Add application file

app.py

@@ -1,7 +1,25 @@
 import gradio as gr
+from indexes import clear_indexes
+from conversation import create_conversation
 
-def greet(name):
-    return "Hello " + name + "!!"
+# Hardcoded values
+HARDCODED_PINECONE_API_KEY = '228cca47-e537-42af-bcef-569cb18fb7cf'
+HARDCODED_PINECONE_ENVIRONMENT = 'us-west1-gcp-free'
+HARDCODED_PINECONE_INDEX_NAME = 'chatbot'
+HARDCODED_OPENAI_API_KEY = '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'
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+def update_chat_history(query, chatbot_state):
+    current_chat_history = chatbot_state if chatbot_state else []
+    _, updated_chat_history = create_conversation(query, current_chat_history)
+    return "", updated_chat_history  # Return an empty string to clear the textbox
+
+with gr.Blocks() as demo:
+    chatbot = gr.Chatbot(label='Talk to the Document')
+    msg = gr.Textbox()
+    clear = gr.ClearButton([msg, chatbot])
+
+    # Link the Gradio interface with the update_chat_history function
+    msg.submit(update_chat_history, inputs=[msg, chatbot], outputs=[msg, chatbot])
+
+if __name__ == '__main__':
+    demo.launch()

conversation.py

@@ -0,0 +1,67 @@
+from langchain.chains import ConversationalRetrievalChain
+from langchain.chat_models import ChatOpenAI
+from langchain.vectorstores import Pinecone
+from langchain.embeddings.openai import OpenAIEmbeddings
+from langchain.memory import ConversationBufferMemory
+import pinecone
+import os
+import logging
+
+# Load environment variables
+from dotenv import load_dotenv
+load_dotenv()
+
+# Retrieve values from .env file
+pinecone_api_key = '228cca47-e537-42af-bcef-569cb18fb7cf'
+pinecone_environment = 'us-west1-gcp-free'
+pinecone_index_name = 'chatbot'
+openai_api_key = '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'
+
+# Set up logging
+logging.basicConfig(level=logging.DEBUG)
+logger = logging.getLogger(__name__)
+
+def create_conversation(query: str, chat_history: list) -> tuple:
+    logger.debug("Starting create_conversation function")
+
+    try:
+        logger.debug("Initializing Pinecone")
+        pinecone.init(api_key=pinecone_api_key, environment=pinecone_environment)
+        logger.debug("Pinecone initialized")
+
+        logger.debug("Creating embeddings")
+        embeddings = OpenAIEmbeddings(openai_api_key=openai_api_key)
+        logger.debug("Embeddings created")
+
+        logger.debug("Accessing existing Pinecone index")
+        db = Pinecone.from_existing_index(index_name=pinecone_index_name, embedding=embeddings)
+        logger.debug("Index accessed")
+
+        logger.debug("Setting up memory for conversation")
+        memory = ConversationBufferMemory(memory_key='chat_history', return_messages=False)
+        logger.debug("Memory set up")
+
+        logger.debug("Creating ConversationalRetrievalChain")
+        cqa = ConversationalRetrievalChain.from_llm(
+            llm=ChatOpenAI(temperature=0.0, openai_api_key=openai_api_key),
+            retriever=db.as_retriever(),
+            memory=memory,
+            get_chat_history=lambda h: h,
+        )
+        logger.debug("ConversationalRetrievalChain created")
+
+        logger.debug(f"Processing query: {query}")
+        result = cqa({'question': query, 'chat_history': chat_history})
+        logger.debug(f"Received result: {result}")
+
+        logger.debug("Appending result to chat history")
+        chat_history.append((query, result['answer']))
+        logger.debug(f"Updated chat history: {chat_history}")
+
+        return '', chat_history
+
+    except Exception as e:
+        logger.exception("Exception occurred in create_conversation")
+        chat_history.append((query, "Error: " + str(e)))
+        return '', chat_history
+

indexes.py

@@ -0,0 +1,33 @@
+import os
+from PyPDF2 import PdfReader
+import pinecone
+from langchain.embeddings.openai import OpenAIEmbeddings
+from langchain.vectorstores import Pinecone
+
+from pinecone import init, create_index, Index
+#from langchain.vectorstores import OpenAIEmbeddings
+#from langchain.processing import PDFProcessor
+#from langchain import configuration
+
+debug_mode = os.getenv('DEBUG', 'False') == 'True'
+verbose_mode = os.getenv('VERBOSE', 'False') == 'True'
+
+def clear_indexes(pinecone_api_key: str, pinecone_environment: str, pinecone_index_name: str) -> str:
+    try:
+        print("Initializing Pinecone for clearing indexes...")
+        pinecone.init(api_key=pinecone_api_key, environment=pinecone_environment)
+
+        print("Checking existing Pinecone indexes for clearing...")
+        indexes_list = pinecone.list_indexes()
+        if pinecone_index_name in indexes_list:
+            print(f"Deleting Pinecone index: {pinecone_index_name}")
+            pinecone.delete_index(name=pinecone_index_name)
+            print("Index cleared.")
+        else:
+            print(f"No index named {pinecone_index_name} found to clear.")
+
+        return 'Indexes cleared.'
+
+    except Exception as e:
+        print(f"Error occurred in clear_indexes: {str(e)}")
+        return f"Error occurred: {str(e)}"