Streamlined Emotion API with Gradio UI and MCP Server.
Project details
Emotion-server-demo offers a comprehensive Docker Compose setup for the Emotion API service. With an integrated Gradio UI and an MCP server, it facilitates seamless experimentation and access. Additional projects include a sentiment monitoring dashboard and AI-powered customer service demonstrations, enriching the user experience with insightful interactions and real-time analysis.
The Emotion Server Demo provides a comprehensive Docker Compose setup for the Emotion API service, designed for seamless experimentation and interaction through a Gradio UI and a powerful MCP server. This stack facilitates easy access to emotion prediction capabilities through intuitive interfaces.

The repository houses additional projects to enrich the user experience:
src/Demo_Firehose/src/Demo_Agentic_Routing/The Emotion service is powered by a robust architecture consisting of:
Access the Emotion Server through the following ports once Docker containers are running:
Users can interact with the service, input text, and receive real-time emotion predictions through the Gradio interface.
The Emotion API can be tested via command-line using curl, allowing for quick verification and integration into scripts. Examples of requests include:
curl -s -X POST http://localhost:8000/predict \
-H "Content-Type: application/json" \
-d '{"text":"I am so happy today!"}'
For detailed emotion analysis, the endpoint /predict_detailed provides comprehensive insights into the emotional landscape:
curl -s -X POST http://localhost:8000/predict_detailed \
-H "Content-Type: application/json" \
-d '{"text":"I am so happy today!"}'
For users preferring not to run the Emotion Service locally, a hosted version is available:
https://stevef1uk--emotion-server-serve.modal.run/predicthttps://stevef1uk--mcp-emotion-server-working-solution-serve.modal.run/mcpTesting the hosted API can be done similarly through curl calls, ensuring flexibility in deployment approaches.
The Emotion Server Demo stands as a comprehensive toolkit for sentiment analysis and emotion prediction through a structured API, interactive UI, and support for various deployment strategies. It encourages experimentation and exploration in understanding human emotions through technology.
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