Spaces:
Sleeping
Sleeping
File size: 2,886 Bytes
b29b783 b873bf2 e768b29 b873bf2 b29b783 b873bf2 b29b783 b873bf2 e768b29 b873bf2 b29b783 b873bf2 b29b783 b873bf2 b29b783 b873bf2 b29b783 b873bf2 b29b783 b873bf2 b29b783 b873bf2 b29b783 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 |
import os
import logging
import pandas as pd
import streamlit as st
import requests
from transformers import pipeline
# Set up logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
# Load environment variables from .env file
load_dotenv()
# Get the Hugging Face API key from environment variables
hf_api_key = os.getenv("HUGGINGFACE_API_KEY")
if not hf_api_key:
raise ValueError("HUGGINGFACE_API_KEY is not set. Please provide a valid API key.")
# Hugging Face API URL
hf_api_url = "https://api-inference.huggingface.co/models/{model_name}"
# Function to load and preprocess data
@st.cache_data
def load_data(file):
try:
df = pd.read_csv(file)
return df
except Exception as e:
logger.error(f"Error loading CSV file: {e}")
st.error("There was an issue loading the file. Please try again.")
return pd.DataFrame() # Return an empty DataFrame in case of error
# Function to call Hugging Face API for text generation
def generate_text_from_model(model_name, text_input):
headers = {"Authorization": f"Bearer {hf_api_key}"}
data = {"inputs": text_input}
try:
response = requests.post(hf_api_url.format(model_name=model_name), headers=headers, json=data)
response.raise_for_status()
result = response.json()
if 'generated_text' in result:
return result['generated_text']
else:
return "No result from model. Please try again."
except requests.exceptions.RequestException as err:
logger.error(f"Error interacting with Hugging Face API: {err}")
st.error(f"Error interacting with Hugging Face API: {err}")
return ""
# Streamlit app layout
def main():
# Set a background color and style
st.markdown(
"""
<style>
.stApp {
background-color: #F4F4F9;
}
.stButton>button {
background-color: #6200EE;
color: white;
font-size: 18px;
}
.stSlider>div>div>span {
color: #6200EE;
}
.stTextInput>div>div>input {
background-color: #E0E0E0;
}
</style>
""",
unsafe_allow_html=True
)
# Title and header
st.title("🌟 **Hugging Face Text Generation** 🌟")
st.markdown("### **Generate text using Hugging Face Models**")
# User input for text generation
model_name = st.selectbox("🔹 Select Hugging Face Model", ["gpt2", "distilgpt2", "t5-small"])
text_input = st.text_area("🔹 Input Text", "Once upon a time...")
# Generate text based on input
if st.button("🔍 Generate Text"):
st.subheader("🔔 **Generated Text** 🔔")
generated_text = generate_text_from_model(model_name, text_input)
st.write(f"📜 {generated_text}")
if __name__ == "__main__":
main()
|