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Gemini - Google AI Studio

Pre-requisites

  • pip install -q google-generativeai

Gemini-Pro

Sample Usage

from litellm import completion
import os

os.environ['GEMINI_API_KEY'] = ""
response = completion(
model="gemini/gemini-pro",
messages=[{"role": "user", "content": "write code for saying hi from LiteLLM"}]
)

Specifying Safety Settings

In certain use-cases you may need to make calls to the models and pass safety settigns different from the defaults. To do so, simple pass the safety_settings argument to completion or acompletion. For example:

response = completion(
model="gemini/gemini-pro",
messages=[{"role": "user", "content": "write code for saying hi from LiteLLM"}]
safety_settings=[
{
"category": "HARM_CATEGORY_HARASSMENT",
"threshold": "BLOCK_NONE",
},
{
"category": "HARM_CATEGORY_HATE_SPEECH",
"threshold": "BLOCK_NONE",
},
{
"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
"threshold": "BLOCK_NONE",
},
{
"category": "HARM_CATEGORY_DANGEROUS_CONTENT",
"threshold": "BLOCK_NONE",
},
]
)

Gemini-Pro-Vision

LiteLLM Supports the following image types passed in url

Sample Usage

import os
import litellm
from dotenv import load_dotenv

# Load the environment variables from .env file
load_dotenv()
os.environ["GEMINI_API_KEY"] = os.getenv('GEMINI_API_KEY')

prompt = 'Describe the image in a few sentences.'
# Note: You can pass here the URL or Path of image directly.
image_url = 'https://storage.googleapis.com/github-repo/img/gemini/intro/landmark3.jpg'

# Create the messages payload according to the documentation
messages = [
{
"role": "user",
"content": [
{
"type": "text",
"text": prompt
},
{
"type": "image_url",
"image_url": {"url": image_url}
}
]
}
]

# Make the API call to Gemini model
response = litellm.completion(
model="gemini/gemini-pro-vision",
messages=messages,
)

# Extract the response content
content = response.get('choices', [{}])[0].get('message', {}).get('content')

# Print the result
print(content)

Chat Models

Model NameFunction CallRequired OS Variables
gemini-procompletion('gemini/gemini-pro', messages)os.environ['GEMINI_API_KEY']
gemini-pro-visioncompletion('gemini/gemini-pro-vision', messages)os.environ['GEMINI_API_KEY']