config/README.md

LLM Configuration Guide

This directory contains centralized LLM configuration for the CrewAI Data Analyst application.

Quick Start

1. Choose Your LLM Provider

Set the LLM_PROVIDER environment variable (in Replit Secrets or .env file):

LLM_PROVIDER=groq  # Options: groq, openai, ollama, anthropic

2. Add Your API Key

Add the corresponding API key to Replit Secrets:

Provider	API Key Variable	Get Key From
Groq (Default)	GROQ_API_KEY	https://console.groq.com/keys
OpenAI	OPENAI_API_KEY	https://platform.openai.com/api-keys
Anthropic	ANTHROPIC_API_KEY	https://console.anthropic.com/
Ollama	OLLAMA_BASE_URL	http://localhost:11434 (local)

3. Restart the Application

After changing providers, restart the workflow to apply changes.

Supported Providers

🚀 Groq (Recommended)

• Model: llama-3.3-70b-versatile
• Speed: Very fast
• Cost: Low
• Best for: Production use, fast responses

LLM_PROVIDER=groq
GROQ_API_KEY=gsk_...

🤖 OpenAI

• Model: gpt-4o-mini
• Speed: Fast
• Cost: Medium
• Best for: High-quality responses

LLM_PROVIDER=openai
OPENAI_API_KEY=sk-...

🏠 Ollama (Local)

• Model: llama3
• Speed: Depends on hardware
• Cost: Free (runs locally)
• Best for: Privacy, offline use

LLM_PROVIDER=ollama
OLLAMA_BASE_URL=http://localhost:11434

🧠 Anthropic Claude

• Model: claude-3-5-sonnet-20241022
• Speed: Fast
• Cost: Medium
• Best for: Complex reasoning tasks

LLM_PROVIDER=anthropic
ANTHROPIC_API_KEY=sk-ant-...

How It Works

The llm_config.py file provides a centralized configuration system that:

1. Reads environment variables to determine which LLM provider to use
2. Validates credentials before initializing agents
3. Returns standardized config that works with all CrewAI agents
4. Allows easy switching between providers without code changes

Code Example

All agents automatically use the centralized config:

from crewai import Agent, LLM
from config.llm_config import get_llm_params

my_agent = Agent(
    name="My Agent",
    role="My Role",
    llm=LLM(**get_llm_params()),  # Automatically uses configured provider
    verbose=True
)

Customizing Models

To use a different model for a specific provider, edit config/llm_config.py:

GROQ_CONFIG = {
    "model": "groq/llama-3.1-8b-instant",  # Change this
    "api_key": os.getenv("GROQ_API_KEY"),
}

Troubleshooting

Error: "Invalid LLM provider"

• Check that LLM_PROVIDER is set to one of: groq, openai, ollama, anthropic

Error: "API_KEY environment variable is not set"

• Make sure you've added the API key to Replit Secrets
• Restart the workflow after adding secrets

Error: "Connection refused" (Ollama)

• Make sure Ollama is running locally
• Check that OLLAMA_BASE_URL points to the correct address

Security Notes

• Never commit API keys to version control
• Always use Replit Secrets or environment variables
• The .env.example file is safe to commit (contains no real keys)