Multi-agent LLM financial trading research framework with a browser launcher for ticker analysis.
Launch in your Sealos workspace.
Start with the resources defined by the TradingAgents template. Review CPU, memory, persistent storage, and network allocations for every service in Canvas. Capacity needs depend on your data and workload; monitor usage as they grow.
Template configuration and setupUse the application URL or connection details shown in Canvas. Follow the deployment guide for first-time account setup or client configuration, and keep generated credentials available for that step.
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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 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.
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.
Architecture Components:
v0.2.5 source.Configuration:
llm_provider selects the TradingAgents provider.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.
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.
llm_provider and provide the matching API key for real model-backed analysis.After deployment, configure TradingAgents through:
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.
This Sealos template is provided as deployment configuration for Sealos users. TradingAgents itself is licensed under the Apache-2.0 License.
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Start with a ready-made template. Review its configuration and launch from the Sealos console.
Run on managed infrastructure with built-in workload scheduling and recovery.
Give your application a public HTTPS endpoint with certificates managed for you.
Keep application data on persistent volumes across container restarts.
Adjust CPU, memory, and replicas from the console as your workload changes.
Sealos provisions the resources defined by your template and brings them together in your workspace.
Container workloads with configurable CPU, memory, and replicas.
An address for your app, with managed TLS certificates.
A database provisioned alongside your app when the template calls for one.
Storage for the files and data your application needs to keep.
Application settings and secrets configured in one place.
Inspect container logs and resource usage from the console.
Resources and their configuration vary by template. Review the deployment form for this app’s exact setup.
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