small updates/fixes

bigquery/.env.example

@@ -1,7 +1,7 @@
 OPENAI_API_KEY=
 
 # Optional
-# CHAINLIT_API_KEY=
+# LITERAL_API_KEY=
 
 # Optional
 # OAUTH_GOOGLE_CLIENT_ID=

langchain-ask-human/app.py

@@ -1,6 +1,6 @@
 from langchain.chains import LLMMathChain
 from langchain.agents import initialize_agent, Tool, AgentType, AgentExecutor
-from langchain.llms.openai import OpenAI
+from langchain_community.chat_models import ChatOpenAI
 from typing import *
 from langchain.tools import BaseTool
 
@@ -40,7 +40,7 @@ async def _arun(
 
 @cl.on_chat_start
 def start():
- llm = OpenAI(temperature=0, streaming=True)
+ llm = ChatOpenAI(temperature=0, streaming=True, model_name="gpt-4-turbo-preview")
  llm_math_chain = LLMMathChain.from_llm(llm=llm, verbose=True)
 
  tools = [

openai-functions/app.py

@@ -97,7 +97,7 @@ async def call_gpt4(message_history):
  provider="openai-chat",
  messages=[
  cl.GenerationMessage(
- formatted=m["content"], name=m.get("name"), role=m["role"]
+ content=m["content"], name=m.get("name", "function"), role=m["role"]
  )
  for m in message_history
  ],
@@ -131,7 +131,7 @@ async def call_gpt4(message_history):
 @cl.on_message
 async def run_conversation(message: cl.Message):
  message_history = cl.user_session.get("message_history")
- message_history.append({"role": "user", "content": message.content})
+ message_history.append({"name": "user", "role": "user", "content": message.content})
 
  cur_iter = 0
 

resume-chat/.env.example

@@ -1,3 +1,3 @@
-CHAINLIT_API_KEY=
+LITERAL_API_KEY=
 CHAINLIT_AUTH_SECRET=
 OPENAI_API_KEY=

resume-chat/app.py

@@ -1,6 +1,6 @@
 from operator import itemgetter
 
-from langchain.chat_models import ChatOpenAI
+from langchain_community.chat_models import ChatOpenAI
 from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder
 from langchain.schema.output_parser import StrOutputParser
 from langchain.schema.runnable import Runnable, RunnablePassthrough, RunnableLambda
@@ -49,7 +49,7 @@ async def on_chat_resume(thread: ThreadDict):
  memory = ConversationBufferMemory(return_messages=True)
  root_messages = [m for m in thread["steps"] if m["parentId"] == None]
  for message in root_messages:
- if message["type"] == "USER_MESSAGE":
+ if message["type"] == "user_message":
  memory.chat_memory.add_user_message(message["output"])
  else:
  memory.chat_memory.add_ai_message(message["output"])