Can we train the crew with the documents like .pdf, .doc data..?

[shiv-workspace]

I have been trying to train crew using the documents data using crewAI, but encountering EOF error. Please help me through this. Below is the code snippet which I am using to train the crew. Correct me if I am doing anything wrong here.
Context of code: user will upload the document and clicks on train then this function will be triggered. @stephenwithav

def training_upload_view(request, crew_id):
# Get the crew instance
crew = get_object_or_404(Crew, id=crew_id)

if request.method == "POST":
    # Retrieve content and file from POST request
    content = request.POST.get('content')  # Text content (if any)
    document = request.FILES.get('document')  # Single file input

    # Check if a file was uploaded
    if document is None:
        messages.error(request, "No document uploaded. Please try again.")
        return redirect('training', crew_id=crew_id)

    # Validate file type (PDF only for now)
    if not document.name.endswith('.pdf'):
        messages.error(request, "Unsupported file type. Please upload a PDF.")
        return redirect('training', crew_id=crew_id)

    # Get the user who uploaded the document
    user = request.user

    # Save the content and document in the Training model
    training = Training(
        crew=crew,
        document=document,  # Save the uploaded document to the model
        content=content,  # If there's any additional content
        contenttype='File',
        uploaded_by=user
    )
    training.save()  # Save the training instance to the database

    # Extract the content of the PDF using PyPDFLoader
    file_path = training.document.path  # Get the file path of the saved document
    loader = PyPDFLoader(file_path)
    documents = loader.load()
    
    # Combine the text content of all pages in the document
    extracted_content = "\n".join([doc.page_content for doc in documents])

    # Create a document processing agent (if tools are not required, remove tools)
    document_agent = Agent_create(
        role="Document Processor",
        goal="Process and extract insights from the document content",
        verbose=True,
        backstory="You are an expert in processing and extracting information from documents, especially PDF files.",
        tools=[]  # Pass empty if no tool is needed
    )

    # Task for analyzing the document content
    document_task = Task_create(
        description="Analyze the provided document content and store the key insights.",
        expected_output="Extracted key insights from the document content.",
        agent=document_agent
    )

    # Initialize the Crew
    crew = Crew_create(
        agents=[document_agent],
        tasks=[document_task],
        process=Process.sequential,  # Sequential task execution
    )

    # Train the crew for 2 iterations using the extracted document content
    crew.train(n_iterations=1, filename=f'crew_training_data.pkl', inputs={'document_content': extracted_content})

    messages.success(request, "Crew is trained with the uploaded file content.")