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import os
import json
import pandas as pd
from docx import Document
from PyPDF2 import PdfReader
from huggingface_hub import InferenceClient
import gradio as gr
# Retrieve Hugging Face API key from environment variable (secret)
API_KEY = os.getenv("APIHUGGING")
if not API_KEY:
raise ValueError("Hugging Face API key not found. Please set the 'APIHUGGING' secret.")
# Initialize Hugging Face Inference Client
client = InferenceClient(api_key=API_KEY)
# Function to extract text from various file types
def extract_file_content(file_path):
_, file_extension = os.path.splitext(file_path.name)
if file_extension.lower() in [".txt"]:
return file_path.read().decode("utf-8")
elif file_extension.lower() in [".csv"]:
df = pd.read_csv(file_path)
return df.to_string(index=False)
elif file_extension.lower() in [".json"]:
data = json.load(file_path)
return json.dumps(data, indent=4)
elif file_extension.lower() in [".pdf"]:
reader = PdfReader(file_path)
text = ""
for page in reader.pages:
text += page.extract_text()
return text
elif file_extension.lower() in [".docx"]:
doc = Document(file_path)
return "\n".join([para.text for para in doc.paragraphs])
else:
return "Unsupported file type."
# Function to interact with the Hugging Face model
def get_bot_response(file, prompt):
try:
# Extract content from the uploaded file
file_content = extract_file_content(file)
# Prepare conversation history
messages = [
{"role": "user", "content": f"{prompt}\n\nFile Content:\n{file_content}"}
]
# Call Hugging Face API
bot_response = client.chat_completions.create(
model="Qwen/Qwen2.5-Coder-32B-Instruct",
messages=messages,
max_tokens=500
)
# Collect and return the bot's response
return bot_response.choices[0].message.content
except Exception as e:
return f"Error: {str(e)}"
# Gradio Interface
with gr.Blocks() as app:
gr.Markdown("# 📁 AI File Chat with Hugging Face 🚀")
gr.Markdown("Upload any file and ask the AI a question based on the file's content!")
with gr.Row():
file_input = gr.File(label="Upload File")
prompt_input = gr.Textbox(label="Enter your question", placeholder="Ask something about the uploaded file...")
output = gr.Textbox(label="AI Response")
submit_button = gr.Button("Submit")
submit_button.click(get_bot_response, inputs=[file_input, prompt_input], outputs=output)
# Launch the Gradio app
if __name__ == "__main__":
app.launch()
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