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What you can do with a used GPU
Learn to build a personal Telegram assistant using ChromaDB and a local GPU for RAG. Discover system integration challenges, prompt management with Agenta, and optimizing Llama.cpp for low VRAM.
A private Telegram-based personal knowledge assistant that lets me save notes from my phone, store and retrieve them with ChromaDB on a VPS accessible anytime, and ask questions answered by a local llama.cpp model running on my home GPU over a private network i setup.
Will show probably everything, or as much as i can in the time i have, but demo’s are fun and I want to show how the information propagates through what parts of the code to what parts of my telegram UX and use it on stage with suggestions from the crowd for notes. and maybe also show how we can change the prompt handling this assistant on the fly without touching the code using the agenta prompt management platform. maybe also show how i setup lamacpp for maximum inference time even for low vram machines with big beefy models.
- https://t.me/xxaxiomxxbot
Telegram bot Axiom launches a decentralized web3 application interface.
- PythonPython: The high-level, general-purpose language built for readability, powering everything from web backends to advanced machine learning models.Python is the high-level, general-purpose language prioritizing clear, readable syntax (via significant indentation), ensuring rapid development for any team . Its ecosystem is massive: use it for robust web development with frameworks like Django and Flask, or leverage its power in data science with libraries such as Pandas and NumPy . The Python Package Index (PyPI) provides thousands of community-contributed modules, offering immediate solutions for tasks from network programming to GUI creation . The language is actively maintained by the Python Software Foundation (PSF), with the stable release currently at Python 3.14.0 (as of November 2025) .
- llamaMeta's open-weights LLM family optimized for high-performance local deployment and custom fine-tuning across 8B to 405B parameter scales.Llama 3.1 delivers state-of-the-art performance through a flagship 405B parameter model trained on 15 trillion tokens. It supports a 128k context window: ideal for analyzing massive datasets or long-form documentation. Developers utilize Llama for diverse tasks (multilingual translation, Python code generation, and complex reasoning) while maintaining data sovereignty via local hosting. The ecosystem includes the Llama Stack for agentic workflows and optimized weights for 8B and 70B models, ensuring high throughput on consumer hardware or enterprise clusters.
- ChromaDBChromaDB is the open-source vector database built for LLM applications, providing simple, fast semantic search via embedding management.ChromaDB is your go-to open-source embedding database for building advanced LLM applications, specifically Retrieval-Augmented Generation (RAG) systems. It simplifies the storage, indexing, and querying of vector embeddings and their metadata, enabling fast Approximate Nearest Neighbor (ANN) similarity search. Developers appreciate its lightweight design: it runs in-memory, persistently using SQLite 3, or in client/server mode, offering robust Python and JavaScript SDKs. With over 5M+ monthly downloads and deep integration with tools like LangChain and LlamaIndex, Chroma is a proven, developer-friendly component for your AI stack.
- DockerDocker is the open-source platform that packages applications and dependencies into standardized, portable containers for consistent execution across any environment.Docker is the industry-standard containerization platform, enabling developers to build, ship, and run applications efficiently. It uses the Docker Engine (the core runtime) to create lightweight, isolated environments called containers: these units bundle an application’s code, libraries, and configuration. This self-contained approach guarantees consistency, eliminating the 'it works on my machine' problem across development, testing, and production environments (local workstations, cloud, or on-premises). Docker debuted in 2013 and now serves over 20 million developers monthly, simplifying complex workflows like CI/CD and microservices architecture by leveraging tools like Docker Hub for image sharing and Docker Compose for multi-container applications.
- Telegram BotsTelegram Bots are automated accounts that run inside the Telegram app, allowing developers to build interactive tools, services, and full-featured HTML5 mini-apps.Telegram Bots operate as automated accounts that do not require an associated phone number, serving as highly customizable interfaces for code running on your own servers (communicated via a simple HTTPS-based API). Developers use @BotFather to instantly spin up new bots, which can then process payments, send rich media, and launch immersive HTML5 Mini Apps directly inside chats. With support for webhooks, custom keyboards, inline queries, and deep integration into group chats, they allow you to deliver complex web services and interactive tools to Telegram's global user base without forcing them to leave the messaging interface.
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