Update app.py

app.py

@@ -14,6 +14,8 @@ from langchain.schema import LLMResult
 from langchain.llms.base import LLM
 import torch
 import os
+import random
+import PyPDF2
 
 # --------------------------
 # Load Quantized LLaMA 2 via AutoGPTQ
@@ -61,8 +63,6 @@ def generate_text(prompt):
 class CustomLlamaLLM(LLM):
     def _call(self, prompt: str, stop=None) -> str:
         output = generate_text(prompt)
-        # Return only the generated part after prompt
-        # Assume output contains prompt + generated text
         generated = output.split("[/INST]")[-1].strip()
         return generated
 
@@ -125,6 +125,40 @@ def upload_and_index_pdf(pdf_file):
     vector_db.persist()
     return f"Uploaded and indexed: {os.path.basename(pdf_file.name)}"
 
+# --------------------------
+# Generate Sample Questions from PDF
+# --------------------------
+def generate_test_questions_from_pdf(pdf_file):
+    if pdf_file is None:
+        return "No file uploaded."
+
+    # Read text from PDF
+    pdf_reader = PyPDF2.PdfReader(pdf_file.name)
+    text = ""
+    for page in pdf_reader.pages:
+        text += page.extract_text() + " "
+
+    # Split text into sentences
+    sentences = [s.strip() for s in text.split(".") if s.strip()]
+    if not sentences:
+        return "No extractable text found in PDF."
+
+    # Generate sample questions (randomly)
+    questions = []
+    templates = [
+        "Explain the following: {}?",
+        "What is the main point of: {}?",
+        "Summarize: {}",
+        "Why is {} important?"
+    ]
+
+    for _ in range(min(10, len(sentences))):
+        sentence = random.choice(sentences)
+        template = random.choice(templates)
+        questions.append(template.format(sentence[:100]))  # limit to 100 chars
+
+    return "\n".join(questions)
+
 # --------------------------
 # Gradio UI
 # --------------------------
@@ -160,11 +194,8 @@ with gr.Blocks(title="GenAI Customer Support") as demo:
         generated_questions = gr.Textbox(label="Generated Sample Questions", lines=10)
         gen_qs_button = gr.Button("Generate Questions")
         gen_qs_button.click(fn=generate_test_questions_from_pdf, inputs=pdf_file_for_qs, outputs=generated_questions)
-    
 
 # --------------------------
 # Launch
 # --------------------------
 demo.launch(server_name="0.0.0.0", server_port=7860, share=True)
-
-