Build 6-Agent Research Team with LangGraph and Function Calling Tools
Автор: Launch Intelligence
Загружено: 2024-12-10
Просмотров: 3179
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Let's build our own AI Financial Agents Network! In this video, we’ll create a network of AI-powered financial experts that will work together seamlessly to handle complex financial queries. 🚀
They will write and execute Python code, bring relevant data to the LLM via tools and combine multiple sources to generate beautiful financial charts and visualizations!
📊 Here’s what else they’ll do:
▶︎ Gather Data: Fetch real-time financial information from various sources.
▶︎ Analyze Trends: Perform in-depth financial and market analysis.
▶︎ Compile Data: Organize results into structured formats like CSV files.
▶︎ Visualize Insights: Plot insightful charts to make data actionable.
▶︎ Generate Reports: Prepare comprehensive, professional reports.
The tools we're going to use:
◦ File System from LangChain - https://python.langchain.com/docs/int...
◦ Python REPL - https://python.langchain.com/docs/int...
◦ Tavily Search - https://python.langchain.com/docs/int...
◦ Alpha Vantage - https://python.langchain.com/docs/int...
◦ Custom IMF API tool - https://www.imf.org/external/datamapp...
Whether you're a finance enthusiast, data scientist, or developer, this project will show you how to harness the power of LangGraph and ReAct to create an intelligent, automated system that transforms raw data into valuable insights.
🎯 Let’s build the future of financial analysis together—step by step!
🔗 Links & Resources:
Skool: https://www.skool.com/ai-software-dev...
Code the Revolution: Newsletter - https://aidev9.substack.com/
Discord server: / discord
Langsmith: https://www.langchain.com/langsmith
LangGraph Python docs: https://www.langchain.com/langgraph
LangChain Tools: https://python.langchain.com/docs/int...
Tavily Search: https://tavily.com/
IMF APIs: https://www.imf.org/external/datamapp...
#ai #openai #langgraph #chatbot #langsmith #agent #llm #developer #software #tutorial #genai #tavily #api #react #pydantic
🕒 TIMESTAMPS:
00:00 - Introduction
00:33 - Sample queries
01:02 - Graph architecture
02:17 - ReAct concepts
04:31 - Supervisor agent
12:34 - Memory demo
17:00 - LLM agent
22:16 - File writer agent
28:00 - Python REPL agent
35:06 - Tavily search agent
41:35 Alpha Vantage agent
48:10 - Custom GDP agent
53:00 - Summary
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