--- title: "Google AI Studio SDK" description: "import Image from '@theme/IdealImage'; import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem';" type: skill canonical_url: https://claudary.paisolsolutions.com/skills/google-ai-studio source: "Claudary" difficulty: intermediate author: "Claude Code Knowledge Pack" date: 2026-07-10T11:24:59.717Z license: CC-BY-4.0 attribution: "Google AI Studio SDK — Claudary (https://claudary.paisolsolutions.com/skills/google-ai-studio)" --- # Google AI Studio SDK import Image from '@theme/IdealImage'; import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem'; ## Overview import Image from '@theme/IdealImage'; import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem'; # Google AI Studio SDK Pass-through endpoints for Google AI Studio - call provider-specific endpoint, in native format (no translation). | Feature | Supported | Notes | |-------|-------|-------| | Cost Tracking | ✅ | supports all models on `/generateContent` endpoint | | Logging | ✅ | works across all integrations | | End-user Tracking | ❌ | [Tell us if you need this](https://github.com/BerriAI/litellm/issues/new) | | Streaming | ✅ | | Just replace `https://generativelanguage.googleapis.com` with `LITELLM_PROXY_BASE_URL/gemini` #### **Example Usage** ```bash curl 'http://0.0.0.0:4000/gemini/v1beta/models/gemini-1.5-flash:countTokens?key=sk-anything' \\ -H 'Content-Type: application/json' \\ -d '{ "contents": [{ "parts":[{ "text": "The quick brown fox jumps over the lazy dog." }] }] }' ``` ```javascript const { GoogleGenAI } = require("@google/genai"); const ai = new GoogleGenAI({ apiKey: "sk-1234", // litellm proxy API key httpOptions: { baseUrl: "http://localhost:4000/gemini", // http:///gemini }, }); async function main() { try { const response = await ai.models.generateContent({ model: "gemini-2.5-flash", contents: "Explain how AI works", }); console.log(response.text); } catch (error) { console.error('Error:', error); } } // For streaming responses async function main_streaming() { try { const response = await ai.models.generateContentStream({ model: "gemini-2.5-flash", contents: "Explain how AI works", }); for await (const chunk of response) { process.stdout.write(chunk.text); } } catch (error) { console.error('Error:', error); } } main(); // main_streaming(); ``` Supports **ALL** Google AI Studio Endpoints (including streaming). [**See All Google AI Studio Endpoints**](https://ai.google.dev/api) ## Quick Start Let's call the Gemini [`/countTokens` endpoint](https://ai.google.dev/api/tokens#method:-models.counttokens) 1. Add Gemini API Key to your environment ```bash export GEMINI_API_KEY="" ``` 2. Start LiteLLM Proxy ```bash litellm # RUNNING on http://0.0.0.0:4000 ``` 3. Test it! Let's call the Google AI Studio token counting endpoint ```bash http://0.0.0.0:4000/gemini/v1beta/models/gemini-1.5-flash:countTokens?key=anything' \\ -H 'Content-Type: application/json' \\ -d '{ "contents": [{ "parts":[{ "text": "The quick brown fox jumps over the lazy dog." }] }] }' ``` ## Examples Anything after `http://0.0.0.0:4000/gemini` is treated as a provider-specific route, and handled accordingly. Key Changes: | **Original Endpoint** | **Replace With** | |------------------------------------------------------|-----------------------------------| | `https://generativelanguage.googleapis.com` | `http://0.0.0.0:4000/gemini` (LITELLM_PROXY_BASE_URL="http://0.0.0.0:4000") | | `key=$GOOGLE_API_KEY` | `key=anything` (use `key=LITELLM_VIRTUAL_KEY` if Virtual Keys are setup on proxy) | ### **Example 1: Counting tokens** #### LiteLLM Proxy Call ```bash curl http://0.0.0.0:4000/gemini/v1beta/models/gemini-1.5-flash:countTokens?key=anything \\ -H 'Content-Type: application/json' \\ -X POST \\ -d '{ "contents": [{ "parts":[{ "text": "The quick brown fox jumps over the lazy dog." }], }], }' ``` #### Direct Google AI Studio Call ```bash curl https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash:countTokens?key=$GOOGLE_API_KEY \\ -H 'Content-Type: application/json' \\ -X POST \\ -d '{ "contents": [{ "parts":[{ "text": "The quick brown fox jumps over the lazy dog." }], }], }' ``` ### **Example 2: Generate content** #### LiteLLM Proxy Call ```bash curl "http://0.0.0.0:4000/gemini/v1beta/models/gemini-1.5-flash:generateContent?key=anything" \\ -H 'Content-Type: application/json' \\ -X POST \\ -d '{ "contents": [{ "parts":[{"text": "Write a story about a magic backpack."