forked from MCP/llm-fusion-mcp
Ryan Malloy
c335ba0e1e
- Unified access to 4 major LLM providers (Gemini, OpenAI, Anthropic, Grok) - Real-time streaming support across all providers - Multimodal capabilities (text, images, audio) - Intelligent document processing with smart chunking - Production-ready with health monitoring and error handling - Full OpenAI ecosystem integration (Assistants, DALL-E, Whisper) - Vector embeddings and semantic similarity - Session-based API key management - Built with FastMCP and modern Python tooling 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
80 lines
2.8 KiB
Python
80 lines
2.8 KiB
Python
#!/usr/bin/env python3
|
|
"""Test multi-provider LLM support."""
|
|
|
|
import os
|
|
import sys
|
|
sys.path.insert(0, 'src')
|
|
|
|
from llm_fusion_mcp.server import llm_set_provider, llm_get_provider, llm_list_providers, llm_generate
|
|
from dotenv import load_dotenv
|
|
|
|
load_dotenv()
|
|
|
|
def test_provider_management():
|
|
"""Test provider switching and info."""
|
|
print("Testing provider management...")
|
|
print("=" * 50)
|
|
|
|
# List all providers
|
|
providers = llm_list_providers()
|
|
print("Available providers:")
|
|
for provider, info in providers["providers"].items():
|
|
print(f" {provider}: {info['default_model']} (API key: {'✓' if info['api_key_configured'] else '✗'})")
|
|
|
|
# Get current provider
|
|
current = llm_get_provider()
|
|
print(f"\nCurrent provider: {current['current_provider']}")
|
|
|
|
# Test switching providers
|
|
if os.getenv("ANTHROPIC_API_KEY"):
|
|
print("\nSwitching to Anthropic...")
|
|
result = llm_set_provider("anthropic")
|
|
if result["success"]:
|
|
print(f"✓ Switched to {result['provider']}")
|
|
print(f" Default model: {result['default_model']}")
|
|
print(f" Available models: {len(result['available_models'])} models")
|
|
|
|
# Show Claude 4 models
|
|
claude_4_models = [m for m in result['available_models'] if 'claude-4' in m]
|
|
print(f" Claude 4 models: {claude_4_models}")
|
|
else:
|
|
print(f"✗ Failed: {result['error']}")
|
|
|
|
def test_llm_generate():
|
|
"""Test the new llm_generate function."""
|
|
print("\nTesting llm_generate function...")
|
|
print("=" * 50)
|
|
|
|
prompt = "Write a haiku about coding"
|
|
|
|
# Test with current provider (streaming)
|
|
print("Testing streaming with current provider...")
|
|
try:
|
|
for chunk in llm_generate(prompt, stream=True):
|
|
if chunk.get("success") and chunk.get("type") == "content":
|
|
print(chunk.get("chunk", ""), end="", flush=True)
|
|
elif chunk.get("finished"):
|
|
print(f"\n✓ Generated with {chunk.get('provider')} / {chunk.get('model')}")
|
|
break
|
|
except Exception as e:
|
|
print(f"✗ Error: {e}")
|
|
|
|
# Test provider override
|
|
if os.getenv("GOOGLE_API_KEY"):
|
|
print("\nTesting provider override (Gemini)...")
|
|
try:
|
|
result = llm_generate(prompt, provider="gemini", stream=False)
|
|
if result.get("success"):
|
|
print(f"✓ Generated with {result['provider']} / {result['model']}")
|
|
print(f"Text: {result['text'][:100]}...")
|
|
else:
|
|
print(f"✗ Error: {result.get('error')}")
|
|
except Exception as e:
|
|
print(f"✗ Error: {e}")
|
|
|
|
if __name__ == "__main__":
|
|
test_provider_management()
|
|
test_llm_generate()
|
|
|
|
print("\n" + "=" * 50)
|
|
print("Provider tests completed!") |