add support for anthropic and anysclae

docker-compose.yml

@@ -1,8 +1,8 @@
 version: '3.8'
 
 services:
- streamlit-chat:
- image: streamlit-chat:latest
+ langchain-streamlit-demo:
+ image: langchain-streamlit-demo:latest
  build: .
  ports:
  - "${APP_PORT:-7860}:${APP_PORT:-7860}"

langchain-streamlit-demo/app.py

@@ -4,58 +4,76 @@ from langchain.callbacks.manager import tracing_v2_enabled
 from langchain.callbacks.tracers.langchain import wait_for_all_tracers
 from langchain.callbacks.tracers.run_collector import RunCollectorCallbackHandler
 from langchain.schema.runnable import RunnableConfig
-from openai.error import AuthenticationError
+import openai
+import anthropic
+from langsmith.client import Client
 
 from llm_stuff import (
  _DEFAULT_SYSTEM_PROMPT,
- get_memory,
  get_llm_chain,
  StreamHandler,
  feedback_component,
- get_langsmith_client,
 )
 
 st.set_page_config(
- page_title="Chat LangSmith",
+ page_title="langchain-streamlit-demo",
  page_icon="🦜",
 )
 
-# "# Chat🦜🛠️"
 # Initialize State
 if "trace_link" not in st.session_state:
  st.session_state.trace_link = None
 if "run_id" not in st.session_state:
  st.session_state.run_id = None
-st.sidebar.markdown(
- """
-# Menu
-""",
-)
 
-openai_api_key = st.sidebar.text_input("OpenAI API Key", type="password")
-st.session_state.openai_api_key = openai_api_key
+st.sidebar.markdown("# Menu")
+models = [
+ "gpt-3.5-turbo",
+ "gpt-4",
+ "claude-instant-v1",
+ "claude-2",
+ "meta-llama/Llama-2-7b-chat-hf",
+ "meta-llama/Llama-2-13b-chat-hf",
+ "meta-llama/Llama-2-70b-chat-hf",
+]
+model = st.sidebar.selectbox(label="Chat Model", options=models, index=0)
+
+if model.startswith("gpt"):
+ provider = "OpenAI"
+elif model.startswith("claude"):
+ provider = "Anthropic"
+elif model.startswith("meta-llama"):
+ provider = "Anyscale"
+else:
+ st.stop()
+
+if not model:
+ st.error("Please select a model and provide an API key.", icon="❌")
+ st.stop()
+
+provider_api_key = st.sidebar.text_input(f"{provider} API key", type="password")
 
 langsmith_api_key = st.sidebar.text_input(
  "LangSmith API Key (optional)",
  type="password",
 )
-st.session_state.langsmith_api_key = langsmith_api_key
-if st.session_state.langsmith_api_key.startswith("ls__"):
+
+if langsmith_api_key.startswith("ls__"):
  langsmith_project = st.sidebar.text_input(
  "LangSmith Project Name",
  value="langchain-streamlit-demo",
  )
  os.environ["LANGCHAIN_ENDPOINT"] = "https://api.smith.langchain.com"
- os.environ["LANGCHAIN_API_KEY"] = st.session_state.langsmith_api_key
+ os.environ["LANGCHAIN_API_KEY"] = langsmith_api_key
  os.environ["LANGCHAIN_TRACING_V2"] = "true"
  os.environ["LANGCHAIN_PROJECT"] = langsmith_project
 
- client = get_langsmith_client()
+ client = Client(api_key=langsmith_api_key)
 else:
  langsmith_project = None
  client = None
 
-if st.session_state.openai_api_key.startswith("sk-"):
+if provider_api_key:
  system_prompt = (
  st.sidebar.text_area(
  "Custom Instructions",
@@ -75,15 +93,13 @@ if st.session_state.openai_api_key.startswith("sk-"):
  help="Higher values give more random results.",
  )
 
