Showing 4 open source projects for "python script"

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    Gemini Fullstack LangGraph Quickstart

    Gemini Fullstack LangGraph Quickstart

    Get started w/ building Fullstack Agents using Gemini 2.5 & LangGraph

    gemini-fullstack-langgraph-quickstart is a fullstack reference application from Google DeepMind’s Gemini team that demonstrates how to build a research-augmented conversational AI system using LangGraph and Google Gemini models. The project features a React (Vite) frontend and a LangGraph/FastAPI backend designed to work together seamlessly for real-time research and reasoning tasks. The backend agent dynamically generates search queries based on user input, retrieves information via the...
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    Laminar

    Laminar

    Open-source all-in-one platform for engineering AI products

    ...All traces are sent in the background via gRPC with minimal overhead. Tracing of text and image models is supported, audio models are coming soon. You can set up LLM-as-a-judge or Python script evaluators to run on each received span. Evaluators label spans, which is more scalable than human labeling, and especially helpful for smaller teams. Laminar lets you go beyond a single prompt. You can build and host complex chains, including mixtures of agents or self-reflecting LLM pipelines.
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  • 3
    SkyAGI

    SkyAGI

    SkyAGI: Emerging human-behavior simulation capability in LLM

    ...The interesting observations in this demo show a huge potential for rethinking game development in many aspects, such as NPC script writing.
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  • 4
    TensorFlow.js models

    TensorFlow.js models

    Pretrained models for TensorFlow.js

    ...To find out about APIs for models, look at the README in each of the respective directories. In general, we try to hide tensors so the API can be used by non-machine learning experts. New models should have a test NPM script. You can run the unit tests for any of the models by running "yarn test" inside a directory. Use off-the-shelf JavaScript models or convert Python TensorFlow models to run in the browser or under Node.js. Build and train models directly in JavaScript using flexible and intuitive APIs. Develop ML models in JavaScript, and use ML directly in the browser or in Node.js.
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