Check out SearchAugmentedLLM, a new project that empowers Large Language Models by integrating real-time web search capabilities. This tool performs Google searches based on user queries, extracts relevant content, and ranks it for contextualized responses. Ideal for Retrieval Augmented Generation (RAG) applications, it's currently in beta and comes with REST API support. Great for developers looking to improve LLM accuracy with up-to-date information! Explore more on GitHub: https://github.com/EliasPereirah/SearchAugmentedLLM
This is a open source project allows you to use various models, including those from OpenAI itself and some free ones like Google Gemini, Cohere, SambaNova, Groq, and Cerebras.
It's worth noting that Google Gemini is among the best in the LLM Arena.
Why is it free? Google provides a free API with up to 1500 requests per day if it's a Flash model, and 50 requests for the Pro model.
Google isn't the only one; there are several other free options.
All have good models, but i agree with jtbx, Gemini it is very good choice.
Sometimes i use gemini-2.0-flash-exp because the gemini-exp-1206 do not work all the times. I think Google is about to release new models
This OpenSource project allows you to use various models, including those from OpenAI itself and some free ones like Google Gemini, Cohere, SambaNova, Groq, and Cerebras.
It's worth noting that Google Gemini is among the best in the LLM Arena.
Why is it free? Google provides a free API with up to 1500 requests per day if it's a Flash model, and 50 requests for the Pro model.
Google isn't the only one; there are several other free options.