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Top 23 TypeScript llm Projects
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dify
Dify is an open-source LLM app development platform. Dify's intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features and more, letting you quickly go from prototype to production.
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SurveyJS
Open-Source JSON Form Builder to Create Dynamic Forms Right in Your App. With SurveyJS form UI libraries, you can build and style forms in a fully-integrated drag & drop form builder, render them in your JS app, and store form submission data in any backend, inc. PHP, ASP.NET Core, and Node.js.
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FastGPT
FastGPT is a knowledge-based platform built on the LLMs, offers a comprehensive suite of out-of-the-box capabilities such as data processing, RAG retrieval, and visual AI workflow orchestration, letting you easily develop and deploy complex question-answering systems without the need for extensive setup or configuration.
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web-llm
Bringing large-language models and chat to web browsers. Everything runs inside the browser with no server support.
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activepieces
Your friendliest open source all-in-one automation tool ✨ Workflow automation tool 100+ integration / Enterprise automation tool / Zapier Alternative
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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CopilotKit
A framework for building custom AI Copilots 🤖 in-app AI chatbots, in-app AI Agents, & AI-powered Textareas.
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RWKV-Runner
A RWKV management and startup tool, full automation, only 8MB. And provides an interface compatible with the OpenAI API. RWKV is a large language model that is fully open source and available for commercial use.
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reader
Convert any URL to an LLM-friendly input with a simple prefix https://r.jina.ai/ (by jina-ai)
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FreedomGPT
This codebase is for a React and Electron-based app that executes the FreedomGPT LLM locally (offline and private) on Mac and Windows using a chat-based interface
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obsidian-textgenerator-plugin
Text generator is a handy plugin for Obsidian that helps you generate text content using GPT-3 (OpenAI).
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
Project mention: Dify, a visual workflow to build/test LLM applications | news.ycombinator.com | 2024-04-22> https://github.com/langgenius/dify/blob/main/LICENSE
everyone is apparently a license pioneer
Project mention: What stack would you recommend to build a LLM app in React without a backend? | /r/react | 2023-12-08
Project mention: Building a SQL Expert Bot: A Step-by-Step Guide with Vercel AI SDK and OpenAI API | dev.to | 2024-03-05The Vercel AI SDK is built for OpenAI APIs and includes a range of tools for utilizing OpenAI APIs.
Project mention: A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev | dev.to | 2024-02-05Activepieces - Build automation flows to connect several apps together in your app's backend. For example, send a Slack message or add a Google Sheet row when an event fires in your app. Free up to 5,000 tasks per month.
Project mention: Show HN: Add AI code interpreter to any LLM via SDK | news.ycombinator.com | 2024-04-12Hi, I'm the CEO of the company that built this SDK.
We're a company called E2B [0]. We're building and open-source [1] secure environments for running untrusted AI-generated code and AI agents. We call these environments sandboxes and they are built on top of micro VM called Firecracker [2].
You can think of us as giving small cloud computers to LLMs.
We recently created a dedicated SDK for building custom code interpreters in Python or JS/TS. We saw this need after a lot of our users have been adding code execution capabilities to their AI apps with our core SDK [3]. These use cases were often centered around AI data analysis so code interpreter-like behavior made sense
The way our code interpret SDK works is by spawning an E2B sandbox with Jupyter Server. We then communicate with this Jupyter server through Jupyter Kernel messaging protocol [4].
We don't do any wrapping around LLM, any prompting, or any agent-like framework. We leave all of that on users. We're really just a boring code execution layer that sats at the bottom that we're building specifically for the future software that will be building another software. We work with any LLM. Here's how we added code interpreter to Claude [5].
Our long-term plan is to build an automated AWS for AI apps and agents.
Happy to answer any questions and hear feedback!
[0] https://e2b.dev/
[1] https://github.com/e2b-dev
[2] https://github.com/firecracker-microvm/firecracker
[3] https://e2b.dev/docs
[4] https://jupyter-client.readthedocs.io/en/latest/messaging.ht...
[5] https://github.com/e2b-dev/e2b-cookbook/blob/main/examples/c...
chainlit is open source project that makes it very easy to build frontend interfaces like chatgpt and other features that are required for conversational ai app, so we can focus on the core part and don't need to worry about basic things, and it is dead simple to work with
Designed to alleviate exactly the pain points in the article.
Devs define simple Copilot entrypoints into state (frontend + backend + 3rd party), action, purpose-specific LLM chains, etc. And the CopilotKit engine takes care of the rest.
https://github.com/CopilotKit/CopilotKit
Project mention: Jina Reader: Convert any URL to an LLM-friendly input | news.ycombinator.com | 2024-04-17
But now coming to today's tool, let's talk about a topic that comes and goes, but it's always fun to play around with. I'm referring to AI; as you know, I'm not an AI-addicted person, but I like to have my share of fun with it! And a few days ago I came across the program that I am presenting to you today which aims to be very interesting and fun! Rivet, this is the name of the tool of this week, is a visual development environment for AI agents. But in what sense? Well, once you download the software, you will have a drag and drop interface to create a flow of information that can interact with various LLMs, whether it's GPT, Google models, or even Open models like Ollama running locally. It can handle all the classic control flows (if, loop etc.) and can integrate JS functions directly into it or import them from the project where we decide to incorporate it.
Project mention: Ask HN: How does deploying a fine-tuned model work | news.ycombinator.com | 2024-04-23- Fireworks: $0.20
If you're looking for an end-to-end flow that will help you gather the training data, validate it, run the fine tune and then define evaluations, you could also check out my company, OpenPipe (https://openpipe.ai/). In addition to hosting your model, we help you organize your training data, relabel if necessary, define evaluations on the finished fine-tune, and monitor its performance in production. Our inference prices are higher than the above providers, but once you're happy with your model you can always export your weights and host them on one of the above!
Project mention: Tutorial: Extracting structured data from websites using Groq and Firecrawl | news.ycombinator.com | 2024-04-22
4️⃣ React Agent 🕵️♂️
Project mention: Rebuff: Detect and protect against prompt injection attacks in LLMs | news.ycombinator.com | 2023-07-05
TypeScript llm related posts
- Show HN: Langtrace – OpenTelemetry-Based LLM App Observability
- WrenAI: Open-Source Natural Language Interface to Your Data
- Dify, an end-to-end, visualized workflow to build/test LLM applications
- Chat with your Github Repo using llama_index and chainlit
- Rivet - JS, AI and the agent builder we deserve
- I accidentally built a meme search engine
- Agent Cloud VS OpenAI
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A note from our sponsor - SurveyJS
surveyjs.io | 28 Apr 2024
Index
What are some of the best open-source llm projects in TypeScript? This list will help you:
Project | Stars | |
---|---|---|
1 | Flowise | 24,074 |
2 | dify | 23,073 |
3 | FastGPT | 12,707 |
4 | botpress | 11,954 |
5 | web-llm | 9,102 |
6 | ai | 7,726 |
7 | activepieces | 7,153 |
8 | E2B | 6,076 |
9 | chainlit | 5,401 |
10 | CopilotKit | 4,618 |
11 | RWKV-Runner | 4,488 |
12 | reader | 3,244 |
13 | databerry | 2,863 |
14 | FreedomGPT | 2,547 |
15 | rivet | 2,385 |
16 | OpenPipe | 2,367 |
17 | chat-with-gpt | 2,258 |
18 | firecrawl | 1,659 |
19 | react-agent | 1,303 |
20 | obsidian-textgenerator-plugin | 1,260 |
21 | axflow | 1,085 |
22 | hash | 951 |
23 | rebuff | 921 |
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