Update app.py

app.py

@@ -1,5 +1,6 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+import fitz  # PyMuPDF
 
 """
 For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
@@ -7,6 +8,18 @@ For more information on `huggingface_hub` Inference API support, please check th
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
 
+def extract_text_from_pdf(pdf_path):
+    # Open the provided PDF file
+    doc = fitz.open(pdf_path)
+    text = ""
+
+    # Extract text from each page
+    for page in doc:
+        text += page.get_text()
+
+    return text
+
+
 def respond(
     message,
     history: list[tuple[str, str]],
@@ -39,12 +52,23 @@ def respond(
         response += token
         yield response
 
+
+def process_resume_and_respond(pdf_file, message, history, system_message, max_tokens, temperature, top_p):
+    # Extract text from the PDF file
+    resume_text = extract_text_from_pdf(pdf_file.name)
+    # Combine the resume text with the user message
+    combined_message = f"Resume:\n{resume_text}\n\nUser message:\n{message}"
+    # Respond using the combined message
+    return respond(combined_message, history, system_message, max_tokens, temperature, top_p)
+
+
 """
 For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
 """
 demo = gr.ChatInterface(
-    respond,
+    process_resume_and_respond,
     additional_inputs=[
+        gr.File(label="Upload Resume PDF"),
         gr.Textbox(value="You are a Job Advisor Chatbot.", label="System message"),
         gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
         gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
@@ -60,4 +84,4 @@ demo = gr.ChatInterface(
 
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()