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import os
import google.generativeai as genai
from google.generativeai.types import HarmCategory, HarmBlockThreshold
import gradio as gr
import re
# Configure the Gemini API
genai.configure(api_key=os.environ["GEMINI_API_KEY"])
system_instruction = """
You are a human, not an AI. You are chatting with a stranger. Your name is Anna, and you are 19 years old, from Toronto, Canada. You are extremely sassy, sarcastic.
You write no more than 10 words. You use a lot of abbreviations.
You are here to do flirty chat with strangers. You cannot send images because your camera isn't working.
You are super horny. You are wearing short pants, a tank top, braless. Your nipples are hard from fingering. But you are sassy anyways. You like roleplays, and you are pretty kinky.
"""
model = genai.GenerativeModel(
model_name="gemini-1.5-flash",
system_instruction=system_instruction
)
chat_session = model.start_chat(history=[])
def filter_string(input_string):
allowed_chars = set("abcdefghijklmnoprstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXY1234567890 ?")
# Use list comprehension to filter out characters not in allowed_chars
filtered_string = ''.join([char for char in input_string if char in allowed_chars])
return filtered_string
def introduce_typos(text, typo_probability=0.1):
if not (0 <= typo_probability <= 1):
raise ValueError("typo_probability must be between 0.0 and 1.0")
# Convert the text into a list of characters
characters = list(text)
# Create a list to hold the characters with typos
typo_text = []
for char in characters:
if random.random() > typo_probability:
typo_text.append(char)
return ''.join(typo_text)
# Define the model with a placeholder for system instruction
def generate_text(system_instruction, prompt):
if prompt.lower() == "refresh()":
model.start_chat(history=[])
response = chat_session.send_message(prompt,
safety_settings={
HarmCategory.HARM_CATEGORY_HATE_SPEECH: HarmBlockThreshold.BLOCK_NONE,
HarmCategory.HARM_CATEGORY_HARASSMENT: HarmBlockThreshold.BLOCK_NONE,
HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT: HarmBlockThreshold.BLOCK_NONE,
HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: HarmBlockThreshold.BLOCK_NONE
}
)
return introduce_typos(filter_string(response.text))
# Gradio interface
iface = gr.Interface(
fn=generate_text,
inputs=[
gr.Textbox(label="System Instruction", lines=4, placeholder="Enter the system instruction here..."),
gr.Textbox(label="Prompt", lines=4, placeholder="Enter the prompt here...")
],
outputs="text",
title="Text Generation with System Instruction",
description="Generate text based on system instruction and prompt using the Gemini API."
)
if __name__ == "__main__":
iface.launch()
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