wikipedia

langchain-streamlit-demo/app.py

@@ -13,7 +13,9 @@ from langchain.memory import ConversationBufferMemory, StreamlitChatMessageHisto
 from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder
 from langchain.schema.document import Document
 from langchain.schema.retriever import BaseRetriever
+from langchain.tools import DuckDuckGoSearchRun, WikipediaQueryRun
 from langchain.tools import Tool
+from langchain.utilities import WikipediaAPIWrapper
 from langsmith.client import Client
 from streamlit_feedback import streamlit_feedback
 
@@ -440,6 +442,10 @@ if st.session_state.llm:
  # callbacks.append(stream_handler)
  message_placeholder = st.empty()
 
+ default_tools = [
+ DuckDuckGoSearchRun(),
+ WikipediaQueryRun(api_wrapper=WikipediaAPIWrapper()),
+ ]
  if st.session_state.provider in ("Azure OpenAI", "OpenAI"):
  st_callback = StreamlitCallbackHandler(st.container())
  callbacks.append(st_callback)
@@ -449,10 +455,10 @@ if st.session_state.llm:
  config=get_config(callbacks),
  ),
  name="web-research-assistant",
- description="this assistant returns a report based on web research",
+ description="this assistant returns a comprehensive report based on web research. for quick facts, use duckduckgo instead.",
  )
 
- TOOLS = [research_assistant_tool]
+ TOOLS = [research_assistant_tool] + default_tools
  if use_document_chat:
  st.session_state.doc_chain = get_runnable(
  use_document_chat,
@@ -471,7 +477,7 @@ if st.session_state.llm:
  name="user-document-chat",
  description="this assistant returns a response based on the user's custom context. if the user's meaning is unclear, perhaps the answer is here. generally speaking, try this tool before conducting web research.",
  )
- TOOLS = [doc_chain_tool, research_assistant_tool]
+ TOOLS = [doc_chain_tool, research_assistant_tool] + default_tools
 
  st.session_state.chain = get_agent(
  TOOLS,

langchain-streamlit-demo/defaults.py

@@ -25,7 +25,7 @@ DEFAULT_MODEL = os.environ.get("DEFAULT_MODEL", "gpt-3.5-turbo")
 
 DEFAULT_SYSTEM_PROMPT = os.environ.get(
  "DEFAULT_SYSTEM_PROMPT",
- "You are a helpful chatbot.",
+ "You are a helpful chatbot. Do not rush. Always plan, think, and act in a step-by-step manner.",
 )
 
 MIN_TEMP = float(os.environ.get("MIN_TEMPERATURE", 0.0))

requirements.txt

@@ -14,3 +14,4 @@ streamlit-feedback==0.1.3
 tiktoken==0.5.2
 tornado>=6.3.3 # not directly required, pinned by Snyk to avoid a vulnerability
 validators>=0.21.0 # not directly required, pinned by Snyk to avoid a vulnerability
+wikipedia==1.4.0