LangGraph - Build Your Own AI Financial Agent Application (Beginners)

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AI Summary

Summary: Building a Financial Agent Application with Lang Chain

Introduction

• Creating a financial agent application for beginners using Lang Chain.
• The application will check stock prices, latest news, financial reports, and historical prices.
• Steps include creating tools, assigning them to an agent, coordinating with a graph, and adding a user interface with Gradio.

Setup

• Install Lang Chain and dependencies using Conda and pip.
• Set up API keys for OpenAI and Polygon, which provides financial data.

Development Steps

1. Define Tools:
   • Import necessary packages and set up prompt templates.
   • Define a large language model (GPT-4 Turbo Preview) and Polygon API wrapper.
   • Assign tools for stock price, news, financial reports, and historical prices.
2. Create Agent:
   • Define the agent with the large language model and tools.
   • Create helper functions to execute tools when needed by the agent.
3. Define Graph:
   • Set up the workflow with nodes for the agent and tools.
   • Add entry points and conditional logic for the agent’s operation.
   • Compile the graph and invoke the chain with a sample question about Airbnb’s stock price.

User Interface

• Modify the code to include a Gradio interface.
• The interface takes user input, processes requests, and returns outputs.
• Demonstration of various queries and their results using the interface.

Conclusion

• The code will be provided for users to try out.
• Encourages likes, shares, and subscriptions for support.