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Generative AI TypeScript Clear Filters & Widen Search

Context for your AI agents
Crawl websites, sync to vector databases, and power RAG applications. Pre-built integrations for LLM pipelines and AI assistants.

Build data pipelines that feed your AI models and agents without managing infrastructure. Crawl any website, transform content, and push directly to your preferred vector store. Use 10,000+ tools for RAG applications, AI assistants, and real-time knowledge bases. Monitor site changes, trigger workflows on new data, and keep your AIs fed with fresh, structured information. Cloud-native, API-first, and free to start until you need to scale.

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Create and run cloud-based virtual machines.
Secure and customizable compute service that lets you create and run virtual machines.

Computing infrastructure in predefined or custom machine sizes to accelerate your cloud transformation. General purpose (E2, N1, N2, N2D) machines provide a good balance of price and performance. Compute optimized (C2) machines offer high-end vCPU performance for compute-intensive workloads. Memory optimized (M2) machines offer the highest memory and are great for in-memory databases. Accelerator optimized (A2) machines are based on the A100 GPU, for very demanding applications.

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1

Matrix ChatGPT Bot

Talk to ChatGPT via any Matrix client

Matrix ChatGPT Bot allows you to talk to ChatGPT via any Matrix client. OpenAI released the official API for ChatGPT. Thus, we no longer have to use any older models or any models which kept on being turned off by OpenAI. This means the bot is now way more stable and way faster. However, please note: The usage of the API is no longer free. If you use this bot, your OpenAI account will be charged! You might want to limit your budget in your account using the OpenAI website. You need to remove...

Downloads: 0 This Week

Last Update: 2024-02-21
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2

node-markov-generator

Generates simple sentences based on given text corpus

This simple generator emits short sentences based on the given text corpus using a Markov chain. To put it simply, it works kinda like word suggestions that you have while typing messages in your smartphone. It analyzes which word is followed by which in the given corpus and how often. And then, for any given word it tries to predict what the next one might be. Here you create an instance of TextGenerator passing an array of strings to it - it represents your text corpus which will be used to "train" the generator. ...

Downloads: 0 This Week

Last Update: 2023-03-23
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