financial-chat

A financial chat application powered by LangChain, LangGraph, OpenBB, Claude 3 Opus, and Streamlit.

Blog Articles

If you're curious about the journey of building this project, check out these blog articles:

Features

Fetches financial data using OpenBB
Generates technical analysis summaries using AI
Provides stock price history, quantitative stats, and more
Calculates relative strength for stocks
Sentiment analysis on news articles
Universe scanning using FinViz filters
Risk management techniques using technically-derived stops and R Multiples
Interactive Streamlit UI for chat-based interaction
Multiple Agent Workflows using LangGraph
Deployment to AWS with the Copilot CLI

Installation

Install the required dependencies using Poetry:

poetry install

Set up the necessary environment variables. You can create an .env at the project root for these:

export OPENAI_API_KEY=<your-api-key>
export OPENBB_TOKEN=<your-openbb-token>
export TIINGO_API_KEY=<your-tiingo-api-key>
export IMGUR_CLIENT_ID=<your-imgur-client-id>
export IMGUR_CLIENT_SECRET=<your-imgur-client-secret>
export FMP_API_KEY=<fmp-api-key>
export INTRINIO_API_KEY=<intrinio-api-key>

Usage

Streamlit UI

Run the Streamlit app:

streamlit run app/ui.py

FastAPI Server

Start the FastAPI server:

uvicorn app.server:app --host 0.0.0.0 --port 8080

You can view the Swagger Docs and test out the Playground, courtesy of LangServe.

Docker

Build the Docker image:

docker build -t financial-chat .

Run the Docker container:

docker run -p 8080:8080 --env-file .env financial-chat

Project Structure

app/: Main application code
- chains/: LangChain agent and prompts
- features/: Feature-specific code (technical analysis, charting)
- tools/: Custom tools for data retrieval and analysis
- ui.py: Streamlit UI
- server.py: FastAPI server
Dockerfile: Dockerfile for building the application
pyproject.toml: Project dependencies and configuration
README.md: Project documentation

Flowchart

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wshobson/financial-chat

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