Create app.py

app.py

@@ -0,0 +1,136 @@
+#!/usr/bin/env python3
+import csv
+from langchain.embeddings.openai import OpenAIEmbeddings
+from langchain.vectorstores import FAISS
+from langchain.llms import OpenAI
+from langchain.chat_models import ChatOpenAI
+from langchain.vectorstores import Pinecone
+from langchain.chains import RetrievalQA
+import os
+import gradio as gr
+import time
+from fuzzywuzzy import fuzz
+import pinecone
+from getpass import getpass
+
+os.environ["OPENAI_API_KEY"] = "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"
+YOUR_API_KEY = "7fd42be9-4380-44f0-8f9e-c6f6a9c2f088"
+YOUR_ENV = "northamerica-northeast1-gcp"
+
+index_name = 'knowledgebase'
+pinecone.init(
+	api_key=YOUR_API_KEY,
+	environment=YOUR_ENV
+)
+
+
+faiss_index_folder_path = "/Users/axelwindbrake/Desktop/AI Automation folders/Chatbot Ver 3/Memory/faiss_index"
+
+
+model_name = 'text-embedding-ada-002'
+
+embed = OpenAIEmbeddings(
+	model=model_name,
+	openai_api_key=os.environ["OPENAI_API_KEY"]
+)
+text_field = "text"
+res = embed.embed_documents(text_field)
+
+# switch back to normal index for langchain
+index = pinecone.Index(index_name)
+
+vectorstore = Pinecone(index, embed.embed_query, text_field)
+
+llm = ChatOpenAI(
+	openai_api_key=os.environ["OPENAI_API_KEY"],
+	model_name='gpt-4',
+	temperature=0.5 ,
+	max_tokens=450
+)
+
+qa = RetrievalQA.from_chain_type(
+	llm=llm,
+	chain_type="stuff",
+	retriever=vectorstore.as_retriever()
+)
+
+inputs = gr.inputs.Textbox(lines=7, label="Frage:")
+outputs = gr.outputs.Textbox(label="Antwort")
+
+query = inputs
+
+def answer_question(query): 
+	result = vectorstore.similarity_search(query, k=3)
+	llm = ChatOpenAI(
+		openai_api_key=os.environ["OPENAI_API_KEY"],
+		model_name='gpt-4',
+		temperature=0.5 ,
+		max_tokens=850
+	)
+	qa = RetrievalQA.from_chain_type(
+		llm=llm,
+		chain_type="stuff",
+		retriever=vectorstore.as_retriever()
+	)
+	answer = qa.run(query)
+	return {"answer": answer}  # Return the result as a dictionary with an "answer" key
+
+with gr.Blocks() as demo:
+	chatbot = gr.Chatbot()
+	msg = gr.Textbox()
+	clear = gr.Button("Clear")
+	
+	def respond(message, chat_history):
+		# If the message starts with "??", skip the CSV lookup
+		if not message.startswith("??"):
+			# Check if the question already has an answer in the CSV file
+			with open("q&a.csv", "r", newline='') as f:
+				reader = csv.reader(f)
+				for row in reader:
+					if fuzz.token_set_ratio(row[0], message) > 80:  # Adjust the threshold as needed
+						bot_message = row[1]
+						break
+				else:
+					# If the question doesn't have an answer in the CSV file, proceed with the existing process
+					bot_response = answer_question(message)
+					if isinstance(bot_response, dict) and "answer" in bot_response:
+						bot_message = bot_response["answer"]
+					else:
+						bot_message = "Sorry, I couldn't generate a response."
+		else:
+			# If the message starts with "??", remove the "??" and proceed with the existing process
+			message = message[2:]
+			bot_response = answer_question(message)
+			if isinstance(bot_response, dict) and "answer" in bot_response:
+				bot_message = bot_response["answer"]
+			else:
+				bot_message = "Sorry, I couldn't generate a response."
+				
+		# Save to CSV file
+		with open("q&a.csv", "a", newline='') as f:
+			writer = csv.writer(f)
+			writer.writerow([message, bot_message])
+			
+		chat_history.append((message, bot_message))
+		time.sleep(1)
+		return "", chat_history
+	
+	
+	
+	
+	msg.submit(respond, [msg, chatbot], [msg, chatbot])
+	clear.click(lambda: None, None, chatbot, queue=False)
+
+with gr.Blocks() as demo:
+	instructions = gr.Markdown("## Willkommen zur Vertriebs Knowledgebase\n\n\nBitte stelle deine Frage in der Textbox unten. \n\n\nAntworten werden zunächst in den gespeicherten Chatverläufen gesucht - wenn du das nicht möchtest, beginne deine Frage mit '??'.")
+	chatbot = gr.Chatbot()
+	msg = gr.Textbox()
+	clear = gr.Button("Clear")
+	
+	msg.submit(respond, [msg, chatbot], [msg, chatbot])
+	clear.click(lambda: None, None, chatbot, queue=False)
+	
+	
+if __name__ == "__main__":
+	demo.launch(share=True, inbrowser=True)
+