothing else."),
]
try:
response = await client.generate(messages=messages)
print(f"Response: {response.content}")
print(f"Finish reason: {response.finish_reason}")
assert response.content, "Response content is empty"
assert "Hello" in response.content or "hello" in response.content, (
f"Response doesn't contain 'Hello': {response.content}"
)
print("✅ OpenAI provider test passed")
return True
except Exception as e:
print(f"❌ OpenAI provider test failed: {e}")
import traceback
traceback.print_exc()
return False
@pytest.mark.asyncio
async def test_wrapper_default_provider():
"""Test LLM wrapper with default provider (Anthropic)."""
print("\n=== Testing LLM Wrapper (Default Provider) ===")
# Load config
config_path = Path("mini_agent/config/config.yaml")
with open(config_path, encoding="utf-8") as f:
config = yaml.safe_load(f)
# Create client without specifying provider (should default to Anthropic)
client = LLMClient(
api_key=config["api_key"],
model=config.get("model"),
)
assert client.provider == LLMProvider.ANTHROPIC
print("✅ Default provider is Anthropic")
return True
@pytest.mark.asyncio
async def test_wrapper_tool_calling():
"""Test LLM wrapper with tool calling."""
print("\n=== Testing LLM Wrapper Tool Calling ===")
# Load config
config_path = Path("mini_agent/config/config.yaml")
with open(config_path, encoding="utf-8") as f:
config = yaml.safe_load(f)
# Create client with Anthropic provider
client = LLMClient(
api_key=config["api_key"],
provider=LLMProvider.ANTHROPIC,
model=config.get("model"),
)
# Messages requesting tool use
messages = [
Message(
role="system", content="You are a helpful assistant with access to tools."
),
Message(role="user", content="Calculate 123 + 456 using the calculator tool."),
]
# Define a simple calculator tool using dict format
tools = [
{
"name": "calculator",
"description": "Perform arithmetic operations",
"input_schema": {
"type": "object",
"properties": {
"operation": {
"type": "string",
"enum": ["add", "subtract", "multiply", "divide"],
"description": "The operation to perform",
},
"a": {
"type": "number",
"description": "First number",
},
"b": {
"type": "number",
"description": "Second number",
},
},
"required": ["operation", "a", "b"],
},
}
]
try:
response = await client.generate(messages=messages, tools=tools)
print(f"Response: {response.content}")
print(f"Tool calls: {response.tool_calls}")
print(f"Finish reason: {response.finish_reason}")
if response.tool_calls:
print("✅ Tool calling test passed - LLM requested tool use")
else:
print("⚠️ Warning: LLM didn't use tools, but request succeeded")
return True
except Exception as e:
print(f"❌ Tool calling test failed: {e}")
import traceback
traceback.print_exc()
return False
async def main():
"""Run all LLM wrapper tests."""
print("=" * 80)
print("Running LLM Wrapper Tests")
print("=" * 80)
print("\nNote: These tests require a valid MiniMax API key in config.yaml")
results = []
# Test default provider
results.append(await test_wrapper_default_provider())
# Test Anthropic provider
results.append(await test_wrapper_anthropic_provider())
# Test OpenAI provider
results.append(await test_wrapper_openai_provider())
# Test tool calling
results.append(await test_wrapper_tool_calling())
print("\n" + "=" * 80)
if all(results):
print("All LLM wrapper tests passed! ✅")
else:
print("Some LLM wrapper tests failed. Check the output above.")
print("=" * 80)
if __name__ == "__main__":
asyncio.run(main())
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