Implemented FastAPI service with Docker deployment

📅 2025-04-15 — Session: Implemented FastAPI service with Docker deployment

🕒 14:10–15:15
🏷️ Labels: Fastapi, Docker, Deployment, Troubleshooting, Python
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The primary goal of this session was to implement and deploy a FastAPI service using Docker, ensuring robust API functionality and resolving any deployment issues.

Key Activities

• Dockerfile Creation: Developed a Dockerfile to set up a Python 3.11 environment for application deployment.
• Service Launch: Provided detailed instructions for launching a FastAPI service within a Docker container, including necessary scripts and configurations.
• Backend Finalization: Finalized the minimal FastAPI backend, maintaining customizations and adapting new logic.
• Flow Runner Fixes: Addressed a critical edge case in flow input handling, ensuring data is loaded correctly from a YAML file.
• Execution Differences: Analyzed differences between CLI and API flow execution, providing troubleshooting steps.
• Merged run() Method: Merged two run() methods for PromptBlock, enhancing error handling and output formatting.
• POST Error Diagnosis: Diagnosed FastAPI POST request errors, offering fixes for asynchronous handling.
• Connection Issue Diagnosis: Diagnosed FastAPI connection issues with OpenAI, providing strategies for resolution.
• Log Validation: Validated startup logs, confirming successful API connectivity and suggesting next steps.

Achievements

• Successfully created a Docker environment for FastAPI deployment.
• Finalized backend code for phase 2, ensuring readiness for production.
• Resolved input handling issues in flow runner and improved error handling in PromptBlock.
• Diagnosed and provided solutions for FastAPI POST and connection issues.

Pending Tasks

• Implement the suggested next steps from the startup log validation, including model list checks and health route additions.