Showing 8 open source projects for "python text"

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    Train ML Models With SQL You Already Know

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  • 1
    Parlant

    Parlant

    The behavior guidance framework for customer-facing LLM agents

    Parlant is a lightweight speech-to-text and text-to-speech framework designed for real-time AI-driven voice applications.
    Downloads: 9 This Week
    Last Update:
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  • 2
    DeerFlow

    DeerFlow

    Deep Research framework, combining language models with tools

    DeerFlow is an open-source, community-driven “deep research” framework / multi-agent orchestration platform developed by ByteDance. It aims to combine the reasoning power of large language models (LLMs) with automated tool-use — such as web search, web crawling, Python execution, and data processing — to enable complex, end-to-end research workflows. Instead of a monolithic AI assistant, DeerFlow defines multiple specialized agents (e.g. “planner,” “searcher,” “coder,” “report generator”)...
    Downloads: 34 This Week
    Last Update:
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  • 3
    Bolna

    Bolna

    Conversational voice AI agents

    Bolna is an end-to-end open-source platform for building conversational voice AI agents, enabling developers to create voice-first conversational assistants efficiently.
    Downloads: 6 This Week
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  • 4
    TEN

    TEN

    Open-source framework for conversational voice AI agents

    TEN (Transformative Extensions Network) is an open source framework designed to empower developers to build real-time multimodal AI agents capable of voice, video, text, image, and data-stream interaction with ultra-low latency. It includes a full ecosystem, TEN Turn Detection, TEN Agent, and TMAN Designer, allowing developers to rapidly assemble human-like, responsive agents that can see, speak, hear, and interact. With support for languages like Python, C++, and Go, it offers flexible deployment on both edge and cloud environments. ...
    Downloads: 5 This Week
    Last Update:
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    99.99% Uptime for MySQL and PostgreSQL Databases

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  • 5
    cognee

    cognee

    Deterministic LLMs Outputs for AI Applications and AI Agents

    Cognee implements scalable, modular data pipelines that allow for creating the LLM-enriched data layer using graph and vector stores. Cognee acts a semantic memory layer, unveiling hidden connections within your data and infusing it with your company's language and principles. This self-optimizing process ensures ultra-relevant, personalized, and contextually aware LLM retrievals. Any kind of data works; unstructured text or raw media files, PDFs, tables, presentations, JSON files, and so...
    Downloads: 8 This Week
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  • 6
    Open-AutoGLM

    Open-AutoGLM

    An open phone agent model & framework

    Open-AutoGLM is an open-source framework and model designed to empower autonomous mobile intelligent assistants by enabling AI agents to understand and interact with phone screens in a multimodal manner, blending vision and language capability to control real devices. It aims to create an “AI phone agent” that can perceive on-screen content, reason about user goals, and execute sequences of taps, swipes, and text input via automated device control interfaces like ADB, enabling hands-off...
    Downloads: 9 This Week
    Last Update:
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  • 7
    Self-Operating Computer

    Self-Operating Computer

    A framework to enable multimodal models to operate a computer

    The Self-Operating Computer Framework is an innovative system that enables multimodal models to autonomously operate a computer by interpreting the screen and executing mouse and keyboard actions to achieve specified objectives. This framework is compatible with various multimodal models and currently integrates with GPT-4o, o1, Gemini Pro Vision, Claude 3, and LLaVa. Notably, it was the first known project to implement a multimodal model capable of viewing and controlling a computer screen....
    Downloads: 7 This Week
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  • 8
    PromethAI

    PromethAI

    Open-source framework that gives you AI Agents

    PromethAI-Backend is a backend framework for AI-driven automation and knowledge extraction. It is designed to integrate with large language models (LLMs) to provide AI-enhanced workflows, including content generation, summarization, and data analysis.
    Downloads: 0 This Week
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