| # Copy as .env file and fill your values below | |
| # Run ./update_dotenv_example.sh to update .env-example from your .env file. | |
| # Choose Model Backend: 0 -> ML Dev, 1 -> Vertex | |
| GOOGLE_GENAI_USE_VERTEXAI=1 | |
| # ML Dev backend config | |
| GOOGLE_API_KEY=YOUR_VALUE_HERE | |
| # Vertex backend config | |
| # Rag Engine only works with Vertex. So we should configure it to use Vertex: | |
| GOOGLE_CLOUD_PROJECT=YOUR_VALUE_HERE | |
| GOOGLE_CLOUD_LOCATION=YOUR_VALUE_HERE | |
| # Existing corpus in Vertex RAG Engine to be used by RAG agent | |
| # e.g. projects/123/locations/us-central1/ragCorpora/456 | |
| RAG_CORPUS=YOUR_VALUE_HERE | |
| # Staging bucket name for ADK agent deployment to Vertex AI Agent Engine (Shall respect this format gs://your-bucket-name) | |
| STAGING_BUCKET=YOUR_VALUE_HERE | |
| # Agent Engine ID in the following format: projects/<PROJECT_NUMBER>/locations/us-central1/reasoningEngines/<AGENT_ENGINE_ID> | |
| AGENT_ENGINE_ID=YOUR_VALUE_HERE |