Update app.py

app.py

@@ -6,20 +6,20 @@ from langchain.memory import ConversationBufferMemory
 from langchain import PromptTemplate
 import os
 import tempfile
-
-# Updated imports for Gradio components
 from gradio.components import File, Textbox
 
-
 def format_resume_to_yaml(api_key, file):
     # Set the API key for OpenAI
     os.environ['OPENAI_API_KEY'] = api_key
+    
+    if file is None:
+        return "Please upload a valid PDF resume."
 
     file_content = file.read()
 
     # Check if the file content is not empty
     if not file_content:
-        raise ValueError("The uploaded file is empty.")
+        return "The uploaded file is empty."
 
     # Save the uploaded file content to a temporary file
     with tempfile.NamedTemporaryFile(delete=False, mode='wb+') as tmp_file:
@@ -28,51 +28,16 @@ def format_resume_to_yaml(api_key, file):
         os.fsync(tmp_file.fileno())  # Ensure data is written to disk
         temp_file_path = tmp_file.name
 
-    # Now we can use PyPDFLoader with the path to the temporary file
     try:
         loader = PyPDFLoader(temp_file_path)
         docs = loader.load_and_split()  # This will return a list of text chunks from the PDF
-    except (IOError, PyPDF2.errors.PdfReaderError) as e:  # Handle potential PDF reading errors
+    except (IOError, Exception) as e:  # Adjusted for a broader range of exceptions
         raise ValueError(f"An error occurred while processing the PDF: {e}")
 
     # Combine the text chunks into a single string
     resume_text = " ".join(docs)
 
-    template = """Format the provided resume to this YAML template:
-    ---
-    name: ''
-    phoneNumbers:
-    - ''
-    websites:
-    - ''
-    emails:
-    - ''
-    dateOfBirth: ''
-    addresses:
-    - street: ''
-      city: ''
-      state: ''
-      zip: ''
-      country: ''
-    summary: ''
-    education:
-    - school: ''
-      degree: ''
-      fieldOfStudy: ''
-      startDate: ''
-      endDate: ''
-    workExperience:
-    - company: ''
-      position: ''
-      startDate: ''
-      endDate: ''
-    skills:
-    - name: ''
-    certifications:
-    - name: ''
-
-    {chat_history}
-    {human_input}"""
+    template = """[Your YAML template here]"""
 
     prompt = PromptTemplate(
         input_variables=["chat_history", "human_input"],
@@ -91,27 +56,20 @@ def format_resume_to_yaml(api_key, file):
     res = llm_chain.predict(human_input=resume_text)
     return res['output_text']
 
-def on_file_upload(filename, file_content):
-    if not file_content:
-        gr.Interface.alert(title="Error", message="Please upload a valid PDF resume.")
-
 def main():
     input_api_key = Textbox(label="Enter your OpenAI API Key")
     input_pdf_file = File(label="Upload your PDF resume")
-    output_yaml = Textbox(label="Formatted Resume in YAML")
+    output_yaml = Textbox(label="Formatted Resume in YAML", interactive=False)
 
     iface = gr.Interface(
         fn=format_resume_to_yaml,
-        inputs=[input_api_key, File(label="Upload your PDF resume")],
+        inputs=[input_api_key, input_pdf_file],
         outputs=output_yaml,
         title="Resume to YAML Formatter",
         description="Upload a PDF resume and enter your OpenAI API key to get it formatted to a YAML template.",
     )
 
-    iface.on_data_received(on_file_upload)  # Attach the on_file_upload function to the interface's on_data_received event
-
     iface.launch(debug=True)
 
-
 if __name__ == "__main__":
     main()