create app.py

app.py

@@ -0,0 +1,66 @@
+import gradio as gr
+import os
+import openai
+import gradio as gr
+# Get the value of the openai_api_key from environment variable
+openai.api_key = os.getenv("OPENAI_API_KEY")
+
+# Import things that are needed generically from langchain
+from langchain import LLMMathChain, SerpAPIWrapper
+from langchain.agents import AgentType, initialize_agent, load_tools
+from langchain.chat_models import ChatOpenAI
+from langchain.tools import BaseTool, StructuredTool, Tool, tool
+from langchain.tools import MoveFileTool, format_tool_to_openai_function
+from langchain.schema import (
+    AIMessage,
+    HumanMessage,
+    SystemMessage
+)
+from langchain.utilities import WikipediaAPIWrapper
+from langchain.tools import AIPluginTool
+
+
+# Setting up a system message for our Chatbot
+#system = SystemMessage(content = "You are a helpful AI assistant") # that translates English to Pirate English.")
+
+# driver
+def predict(user_input, chatbot):
+
+    print(f"chatbot - {chatbot}")
+    print(f"user_input - {user_input}")
+
+    chat = ChatOpenAI(
+    #openai_api_key=openai_api_key,
+    temperature=1.0, #temperature, #1.0
+    streaming=True,
+    model='gpt-3.5-turbo-0613')
+    #messages = [system]
+    messages=[]
+    #function_call_decision = True if any(plugins) else False
+
+    if len(chatbot) != 0:
+        for conv in chatbot:
+            human = HumanMessage(content=conv[0])
+            ai = AIMessage(content=conv[1])
+            messages.append(human)
+            messages.append(ai)
+        messages.append(HumanMessage(content=user_input))
+        print(f"messages list is - {messages}")
+
+    else: # for first user message
+        messages.append(HumanMessage(content=user_input))
+        print(f"messages list is - {messages}")
+
+    # getting gpt3.5's response
+    gpt_response = chat(messages)
+    print(f"gpt_response - {gpt_response}")
+    bot_message = gpt_response.content
+    print(f"bot_message - {bot_message}")
+
+    chatbot.append((user_input, bot_message))
+
+    #return "", chatbot, None #"", chatbot
+    return bot_message
+
+#chatbot = gr.Chatbot()
+gr.ChatInterface(predict, delete_last_btn="del").launch(share=False, debug=True) #examples=["How are you?", "What's up?"],