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It is a headless LLM chatbot platform built on top of Rasa and Langchain. It is a boilerplate and a reference implementation of Rasa and Telegram utilizing an LLM library like Langchain for indexing, retrieval and context injection. | It is a platform for building production-grade LLM applications. It lets you debug, test, evaluate, and monitor chains and intelligent agents built on any LLM framework and seamlessly integrates with LangChain, the go-to open source framework for building with LLMs. |
Document versioning and automatic “re-training” implemented on upload;
Customize your own async end-points and database models via FastAPI and SQLModel;
Full API documentation via Swagger and Redoc included;
PGAdmin included so you can browse your database | Collaborate with teammates to get app behavior just right;
A unified DevOps platform for your LLM applications;
The platform for your LLM development lifecycle;
Develop with greater visibility |
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GitHub Stars 2.4K | GitHub Stars - |
GitHub Forks 255 | GitHub Forks - |
Stacks 0 | Stacks 11 |
Followers 5 | Followers 6 |
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Integrations | |

The most advanced, consistent, and effective AI humanizer on the market. Instantly transform AI-generated text into undetectable, human-like writing in one click.

Waxell is the AI governance plane for agentic systems in production. It sits above agents, models, and integrations, enforcing constraints and defining what's allowed. Auto-instrumentation for 200+ libraries without code changes. Real-time tracing, token and cost tracking, and 11 categories of agentic governance policy enforcement.

That transforms AI-generated content into natural, undetectable human-like writing. Bypass AI detection systems with intelligent text humanization technology

It is a framework built around LLMs. It can be used for chatbots, generative question-answering, summarization, and much more. The core idea of the library is that we can “chain” together different components to create more advanced use cases around LLMs.

It allows you to run open-source large language models, such as Llama 2, locally.

It is a project that provides a central interface to connect your LLMs with external data. It offers you a comprehensive toolset trading off cost and performance.

It is a library for building stateful, multi-actor applications with LLMs, built on top of (and intended to be used with) LangChain. It extends the LangChain Expression Language with the ability to coordinate multiple chains (or actors) across multiple steps of computation in a cyclic manner.

Transform basic prompts into expert-level AI instructions. Enhance, benchmark & optimize prompts for ChatGPT, Claude, Gemini & more.

Find what caused your AI bill. Opsmeter gives endpoint, user, model, and prompt-level AI cost attribution in one view.
Developer CLI tool for AI content compliance. Stamps files with provenance metadata, audits against EU AI Act, SOX, HIPAA. Integrates with GitHub Actions, pre-commit, and MCP.