Google has introduced LangExtract, an open-source Python library designed to help developers extract structured information from unstructured text using large language models such as the Gemini models. The library simplifies the process of converting free-form text into structured data, offering features like controlled generation, text chunking, parallel processing, and integration with various LLMs.
This tutorial demonstrates how to integrate Google’s Gemini 2.0 with an in-process Model Context Protocol (MCP) server using FastMCP, creating tools for weather information and integrating them into Gemini's function calling workflow.
A web crawling project using Python, Selenium, Gemini, and Brightdata
- needs slight refactoring for openapi/llama.cpp integration
- needs slight refactoring for openapi/llama.cpp integration
LLM 0.17 release enables multi-modal input, allowing users to send images, audio, and video files to Large Language Models like GPT-4o, Llama, and Gemini, with a Python API and cost-effective pricing.
