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import os
import time
from typing import List, Tuple, Optional
from pathlib import Path
import google.generativeai as genai
import gradio as gr
from PIL import Image
print("google-generativeai:", genai.__version__)
GOOGLE_API_KEY = os.environ.get("GOOGLE_API_KEY")
TITLE = """<h1 align="center">🕹️ Google Gemini Playground 🔥</h1>"""
SUBTITLE = """<h2 align="center">Play with Gemini Text and Vision Model API 🖇️</h2>"""
DUPLICATE = """
<div style="text-align: center; display: flex; justify-content: center; align-items: center;">
<a href="https://huggingface.co/spaces/tsereno/Gemini-Powered-App?logs=container&duplicate=true">
<img src="https://bit.ly/3gLdBN6" alt="Duplicate Space" style="margin-right: 10px;">
</a>
<span>Duplicate the Space and run securely with your
<a href="https://makersuite.google.com/app/apikey">GOOGLE API KEY</a>.
</span>
</div>
"""
IMAGE_WIDTH = 512
def preprocess_stop_sequences(stop_sequences: str) -> Optional[List[str]]:
if not stop_sequences:
return None
return [sequence.strip() for sequence in stop_sequences.split(",")]
def preprocess_image(image: Image.Image) -> Optional[Image.Image]:
image_height = int(image.height * IMAGE_WIDTH / image.width)
return image.resize((IMAGE_WIDTH, image_height))
def user(text_prompt: str, chatbot: List[Tuple[str, str]]):
return "", chatbot + [[text_prompt, None]]
def bot(
google_key: str,
model_name: str,
image_prompt: Optional[Image.Image],
video_prompt,
file_prompt,
temperature: float,
max_output_tokens: int,
stop_sequences: str,
top_k: int,
top_p: float,
text_prompt_component: str,
chatbot: List[Tuple[str, str]]
):
google_key = google_key if google_key else GOOGLE_API_KEY
if not google_key:
raise ValueError(
"GOOGLE_API_KEY is not set. "
"Please follow the instructions in the README to set it up.")
text_prompt = chatbot[-1][0]
if file_prompt is not None:
# Initialize an empty string to store content
all_content = ""
for file in file_prompt:
# Open the file in read binary mode ('rb')
with open(file.name, 'rb') as f:
# Read the entire file content into a byte string
content = f.read()
# Decode the byte string to a UTF-8 string (assuming text file)
all_content += content.decode('utf-8')
text_prompt = all_content + " " + chatbot[-1][0]
genai.configure(api_key=google_key)
generation_config = genai.types.GenerationConfig(
temperature=temperature,
max_output_tokens=max_output_tokens,
stop_sequences=preprocess_stop_sequences(stop_sequences=stop_sequences),
top_k=top_k,
top_p=top_p)
if video_prompt is not None:
#video_prompt = preprocess_image(video_prompt)
model = genai.GenerativeModel(model_name)
video_file = genai.upload_file(path=video_prompt)
while video_file.state.name == "PROCESSING":
print('.', end='')
time.sleep(10)
video_file = genai.get_file(video_file.name)
if video_file.state.name == "FAILED":
raise ValueError(video_file.state.name)
response = model.generate_content(
contents=[text_prompt, video_file],
stream=True,
generation_config=generation_config,
request_options={"timeout": 600})
response.resolve()
elif image_prompt is not None:
image_prompt = preprocess_image(image_prompt)
model = genai.GenerativeModel(model_name)
response = model.generate_content(
contents=[text_prompt, image_prompt],
stream=True,
generation_config=generation_config)
response.resolve()
else:
model = genai.GenerativeModel(model_name)
response = model.generate_content(
text_prompt,
stream=True,
generation_config=generation_config)
response.resolve()
# streaming effect
chatbot[-1][1] = ""
for chunk in response:
for i in range(0, len(chunk.text), 10):
section = chunk.text[i:i + 10]
chatbot[-1][1] += section
time.sleep(0.01)
yield chatbot
google_key_component = gr.Textbox(
label="GOOGLE API KEY",
value="",
type="password",
placeholder="...",
info="You have to provide your own GOOGLE_API_KEY for this app to function properly",
visible=GOOGLE_API_KEY is None
)
def upload_file(files):
file_paths = [file.name for file in files]
return file_paths
image_prompt_component = gr.Image(type="pil", label="Image", scale=1)
video_prompt_component = gr.Video(label="Video")
file_prompt_component = gr.UploadButton("Click to Upload Text Files", file_count="multiple", label="File")
#model_selection = gr.Dropdown(["gemini-1.0-pro", "gemini-pro-vision","gemini-1.5-flash-latest", "gemini-1.5-pro-latest","gemini-1.0-pro-001"],label="Select Gemini Model",value="gemini-1.0-pro")
model_selection = gr.Dropdown(["gemini-1.5-flash-latest", "gemini-1.5-pro-latest"],label="Select Gemini Model",value="gemini-1.5-pro-latest")
chatbot_component = gr.Chatbot(
label='Gemini',
bubble_full_width=False,
scale=2
)
text_prompt_component = gr.Textbox(
placeholder="Hi there!",
label="Ask me anything and press Enter"
)
run_button_component = gr.Button()
temperature_component = gr.Slider(
minimum=0,
maximum=1.0,
value=0.4,
step=0.05,
label="Temperature",
info=(
"Temperature controls the degree of randomness in token selection. Lower "
"temperatures are good for prompts that expect a true or correct response, "
"while higher temperatures can lead to more diverse or unexpected results. "
))
max_output_tokens_component = gr.Slider(
minimum=1,
maximum=2048,
value=1024,
step=1,
label="Token limit",
info=(
"Token limit determines the maximum amount of text output from one prompt. A "
"token is approximately four characters. The default value is 2048."
