Ollama Embedding: How to Feed Data to AI for Better Response?

🌟 Welcome to our deep dive into Ollama Embedding for AI applications! In this comprehensive tutorial, we're unlocking the power of Ollama Embedding to enhance your app's performance significantly. 🌟 Feed Data to AI for better response.

🔍 What We Cover:
Introduction to Ollama Embedding and its advantages.
Step-by-step guide on ingesting data from URLs, converting them into embeddings, and storing in Vector Database using ChromaDB.
Integration with Nomic Embed Text for superior embedding performance.
Utilising RAG for data retrieval.
Building a user-friendly interface with Gradio.

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🛠️ Setup Steps:
Installation of necessary packages (Lang Chain, Chroma Embeddings, etc.)
Detailed walkthrough for setting up your application file.
Splitting data, converting to embeddings, and database storage.
Creating and integrating the user interface with Gradio.

🔗 Resources & Links:
Ollama Tutorials:    • Ollama Tutorial  
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Discord:   / discord  
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Code: https://mer.vin/2024/02/ollama-embedd...

👀 Why Watch:
Learn to create AI applications with enhanced performance.
Understand the benefits of using Nomic Embed Text over other models.
Gain insights into creating efficient user interfaces for your AI apps.

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Timestamps:
0:00 - Introduction to Ollama Embedding
0:39 - Benefits of Nomic Embed Text
1:00 - User Interface Preview
1:04 - Subscription Reminder
1:21 - Setting Up Your Application
3:00 - Understanding the Rag Process
4:01 - Running the Code
5:00 - Adding User Interface with Gradio

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