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import streamlit as st
from huggingface_hub import InferenceClient
from gradio_client import Client
import re
# Set the page config
st.set_page_config(layout="wide")
# Load custom CSS
with open('style.css') as f:
st.markdown(f'<style>{f.read()}</style>', unsafe_allow_html=True)
# Initialize the HuggingFace Inference Client
text_client = InferenceClient(model="mistralai/Mistral-7B-Instruct-v0.1")
image_client = Client("phenixrhyder/nsfw-waifu-gradio")
def format_prompt_for_description(caption_text):
prompt = f"Generate a funny and relatable meme caption for Pepe the Frog: {caption_text}"
return prompt
def format_prompt_for_image(caption_text):
prompt = f"Generate an image prompt for a Pepe the Frog meme with the following caption: {caption_text}"
return prompt
def clean_generated_text(text):
# Remove any unwanted trailing tags or characters like </s>
clean_text = re.sub(r'</s>$', '', text).strip()
return clean_text
def generate_text(prompt, temperature=0.9, max_new_tokens=512, top_p=0.95, repetition_penalty=1.0):
temperature = max(temperature, 1e-2)
generate_kwargs = dict(
temperature=temperature,
max_new_tokens=max_new_tokens,
top_p=top_p,
repetition_penalty=repetition_penalty,
do_sample=True,
seed=42,
)
try:
stream = text_client.text_generation(prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
output = ""
for response in stream:
output += response.token.text
return clean_generated_text(output)
except Exception as e:
st.error(f"Error generating text: {e}")
return ""
# Updated part for the new API
def generate_image(prompt):
try:
result = image_client.predict(
param_0=prompt,
api_name="/predict"
)
# Process and display the result
if result:
return [result] # Assuming the API returns a single image path as a result
else:
st.error("Unexpected result format from the Gradio API.")
return None
except Exception as e:
st.error(f"Error generating image: {e}")
st.write("Full error details:", e)
return None
def main():
st.title("Pepe Meme Generator")
# User inputs
col1, col2 = st.columns(2)
with col1:
caption_text = st.text_input("Enter a caption or meme idea for Pepe")
# Advanced settings
with st.expander("Advanced Settings"):
temperature = st.slider("Temperature", 0.0, 1.0, 0.9, step=0.05)
max_new_tokens = st.slider("Max new tokens", 0, 8192, 512, step=64)
top_p = st.slider("Top-p (nucleus sampling)", 0.0, 1.0, 0.95, step=0.05)
repetition_penalty = st.slider("Repetition penalty", 1.0, 2.0, 1.0, step=0.05)
# Initialize session state for generated text and image prompt
if "meme_caption" not in st.session_state:
st.session_state.meme_caption = ""
if "image_prompt" not in st.session_state:
st.session_state.image_prompt = ""
if "image_paths" not in st.session_state:
st.session_state.image_paths = []
# Generate button
if st.button("Generate Pepe Meme"):
with st.spinner("Generating Pepe meme..."):
description_prompt = format_prompt_for_description(caption_text)
image_prompt = format_prompt_for_image(caption_text)
# Generate meme caption
st.session_state.meme_caption = generate_text(description_prompt, temperature, max_new_tokens, top_p, repetition_penalty)
# Generate image prompt
st.session_state.image_prompt = generate_text(image_prompt, temperature, max_new_tokens, top_p, repetition_penalty)
# Generate image from image prompt
st.session_state.image_paths = generate_image(st.session_state.image_prompt)
st.success("Pepe meme generated!")
with col2:
# Display the generated meme caption and image prompt
if st.session_state.meme_caption:
st.subheader("Generated Meme Caption")
st.write(st.session_state.meme_caption)
if st.session_state.image_prompt:
st.subheader("Image Prompt")
st.write(st.session_state.image_prompt)
if st.session_state.image_paths:
st.subheader("Generated Image")
for image_path in st.session_state.image_paths:
st.image(image_path, caption="Generated Pepe Meme Image")
if __name__ == "__main__":
main() |