fix

app.py

@@ -1,36 +1,86 @@
 import gradio as gr
+import time
 from utils import Bot
+from utils import make_documens, make_descriptions
 
-def chatbot_interface():
-    openai_api_key = gr.inputs.Textbox(label="OpenAI API Key")
-    table_descriptions = gr.inputs.Textbox(label="Table Descriptions")
-    text_documents = gr.inputs.Textbox(label="Text Documents")
-    init_inputs = [openai_api_key, table_descriptions, text_documents]
-
-    def init_bot(openai_api_key, table_descriptions, text_documents):
-        bot = Bot(openai_api_key=openai_api_key, table_descriptions=table_descriptions, text_documents=text_documents)
-        return bot
-
-    chatbot = gr.inputs.Textbox(label="Ask a question")
-    submit_init_button = gr.Interface(
-        fn=init_bot,
-        inputs=init_inputs,
-        outputs=None,
-        title="Chat with your Bot",
-        description="Enter initialization parameters and click submit to start chatting with your bot."
-    )
-    submit_chat_button = gr.Interface(
-        fn=lambda bot, question: bot(question),
-        inputs=[gr.inputs.Textbox(), chatbot],
-        outputs=gr.outputs.Textbox(label="Bot Response"),
-        title="Chat with your Bot",
-        description="Type a question and click submit to get a response from your bot."
+def init_bot(table=None,tittle=None,pdf=None,key=None):
+    
+    if key is None:
+        return 'You must submit OpenAI key'
+    
+    if pdf is None:
+        return 'You must submit pdf file'
+    
+    if table is None:
+        return 'You must submit table file'
+    
+    if tittle is None:
+        return 'You must submit tittle of table'
+    
+    table = table.name
+    pdf = pdf.name
+    table_descriptions = make_descriptions(tittle=tittle,table=table)
+    documents = make_documens(pdf)
+    
+    print(documents[0])
+    global bot
+    
+    bot = Bot(
+        openai_api_key=key,
+        table_descriptions=table_descriptions,
+        text_documents=documents,
+        verbose=False
     )
+    
+    return 'Chat bot successfully initialized'
+
+def msg_bot(history):
+    message = history[-1][0]
+    
+    bot_message = bot(message)['output']
+    history[-1][1] = ""
+    for character in bot_message:
+        history[-1][1] += character
+        time.sleep(0.05)
+        yield history
+
+def user(user_message, history):
+    return "", history + [[user_message, None]]
+
+with gr.Blocks() as demo:
+    
+    with gr.Tab("Chat bot initialization"):
+        
+        key = gr.Textbox(label='OpenAI key')
+    
+        with gr.Row(variant='panel'):
+            with gr.Column():
+                with gr.Row():
+                    title = gr.Textbox(label='Table tittle')
+                with gr.Row():
+                    table = gr.File(label='csv table')
+
+            pdf = gr.File(label='pdf')
+        with gr.Row(variant='panel'):
+
+            init_button = gr.Button('submit')
+            init_output = gr.Textbox(label="Initialization status")
+            init_button.click(fn=init_bot,inputs=[table,title,pdf,key],outputs=init_output,api_name='init')
+    
+    
+    
+    with gr.Tab("Chat bot"):
+    
+        chatbot = gr.Chatbot()
+        msg = gr.Textbox(label='Ask the bot')
+        clear = gr.Button('Clear')
+        msg.submit(user,[msg,chatbot],[msg,chatbot],queue=False).then(
+            msg_bot, chatbot, chatbot
+        )
+        clear.click(lambda: None, None, chatbot, queue=False)
 
-    return submit_init_button, submit_chat_button
+demo.queue()
+demo.launch()
 
-submit_init_button, submit_chat_button = chatbot_interface()
 
-submit_init_button.launch()
-submit_chat_button.launch()
 

utils/__init__.py

@@ -1 +1,3 @@
 from .bot import Bot
+from .functions import make_documens, make_descriptions
+

utils/functions.py

@@ -0,0 +1,38 @@
+
+import pandas as pd
+from langchain.document_loaders import PyPDFLoader
+from langchain.text_splitter import CharacterTextSplitter
+
+
+def make_descriptions(table, tittle):
+
+    df = pd.read_csv(table)
+    columns = list(df.columns)
+
+    table_description0 = {
+        'path': 'random',
+        'number': 1,
+        'columns': ["clothes", "animals", "students"],
+        'tittle': "fashionable student clothes"
+    }
+
+    table_description1 = {
+        'path': table,
+        'number': 2,
+        'columns': columns,
+        'tittle': tittle
+    }
+
+    table_descriptions = [table_description0, table_description1]
+    return table_descriptions
+
+
+def make_documens(pdf):
+    loader = PyPDFLoader(pdf)
+    documents = loader.load()
+
+    text_splitter = CharacterTextSplitter(chunk_size=500, chunk_overlap=0, separator='\n')
+    documents = text_splitter.split_documents(documents)
+    return documents
+
+