A reverse-engineered asynchronous python wrapper for Google Gemini (formerly Bard).

• ImageFx Support - Supports retrieving images generated by ImageFx, Google's latest AI image generator.
• Extension Support - Supports generating contents with Gemini extensions on, like YouTube and Gmail.
• Classified Outputs - Auto categorizes texts, web images and AI generated images from the response.
• Official Flavor - Provides a simple and elegant interface inspired by Google Generative AI's official API.
• Asynchronous - Utilizes asyncio to run generating tasks and return outputs efficiently.

pip install gemini-webapi

• Go to https://gemini.google.com and login with your Google account
• Press F12 for web inspector, go to Network tab and refresh the page
• Click any request and copy cookie values of __Secure-1PSID and __Secure-1PSIDTS

Note: __Secure-1PSIDTS could get expired frequently if the Google account is actively used elsewhere, especially when visiting https://gemini.google.com directly. It's recommended to use a separate Google account if you are builing a keep-alive service with this package.

Import required packages and initialize a client with your cookies obtained from the previous step.

import asyncio
from gemini import GeminiClient

# Replace "COOKIE VALUE HERE" with your actual cookie values
Secure_1PSID = "COOKIE VALUE HERE"
Secure_1PSIDTS = "COOKIE VALUE HERE"

async def main():
    client = GeminiClient(Secure_1PSID, Secure_1PSIDTS, proxy=None)
    await client.init(timeout=30)

asyncio.run(main())

Ask a one-turn quick question by calling GeminiClient.generate_content.

async def main():
    response = await client.generate_content("Hello World!")
    print(response.text)

asyncio.run(main())

Note: simply use print(response) to get the same output if you just want to see the response text

If you want to keep conversation continuous, please use GeminiClient.start_chat to create a ChatSession object and send messages through it. The conversation history will be automatically handled and get updated after each turn.

async def main():
    chat = client.start_chat()
    response1 = await chat.send_message("Briefly introduce Europe")
    response2 = await chat.send_message("What's the population there?")
    print(response1.text, response2.text, sep="\n\n----------------------------------\n\n")

asyncio.run(main())

Images in the API's output are stored as a list of Image objects. You can access the image title, URL, and description by calling image.title, image.url and image.alt respectively.

async def main():
    response = await client.generate_content("Send me some pictures of cats")
    for image in response.images:
        print(image, "\n\n----------------------------------\n")

asyncio.run(main())

In February 2022, Google introduced a new AI image generator called ImageFx and integrated it into Gemini. You can ask Gemini to generate images with ImageFx simply by natural language.

Important: Google has some limitations on the image generation feature in Gemini, so its availability could be different per region/account. Here's a summary copied from official documentation (as of February 15th, 2024):

Image generation in Gemini Apps is available in most countries, except in the European Economic Area (EEA), Switzerland, and the UK. It’s only available for English prompts.

This feature’s availability in any specific Gemini app is also limited to the supported languages and countries of that app.

For now, this feature isn’t available to users under 18.

async def main():
    response = await client.generate_content("Generate some pictures of cats")
    for image in response.images:
        print(image, "\n\n----------------------------------\n")

asyncio.run(main())

Note: by default, when asked to send images (like the previous example), Gemini will send images fetched from web instead of generating images with AI model, unless you specifically require to "generate" images in your prompt. In this package, web images and generated images are treated differently as WebImage and GeneratedImage, and will be automatically categorized in the output.

You can save images returned from Gemini to local files under /temp by calling Image.save(). Optionally, you can specify the file path and file name by passing path and filename arguments to the function. Works for both WebImage and GeneratedImage.

async def main():
    response = await client.generate_content("Generate some pictures of cats")
    for i, image in enumerate(response.images):
        await image.save(path="temp/", filename=f"cat_{i}.png")

asyncio.run(main())

Important: To access Gemini extensions in API, you must activate them on the Gemini website first. Same as image generation, Google also has limitations on the availability of Gemini extensions. Here's a summary copied from official documentation (as of February 18th, 2024):

To use extensions in Gemini Apps:

Sign in with your personal Google Account that you manage on your own. Extensions, including the Google Workspace extension, are currently not available to Google Workspace accounts for school, business, or other organizations.

Have Gemini Apps Activity on. Extensions are only available when Gemini Apps Activity is turned on.

Important: For now, extensions are available in English, Japanese, and Korean only.

Note: for the last item, instead of region requirement, it actually only requires your Google account's preferred language to be set to one of the supported languages. You can change your language settings here.

A response from Gemini usually contains multiple reply candidates with different generated contents. You can check all candidates and choose one to continue the conversation. By default, the first candidate will be chosen automatically.

async def main():
    # Start a conversation and list all reply candidates
    chat = client.start_chat()
    response = await chat.send_message("What's the best Japanese dish? Recommend one only.")
    for candidate in response.candidates:
        print(candidate, "\n\n----------------------------------\n")

    # Control the ongoing conversation flow by choosing candidate manually
    new_candidate = chat.choose_candidate(index=1)  # Choose the second candidate here
    followup_response = await chat.send_message("Tell me more about it.")  # Will generate contents based on the chosen candidate
    print(new_candidate, followup_response, sep="\n\n----------------------------------\n\n")

asyncio.run(main())

Google AI Studio

acheong08/Bard