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#!/usr/bin/env python3
"""
Quick test to verify LLM integration is working
"""
import os
from dotenv import load_dotenv
from agent.llm_client import LLMClient, LLMMessage
from agent.consultation import NetworkConsultant
# Load environment variables
load_dotenv()
print("=" * 60)
print("Testing LLM Integration")
print("=" * 60)
# Test 1: Check API keys
print("\n1. Checking API keys...")
anthropic_key = os.getenv("ANTHROPIC_API_KEY")
openai_key = os.getenv("OPENAI_API_KEY")
if anthropic_key:
print(f"✅ Anthropic API key found: {anthropic_key[:20]}...")
else:
print("❌ Anthropic API key not found")
if openai_key:
print(f"✅ OpenAI API key found: {openai_key[:20]}...")
else:
print("⚠️ OpenAI API key not found (optional)")
# Test 2: Initialize LLM client
print("\n2. Initializing LLM client...")
llm = LLMClient()
print(f"✅ LLM client initialized with provider: {llm.provider}")
# Test 3: Simple chat test
print("\n3. Testing basic chat completion...")
try:
messages = [
LLMMessage(role="user", content="Reply with just 'Hello from Overgrowth!' and nothing else.")
]
response = llm.chat(messages, temperature=0.1)
print(f"✅ Response received: {response[:100]}")
except Exception as e:
print(f"❌ Chat test failed: {e}")
# Test 4: Test consultation
print("\n4. Testing network consultation...")
try:
consultant = NetworkConsultant()
test_input = """
We're a coffee shop chain with 3 locations. We need WiFi for customers,
POS systems with payment processing, security cameras, and secure VPN to HQ
for centralized management. Each location has ~50 customers at peak time.
"""
is_complete, output, intent = consultant.start_consultation(test_input)
if is_complete:
print("✅ Consultation completed immediately")
print(f"\nIntent captured:\n{output}")
else:
print("✅ Consultation started - follow-up questions:")
print(f"\n{output}")
except Exception as e:
print(f"❌ Consultation test failed: {e}")
import traceback
traceback.print_exc()
print("\n" + "=" * 60)
print("LLM Integration Test Complete!")
print("=" * 60)
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