))
stop_sequences_component = gr.Textbox(
label="Add stop sequence",
value="",
type="text",
placeholder="STOP, END",
info=(
"A stop sequence is a series of characters (including spaces) that stops "
"response generation if the model encounters it. The sequence is not included "
"as part of the response. You can add up to five stop sequences."
))
top_k_component = gr.Slider(
minimum=1,
maximum=40,
value=32,
step=1,
label="Top-K",
info=(
"Top-k changes how the model selects tokens for output. A top-k of 1 means the "
"selected token is the most probable among all tokens in the model’s "
"vocabulary (also called greedy decoding), while a top-k of 3 means that the "
"next token is selected from among the 3 most probable tokens (using "
"temperature)."
))
top_p_component = gr.Slider(
minimum=0,
maximum=1,
value=1,
step=0.01,
label="Top-P",
info=(
"Top-p changes how the model selects tokens for output. Tokens are selected "
"from most probable to least until the sum of their probabilities equals the "
"top-p value. For example, if tokens A, B, and C have a probability of .3, .2, "
"and .1 and the top-p value is .5, then the model will select either A or B as "
"the next token (using temperature). "
))
user_inputs = [text_prompt_component,
chatbot_component
]
bot_inputs = [
google_key_component,
model_selection,
image_prompt_component,
video_prompt_component,
file_prompt_component,
temperature_component,
max_output_tokens_component,
stop_sequences_component,
top_k_component,
top_p_component,
text_prompt_component,
chatbot_component
]
with gr.Blocks() as demo:
gr.HTML(TITLE)
gr.HTML(SUBTITLE)
gr.HTML(DUPLICATE)
with gr.Column():
google_key_component.render()
with gr.Row():
image_prompt_component.render()
video_prompt_component.render()
file_prompt_component.render()
file_output = gr.File()
file_prompt_component.upload(upload_file, file_prompt_component, file_output)
model_selection.render()
chatbot_component.render()
text_prompt_component.render()
run_button_component.render()
with gr.Accordion("Parameters", open=False):
temperature_component.render()
max_output_tokens_component.render()
stop_sequences_component.render()
with gr.Accordion("Advanced", open=False):
top_k_component.render()
top_p_component.render()
run_button_component.click(
fn=user,
inputs=user_inputs,
outputs=[text_prompt_component, chatbot_component],
queue=False
).then(
fn=bot, inputs=bot_inputs, outputs=[chatbot_component]
)
text_prompt_component.submit(
fn=user,
inputs=user_inputs,
outputs=[text_prompt_component, chatbot_component],
queue=False
).then(
fn=bot, inputs=bot_inputs, outputs=[chatbot_component]
)
gr.Examples(
fn=bot,
inputs=bot_inputs,
outputs=[chatbot_component],
examples=
[
[
"",
"gemini-1.5-pro-latest",
None,
None,
None,
.4,
1024,
"",
32,
1,
"How far is the moon from the earth?",
[("", "")]
],
[
"",
"gemini-1.5-pro-latest",
None,
None,
None,
.4,
1024,
"",
32,
1,
"What is 2+2?",
[("", "")]
],
[
"",
"gemini-1.5-pro-latest",
"./example1.webp",
None,
None,
.4,
1024,
"",
32,
1,
"What is the ball doing? What did the club do to influence the ball? What did player do to influence the golf club?",
[("", "")]
],
[
"",
"gemini-1.5-pro-latest",
"./example2.jpg",
None,
None,
.4,
1024,
"",
32,
1,
"What is the ball doing? What did the club do to influence the ball? What did player do to influence the golf club?",
[("", "")]
],
[
"",
"gemini-1.5-pro-latest",
None,
"./example1.mp4",
None,
.4,
1024,
"",
32,
1,
"What is the ball doing? What did the club do to influence the ball? What did player do to influence the golf club?",
[("", "")]
],
[
"",
"gemini-1.5-pro-latest",
None,
"./example2.mp4",
None,
.4,
1024,
"",
32,
1,
"What is the ball doing? What did the club do to influence the ball? What did player do to influence the golf club?",
[("", "")]
],
[
"",
"gemini-1.5-pro-latest",
None,
"./example3.mp4",
None,
.4,
1024,
"",
32,
1,
"Transcribe",
[("", "")]
]
],
#cache_examples="lazy",
)
demo.queue(max_size=99).launch(debug=False, show_error=True)
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