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import gradio as gr
from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM
import PyPDF2
# Load Models
model1_name = "t5-small" # Model 1
model2_name = "codeparrot/codeparrot-small" # Model 2
model3_name = "Salesforce/blip-image-captioning" # Model 3
# Load Pipelines
model1 = pipeline("text2text-generation", model=model1_name, tokenizer=model1_name)
model2 = pipeline("text-generation", model=model2_name, tokenizer=model2_name)
model3 = pipeline("image-to-text", model=model3_name) # We'll adapt this for PDF processing
# Helper: Extract text from PDF
def extract_text_from_pdf(pdf_file):
pdf_reader = PyPDF2.PdfReader(pdf_file)
text = ""
for page in pdf_reader.pages:
text += page.extract_text()
return text
# Function for Model 1
def model1_func(input_text):
try:
result = model1(input_text, max_length=50, num_return_sequences=1)
answer = result[0]["generated_text"]
return f"Model 1 Output: {answer}"
except Exception as e:
return f"Error: {str(e)}"
# Function for Model 2
def model2_func(input_text):
try:
result = model2(input_text, max_length=50, num_return_sequences=1)
answer = result[0]["generated_text"]
return f"Model 2 Output: {answer}"
except Exception as e:
return f"Error: {str(e)}"
# Function for Model 3
def model3_func(pdf_file):
try:
extracted_text = extract_text_from_pdf(pdf_file)
if not extracted_text.strip():
return "No text found in the PDF. Please upload a valid file."
result = model3(extracted_text)
answer = result[0]["generated_text"]
return f"Model 3 Output: {answer}"
except Exception as e:
return f"Error: {str(e)}"
# Gradio Interface
with gr.Blocks() as demo:
gr.Markdown("<h1>Multi-Model NLP Tool</h1>")
with gr.Tab("Model 1"):
gr.Markdown("**Model 1: Text-to-Text (e.g., Summarization)**")
model1_input = gr.Textbox(label="Enter Text", placeholder="Type here...")
model1_output = gr.Textbox(label="Output")
model1_button = gr.Button("Generate")
model1_button.click(model1_func, inputs=model1_input, outputs=model1_output)
with gr.Tab("Model 2"):
gr.Markdown("**Model 2: Text Generation (e.g., Code Generation)**")
model2_input = gr.Textbox(label="Enter Text", placeholder="Type here...")
model2_output = gr.Textbox(label="Output")
model2_button = gr.Button("Generate")
model2_button.click(model2_func, inputs=model2_input, outputs=model2_output)
with gr.Tab("Model 3"):
gr.Markdown("**Model 3: Document Reader (PDF Input)**")
pdf_input = gr.File(label="Upload PDF")
model3_output = gr.Textbox(label="Output")
model3_button = gr.Button("Process PDF")
model3_button.click(model3_func, inputs=pdf_input, outputs=model3_output)
# Launch the app
demo.launch()
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