FREE Unstract AI Open Source 🤖Convert ANY Unstructured Data To RAG Ready LLM Data API Endpoints

FREE Unstract AI Open Source 🤖Convert ANY Unstructured Data To RAG Ready LLM Data API Endpoints

https://docs.google.com/document/d/1v...

Github Repo: https://github.com/Zipstack/unstract
Unstract Website: https://unstract.com/
Unstruct Docs: https://docs.unstract.com/unstract_pl...

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⏳ Timestamps
00:00 - Introduction: Building RAG Systems with Unstructured Data
00:49 - Discovering Unstract: No-Code LLM Platform for Data Extraction
01:43 - Unstract Overview: Features & Capabilities
02:20 - Prerequisites for Setting Up Unstract (Git, Python, Docker)
03:02 - Challenges with Unstructured Data and Conversion Process
03:47 - GitHub Setup: Cloning Unstract Repository
04:53 - Running Unstract Locally: Docker Setup and Login
05:34 - Free vs. Hosted Unstract: Platform Walkthrough
06:19 - Connecting an LLM and Vector Database in Unstract
06:45 - Setting Up LLM API Keys and Model Selection
07:24 - Configuring Quadrant Database and Embedding Models
08:55 - Choosing a Text Extractor: Llama Parse Setup
09:28 - Integrating AI-Powered Appointment Setters with Stride Agents
10:03 - Setting Up Unstract for Data Extraction: Prompt Studio
11:12 - Creating and Managing Projects in Prompt Studio
12:22 - Customizing LLM Profiles and Pre/Postambles in Prompt Studio
13:37 - Creating Extraction Prompts and Managing Documents
14:36 - Running LLMs for Document Extraction
15:59 - Viewing and Analyzing Extracted Data in Prompt Studio
16:38 - API Workflows vs. ETL Pipelines: Structuring Unstructured Data
17:18 - Building a Workflow: API Input/Output Configuration
17:46 - Deploying Workflows as API or ETL Pipelines
18:40 - Conclusion: Unstract's Versatility for LLM Projects
19:30 - Final Thoughts: Community Engagement & AI-Powered Appointment Setting