modelfusion VS langchainjs

ModelFusion is an AI integration library that I am developing. It enables you to integrate AI models into your JavaScript and TypeScript applications. You can install it with the following command:

ModelFusion is an open-source library I'm developing to integrate AI models seamlessly into TypeScript projects. It provides an Ollama client and a generateStructure function.

ModelFusion: ModelFusion is a library for building multi-modal AI applications that I've been working on. It provides a streamText function that calls AI models and returns a streaming response. ModelFusion also contains an Ollama integration that we will use to access the OpenHermes 2.5 Mistral model.

You can find the complete code for the chatbot here: github/com/lgrammel/modelfusion/examples/pdf-chat-terminal

I’m working on ModelFusion, a TypeScript library for working with AI models (llm, image, etc.)

https://github.com/lgrammel/modelfusion

It is only getting limited traction so I’m wondering if I’m missing something fundamental with the approach that I’m taking.

If you work with JS or TS, check out this alternative that I've been working on:

https://github.com/lgrammel/modelfusion

It lets you stay in full control over the prompts and control flow while make a lot of things easier and more convenient.

The response also contains additional information such as the metadata and the full response. The ModelFusion documentation contains many examples and demo apps.

*** all code examples are using LangChain TS on the main branch on September 22nd, 2023 (roughly version 0.0.153).

At the time of the prototype's development, the Langchain GitHub loader sent one request per file to fetch the repository sequentially, leading to prolonged download times. In our case about 2 minutes for the insights.opensauced.pizza repository. This issue was later resolved in hwchase17/langchainjs#2224, enabling parallel requests for faster retrieval.

Another llm orchestration library for js/ts

You will probably need to create a custom agent with custom tools to do what you want to do. Look at Langchain (seems like there is an open PR for Google calendar tools here: https://github.com/hwchase17/langchainjs/pull/1777). There are a lot of great integration examples on their website (including for vectorDB memory https://python.langchain.com/docs/modules/memory/how_to/vectorstore_retriever_memory)

You can checkout there docs (here)[https://js.langchain.com/docs/].

The strategy I tried, was to point scalablytyped, at langchainJS.

TL;DR the BANGER TWEET BRAINSToRMER 💥 🐦 🧠 is an open-source, fullstack React/Express/Postgres/Pinecone app that brainstorms new ideas and tweet drafts based on your own notes/ideas and the tweets of your favorite twitter users. This isn't a bot, but you can think of it rather as your personal twitter intern that monitors current twitter **trends**, keeps note of your **ideas**, helps you **brainstorm** new ones, and write **draft** tweets. It's your job to find and edit the best ideas before saving them to your personal notes database or tweeting them out from the app itself. it uses pg-boss cron jobs via Wasp, OpenAI, langChain, and Pinecone for the vector store https://github.com/vincanger/twitter-brainstorming-agent

It is not great. It has a lot of limitations, but can be used under certain conditions. https://github.com/hwchase17/langchainjs/pull/655