Update app.py

app.py

@@ -1,3 +1,42 @@
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+app.py
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+Update app.py
+133e845
+1 day ago
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+2.83 kB
 import gradio as gr
 import os
 import tempfile
@@ -12,21 +51,12 @@ from langchain import HuggingFaceHub
 
 # Set your API keys
 API_KEY = os.environ["API_KEY"] 
-pdf_path = './Adventure Works Analysis Report.pdf'
 
 # Create a temporary upload directory
 
 # Define global variables for loaders and index
 index = None
-def load_file(pdf_path):
-                global index
-                pdf_loader = UnstructuredPDFLoader(pdf_path)
-                index = VectorstoreIndexCreator(
-                embedding=HuggingFaceEmbeddings(),
-                text_splitter=CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
-                ).from_loaders([pdf_loader])
-                return "DONE ✅"
-load_file(pdf_path)
+
 
 def chat(message,history):
     global index
@@ -57,11 +87,27 @@ chat_interface = gr.ChatInterface(
 
 with gr.Blocks(theme=gr.themes.Soft()) as demo:
     with gr.Row():
-        with gr.Column():
-            # text = gr.Textbox(load_file, [pdf_path],label="Status")
+        with gr.Column(scale=1):
+            with gr.Row():
+                upload_file = gr.File(label="Upload a PDF",file_types=["pdf"])
+            with gr.Row():
+                upload_button = gr.Button(label="Upload a PDF")
+            with gr.Row():
+                text = gr.Textbox(label="Status")
+            def load_file(pdf_file):
+                global index
+                pdf_loader = UnstructuredPDFLoader(pdf_file.name)
+                index = VectorstoreIndexCreator(
+                embedding=HuggingFaceEmbeddings(),
+                text_splitter=CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
+                ).from_loaders([pdf_loader])
+                return "DONE ✅"
+            upload_button.click(load_file, [upload_file], text)
+        with gr.Column(scale=2):
             chat_interface = gr.ChatInterface(
                             chat,
                             theme=gr.themes.Soft()
                         )
 
 demo.queue().launch(inline=False)
+