gemini

Google Gemini Examples

This folder contains examples demonstrating how to use Google Gemini models with the Agent Framework.

Examples

File	Description
gemini_basic.py	Basic agent with a weather tool, demonstrating both streaming and non-streaming responses.
gemini_advanced.py	Extended thinking via ThinkingConfig for reasoning-heavy questions (Gemini 2.5+).
gemini_with_google_search.py	Google Search grounding for up-to-date answers.
gemini_with_google_maps.py	Google Maps grounding for location and mapping information.
gemini_with_code_execution.py	Built-in code execution tool for computing precise answers in a sandboxed environment.
gemini_embeddings.py	Per-call document and query text embeddings with stable Gemini Embedding 2.
gemini_search_agent.py	Document upsert and create_vector_search_tool with distinct per-operation embedding options.
gemini_image_search_agent.py	Cross-modal image indexing and Agent text-to-image search with query embedding options.

Run the image search example with two or more local PNG/JPEG files:

uv run samples/02-agents/providers/gemini/gemini_image_search_agent.py \
  --query "Which image shows a dog?" photos/dog.jpg photos/cat.png

Image embeddings are generated without a task prefix. The search tool uses RETRIEVAL_QUERY for text queries and shares the image index's 768 dimensions.

Environment Variables

• GOOGLE_MODEL: The Gemini chat model to use (for example, gemini-2.5-flash-lite or gemini-2.5-pro)
• For Gemini Developer API: GOOGLE_API_KEY
• For Gemini Enterprise Agent Platform (chat and embeddings): GOOGLE_GENAI_USE_ENTERPRISE=true, GOOGLE_CLOUD_PROJECT, and GOOGLE_CLOUD_LOCATION. The older GOOGLE_GENAI_USE_VERTEXAI=true setting remains supported.
• GOOGLE_EMBEDDING_MODEL: Optional gemini-embedding-2-preview override (defaults to gemini-embedding-2)