Project background
The healthcare platform needed a conversational feature that users could access within the existing application. The assistant needed to handle follow-up interactions and present responses without making users wait for the entire answer.
Challenges
- Responses needed to remain relevant as a conversation continued.
- Users needed timely feedback while an AI response was being generated.
- The AI integration needed to work within the platform's existing application flows.
My contributions
- Developed FastAPI endpoints for the AI-powered healthcare project.
- Integrated the OpenAI GPT-4 API into the application.
- Worked on prompt design, response streaming, and conversation context management.
- Implemented the application interactions around the assistant's responses.
Solutions
- Connected the application to GPT-4 through backend endpoints.
- Streamed responses so users could read answers as they arrived.
- Managed conversation context to support relevant follow-up exchanges.
Outcomes
- Delivered a production conversational assistant within the healthcare platform.
- Improved the application's self-service experience; no numerical improvement is claimed.
Project details describe my contributions. Results reflect prior work and may vary by application.