ditto190 Goto Github PK

google_generative_language_api

gorilla_api_ai_calling_llm

Gorilla: An API store for LLMs that can call APIs

gpt-crawler

Crawl a site to generate knowledge files to create your own custom GPT from a URL

gpt-pilot

Dev tool that writes scalable apps from scratch while the developer oversees the implementation

gpt-researcher

GPT based autonomous agent that does online comprehensive research on any given topic

grobid

A machine learning software for extracting information from scholarly documents

grobid_client_python

Python client for GROBID Web services

infinity

The AI-native database built for LLM applications, providing incredibly fast full-text and vector search

jan

Jan is an open source alternative to ChatGPT that runs 100% offline on your computer

jcloud

Simplify deploying and managing Jina projects on Jina Cloud

jina

☁️ Build multimodal AI applications with cloud-native stack

knowledge_gpt

Accurate answers and instant citations for your documents.

langchain

⚡ Building applications with LLMs through composability ⚡

langchain-0.1-guides

langchain-quickstart

Build your first LLM powered app with Langchain and Streamlit.

langchain_dart

Build powerful LLM-based Dart/Flutter applications.

langserve

LangServe 🦜️🏓

llama-fs

A self-organizing file system with llama 3

llm-augmenter

llmlingua

To speed up LLMs' inference and enhance LLM's perceive of key information, compress the prompt and KV-Cache, which achieves up to 20x compression with minimal performance loss.

llmware-project

Unified framework for building enterprise RAG pipelines with small, specialized models

lmstudio_llm-configs

LM Studio JSON configuration file format and a collection of example config files.

lmstudio_model-catalog

A collection of standardized JSON descriptors for Large Language Model (LLM) files.

mass

Massdriver CLI

memgpt

Teaching LLMs memory management for unbounded context 📚🦙

metagpt

🌟 The Multi-Agent Framework: Given one line Requirement, return PRD, Design, Tasks, Repo

microservices-reference-implementation

A reference implementation demonstrating microservices architecture and best practices for Microsoft Azure

miyagi

Sample to envision intelligent apps with Microsoft's Copilot stack for AI-infused product experiences.

mlc-llm

Enable everyone to develop, optimize and deploy AI models natively on everyone's devices.

mlops-templates

Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.