Gemini-Playground provides a Python interface and a UI to interact with last Google's
Gemini's version, models/gemini-1.5-pro-latest, and other variants of Gemini. With Gemini Playground,
you can:
- Engage in conversation with your data: Upload images, and videos using a simple API and generate responses based on your prompts.
- Chat with your codebase: Ask Gemini to analyze your code, explain its functionality, suggest improvements, or even write documentation for it.
- Explore multimodal capabilities: Combine different data types in your prompts, like asking Gemini to describe what's happening in a video and an image simultaneously.
- Intuitive API: The
GeminiClientclass offers a simple and easy-to-use interface for interacting with the Gemini API. - Multimodal Support: Upload and use text, images, videos, and code in your prompts.
- File Management: Upload, list, and remove files from your Gemini storage.
- Token Counting: Estimate the number of tokens required for a prompt and response.
- Response Generation: Generate responses from Gemini based on your prompts and uploaded content.
- Rich Logging: Get informative and colorful logging messages for better understanding of the process.
You can find usage examples in the examples directory.
pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ geminiplayground-
Set up your API key:
- Obtain an API key from Google AI-Studio.
- Set the
AISTUDIO_API_KEYenvironment variable with your API key.
-
Create a
GeminiClientinstance:
from geminiplayground.core import GeminiClient
from geminiplayground.parts import VideoFile, ImageFile
from geminiplayground.schemas import HarmCategory, HarmBlockThreshold
gemini_client = GeminiClient()- Upload files:
video_file_path = "BigBuckBunny_320x180.mp4"
video_file = VideoFile(video_file_path, gemini_client=gemini_client)
video_file.upload()
image_file_path = "https://upload.wikimedia.org/wikipedia/commons/4/47/PNG_transparency_demonstration_1.png"
image_file = ImageFile(image_file_path, gemini_client=gemini_client)
image_file.upload()- Create a prompt:
multimodal_prompt = [
"See this video",
video_file,
"and this image",
image_file,
"Explain what you see."
]- Generate a response:
response = gemini_client.generate_response("models/gemini-1.5-pro-latest", multimodal_prompt,
generation_config={"temperature": 0.0, "top_p": 1.0},
safety_settings={
"category": HarmCategory.DANGEROUS_CONTENT,
"threshold": HarmBlockThreshold.BLOCK_NONE
})
# Print the response
for candidate in response.candidates:
for part in candidate.content.parts:
if part.text:
print(part.text)The video is a short animated film called "Big Buck Bunny." It is a comedy about a large, white rabbit
who is bullied by three smaller animals. The rabbit eventually gets revenge on his tormentors. The film
was created using Blender, a free and open-source 3D animation software.
The image is of four dice, each a different color. The dice are transparent and have white dots. The
image is isolated on a black background.
- You can also chat with your data:
Chat with your codebase:
from rich import print
from geminiplayground.core import GeminiClient
from geminiplayground.parts.git_repo_part import GitRepo
from geminiplayground.schemas import GenerateRequestParts, TextPart, GenerateRequest
def chat_wit_your_code():
"""
Get the content parts of a github repo and generate a request.
:return:
"""
repo = GitRepo.from_url("https://github.com/karpathy/ng-video-lecture",
branch="master",
config={
"content": "code-files", # "code-files" or "issues"
"exclude_dirs": ["frontend", "ui"],
"file_extensions": [".py"]
})
repo_parts = repo.content_parts()
request_parts = GenerateRequestParts(parts=[
TextPart(text="use this codebase:"),
*repo_parts,
TextPart(
text="Help me to write a Readme file for this codebase."),
])
request = GenerateRequest(
contents=[
request_parts
]
)
model = "models/gemini-1.5-pro-latest"
gemini_client = GeminiClient()
tokens_count = gemini_client.get_tokens_count(model, request)
print("Tokens count: ", tokens_count)
response = gemini_client.generate_response(model, request)
# Print the response
for candidate in response.candidates:
for part in candidate.content.parts:
if part.text:
print(part.text)
if __name__ == '__main__':
chat_wit_your_code()Chat with your videos:
from rich import print
from geminiplayground.core import GeminiClient
from geminiplayground.parts import VideoFile
from geminiplayground.schemas import GenerateRequestParts, TextPart, GenerateRequest
def chat_wit_your_video():
"""
Get the content parts of a video and generate a request.
:return:
"""
gemini_client = GeminiClient()
model = "models/gemini-1.5-pro-latest"
video_file_path = "./../data/BigBuckBunny_320x180.mp4"
video_file = VideoFile(video_file_path, gemini_client=gemini_client)
video_parts = video_file.content_parts()
video_files = video_file.files[-4:]
for part in video_parts[:5]:
print(part)
request_parts = GenerateRequestParts(parts=[
TextPart(text="check this video?:"),
*video_parts,
TextPart(text="list the object you see in the video")
])
request = GenerateRequest(
contents=[
request_parts
]
)
tokens_count = gemini_client.get_tokens_count(model, request)
print("Tokens count: ", tokens_count)
response = gemini_client.generate_response(model, request)
# Print the response
for candidate in response.candidates:
for part in candidate.content.parts:
if part.text:
print(part.text)
if __name__ == '__main__':
chat_wit_your_video()Chat with your images:
from rich import print
from geminiplayground.core import GeminiClient
from geminiplayground.parts import ImageFile
from geminiplayground.schemas import GenerateRequestParts, TextPart, GenerateRequest
def chat_wit_your_images():
"""
Get the content parts of an image and generate a request.
:return:
"""
gemini_client = GeminiClient()
model = "models/gemini-1.5-pro-latest"
image_file_path = "https://upload.wikimedia.org/wikipedia/commons/4/47/PNG_transparency_demonstration_1.png"
image_file = ImageFile(image_file_path, gemini_client=gemini_client)
image_parts = image_file.content_parts()
image_files = image_file.files
print("Image files: ", image_files)
request_parts = GenerateRequestParts(parts=[
TextPart(text="You see this image?:"),
*image_parts,
TextPart(text="Describe what you see"),
])
request = GenerateRequest(
contents=[
request_parts
],
)
tokens_count = gemini_client.get_tokens_count(model, request)
print("Tokens count: ", tokens_count)
response = gemini_client.generate_response(model, request)
# Print the response
for candidate in response.candidates:
for part in candidate.content.parts:
if part.text:
print(part.text)
if __name__ == '__main__':
chat_wit_your_images()This is a basic example.Explore the codebase and documentation for more advanced functionalities and examples.
You can also use the GUI to interact with Gemini.
Remember to set the AISTUDIO_API_KEY environment variable with your API key. You can do so globally, pass it as an
argument to the command, or create a .env file in the root of your project and set the AISTUDIO_API_KEY variable
there.
For running the GUI, use the following command:
geminiplayground uior
AISTUDIO_API_KEY=your_api_key geminiplaygroundThis will start a local server and open the GUI in your default browser.
Contributions are welcome! Please see theCONTRIBUTING.md file for guidelines [Coming soon].
This codebase is licensed under the MIT License.See theLICENSEfile for details.
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