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BotSharp
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BotSharp

Active·★ 3.1k·Apache-2.0·Updated 2026-10-13
★ Trending★ Essential

BotSharp is an open-source AI agent application framework written in C# on .NET, meant to connect LLMs to an existing business application. The README lists built-in multi-agent support with conversation and state management, several LLM planning approaches, RAG interfaces with memory-based vector search, agents with different responsibilities cooperating on a task, building, testing, evaluating and auditing agents in one place, a SvelteKit admin UI, rich-content integration with channels such as Facebook Messenger, Slack and Telegram, a REST API plus WebSocket, and MCP integration with visual management.

The kernel is kept small and most functions are plugins. Core modules include a plugin loader, hooks, authentication, agent profiles, conversation and state, routing and planning, templating, caching and LLM providers. Plugins cover data storage (MongoDB, LiteDB), LLMs (OpenAI, Azure OpenAI, Anthropic, Google, DeepSeek, Meta, HuggingFace, LLamaSharp, Semantic Kernel and others), messaging (ChatHub, Messenger, Twilio, Telegram, WeChat), RAG (knowledge base, Qdrant) and vision (PaddleSharp). To try it, run the WebStarter project with `dotnet run` and start the separate BotSharp UI with npm, then open localhost:5015. It is Apache-2.0 licensed.

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Not affiliated with Anthropic, OpenAI or Microsoft.

This write-up is based on the project's README and public repository data. We have not hand-tested the tool. Data as of 2026-10-11.

License
Apache-2.0
Latest release
r5.2-image-composition · 2025-10-17
Last commit
2026-09-29
Contributors
91
Forks
650
Open issues and PRs
51
First published
2017-12-17

Source: GitHub, npm and PyPI public APIs.

#AI Agent#LLM Framework#NLU#.NET#Multi-Agent
$ Install
$ dotnet run --project .\src\WebStarter\WebStarter.csproj -p SolutionName=BotSharp
↗ Visit site★ GitHub
01

Features

01Built-in multi-agents and conversation with state management.
02Support multiple LLM Planning approaches for diverse tasks.
03Built-in RAG interfaces and memory-based vector searching.
04Compatibility with multiple AI platforms (e.g., ChatGPT, Gemini, LLaMA, Claude, DeepSeek, HuggingFace).
05Enables cooperation between multiple agents with distinct responsibilities.
02

Why choose it

+One of the few full agent frameworks for the .NET ecosystem, with a plugin architecture
+Many LLM providers as plugins, including local models through LLamaSharp
+Includes an admin UI, REST API and WebSocket, and chat-channel integrations
+Built-in RAG interfaces, multi-agent routing and planning, and MCP management
03

Trade-offs

!Aimed at .NET developers; teams on other stacks get little from it
!Quick start needs two repositories (backend and UI) and separate runtimes (dotnet and npm)
!The README is a feature and plugin list, with few worked examples
!Part of the README still describes a general machine-learning framework for bot platforms, which can confuse newcomers
04

Compatibility

ChatGPT
Supported
Verified via docs
Gemini
Supported
Verified via docs
LLaMA
Supported
Verified via docs
Claude
Supported
Verified via docs
DeepSeek
Supported
Verified via docs
HuggingFace
Supported
Verified via docs
05

Quick start

1
$ dotnet run --project .\src\WebStarter\WebStarter.csproj -p SolutionName=BotSharp
06

Use cases

↳Developing intelligent robot assistants for information systems.
↳Integrating AI capabilities into existing enterprise business applications.
↳Building custom conversational AI platforms (CaaP) with flexible LLM choices.
07

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Stats
GitHub Stars★ 3.1k
Last commit2d ago
StatusActive
LicenseApache-2.0
CategoryMulti-Agent
Trend (30d)
+0.1k↑ 4.8%
Links
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