Update app.py

app.py

@@ -1,71 +1,27 @@
-#last updated 3/18
-from langchain.docstore.document import Document
-from langchain.vectorstores import FAISS
-from langchain.embeddings.openai import OpenAIEmbeddings
-from langchain.memory.simple import SimpleMemory
-
-from langchain.chains import ConversationChain, LLMChain, SequentialChain
-from langchain.memory import ConversationBufferMemory
-
-from langchain.prompts import ChatPromptTemplate, PromptTemplate
-from langchain.document_loaders import UnstructuredFileLoader
+#0.0.1
+import openai
 
+#Langchain Imports
+from langchain.prompts import ChatPromptTemplate
 from langchain.chat_models import ChatOpenAI
-from langchain.llms import OpenAI
-from langchain.memory import ConversationSummaryMemory
-
-from langchain.callbacks import PromptLayerCallbackHandler
-from langchain.prompts.chat import (
-    ChatPromptTemplate,
-    SystemMessagePromptTemplate,
-    AIMessagePromptTemplate,
-    HumanMessagePromptTemplate,
-)
-
-from langchain.schema import AIMessage, HumanMessage, SystemMessage
-from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
-from langchain.callbacks.base import BaseCallbackHandler
-import gradio as gr
+from langchain.schema import StrOutputParser
 
-from threading import Thread
-from queue import Queue, Empty
-from threading import Thread
-from collections.abc import Generator
-from langchain.llms import OpenAI
-from langchain.callbacks.base import BaseCallbackHandler
-
-import itertools
-import time
-import os
-import getpass
+#Type Hinting
+from typing import Any, Callable, Dict, List, Literal, Optional, Tuple, Type, Union
+
+#Utils
+from operator import itemgetter
 import json
+from dataclasses import dataclass
 import sys
-from typing import Any, Dict, List, Union
+import logging
+from google.colab import userdata
 
-import promptlayer
-import openai
+from queue import Queue, Empty
+from threading import Thread
 import gradio as gr
 
-from pydantic import BaseModel, Field, validator
-
-#Load the FAISS Model ( vector )
-openai.api_key = os.environ["OPENAI_API_KEY"]
-db = FAISS.load_local("db", OpenAIEmbeddings())
-
-#API Keys 
-promptlayer.api_key = os.environ["PROMPTLAYER"]
-
-MODEL = "gpt-3.5-turbo"
-# MODEL = "gpt-4"
-
-from langchain.callbacks import PromptLayerCallbackHandler
-from langchain.prompts.chat import (
-    ChatPromptTemplate,
-    SystemMessagePromptTemplate,
-    AIMessagePromptTemplate,
-    HumanMessagePromptTemplate,
-)
-from langchain.memory import ConversationSummaryMemory
+MODEL = "gpt-3.5-turbo-16k"
 
 # Defined a QueueCallback, which takes as a Queue object during initialization. Each new token is pushed to the queue.
 class QueueCallback(BaseCallbackHandler):
@@ -80,8 +36,6 @@ class QueueCallback(BaseCallbackHandler):
     def on_llm_end(self, *args, **kwargs: Any) -> None:
         return self.q.empty()
 
-MODEL = "gpt-3.5-turbo-16k"
-
 # Defined a QueueCallback, which takes as a Queue object during initialization. Each new token is pushed to the queue.
 class QueueCallback(BaseCallbackHandler):
     """Callback handler for streaming LLM responses to a queue."""
@@ -97,9 +51,10 @@ class QueueCallback(BaseCallbackHandler):
 
 class Agent:
 
-  def __init__(self, prompt_template='', model_name=MODEL, verbose=False, temp=0.2):
+  def __init__(self, prompt_template='', model_name=MODEL, verbose=True, temp=0.2):
     self.verbose = verbose
     self.llm = ChatOpenAI(
+      openai_api_key=api_key,
       model_name=MODEL,
       temperature=temp
       )
@@ -122,8 +77,7 @@ class Agent:
 
     llm = ChatOpenAI(
         model_name=MODEL,
-        callbacks=[QueueCallback(q),
-                  PromptLayerCallbackHandler(pl_tags=["unit-generator"])],
+        callbacks=[QueueCallback(q)],
         streaming=True,
         )
 
@@ -160,9 +114,7 @@ unit_generator_prompt = """
             $$$
             {input}
             $$$
-
             Do the following:
-
             Enduring Ideas: Make a list of 5 big and enduring ideas that students should walk away with.
             Essential Questions: Make a list of 5 essential questions we want students to think about. These questions should be open-ended and provocative. Written in "kid friendly" language. Designed to focus instruction for uncovering the important ideas of the content.
             Key Concepts: Make a list of 5 ideas, concepts, generalizations and principles we want students to know and understand about the unit or topic we are teaching?
@@ -225,9 +177,7 @@ with app:
   gr.Markdown(
     """
     # Syllabo
-
     A suite of generative ai tools for designing and building learning experiences.
-
     """)
 
   with gr.Tab("Unit Builder"):