Step 2: Project Setup

# Create the project directory and navigate into it
mkdir research-agent
cd research-agent
 
# Create a virtual environment
python -m venv venv
 
# Activate it (Linux/macOS)
source venv/bin/activate
 
# Activate it (Windows)
# venv\Scripts\activate

# Install all required packages
pip install anthropic duckduckgo-search fastapi uvicorn python-dotenv

# Freeze dependencies to a requirements file
pip freeze > requirements.txt

# .env
# Your Anthropic API key — get one at https://console.anthropic.com/
ANTHROPIC_API_KEY=sk-ant-your-key-here

# config.py
# ==========================================
# Configuration — loads API keys from .env
# ==========================================
 
import os
from dotenv import load_dotenv
 
# Load environment variables from .env file
load_dotenv()
 
# Anthropic API key for Claude
ANTHROPIC_API_KEY = os.getenv("ANTHROPIC_API_KEY")
if not ANTHROPIC_API_KEY:
    raise ValueError("ANTHROPIC_API_KEY is not set. Add it to your .env file.")
 
# Model to use — claude-sonnet-4-20250514 is fast and capable
MODEL = "claude-sonnet-4-20250514"
 
# Maximum tokens per response
MAX_TOKENS = 4096

# test_setup.py
# ==========================================
# Quick smoke test — verifies API key works
# ==========================================
 
import anthropic
from config import ANTHROPIC_API_KEY, MODEL
 
# Initialize the client
client = anthropic.Anthropic(api_key=ANTHROPIC_API_KEY)
 
# Make a minimal API call
response = client.messages.create(
    model=MODEL,
    max_tokens=100,
    messages=[{"role": "user", "content": "Say hello in exactly 5 words."}],
)
 
# Print the response
print(response.content[0].text)
print("\nSetup verified — you're ready to build.")

python test_setup.py