데브허브 | DEVHUB | LangChain REVOLUTIONISES AI Report Generation!
📝 Structured Report Generation using LangChain & NVIDIA NIM | AI-Powered Report Generation Research Pipeline
Learn how to generate comprehensive, well-structured reports automatically using LangChain, NVIDIA NIM, and LLaMA 3.3 70B! This tutorial walks you through creating an AI-powered research and writing pipeline.
Code: https://nvda.ws/4jmQtjC
🔍 What You'll Learn:
Complete AI report generation pipeline architecture
Integration of Planning, Research, and Writing agents
Parallel processing with NVIDIA NIM
Web research automation using Tavily API
Structured content generation with LLaMA 3.3 70B
⚙️ Prerequisites:
NVIDIA NIM API Key
LangChain API Key
Tavily API Key
Python environment setup
🛠️ Technical Stack:
LangChain
NVIDIA NIM
LLaMA 3.3 70B Instruct Model
Tavily Web Search API
Python
📊 Key Features:
Automated research query generation
Parallel web searching
AI-powered content structuring
Multi-agent coordination
Scalable report generation
#AI #MachineLearning #NVIDIA #LangChain #Python #Programming #TechTutorial #DataScience #ArtificialIntelligence #LLM #NLP
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Let me know if you'd like me to modify or add anything to this description!
Timestamp:
0:00 - Intro to structured report generation with LangChain
0:20 - AI agent roles explained
0:30 - Planning agent process
0:41 - Research agent functionality
0:51 - Parallel web search process
1:02 - GitHub code availability
1:18 - Detailed project layout
1:35 - Three agent types overview
2:18 - Prerequisites and API setup
2:40 - Planning agent implementation
3:22 - Research agents deep dive
4:24 - Final report generation
4:58 - Q&A and conclusion
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