Update contribution and setup docs for LLM configuration

Improved instructions in CONTRIBUTING.md and README.md for setting up the development environment, running tests, and configuring LLM providers. Added details on using mock API keys for testing, clarified environment variable requirements, and provided guidance for integrating with alternative LLM providers and optillm.

Author: codelion

CONTRIBUTING.md

@@ -6,8 +6,15 @@ Thank you for your interest in contributing to OpenEvolve! This document provide
 
 1. Fork the repository
 2. Clone your fork: `git clone https://github.com/codelion/openevolve.git`
-3. Install the package in development mode: `pip install -e .`
-4. Run the tests to ensure everything is working: `python -m unittest discover tests`
+3. Install the package in development mode: `pip install -e ".[dev]"`
+4. Set up environment for testing:
+   ```bash
+   # Unit tests don't require a real API key, but the environment variable must be set
+   export OPENAI_API_KEY=test-key-for-unit-tests
+   ```
+5. Run the tests to ensure everything is working: `python -m unittest discover tests`
+
+**Note**: The unit tests do not make actual API calls to OpenAI or any LLM provider. However, the `OPENAI_API_KEY` environment variable must be set to any non-empty value for the tests to run. You can use a placeholder value like `test-key-for-unit-tests`.
 
 ## Development Environment
 
@@ -17,14 +24,32 @@ We recommend using a virtual environment for development:
 python -m venv env
 source env/bin/activate  # On Windows: env\Scripts\activate
 pip install -e ".[dev]"
+
+# For running tests (no actual API calls are made)
+export OPENAI_API_KEY=test-key-for-unit-tests
+
+# For testing with real LLMs during development
+# export OPENAI_API_KEY=your-actual-api-key
 ```
 
+### LLM Configuration for Development
+
+When developing features that interact with LLMs:
+
+1. **Local Development**: Use a mock API key for unit tests
+2. **Integration Testing**: Use your actual API key and configure `api_base` if using alternative providers
+3. **Cost Management**: Consider using cheaper models or [optillm](https://github.com/codelion/optillm) for rate limiting during development
+
 ## Pull Request Process
 
 1. Create a new branch for your feature or bugfix: `git checkout -b feat-your-feature-name`
 2. Make your changes
 3. Add tests for your changes
-4. Run the tests to make sure everything passes: `python -m unittest discover tests`
+4. Run the tests to make sure everything passes:
+   ```bash
+   export OPENAI_API_KEY=test-key-for-unit-tests
+   python -m unittest discover tests
+   ```
 5. Commit your changes: `git commit -m "Add your descriptive commit message"`
 6. Push to your fork: `git push origin feature/your-feature-name`
 7. Submit a pull request to the main repository

README.md

@@ -42,13 +42,41 @@ pip install -e .
 
 ### Quick Start
 
-We use the OpenAI SDK, so you can use any LLM or provider that supports an OpenAI compatible API. Just set the `OPENAI_API_KEY` environment variable
-and update the `api_base` in config.yaml if you are using a provider other than OpenAI. For local models, you can use
-an inference server like [optillm](https://github.com/codelion/optillm).
+#### Setting up LLM Access
+
+OpenEvolve uses the OpenAI SDK, which means it works with any LLM provider that supports an OpenAI-compatible API:
+
+1. **Set the API Key**: Export the `OPENAI_API_KEY` environment variable:
+   ```bash
+   export OPENAI_API_KEY=your-api-key-here
+   ```
+
+2. **Using Alternative LLM Providers**: 
+   - For providers other than OpenAI (e.g., Anthropic, Cohere, local models), update the `api_base` in your config.yaml:
+   ```yaml
+   llm:
+     api_base: "https://your-provider-endpoint.com/v1"
+   ```
+   
+3. **Maximum Flexibility with optillm**: 
+   - For advanced routing, rate limiting, or using multiple providers, we recommend [optillm](https://github.com/codelion/optillm)
+   - optillm acts as a proxy that can route requests to different LLMs based on your rules
+   - Simply point `api_base` to your optillm instance:
+   ```yaml
+   llm:
+     api_base: "http://localhost:8000/v1"
+   ```
+
+This setup ensures OpenEvolve can work with any LLM provider - OpenAI, Anthropic, Google, Cohere, local models via Ollama/vLLM, or any OpenAI-compatible endpoint.
 
 ```python
+import os
 from openevolve import OpenEvolve
 
+# Ensure API key is set
+if not os.environ.get("OPENAI_API_KEY"):
+    raise ValueError("Please set OPENAI_API_KEY environment variable")
+
 # Initialize the system
 evolve = OpenEvolve(
     initial_program_path="path/to/initial_program.py",