Google AI Studio SDK
Pass-through endpoints for Google AI Studio - call provider-specific endpoint, in native format (no translation).
Just replace https://generativelanguage.googleapis.com
with LITELLM_PROXY_BASE_URL/gemini
🚀
Example Usage
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."
}]
}]
}'
Supports ALL Google AI Studio Endpoints (including streaming).
See All Google AI Studio Endpoints
Quick Start
Let's call the Gemini /countTokens
endpoint
- Add Gemini API Key to your environment
export GEMINI_API_KEY=""
- Start LiteLLM Proxy
litellm
# RUNNING on http://0.0.0.0:4000
- Test it!
Let's call the Google AI Studio token counting endpoint
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=$GOOGLE_API_KEY | key=anything (use key=LITELLM_VIRTUAL_KEY if Virtual Keys are setup on proxy) |
Example 1: Counting tokens
LiteLLM Proxy Call
curl http://0.0.0.0:4000/gemini/v1beta/models/gemini-1.5-flash:countTokens?key=anything \
-H 'Content-Type: application/json' \
-X POST \
-d '{
"contents": [{
"parts":[{
"text": "The quick brown fox jumps over the lazy dog."
}],
}],
}'
Direct Google AI Studio Call
curl https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash:countTokens?key=$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
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
curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash:generateContent?key=$GOOGLE_API_KEY" \
-H 'Content-Type: application/json' \
-X POST \
-d '{
"contents": [{
"parts":[{"text": "Write a story about a magic backpack."}]
}]
}' 2> /dev/null
Example 3: Caching
curl -X POST "http://0.0.0.0:4000/gemini/v1beta/models/gemini-1.5-flash-001:generateContent?key=anything" \
-H 'Content-Type: application/json' \
-d '{
"contents": [
{
"parts":[{
"text": "Please summarize this transcript"
}],
"role": "user"
},
],
"cachedContent": "'$CACHE_NAME'"
}'
Direct Google AI Studio Call
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'"
}'
Advanced - Use with Virtual Keys
Pre-requisites
Use this, to avoid giving developers the raw Google AI Studio key, but still letting them use Google AI Studio endpoints.
Usage
- Setup environment
export DATABASE_URL=""
export LITELLM_MASTER_KEY=""
export GEMINI_API_KEY=""
litellm
# RUNNING on http://0.0.0.0:4000
- Generate virtual key
curl -X POST 'http://0.0.0.0:4000/key/generate' \
-H 'Authorization: Bearer sk-1234' \
-H 'Content-Type: application/json' \
-d '{}'
Expected Response
{
...
"key": "sk-1234ewknldferwedojwojw"
}
- Test it!
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."
}]
}]
}'