gemini-genai

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Google python-genai SDK for Gemini 3 Flash, Gemini 3 Pro, and Gemini models. Use when building with Google's Gemini API, google-genai, implementing thinking/reasoning, structured outputs, function calling, image generation, or multimodal. Triggers on "gemini", "google ai", "genai".

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[API Helpers]

When & Why to Use This Skill

This Claude skill provides comprehensive support for the Google python-genai SDK, enabling developers to seamlessly integrate Gemini 3 Flash and Pro models into their applications. It facilitates advanced AI capabilities including multimodal processing (text, image, video, audio, PDF), structured outputs, function calling, and sophisticated reasoning configurations, making it an essential tool for building high-performance agentic workflows.

Use Cases

  • Building multimodal AI applications that can process and analyze diverse inputs like video, audio, and complex PDF documents.
  • Implementing advanced reasoning tasks by fine-tuning Gemini 3's thinking levels to balance latency and depth of thought.
  • Generating structured, type-safe data outputs using JSON schemas and Enum responses for reliable integration with existing software systems.
  • Enhancing agent capabilities with real-time web search grounding and secure code execution through built-in Gemini tools.
  • Optimizing large-scale AI deployments using asynchronous programming patterns and context caching to significantly reduce operational costs.
namegemini-genai
descriptionGoogle python-genai SDK for Gemini 3 Flash, Gemini 3 Pro, and Gemini models. Use when building with Google's Gemini API, google-genai, implementing thinking/reasoning, structured outputs, function calling, image generation, or multimodal. Triggers on "gemini", "google ai", "genai".

Google Gemini python-genai SDK

Model IDs

Model ID
Gemini 3 Flash gemini-3-flash-preview
Gemini 3 Pro gemini-3-pro-preview
Gemini 3 Pro Image gemini-3-pro-image-preview
Gemini 2.5 Flash gemini-2.5-flash
Gemini 2.5 Pro gemini-2.5-pro

Gemini 3 Flash Capabilities

Token Limits: 1,048,576 input / 65,536 output (confirmed 1M context)

Inputs: Text, Image, Video, Audio, PDF

Supported: Batch API, Caching, Code execution, File search, Function calling, Search grounding, Structured outputs, Thinking, URL context

Not Supported: Audio generation, Image generation (use gemini-3-pro-image-preview), Live API, Grounding with Google Maps

Knowledge cutoff: January 2025

Critical: Temperature for Gemini 3

Keep temperature=1.0 - Lower values cause response looping.

Thinking Levels (Gemini 3)

config=types.GenerateContentConfig(
    thinking_config=types.ThinkingConfig(thinking_level="high")  # minimal|low|medium|high
)
  • minimal: No thinking, lowest latency (Flash only)
  • high: Maximum reasoning (default)

Async Pattern

async with genai.Client().aio as client:
    response = await client.models.generate_content(...)

# Async chat
chat = client.aio.chats.create(model="gemini-3-flash-preview")

Media Resolution (v1alpha required)

client = genai.Client(http_options=types.HttpOptions(api_version='v1alpha'))

types.Part(
    inline_data=types.Blob(mime_type="image/jpeg", data=image_bytes),
    media_resolution={"level": "media_resolution_high"}  # low|medium|high|ultra_high
)

Tokens: low=280, medium=560, high=1120

Built-in Tools (Gemini 3)

config=types.GenerateContentConfig(
    tools=[{"google_search": {}}],    # Web search
    # tools=[{"url_context": {}}],    # Fetch URL content
    # tools=[{"code_execution": {}}], # Run code
)

Enum Response

from enum import Enum

class Category(Enum):
    A = "A"
    B = "B"

config={
    "response_mime_type": "text/x.enum",
    "response_schema": Category,
}

Image Generation

response = client.models.generate_content(
    model="gemini-3-pro-image-preview",
    contents="A cyberpunk city",
    config=types.GenerateContentConfig(
        response_modalities=["IMAGE"],
        image_config=types.ImageConfig(aspect_ratio="16:9", image_size="4K"),
    ),
)
image = response.parts[0].as_image()
image.save("out.png")

Grounded (with search): Add tools=[{"google_search": {}}]

Response Helpers

response.text           # Text content
response.parsed         # Auto-parsed JSON (when using response_json_schema)
response.function_calls # List of function calls (cleaner than candidates drilling)

Pricing (Gemini 3 Flash)

Input: $0.50/1M | Output: $3.00/1M | Context caching: up to 90% reduction

Resources