}] }] }' 2> /dev/null ``` #### Direct Google AI Studio Call ```bash curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash:generateContent?key=$GOOGLE_API_KEY" \\ -H 'Content-Type: application/json' \\ -X POST \\ -d '{ "contents": [{ "parts":[{"text": "Write a story about a magic backpack."}] }] }' 2> /dev/null ``` ### **Example 3: Caching** ```bash curl -X POST "http://0.0.0.0:4000/gemini/v1beta/models/gemini-1.5-flash-001:generateContent?key=anything" \\ -H 'Content-Type: application/json' \\ -d '{ "contents": [ { "parts":[{ "text": "Please summarize this transcript" }], "role": "user" }, ], "cachedContent": "'$CACHE_NAME'" }' ``` #### Direct Google AI Studio Call ```bash curl -X POST "https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash-001:generateContent?key=$GOOGLE_API_KEY" \\ -H 'Content-Type: application/json' \\ -d '{ "contents": [ { "parts":[{ "text": "Please summarize this transcript" }], "role": "user" }, ], "cachedContent": "'$CACHE_NAME'" }' ``` ## **Example 4: Video Generation with Veo** Generate videos using Google's Veo model through LiteLLM pass-through routes. [**→ Complete Veo Video Generation Guide**](../proxy/veo_video_generation.md) ## Advanced Pre-requisites - [Setup proxy with DB](../proxy/virtual_keys.md#setup) Use this, to avoid giving developers the raw Google AI Studio key, but still letting them use Google AI Studio endpoints. ### Use with Virtual Keys 1. Setup environment ```bash export DATABASE_URL="" export LITELLM_MASTER_KEY="" export GEMINI_API_KEY="" ``` ```bash litellm # RUNNING on http://0.0.0.0:4000 ``` 2. Generate virtual key ```bash curl -X POST 'http://0.0.0.0:4000/key/generate' \\ -H 'Authorization: Bearer sk-1234' \\ -H 'Content-Type: application/json' \\ -d '{}' ``` Expected Response ```bash { ... "key": "sk-1234ewknldferwedojwojw" } ``` 3. Test it! ```bash http://0.0.0.0:4000/gemini/v1beta/models/gemini-1.5-flash:countTokens?key=sk-1234ewknldferwedojwojw' \\ -H 'Content-Type: application/json' \\ -d '{ "contents": [{ "parts":[{ "text": "The quick brown fox jumps over the lazy dog." }] }] }' ``` ### Send `tags` in request headers Use this if you want `tags` to be tracked in the LiteLLM DB and on logging callbacks. Pass tags in request headers as a comma separated list. In the example below the following tags will be tracked ``` tags: ["gemini-js-sdk", "pass-through-endpoint"] ``` ```bash curl 'http://0.0.0.0:4000/gemini/v1beta/models/gemini-1.5-flash:generateContent?key=sk-anything' \\ -H 'Content-Type: application/json' \\ -H 'tags: gemini-js-sdk,pass-through-endpoint' \\ -d '{ "contents": [{ "parts":[{ "text": "The quick brown fox jumps over the lazy dog." }] }] }' ``` ```javascript const { GoogleGenAI } = require("@google/genai"); const ai = new GoogleGenAI({ apiKey: "sk-1234", httpOptions: { baseUrl: "http://localhost:4000/gemini", // http:///gemini headers: { "tags": "gemini-js-sdk,pass-through-endpoint", }, }, }); async function main() { try { const response = await ai.models.generateContent({ model: "gemini-2.5-flash", contents: "Explain how AI works", }); console.log(response.text); } catch (error) { console.error('Error:', error); } } main(); ``` --- Source: [Claudary](https://claudary.paisolsolutions.com/skills/google-ai-studio) · https://claudary.paisolsolutions.com