media-processing

You can extract searchable insights from local video files by running a multi-stage pipeline that ingests absolute file paths, segments video, and extracts keyframes. The pipeline then structures this visual data for LLM summarization and natural-language Q&A.

Analyzing video content with Gemini and Claude involves a map-reduce pipeline where Gemini extracts structured vision data from keyframes, and Claude performs reasoning over those structured results to provide natural-language summaries and answer specific questions.

Yes, you can generate video clips automatically. After identifying specific moments through analysis, the pipeline provides extraction tools with configurable pre-roll and post-roll padding to create playable video attachments for fast review.

Yes, the video segmentation pipeline supports optional per-segment audio transcription. During the preprocessing phase, the system can transcribe audio alongside keyframe extraction to enrich the structured output for downstream LLM analysis.

Yes, you need absolute local file paths to ingest media for analysis. The pipeline requires exact local file locations to register assets, deduplicate by content hash, and orchestrate the resumable multi-stage processing workflow.

You monitor pipeline progress for ingested media assets by tracking their unique asset ID. The system orchestrates a resumable multi-stage pipeline and provides status monitoring tools to check the progress of each processing stage.