https://github.com/assistant-ui/assistant-ui-stockbroker
https://github.com/assistant-ui/assistant-ui-stockbroker
Last synced: 12 months ago
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- Host: GitHub
- URL: https://github.com/assistant-ui/assistant-ui-stockbroker
- Owner: assistant-ui
- License: mit
- Created: 2024-09-10T20:48:56.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2025-01-12T10:25:51.000Z (over 1 year ago)
- Last Synced: 2025-06-26T11:15:36.260Z (12 months ago)
- Language: TypeScript
- Homepage: https://assistant-ui-stockbroker.vercel.app
- Size: 289 KB
- Stars: 231
- Watchers: 3
- Forks: 57
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Stockbroker Human in the Loop
The code for the Stockbroker Human in the Loop video can be found in this directory. It's setup as a monorepo-style project, with `frontend` and `backend` directories.
The `frontend` directory contains a Next.js application which allows you to interact with the Stockbroker agent via a chat interface.
The backend contains a LangGraph agent which powers the core functionality of the stockbroker.
## Deployment
The stockbroker agent is publicly accessible through two interfaces:
1. API:
> The Cloud API for the stockbroker agent is publicly accessible at the following base URL: `https://assistant-ui-stockbroker.vercel.app/api`
2. Web-based Chat Interface:
> To go along with the API, we've also deployed this web-based chat interface for the stockbroker agent.
>
> You can access, and interact with it [here](https://assistant-ui-stockbroker.vercel.app).
## Setup
To setup the stockbroker, install dependencies from the root of the monorepo:
```bash
yarn install
```
This will install all dependencies required by both the frontend and backend projects. You can also run shared commands from the root of the project:
```bash
yarn format
yarn build
```
## Environment variables
### Backend
The backend requires Financial Datasets AI, Tavily and OpenAI API keys to run. Sign up here:
- Financial Datasets AI: https://financialdatasets.ai/
- Tavily: https://tavily.com/
- OpenAI: https://platform.openai.com/signup
Once you have your API keys, create a `.env` file in the [`./backend`](`./backend`) directory and add the following:
```bash
FINANCIAL_DATASETS_API_KEY=YOUR_API_KEY
TAVILY_API_KEY=YOUR_API_KEY
OPENAI_API_KEY=YOUR_API_KEY
```
### Frontend
The frontend requires the production, or local deployment of your agent, along with a LangSmith API key (if calling the production endpoint), and finally the name of the agent to interact with (in this case `stockbroker`).
For local development, you can find the API endpoint in the bottom left of LangGraph Studio, which defaults to `http://localhost:51497`. You can find the production URL in the deployment page of your LangGraph cloud deployment.
Then, set the variables in a `.env` file inside [`./frontend`](./frontend):
```bash
# Only required for production deployments
# LANGCHAIN_API_KEY=YOUR_API_KEY
LANGGRAPH_API_URL=https://assistant-ui-stockbroker.vercel.app/api # Or your production URL
NEXT_PUBLIC_LANGGRAPH_ASSISTANT_ID=stockbroker
```
## LangGraph Config
The LangGraph configuration file for the stockbroker project is located inside [`./backend/langgraph.json`](./backend/langgraph.json). This file defines the stockbroker graph implemented in the project: `stockbroker`.