# Deploy and Host TradingAgents on Sealos

TradingAgents is a multi-agent LLM financial trading research framework. This template deploys TradingAgents with a browser-accessible Gradio launcher, persistent cache storage, and public HTTPS access on Sealos Cloud.

![TradingAgents Screenshot](https://raw.githubusercontent.com/labring-actions/templates/kb-0.9/template/tradingagents/website-screenshot.webp)

## About Hosting TradingAgents

TradingAgents simulates a financial research team with specialized LLM agents for market, sentiment, technical, fundamental, risk, and portfolio analysis. The upstream project is CLI-first, so this template wraps it with a lightweight browser launcher for Sealos users.

The container installs the upstream `v0.2.5` source into persistent storage, starts a Gradio UI, and saves cache and memory files under `/home/appuser/.tradingagents`. API keys are supplied during deployment through template inputs and exposed as the environment variables expected by TradingAgents.

## Common Use Cases

- **Ticker research experiments**: Run multi-agent analysis for supported market symbols.
- **LLM provider comparison**: Test OpenAI, Gemini, Anthropic, DeepSeek, Qwen, GLM, MiniMax, or OpenRouter.
- **Financial workflow demos**: Demonstrate multi-agent research workflows in a browser.
- **Persistent research cache**: Keep TradingAgents checkpoint and memory files across restarts.

## Dependencies for TradingAgents Hosting

The Sealos template includes a Python runtime StatefulSet, ConfigMap launcher, persistent volume, HTTPS Ingress, Service, and App resources. Real analysis requires at least one matching LLM provider API key.

### Deployment Dependencies

- [TradingAgents GitHub Repository](https://github.com/TauricResearch/TradingAgents) - Source code and documentation
- [TradingAgents README](https://github.com/TauricResearch/TradingAgents#readme) - CLI usage and provider configuration
- [Sealos Documentation](https://sealos.io/docs) - Sealos platform documentation

### Implementation Details

**Architecture Components:**

- **Python StatefulSet**: Installs and runs the TradingAgents `v0.2.5` source.
- **Gradio Launcher**: Provides a browser UI for ticker, date, depth, and runtime status.
- **Persistent Volume**: Stores source checkout, package cache, checkpoints, and memory logs.
- **ConfigMap**: Provides the launcher script and Gradio application.
- **Ingress and App Entry**: Exposes the UI through the generated Sealos HTTPS URL.

**Configuration:**

- `llm_provider` selects the TradingAgents provider.
- Provider API key inputs map to the official environment variables such as `OPENAI_API_KEY`, `GOOGLE_API_KEY`, and `ANTHROPIC_API_KEY`.
- `alpha_vantage_api_key` and `finnhub_api_key` can improve market data and news coverage.

**License Information:**

TradingAgents is licensed under the Apache-2.0 License. This Sealos template provides deployment configuration for running TradingAgents on Sealos Cloud.

## Why Deploy TradingAgents on Sealos?

Sealos is an AI-assisted Cloud Operating System built on Kubernetes that unifies deployment and operations. By deploying TradingAgents on Sealos, you get one-click deployment, automatic HTTPS, persistent storage, resource controls, and Canvas-based updates for a research tool that normally starts from a local CLI.

## Deployment Guide

1. Open the [TradingAgents template](https://sealos.io/products/app-store/tradingagents) and click **Deploy Now**.
2. Choose `llm_provider` and provide the matching API key for real model-backed analysis.
3. Wait for deployment to complete, typically 2-3 minutes. After deployment, you will be redirected to the Canvas. For later changes, describe your requirements in the AI dialog, or click the relevant resource cards to modify settings.
4. Open the generated public URL.
5. Use **Refresh status** to confirm which API keys are configured.
6. Enter a ticker and date, then start an analysis from the page.

## Configuration

After deployment, configure TradingAgents through:

- **Gradio UI**: Start ticker analysis and inspect runtime key status.
- **AI Dialog**: Update provider keys or model-related settings.
- **Resource Cards**: Increase CPU or memory for longer analysis runs.
- **Persistent Volume**: Keep checkpoint and memory data across restarts.

## Scaling

TradingAgents runs one analysis process at a time by default. Increase CPU and memory when running deeper research levels, larger models, or longer ticker analyses.

## Troubleshooting

### Analysis fails immediately

- Cause: The selected provider key is missing or invalid.
- Solution: Confirm the matching API key is configured, then restart the StatefulSet.

### Startup takes longer than expected

- Cause: The first boot clones the upstream repository and installs Python dependencies.
- Solution: Wait for the startup probe to pass; later restarts reuse persistent storage.

### Analysis times out

- Cause: Deep research can exceed the default 30-minute launcher timeout.
- Solution: Increase resources or run a narrower analysis depth.

## Additional Resources

- [TradingAgents GitHub Repository](https://github.com/TauricResearch/TradingAgents)
- [TradingAgents CLI Usage](https://github.com/TauricResearch/TradingAgents#installation-and-cli)
- [Sealos Documentation](https://sealos.io/docs)

## License

This Sealos template is provided as deployment configuration for Sealos users. TradingAgents itself is licensed under the [Apache-2.0 License](https://github.com/TauricResearch/TradingAgents/blob/main/LICENSE).