Video Automation — AI-driven video generation pipeline
The Video Automation project is a fully automated content creation pipeline designed to generate short-form video content with zero manual editing. Given a single topic or prompt, the system orchestrates the entire production process from start to finish.
It utilizes OpenAI’s language models to draft engaging scripts and its Text-to-Speech engine to synthesize high-quality voiceovers. The backend then fetches relevant background visuals, calculates precise audio timings, generates synchronized subtitles, and uses FFmpeg to stitch everything together into a polished mp4 file.
As a backend developer, I built the FastAPI orchestration layer, the integration with third-party AI APIs, and the complex FFmpeg rendering logic. The result is a highly scalable automation tool that reduces video production time from hours to mere minutes.
Core features
- Automated Scripting — AI generation of engaging video scripts from simple text prompts
- Voiceover Synthesis — integration with TTS APIs to generate natural-sounding voiceovers
- Asset Assembly — automated fetching of background clips and media assets
- Video Rendering — programmatically stitching audio, video, and subtitles using FFmpeg
Platform capabilities
- End-to-End Pipeline — seamless transition from text prompt to finalized mp4 export
- Subtitle Generation — synchronized captioning burnt directly into the video
- Local Caching — SQLite database to track generated assets and prevent redundant processing
Technical architecture
Challenges
- Synchronizing AI-generated voiceovers with background video pacing
- Accurate timing and alignment for burned-in subtitles
- Handling rate limits and timeouts from external AI providers
Solutions
- Calculated exact audio durations using FFmpeg to loop or trim background videos accordingly
- Generated proper SRT files locally before executing the final FFmpeg render pass
- Implemented retry mechanisms and job states stored in SQLite to resume failed generations