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Comprehensive desarrollo de chatbots de IA Tools for Every Need

Get access to desarrollo de chatbots de IA solutions that address multiple requirements. One-stop resources for streamlined workflows.

desarrollo de chatbots de IA

  • OpenKBS Apps

    A web platform to build AI-powered knowledge base agents via document ingestion and vector-driven conversational search.
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    What is OpenKBS Apps?
    OpenKBS Apps provides a unified interface to upload and process documents, generate semantic embeddings, and configure multiple LLMs for retrieval-augmented generation. Users can fine-tune query workflows, set access controls, and integrate agents into web or messaging channels. The platform offers analytics on user interactions, continuous learning from feedback, and support for multilingual content, enabling rapid creation of intelligent assistants tailored to organizational data.
    OpenKBS Apps Core Features
    • Document ingestion and parsing
    • Vector embedding index
    • Retrieval-augmented chat builder
    • Multi-LLM support
    • API and webhook integration
    • Usage analytics and reporting
    OpenKBS Apps Pro & Cons

    The Cons

    Limited information on user interface and user experience
    No direct mobile or desktop app links provided
    Potential dependency on cloud services like AWS

    The Pros

    Diverse range of AI Agents covering multiple use cases
    Open-source codebase available on GitHub
    Facilitates easy cloning and adaptation for developers
    Automates complex tasks via AI, enhancing productivity
    OpenKBS Apps Pricing
    Has free planNo
    Free trial details
    Pricing model
    Is credit card requiredNo
    Has lifetime planNo
    Billing frequency
    For the latest prices, please visit: https://openkbs.com/apps/

  • Controllable RAG Agent

    An open-source Python framework to build Retrieval-Augmented Generation agents with customizable control over retrieval and response generation.
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    What is Controllable RAG Agent?
    The Controllable RAG Agent framework provides a modular approach to building Retrieval-Augmented Generation systems. It allows you to configure and chain retrieval components, memory modules, and generation strategies. Developers can plug in different LLMs, vector databases, and policy controllers to adjust how documents are fetched and processed before generation. Built on Python, it includes utilities for indexing, querying, conversation history tracking, and action-based control flows, making it ideal for chatbots, knowledge assistants, and research tools.
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