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llmapparchitect's Projects

dify icon dify

An Open-Source Assistants API and GPTs alternative. Dify.AI is an LLM application development platform. It integrates the concepts of Backend as a Service and LLMOps, covering the core tech stack required for building generative AI-native applications, including a built-in RAG engine.

douyin_tiktok_download_api icon douyin_tiktok_download_api

🚀「Douyin_TikTok_Download_API」是一个开箱即用的高性能异步抖音、快手、TikTok、Bilibili数据爬取工具,支持API调用,在线批量解析及下载。

evals icon evals

Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.

flowise icon flowise

Drag & drop UI to build your customized LLM flow

flyte icon flyte

Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.

glm icon glm

GLM (General Language Model)

haystack icon haystack

:mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.

internlm icon internlm

Official release of InternLM2 7B and 20B base and chat models. 200K context support

kg-llm-papers icon kg-llm-papers

[Paper List] Papers integrating knowledge graphs (KGs) and large language models (LLMs)

lagent icon lagent

A lightweight framework for building LLM-based agents

langchain icon langchain

⚡ Building applications with LLMs through composability ⚡

langchaingo icon langchaingo

LangChain for Go, the easiest way to write LLM-based programs in Go

langflow icon langflow

⛓️ Langflow is a UI for LangChain, designed with react-flow to provide an effortless way to experiment and prototype flows.

llama2.c icon llama2.c

Inference Llama 2 in one file of pure C

llm-agent-paper-list icon llm-agent-paper-list

The paper list of the 86-page paper "The Rise and Potential of Large Language Model Based Agents: A Survey" by Zhiheng Xi et al.

llm.c icon llm.c

LLM training in simple, raw C/CUDA

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