Build a FREE, Local AI Research Agent with Python
Author(s): Taha Azizi Originally published on Towards AI. Give your local LLM the power to browse the real-time web. No APIs, no fees — just Python, LangChain, and your own PC. With Researchgen, the web is your research library. This AI agent …
Use your own customized open-source Large Language Model
Author(s): Taha Azizi Originally published on Towards AI. You’ve built it. Now unleash it. Learn how to use your own fine-tuned model You already fine-tuned a model (great!). Now it’s time to use it. Convert it to GGUF, quantize for local hardware, …
Introduction to RAG: Basics to Mastery. 1-Build Your Own Local RAG Pipeline (No Cloud, No API Keys)
Author(s): Taha Azizi Originally published on Towards AI. Part 1 of the mini-series introduction to RAG A step-by-step guide to running Retrieval-Augmented Generation fully offline with Ollama, ChromaDB, and SentenceTransformers. Introduction Large Language Models (LLMs) are powerful, but they come with two …
Introduction to RAG: Basics to Mastery.2-Hybrid RAG, Combining Semantic & Keyword Search for Better Retrieval
Author(s): Taha Azizi Originally published on Towards AI. Part 2 of the mini-series introduction to RAG Introduction In Article 1, we built a basic local RAG pipeline using embeddings and a vector database.While semantic search is powerful, it can sometimes miss results …
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