Yahoo Finance Agent

This application leverages OpenAI's language models, the Yahoo Finance Python library, and LangChain's agents and tools to provide users with real-time financial data and insights. Whether you're interested in stock prices, company financials, or the latest news, this assistant is here to help.

Features

• Stock Information: Get detailed information about any stock, including historical data and recent news.
• Financial Statements: Access income statements, balance sheets, and cash flow statements, both annual and quarterly.
• Options Data: Explore available options expiration dates and detailed options chains.
• Holders and Recommendations: View information about major holders, insider transactions, and analyst recommendations.
• Interactive Chat Interface: Engage with the assistant through a user-friendly chat interface built with Streamlit.
• LangChain Integration: Utilizes LangChain's agents and tools for efficient task management and interaction with various data sources.
• Conversation Buffer Memory: Maintains the context of the conversation by passing chat message history to the model, ensuring more coherent and context-aware responses over the course of the interaction.
• Powered by OpenAI: Leverages OpenAI's language model to generate responses and provide insights based on user queries.
• Langsmith: Integrated with Langsmith to easily debug, analyze and visualize the agent's conversation flow and model outputs.
• Model Selection: Flexibly choose from different OpenAI models (e.g., gpt-4o, gpt-4o-mini, gpt-3.5-turbo-0125) directly from the sidebar to customize the performance and capabilities of the assistant based on your needs.

Installation

1. Clone the Repository

git clone git@github.com:ojasskapre/yahoo-finance-llm-agent.git
cd yahoo-finance-llm-agent

2. Install Dependencies

pip install -r requirements.txt

3. Copy the .env.sample file to .env and add the OpenAI API key. To enable tracing using Langsmith, add Langchain API Key and Project name as well.

OPENAI_API_KEY=<YOUR_OPENAI_KEY_HERE>
LANGCHAIN_TRACING_V2=true
LANGCHAIN_ENDPOINT="https://api.smith.langchain.com"
LANGCHAIN_API_KEY="<YOUR_LANGCHAIN_API_KEY>"
LANGCHAIN_PROJECT="<YOUR_PROJECT_NAME_HERE>"

4. To start the Streamlit app, run the following command:

streamlit run app.py

Resources

• Streamlit Agent Tools UI with Langchain
• Streamlit Chat Message History UI with Langchain
• Streamlit Agent UI examples GitHub repository
• Functions, Tools and Agents in Langchain