Update app.py

app.py

@@ -1,5 +1,5 @@
 import gradio as gr
-from langchain.document_loaders import OnlinePDFLoader
+from langchain.document_loaders import PyPDFLoader
 from langchain.text_splitter import CharacterTextSplitter
 from langchain.llms import HuggingFaceHub
 from langchain.embeddings import HuggingFaceHubEmbeddings
@@ -36,8 +36,9 @@ def get_chain(llm, retriever):
     )
     return qa_chain
 
-def pdf_changes(pdf_doc, repo_id):
-    loader = OnlinePDFLoader(pdf_doc.name)
+def load_pdf_to_langchain(pdf_path, repo_id):
+    # Load the PDF using PyPDFLoader
+    loader = PyPDFLoader(pdf_path)
     documents = loader.load()
     text_splitter = CharacterTextSplitter(chunk_size=2096, chunk_overlap=0)
     texts = text_splitter.split_documents(documents)
@@ -46,11 +47,10 @@ def pdf_changes(pdf_doc, repo_id):
     retriever = db.as_retriever()
     llm = HuggingFaceHub(
         repo_id=repo_id,
-        model_kwargs={'temperature': 0.5, 'max_new_tokens': 2096}
+        model_kwargs={'temperature': 0.3, 'max_new_tokens': 2096}
     )
-    global qa 
-    qa = get_chain(llm, retriever)
-    return "Ready"
+    qa_chain = get_chain(llm, retriever)
+    return qa_chain
 
 def generate_guideline(infrastructure, location, cyclone_predicted_coordinates, cyclone_speed):
     if infrastructure and location and cyclone_predicted_coordinates and cyclone_speed:
@@ -72,9 +72,9 @@ with gr.Blocks(css=css, theme='Taithrah/Minimal') as demo:
     with gr.Column(elem_id='col-container'):
         gr.HTML(title)
 
-        pdf_doc = gr.File(label='Upload a PDF', file_types=['.pdf'])
+        # LLM selection
         repo_id = gr.Dropdown(
-            label='LLM', 
+            label='Select Language Model (LLM)', 
             choices=[
                 'mistralai/Mistral-7B-Instruct-v0.1', 
                 'HuggingFaceH4/zephyr-7b-beta', 
@@ -84,27 +84,46 @@ with gr.Blocks(css=css, theme='Taithrah/Minimal') as demo:
             ],
             value='mistralai/Mistral-7B-Instruct-v0.1'
         )
-        with gr.Row():
-            langchain_status = gr.Textbox(
-                label='Status', placeholder='', interactive=False
-            )
-            load_pdf = gr.Button('Load PDF to LangChain')
+
+        # Status display
+        langchain_status = gr.Textbox(
+            label='Status', placeholder='', interactive=False, value="Loading guideline1.pdf..."
+        )
 
         # Input fields for user information
         infrastructure = gr.Textbox(label='Infrastructure')
-        location = gr.Textbox(label='Location Coordinate (lat,lon)')
+        location = gr.Textbox(label='Location Coordinates (lat,lon)')
         cyclone_predicted_coordinates = gr.Textbox(label='Predicted Cyclone Coordinates (lat,lon)')
         cyclone_speed = gr.Textbox(label='Cyclone Speed in Knots')
 
         submit_btn = gr.Button('Generate Guideline')
         output = gr.Textbox(label='Personalized Guideline', lines=10)
 
+    # Global variable to store the QA chain
+    qa = None
+
+    # Function to initialize the QA chain
+    def initialize_qa(repo_id_value):
+        global qa
+        pdf_path = 'guideline1.pdf'  # Ensure this PDF is in the same directory
+        qa = load_pdf_to_langchain(pdf_path, repo_id_value)
+        return f"Loaded guideline1.pdf with LLM: {repo_id_value}"
+
+    # Initialize QA chain with default LLM
+    initial_status = initialize_qa(repo_id.value)
+    langchain_status.value = initial_status
+
+    # Update QA chain when LLM selection changes
+    def on_repo_id_change(repo_id_value):
+        status = initialize_qa(repo_id_value)
+        return status
+
     repo_id.change(
-        pdf_changes, inputs=[pdf_doc, repo_id], outputs=[langchain_status], queue=False
-    )
-    load_pdf.click(
-        pdf_changes, inputs=[pdf_doc, repo_id], outputs=[langchain_status], queue=False
+        on_repo_id_change,
+        inputs=repo_id,
+        outputs=langchain_status
     )
+
     submit_btn.click(
         generate_guideline, 
         inputs=[infrastructure, location, cyclone_predicted_coordinates, cyclone_speed],