- memory = get_memory()
-
- chain = get_llm_chain(memory, system_prompt, temperature)
+ chain = get_llm_chain(model, provider_api_key, system_prompt, temperature)
 
  run_collector = RunCollectorCallbackHandler()
 
  if st.sidebar.button("Clear message history"):
  print("Clearing message history")
- memory.clear()
+ chain.memory.clear()
  st.session_state.trace_link = None
  st.session_state.run_id = None
 
@@ -103,7 +119,7 @@ if st.session_state.openai_api_key.startswith("sk-"):
  with st.chat_message(streamlit_type, avatar=avatar):
  st.markdown(msg.content)
 
- if st.session_state.trace_link:
+ if client and st.session_state.trace_link:
  st.sidebar.markdown(
  f'<a href="{st.session_state.trace_link}" target="_blank"><button>Latest Trace: 🛠️</button></a>',
  unsafe_allow_html=True,
@@ -136,8 +152,8 @@ if st.session_state.openai_api_key.startswith("sk-"):
  {"input": prompt},
  config=runnable_config,
  )["text"]
- except AuthenticationError:
- st.error("Please enter a valid OpenAI API key.", icon="❌")
+ except (openai.error.AuthenticationError, anthropic.AuthenticationError):
+ st.error("Please enter a valid {provider} API key.", icon="❌")
  st.stop()
  message_placeholder.markdown(full_response)
 
@@ -153,5 +169,5 @@ if st.session_state.openai_api_key.startswith("sk-"):
  feedback_component(client)
 
 else:
- st.error("Please enter a valid OpenAI API key.", icon="❌")
+ st.error(f"Please enter a valid {provider} API key.", icon="❌")
  st.stop()

langchain-streamlit-demo/llm_stuff.py

@@ -3,21 +3,14 @@ from datetime import datetime
 import streamlit as st
 from langchain import LLMChain
 from langchain.callbacks.base import BaseCallbackHandler
-from langchain.chat_models import ChatOpenAI
+from langchain.chat_models import ChatOpenAI, ChatAnyscale, ChatAnthropic
 from langchain.memory import ConversationBufferMemory, StreamlitChatMessageHistory
 from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder
-from langsmith.client import Client
 from streamlit_feedback import streamlit_feedback
 
 _DEFAULT_SYSTEM_PROMPT = "You are a helpful chatbot."
 
 
-def get_langsmith_client():
- return Client(
- api_key=st.session_state.langsmith_api_key,
- )
-
-
 def get_memory() -> ConversationBufferMemory:
  return ConversationBufferMemory(
  chat_memory=StreamlitChatMessageHistory(key="langchain_messages"),
@@ -26,8 +19,39 @@ def get_memory() -> ConversationBufferMemory:
  )
 
 
+def get_llm(
+ model: str,
+ provider_api_key: str,
+ temperature,
+):
+ if model.startswith("gpt"):
+ return ChatOpenAI(
+ model=model,
+ openai_api_key=provider_api_key,
+ temperature=temperature,
+ streaming=True,
+ )
+ elif model.startswith("claude"):
+ return ChatAnthropic(
+ model_name=model,
+ anthropic_api_key=provider_api_key,
+ temperature=temperature,
+ streaming=True,
+ )
+ elif model.startswith("meta-llama"):
+ return ChatAnyscale(
+ model=model,
+ anyscale_api_key=provider_api_key,
+ temperature=temperature,
+ streaming=True,
+ )
+ else:
+ raise NotImplementedError(f"Unknown model {model}")
+
+
 def get_llm_chain(
- memory: ConversationBufferMemory,
+ model: str,
+ provider_api_key: str,
  system_prompt: str = _DEFAULT_SYSTEM_PROMPT,
  temperature: float = 0.7,
 ) -> LLMChain:
@@ -42,11 +66,8 @@ def get_llm_chain(
  ("human", "{input}"),
  ],
  ).partial(time=lambda: str(datetime.now()))
- llm = ChatOpenAI(
- temperature=temperature,
- streaming=True,
- openai_api_key=st.session_state.openai_api_key,
- )
+ memory = get_memory()
+ llm = get_llm(model, provider_api_key, temperature)
  return LLMChain(prompt=prompt, llm=llm, memory=memory or get_memory())