Open-source tools
Open-source and local-first AI tools.
This page separates open-source, open-core, and source-available tools from commercial workflow listings so builders can focus on local AI, RAG, inference, coding agents, evaluation, and infrastructure.
Reviewed June 2026
How to use this page
Treat this as the open-source lane of the tools directory. Review each tool profile for licensing, deployment notes, maintenance requirements, alternatives, and links to official documentation.
42 open-source and open-core tools
Coding agent
Cline
Open VS Code coding agent for reviewable file edits, configurable model providers, and agentic coding workflows.
Best for: Developers who want a more controllable AI coding agent workflow.
Tool details →Local runner
Ollama
Run open models locally with a simple CLI, model library, desktop app, and local API.
Best for: Developers who want repeatable local model workflows and simple app integrations.
Tool details →Local runner
Jan
Open-source desktop app for running local AI models with a friendly ChatGPT-like interface.
Best for: Users who want a local-first desktop AI workspace with open-source software.
Tool details →Local runner
GPT4All
Local AI desktop and SDK project for running open models on consumer machines.
Best for: Beginners and teams testing local private chat on desktops.
Tool details →Local runner
llamafile
Mozilla-backed project for packaging LLMs into portable executable files.
Best for: Portable demos, simple local distribution, and experiments where one-file packaging matters.
Tool details →Local runner
llama.cpp
Core C/C++ inference project behind many local GGUF model workflows.
Best for: Low-level local inference, quantized models, CPU/GPU experimentation, and embedded deployments.
Tool details →Chat workspace
Open WebUI
Self-hosted AI platform and chat interface for Ollama and other model backends.
Best for: Private ChatGPT-style workspaces over local or self-hosted models.
Tool details →Chat workspace
AnythingLLM
Open-source AI workspace for document chat, agents, and local or hosted models across desktop, self-hosted, and cloud setups.
Best for: Teams and individuals who want private document chat and multi-user AI workspaces without locking into one model provider.
Tool details →Chat workspace
LibreChat
Open-source multi-provider chat platform with a familiar assistant interface.
Best for: Teams wanting a self-hosted chat UI across multiple model providers.
Tool details →Chat workspace
LobeChat
Open-source modern chat UI for multiple model providers and assistant workflows.
Best for: Builders who want a polished self-hostable chat interface with provider flexibility.
Tool details →Coding assistant
Continue
Open-source AI coding assistant for VS Code and JetBrains with configurable models and context.
Best for: Developers who want a local or provider-flexible coding assistant inside their existing IDE.
Tool details →Coding agent
Aider
Terminal-based AI pair programmer that edits files in your local git repo.
Best for: Developers who like command-line workflows and want AI edits tied to git diffs.
Tool details →Coding agent
Cline
Open-source VS Code coding agent for planning, editing files, and using tools.
Best for: Developers who want an agentic coding workflow inside VS Code.
Tool details →Coding agent
Roo Code
VS Code AI coding agent forked from the Cline ecosystem with multi-mode workflows.
Best for: Developers testing agentic coding modes, custom roles, and local/provider model setups.
Tool details →Coding agent
Kilo Code
Open-source VS Code coding agent focused on agentic development workflows.
Best for: Developers comparing modern Cline-style open coding agents.
Tool details →Coding agent
OpenCode
Terminal-based coding agent for working with models and repositories from the command line.
Best for: Developers who want a CLI-native coding agent experience.
Tool details →Coding assistant
Tabby
Self-hosted AI coding assistant for code completion and team-controlled coding workflows.
Best for: Teams that want more control over code completion infrastructure.
Tool details →RAG and workflow
Flowise
Open-source visual builder for AI agents, chat assistants, RAG flows, and multi-agent systems.
Best for: Builders who want to prototype or deploy agentic workflows visually before stitching everything together in custom code.
Tool details →RAG and workflow
LangChain
Framework ecosystem for LLM apps, agents, tools, retrieval, and observability workflows.
Best for: Developers building custom LLM apps that need integrations and agent patterns.
Tool details →RAG and workflow
LlamaIndex
Data framework for connecting LLMs to documents, databases, retrieval, and agents.
