Update app.py

app.py

@@ -1,48 +1,60 @@
-import gradio as gr
 import openai
 import random
 import time
-
-# Set up OpenAI API key
-openai.api_key = "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"
-
-system_message = {"role": "system", "content": "You are a helpful assistant."}
+import gradio as gr
+import os
+from langchain.embeddings.openai import OpenAIEmbeddings
+from langchain.vectorstores import DeepLake
+from langchain.chat_models import ChatOpenAI
+from langchain.chains import ConversationalRetrievalChain
+
+def set_api_key(key):
+    os.environ["OPENAI_API_KEY"] = key
+    return f"Key Successfully Set to: {key}"
+    
+def get_api_key():
+    api_key = os.getenv("OPENAI_API_KEY")
+    return api_key
+
+def respond(message, chat_history):
+    
+    # Get embeddings
+    embeddings = OpenAIEmbeddings()
+    
+    #Connect to existing vectorstore
+    db = DeepLake(dataset_path="./documentation_db", embedding_function=embeddings, read_only=True)
+    #Set retriever settings
+    retriever = db.as_retriever(search_kwargs={"distance_metric":'cos',
+                                               "fetch_k":20,
+                                               "maximal_marginal_relevance":True,
+                                               "k":20})
+
+    # Create ChatOpenAI and ConversationalRetrievalChain
+    model = ChatOpenAI(model='gpt-3.5-turbo')
+    qa = ConversationalRetrievalChain.from_llm(model, retriever)
+
+    chat_history=[]
+    bot_message = qa({"question": message, "chat_history": chat_history})
+    chat_history.append((message, bot_message['answer']))
+    time.sleep(1)
+    return "", chat_history
 
 with gr.Blocks() as demo:
-    chatbot = gr.Chatbot()
-    msg = gr.Textbox()
-    clear = gr.Button("Clear")
-
-    state = gr.State([])
-
-    def user(user_message, history):
-        return "", history + [[user_message, None]]
-
-    def bot(history, messages_history):
-        user_message = history[-1][0]
-        bot_message, messages_history = ask_gpt(user_message, messages_history)
-        messages_history += [{"role": "assistant", "content": bot_message}]
-        history[-1][1] = bot_message
-        time.sleep(1)
-        return history, messages_history
-
-    def ask_gpt(message, messages_history):
-        messages_history += [{"role": "user", "content": message}]
-        response = openai.ChatCompletion.create(
-            model="gpt-3.5-turbo",
-            messages=messages_history
-        )
-        return response['choices'][0]['message']['content'], messages_history
-
-    def init_history(messages_history):
-        messages_history = []
-        messages_history += [system_message]
-        return messages_history
-
-    msg.submit(user, [msg, chatbot], [msg, chatbot], queue=False).then(
-        bot, [chatbot, state], [chatbot, state]
-    )
-
-    clear.click(lambda: None, None, chatbot, queue=False).success(init_history, [state], [state])
-
+    with gr.Tab("OpenAI API Key Submission"):
+        api_input = gr.Textbox(label = "API Key", placeholder = "Please provide your OpenAI API key here")
+        api_submission_conf = gr.Textbox(label = "Submission Confirmation")
+        api_submit_button = gr.Button("Submit")
+    
+    with gr.Tab("Coding Assistant"):
+        api_check_button = gr.Button("Get API Key")
+        api_print = gr.Textbox(label = "OpenAI API Key - Please ensure the API Key is set correctly")
+        chatbot = gr.Chatbot(label="ChatGPT Powered Coding Assistant")
+        msg = gr.Textbox(label="User Prompt", placeholder="Your Query Here")
+        clear = gr.Button("Clear")
+        
+    api_submit_button.click(set_api_key, inputs=api_input, outputs=api_submission_conf)
+    api_check_button.click(get_api_key, outputs=api_print)
+    msg.submit(respond, [msg, chatbot], [msg, chatbot])
+    clear.click(lambda: None, None, chatbot, queue=False)
+    
 demo.launch()