olivas

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Author	SHA1	Message	Date
Vadym Samoilenko	2c5e17c7c4	Add Google Cloud Run offloading for ML inference and image processing - Create cloud_run/saliency: FastAPI service running DeepGaze I/IIE/III on Cloud Run (4 vCPU, 16GB RAM); pre-downloads model weights in Docker build to eliminate cold-start delays; returns saliency map + gaze sequence + hotspots + design scores - Create cloud_run/processing: lightweight FastAPI service for heatmap generation and gaze sequence visualization (2 vCPU, 4GB RAM) - Add cloud_run/deploy.sh for gcloud deployment to project optical-414516 in region europe-west2 - Refactor analysis pipeline to route via Cloud Run when CLOUD_RUN_SALIENCY_URL is set, with local fallback for dev mode - Add cloud_run_client.py with sync httpx wrappers for background tasks - Split pyproject.toml: base = API-only deps, [ml] = torch/deepgaze for local dev; production Dockerfile is now lightweight (~no PyTorch) - Preserve Dockerfile.full + docker-compose.dev.yml for local ML dev - Auth via X-Internal-Secret header (CLOUD_RUN_SECRET env var) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>	2026-03-04 19:39:52 +00:00
DJP	2425cd2677	Fix Docker and install files for current codebase - Fix backend Dockerfile: install deps before copying source for proper layer caching (non-editable install) - Add ai_insights, ai_score, ai_score_reason, ai_cost_usd columns to initial Alembic migration so fresh Docker deploys have full schema - Add ANTHROPIC_API_KEY to docker-compose.yml, docker-compose.dev.yml, and .env.example - Remove accidental backend/=0.40 pip artifact file Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-02-23 21:54:41 -05:00
DJP	3467dbcf03	Initial commit — OliVAS visual attention analysis platform Full-stack application for predicting where humans look in images using DeepGaze saliency models. Includes heatmap overlays, gaze sequence prediction, hotspot detection, AOI analysis, rule-based insights, optional Claude AI design analysis, and professional PDF report generation. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-02-23 20:20:58 -05:00

Author

SHA1

Message

Date

Vadym Samoilenko

2c5e17c7c4

Add Google Cloud Run offloading for ML inference and image processing

- Create cloud_run/saliency: FastAPI service running DeepGaze I/IIE/III
  on Cloud Run (4 vCPU, 16GB RAM); pre-downloads model weights in Docker
  build to eliminate cold-start delays; returns saliency map + gaze
  sequence + hotspots + design scores
- Create cloud_run/processing: lightweight FastAPI service for heatmap
  generation and gaze sequence visualization (2 vCPU, 4GB RAM)
- Add cloud_run/deploy.sh for gcloud deployment to project optical-414516
  in region europe-west2
- Refactor analysis pipeline to route via Cloud Run when
  CLOUD_RUN_SALIENCY_URL is set, with local fallback for dev mode
- Add cloud_run_client.py with sync httpx wrappers for background tasks
- Split pyproject.toml: base = API-only deps, [ml] = torch/deepgaze for
  local dev; production Dockerfile is now lightweight (~no PyTorch)
- Preserve Dockerfile.full + docker-compose.dev.yml for local ML dev
- Auth via X-Internal-Secret header (CLOUD_RUN_SECRET env var)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

2026-03-04 19:39:52 +00:00

DJP

2425cd2677

Fix Docker and install files for current codebase

- Fix backend Dockerfile: install deps before copying source for
  proper layer caching (non-editable install)
- Add ai_insights, ai_score, ai_score_reason, ai_cost_usd columns
  to initial Alembic migration so fresh Docker deploys have full schema
- Add ANTHROPIC_API_KEY to docker-compose.yml, docker-compose.dev.yml,
  and .env.example
- Remove accidental backend/=0.40 pip artifact file

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

2026-02-23 21:54:41 -05:00

DJP

3467dbcf03

Initial commit — OliVAS visual attention analysis platform

Full-stack application for predicting where humans look in images using
DeepGaze saliency models. Includes heatmap overlays, gaze sequence prediction,
hotspot detection, AOI analysis, rule-based insights, optional Claude AI
design analysis, and professional PDF report generation.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

2026-02-23 20:20:58 -05:00

3 commits