Financial Stock Intelligence (FSI)

Financial Stock Intelligence (FSI)#

Overview#

FSI UI

This Solution Blueprint provides a financial analysis workflow through a web interface. It combines real-time stock data, technical indicators, and Large Language Model (LLM) analysis to produce stock insights.

AMD Solution Blueprints are packaged as Helm charts for deployment on a Kubernetes cluster. For development or further exploration, the source code is public and available in the Solution Blueprints GitHub repository.

Architecture#

The Financial Stock Intelligence application runs inside a single container. It is served by an AIM LLM deployed beside it. The Financial Stock Intelligence application runs inside a single container. It is served by an AIM LLM deployed beside it.

The blueprint provides a Gradio web application with a financial analysis pipeline and an AIM LLM service. By default, the Llama 3.3 70B AIM is deployed for analysis and commentary.

Component

Role

Gradio UI

Web interface for entering symbols, date ranges, and reviewing results

Analysis pipeline

Market data retrieval, technical indicators, and visualization

AIM LLM

AI-generated stock insights (default: Llama 3.3 70B Instruct)

Key Features#

  • Real-time stock data: Live prices and history via Yahoo Finance

  • Technical analysis: Simple Moving Average (SMA), Relative Strength Index (RSI), momentum, and price versus SMA comparisons

  • AI-powered analysis: Uses Llama 3.3 70B Instruct for intelligent stock insights

  • Interactive web interface: Gradio UI for easy interaction

  • Historical visualization: Charts and graphs for trend analysis

  • News integration: Incorporates relevant financial news for context

Getting Started#

This is a quick start guide on how to deploy the blueprint. For advanced options, such as reusing an existing AIM, providing a Hugging Face token, or overriding storage classes, see Deploying Solution Blueprints with Helm or explore the advanced deployment guide.

This blueprint supports AMD Instinct (default), AMD EPYC, and AMD Radeon platforms. The section below covers the default Instinct deployment. For EPYC and Radeon deployment and other advanced options, see:

Prerequisites#

System Requirements#

The blueprint requires the following cluster resources by default:

Resource

Default Configuration

GPUs

1

CPUs

5 CPU cores

RAM

68 Gi

To deploy to the Kubernetes cluster, ensure the following prerequisites are met:

  • kubectl: Installed and configured to communicate with the cluster

  • Helm 3.17 or higher: Installed on your local machine

Deployment#

Solution Blueprints are packaged as OCI-compliant Helm charts in the Docker Hub registry and can be deployed to a Kubernetes cluster with a single command. Define the name (deployment name) and the namespace (Kubernetes namespace), then pipe the output of helm template to kubectl apply -f -:

name="my-deployment"
namespace="my-namespace"
helm template $name oci://registry-1.docker.io/amdenterpriseai/aimsb-fsi \
  | kubectl apply -f - -n $namespace

Note: You can create a namespace using kubectl create namespace $namespace.

To check the status of the deployment, run:

kubectl get pods -n $namespace

Wait until all pods report Running and Ready.

Connect to UI#

To connect to the UI, port-forward to 8081. The UI will then be available at http://localhost:8081 in your browser.

kubectl port-forward services/aimsb-fsi-${name} 8081:80 -n $namespace

Once connected, use the application as follows:

  1. Enter a stock symbol/ticker

  2. Set the date range for the analysis period

  3. Click “Analyze Stock” to fetch data, compute indicators, and generate AI commentary

  4. Review the results: Technical indicators, charts, AI-generated analysis, and more

Clean Up#

When you are finished, remove the deployed resources:

helm template $name oci://registry-1.docker.io/amdenterpriseai/aimsb-fsi \
  | kubectl delete -f - -n $namespace

Disclaimer#

This tool is for educational and research purposes only. It is not financial advice.

Third-Party Components#

This Solution Blueprint uses multiple third-party components. To see the full set of software and Python dependencies, explore the repository source and dependency files. The table below highlights some of the main components. For further license information, refer to each component’s official documentation.

Component

License

Gradio

Apache 2.0

LangChain

MIT

yfinance

Apache 2.0

Terms of Use#

AMD Solution Blueprints are released under the MIT License, which governs the parts of the software and materials created by AMD. Third-party Software and Materials used within the Solution Blueprints are governed by their respective licenses.

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