langroid
modelfusion
langroid | modelfusion | |
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15 | 18 | |
1,698 | 962 | |
21.4% | 13.2% | |
9.8 | 9.9 | |
1 day ago | 4 days ago | |
Python | TypeScript | |
MIT License | MIT License |
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langroid
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OpenAI: Streaming is now available in the Assistants API
This was indeed true in the beginning, and I don’t know if this has changed. Inserting messages with Assistant role is crucial for many reasons, such as if you want to implement caching, or otherwise edit/compress a previous assistant response for cost or other reason.
At the time I implemented a work-around in Langroid[1]: since you can only insert a “user” role message, prepend the content with ASSISTANT: whenever you want it to be treated as an assistant role. This actually works as expected and I was able to do caching. I explained it in this forum:
https://community.openai.com/t/add-custom-roles-to-messages-...
[1] the Langroid code that adds a message with a given role, using this above “assistant spoofing trick”:
https://github.com/langroid/langroid/blob/main/langroid/agen...
- FLaNK Stack 29 Jan 2024
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Ollama Python and JavaScript Libraries
Same question here. Ollama is fantastic as it makes it very easy to run models locally, But if you already have a lot of code that processes OpenAI API responses (with retry, streaming, async, caching etc), it would be nice to be able to simply switch the API client to Ollama, without having to have a whole other branch of code that handles Alama API responses. One way to do an easy switch is using the litellm library as a go-between but it’s not ideal (and I also recently found issues with their chat formatting for mistral models).
For an OpenAI compatible API my current favorite method is to spin up models using oobabooga TGW. Your OpenAI API code then works seamlessly by simply switching out the api_base to the ooba endpoint. Regarding chat formatting, even ooba’s Mistral formatting has issues[1] so I am doing my own in Langroid using HuggingFace tokenizer.apply_chat_template [2]
[1] https://github.com/oobabooga/text-generation-webui/issues/53...
[2] https://github.com/langroid/langroid/blob/main/langroid/lang...
Related question - I assume ollama auto detects and applies the right chat formatting template for a model?
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Pushing ChatGPT's Structured Data Support to Its Limits
we (like simpleaichat from OP) leverage Pydantic to specify the desired structured output, and under the hood Langroid translates it to either the OpenAI function-calling params or (for LLMs that don’t natively support fn-calling), auto-insert appropriate instructions into tje system-prompt. We call this mechanism a ToolMessage:
https://github.com/langroid/langroid/blob/main/langroid/agen...
We take this idea much further — you can define a method in a ChatAgent to “handle” the tool and attach the tool to the agent. For stateless tools you can define a “handle” method in the tool itself and it gets patched into the ChatAgent as the handler for the tool.
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Ask HN: How do I train a custom LLM/ChatGPT on my own documents in Dec 2023?
Many services/platforms are careless/disingenuous when they claim they “train” on your documents, where they actually mean they do RAG.
An under-appreciate benefit of RAG is the ability to have the LLM cite sources for its answers (which are in principle automatically/manually verifiable). You lose this citation ability when you finetune on your documents.
In Langroid (the Multi-Agent framework from ex-CMU/UW-Madison researchers) https://github.com/langroid/langroid
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Build a search engine, not a vector DB
This resonates with the approach we’ve taken in Langroid (the Multi-Agent framework from ex-CMU/UW-Madison researchers): our DocChatAgent uses a combination of lexical and semantic retrieval, reranking and relevance extraction to improve precision and recall:
https://github.com/langroid/langroid/blob/main/langroid/agen...
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HuggingChat – ChatGPT alternative with open source models
In the Langroid library (a multi-agent framework from ex-CMU/UW-Madison researchers) we have these and more. For example here’s a script that combines web search and RAG:
https://github.com/langroid/langroid/blob/main/examples/docq...
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SuperDuperDB - how to use it to talk to your documents locally using llama 7B or Mistral 7B?
Thanks, also found Langdroid: https://github.com/langroid/langroid/blob/main/README.md
- memory in ConversationalRetrievalChain removed
- [D] github repositories for ai web search agents
modelfusion
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Next.js and GPT-4: A Guide to Streaming Generated Content as UI Components
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:
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Effortlessly Generate Structured Information with Ollama, Zod, and ModelFusion
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.
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Create Your Own Local Chatbot with Next.js, Ollama, and ModelFusion
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.
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PDF Chat with Node.js, OpenAI and ModelFusion
You can find the complete code for the chatbot here: github/com/lgrammel/modelfusion/examples/pdf-chat-terminal
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Ask HN: Tell us about your project that's not done yet but you want feedback on
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.
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LangChain Agent Simulation – Multi-Player Dungeons and Dragons
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.
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Introducing ModelFusion: Build AI apps with JavaScript and TypeScript.
The response also contains additional information such as the metadata and the full response. The ModelFusion documentation contains many examples and demo apps.
- Show HN: AI-utils.js – TypeScript-first lib for AI apps, chatbots, and agents
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ai-utils.js VS langchainjs - a user suggested alternative
2 projects | 26 Jul 2023
- ai-utils.js: TypeScript-first library for building AI apps, chatbots, and agents.
What are some alternatives?
simpleaichat - Python package for easily interfacing with chat apps, with robust features and minimal code complexity.
langchainjs - 🦜🔗 Build context-aware reasoning applications 🦜🔗
autogen - A programming framework for agentic AI. Discord: https://aka.ms/autogen-dc. Roadmap: https://aka.ms/autogen-roadmap
aipl - Array-Inspired Pipeline Language
vectordb - A minimal Python package for storing and retrieving text using chunking, embeddings, and vector search.
hamilton - Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage and metadata. Runs and scales everywhere python does.
Adala - Adala: Autonomous DAta (Labeling) Agent framework
async-interval-job - ✨ setInterval for promises and async/sync functions. Support graceful shutdown and prevent multiple executions from overlapping in time.
chidori - A reactive runtime for building durable AI agents
chatflow - Leveraging LLM to build Conversational UIs
outlines - Structured Text Generation
meta-parser - Universal meta-tag scrapper for Node.js. Works both with CJS and ESM modules.