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With AI, Everyone is a Dev. EveryDev.ai ©
    1. Home
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    3. ScholasticAI
    ScholasticAI icon

    ScholasticAI

    Research Assistants

    A local, CPU-friendly RAG application that answers questions from uploaded PDFs and OpenAlex using the open Pleias-Pico 350M model.

    Visit Website

    At a Glance

    Pricing
    Free

    No payment gate applies to reading the repository. No application license is specified; the model and dependency licenses must be checked separately. Local compute and optional external data services have separate costs or terms.

    Engagement

    Available On

    Windows
    macOS

    Resources

    WebsiteDocsGitHubllms.txt

    Topics

    Research AssistantsRetrieval-Augmented GenerationLocal Inference

    Alternatives

    raggyLocalGPTMane
    Developer
    Pleias

    Listed Nov 2026

    About ScholasticAI

    ScholasticAI is a retrieval-augmented generation application from Pleias that lets users upload local PDFs and ask questions answered with quotes from those documents. It can also query external knowledge databases such as OpenAlex, which the README describes as holding 250M+ documents. It runs locally on a Pleias-Pico (350M) model served through llamafile, and the README says it is designed to run on consumer laptops or desktops without a GPU.

    What It Is

    ScholasticAI is a desktop-style Python application for document question answering. Users load PDFs, ask questions in a chat window, and receive generated answers grounded in quotes from the source documents. The README says it was built mainly for research articles but can be used with other kinds of PDFs.

    How It Works

    A llamafile server (v0.8.13) loads the Pleias-Pico GGUF model and exposes a local API endpoint at 127.0.0.1:8080. The app is then started with python -m src.main. On first launch it downloads the BGE-M3 embedding model. Documents can be added at any time. A fine-tuned YOLOv8 model is used for layout analysis. The README recommends a temperature of 0 for best answer quality.

    The Pleias-Pico Model

    Pleias-Pico 0.1 is a 350M-parameter model continued from Pleias-350m on a dataset of about 45 billion tokens of retrieval tasks derived from Common Corpus. According to the README, it is trained on permissibly licensed open data and is compliant with the European AI Act. It supports multilingual input across main European languages. It uses a standardized structure for queries, sources and references, and performs source analysis that acts as an integrated reranker. The README says it was originally conceived as an experimental model, and that it works properly only with prompts matching its RAG design.

    Setup and Requirements

    Setup involves cloning the repository, downloading llamafile and the model, installing requirements with pip, and running the app. The README lists Windows or macOS, a Ryzen 5 3000 series, Intel Core i5 (8th gen) or Apple M1 processor, and 8GB of RAM as minimum specs. The interface is designed for bright mode. The README credits the Mozilla Local AI Builders program with supporting development.

    Access and scope

    The application repository is public, but it does not specify an application license. Model openness does not automatically license the application. Inference can run locally; downloading models and querying OpenAlex still use external services. The local llamafile endpoint is a dependency, not a public ScholasticAI API. AI Act compliance is a vendor claim, not an independently established legal conclusion.

    ScholasticAI - 1

    Community Discussions

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    Share your experience with ScholasticAI, ask questions, or help others learn from your insights.

    Pricing

    FREE

    Public source access

    No payment gate applies to reading the repository. No application license is specified; the model and dependency licenses must be checked separately. Local compute and optional external data services have separate costs or terms.

    • Public Python application source and setup instructions
    • Local CPU inference with separately downloaded models

    Capabilities

    Key Features

    • Upload and analyze local PDFs
    • Answers grounded in high-fidelity quotes from documents
    • Query external knowledge databases such as OpenAlex
    • Local CPU inference; external downloads and OpenAlex queries require network access
    • Uses open Pleias-Pico 350M RAG model
    • Multilingual support for main European languages
    • Source analysis with integrated reranking
    • Layout analysis with fine-tuned YOLOv8
    • BGE-M3 embeddings for retrieval

    Integrations

    OpenAlex
    llamafile
    Hugging Face
    BGE-M3
    YOLOv8

    Ratings & Reviews

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    Developer

    Pleias

    Read more about Pleias
    WebsiteGitHub
    1 tool in directory

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