Welcome to ChatFlare, a Lightning framework for building and prototying Large Language Models (LLM) applications with ease and efficiency. Inspired by the powerful usage of Langchain but with much less abstraction, ChatFlare aims to provide a streamlined and modular approach to working with LLM chains.
ChatFlare is designed to simplify the process of integrating and managing LLMs in your applications. By abstracting away the complexity and providing a clean, intuitive interface, ChatFlare allows developers to focus on building innovative solutions without getting bogged down by intricate details.
- Modular Design: Easily integrate various LLM components and functionalities as needed.
- Lightning-fast Performance: Optimized for speed and efficiency, ensuring your applications run smoothly.
- User-friendly API: Intuitive and easy-to-use, making it accessible for both beginners and experienced developers.
- Scalability: Built to handle applications of all sizes, from small projects to large-scale deployments.
- Community-driven: Open-source and community-driven, with a focus on continuous improvement and collaboration.
To install ChatFlare, simply run:
pip install chatflareHere's a quick example to get you started with ChatFlare:
import chatflare as cf
# Initialize your ChatFlare environment
env = cf.Environment()
# Load your preferred LLM model
model = cf.models.load_model('your-llm-model')
# Create a prompt
prompt = "What is the capital of France?"
# Generate a response
response = model.generate(prompt)
print(response)For detailed documentation and tutorials, please visit our official documentation.
We welcome contributions from the community! If you would like to contribute to ChatFlare, please read our contributing guidelines and check out our open issues.
ChatFlare is released under the MIT License.
For any questions or inquiries, please feel free to reach out to us at [email protected].
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