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feat(gemma): configure Gemma 3 LLM service for Hugging Face Spaces (2 vCPU, 16GB RAM)
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metadata 
title: B Map AI Gemma 3 Inference Service
emoji: 🗺️
colorFrom: blue
colorTo: indigo
sdk: docker
app_port: 7860
pinned: false
license: apache-2.0

B Map AI - Gemma 3 (1B) Inference Service

High-performance geospatial LLM inference engine grounded in deep navigation knowledge and chain-of-thought spatial reasoning.

Hardware Profile

  • Platform: Hugging Face Spaces
  • Tier: Free Tier (2 vCPU, 16 GB RAM)
  • Model: google/gemma-3/flax/gemma3-1b-it (Flax/JAX)
  • Container Port: 7860

REST Endpoints

  • GET / - Root dashboard and service summary
  • GET /health - Comprehensive readiness and feature probe
  • POST /v1/chat - Conversational driver copilot inference
  • POST /v1/navigation - Structured geospatial route and navigation synthesis
  • GET /metrics - Internal latency and query execution statistics
  • GET /docs - Interactive Swagger OpenAPI documentation

Space Secrets (Settings -> Variables and secrets)

  • DATABASE_URL: (Optional) Neon PostgreSQL connection string for inference auditing.
  • KAGGLE_USERNAME: (Optional) Kaggle username if authenticating weight downloads.
  • KAGGLE_KEY: (Optional) Kaggle API key.
  • CORS_ORIGINS: (Optional) Comma-separated list of allowed frontend/backend origins (defaults to *).