by stanford-oval · Agent Tool · ★ 50
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ChainLite ChainLite combines LangChain and LiteLLM to provide an easy-to-use and customizable interface for large language model applications. Logo is generated using DALL·E 3. Installation ChainLite has been tested with Python 3.10. To install, do the following: Install ChainLite via pip: or Copy to your project and follow the instructions there to update it with your own configuration. Usage Before you can use Chainlite, you can call the following function to load the configuration file. If you don't, ChainLite will use in the current directory (the directory you are running your script from) by default. Make sure the corresponding API keys are set in environment variables with the name you specified in the configuration file, e.g. etc. Then you can use the following functions in your code: python llmgenerationchain( templatefile: str, engine: str,
| Stars | 50 |
| Forks | 7 |
| Language | Python |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 32.25/100 |
| Open Issues | 4 |
| Last Updated | 2025-09-01 |
| Created | 2024-05-19 |
| Platforms | python |
| Est. Tokens | ~40k |
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chainlite is LangChain + LiteLLM that works. It is categorized as a Agent Tool with 50 GitHub stars.
chainlite is primarily written in Python. It covers topics such as agent, anthropic, gpt.
You can find installation instructions and usage details in the chainlite GitHub repository at github.com/stanford-oval/chainlite. The project has 50 stars and 7 forks, indicating an active community.
chainlite is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
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