Best for: RAG applications where data ingestion, indexing, and retrieval are central.
Tool details →RAG and workflow
Haystack
Open-source framework for production-style search, RAG, and NLP pipelines.
Best for: Teams building retrieval pipelines with a more engineering-oriented architecture.
Tool details →Agent framework
CrewAI
Framework for orchestrating role-based AI agents and multi-agent workflows.
Best for: Experiments where multiple specialized agents coordinate around tasks.
Tool details →Agent framework
AutoGen
Open-source programming framework from Microsoft for building agentic and multi-agent AI systems.
Best for: Developers exploring multi-agent workflows, tool use, and code-first orchestration patterns.
Tool details →Automation
n8n
Workflow automation platform for connecting AI tools, APIs, databases, and business systems.
Best for: Builders who want AI workflows connected to real business processes and integrations.
Tool details →Vector database
Qdrant
Open-source vector database with strong filtering and production-oriented retrieval features.
Best for: RAG apps that need vector search, metadata filtering, and self-hosted or managed options.
Tool details →Vector database
Chroma
Open-source embedding database commonly used for quick RAG prototypes.
Best for: Small teams and prototypes that need fast local retrieval setup.
Tool details →Vector database
Weaviate
Open-source vector database and AI-native search platform with hybrid search features.
Best for: Teams that want vector search, hybrid search, and managed/self-hosted deployment choices.
Tool details →Vector database
Milvus
Open-source vector database designed for large-scale similarity search.
Best for: Teams planning larger vector search systems and scalable retrieval infrastructure.
Tool details →Vector database
LanceDB
Developer-friendly vector database built around Lance columnar data format workflows.
Best for: AI apps that need local-first or data-lake-friendly vector storage.
Tool details →Vector database
pgvector
PostgreSQL extension for storing embeddings and running vector similarity search.
Best for: Teams that already use Postgres and want a simple RAG database path.
Tool details →Inference serving
vLLM
High-throughput open-source LLM serving engine for production and research workloads.
Best for: Serving open models at higher throughput with batching and OpenAI-compatible APIs.
Tool details →Inference serving
SGLang
Fast serving framework and programming interface for language model applications.
Best for: Serving modern open models with efficient inference and structured generation workflows.
Tool details →Inference serving
Text Generation Inference
Hugging Face server for deploying and serving text generation models.
Best for: Teams already using Hugging Face model workflows and deployment patterns.
Tool details →Inference serving
LiteLLM
Proxy and SDK for routing requests across many LLM providers with OpenAI-compatible interfaces.
Best for: Teams managing multiple model providers, budgets, keys, and routing rules.
Tool details →Inference serving
LocalAI
Open-source OpenAI-compatible local inference server for multiple model types.
Best for: Builders who want a self-hosted local API that mimics OpenAI-style endpoints.
Tool details →Inference serving
BentoML
Model serving platform for packaging, deploying, and operating AI services.
Best for: Teams turning model code into deployable services with repeatable infrastructure.
Tool details →Evaluation and observability
Langfuse
Open-source observability, tracing, prompt management, and evaluation platform for LLM apps.
Best for: Teams shipping LLM apps that need traces, evaluations, prompts, and production visibility.
Tool details →Evaluation and observability
Phoenix
Arize Phoenix is an open-source observability and evaluation tool for LLM and ML systems.
Best for: Teams debugging RAG, tracing LLM calls, and evaluating application behavior.
Tool details →Evaluation and observability
OpenTelemetry
Open standard and ecosystem for traces, metrics, and logs increasingly used in LLM app observability.
Best for: Engineering teams that want AI telemetry to fit existing observability systems.
Tool details →Evaluation and observability
Ragas
Open-source framework for evaluating RAG pipelines and LLM application quality.
Best for: RAG builders who need repeatable retrieval and answer-quality checks.
Tool details →Evaluation and observability
DeepEval
Open-source LLM evaluation framework for unit-testing model outputs and app behavior.
Best for: Developers who want tests around LLM responses, agents, and RAG systems.
Tool details →Image workflows
ComfyUI
Node-based interface for building advanced local image generation workflows.
Best for: Creators and builders who need precise, reusable image generation pipelines.
Tool details →