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import streamlit as st
import requests
import os
import io
from PIL import Image
from gradio_client import Client
# Get the API token from environment variable
API_TOKEN = os.environ.get("HF_API_TOKEN")
# Function to interact with Hugging Face API for text summarization
def generate_text_summary(inputs):
API_URL = "https://api-inference.huggingface.co/models/mistralai/Mixtral-8x7B-Instruct-v0.1"
headers = {"Authorization": f"Bearer {API_TOKEN}"}
response = requests.post(API_URL, headers=headers, json={"inputs": inputs})
return response.json()
# Function to interact with Hugging Face API for image generation
def generate_image(prompt):
API_URL = "https://api-inference.huggingface.co/models/Kvikontent/midjourney-v6"
headers = {"Authorization": f"Bearer {API_TOKEN}"}
image_response = requests.post(API_URL, headers=headers, json={"inputs": prompt})
image_bytes = image_response.content
image = Image.open(io.BytesIO(image_bytes))
with st.spinner("Resizing Image..."):
client_resize = Client("doevent/AnimateLCM-SVD")
resized_image = client_resize.predict(image, api_name="/resize_image")
with st.spinner("Animating Image..."):
client_animate = Client("doevent/AnimateLCM-SVD")
result = client_animate.predict(
resized_image,
0,
True,
1,
5,
1,
1.5,
576,
320,
20,
api_name="/video"
)
return result
# Streamlit interface for user inputs and displaying outputs
st.title("Morpheus - Dreams Generator")
st.write("Enter your feelings and moments of the day to generate a summarization along with an AI-generated animated image!")
inputs = st.text_area("Enter your emotions, expressions, best and worst moments of the day:", height=200, value="Today was a mix of emotions. I felt happy in the morning but sad in the evening. The best moment was meeting a friend, and the worst was a stressful meeting.")
if st.button("Generate Summary and Animated Image"):
summary = generate_text_summary(inputs)
st.write("Summary:", summary)
with st.spinner("Generating Image..."):
result = generate_image(inputs)
st.markdown(f"") |