A Langchain Action driven agent demo of a weather conversational chatbot

action_driven_chatbot.py

from langchain.agents import Tool
from langchain.chains.conversation.memory import ConversationBufferMemory
from langchain import OpenAI
from langchain.utilities import SerpAPIWrapper
from langchain.agents import initialize_agent
import os
import config


# Step 1: Please add environment api keys for SerpAPI and OpenAI
os.environ["OPENAI_API_KEY"] = config.openai_key
os.environ["SERPAPI_API_KEY"] = config.serpapi_key

# Step 2: Create a JSON 'weather_agent.json' with the following metadata
weather_agent = {
  "load_from_llm_and_tools": true,
  "_type": "conversational-react-description",
  "prefix": "Assistant is a large language model trained for forecasting weather.\n\nAssistant is designed to be able to assist with a wide range of tasks, from answering simple questions to providing in-depth explanations and discussions on a wide range of topics. As a language model, Assistant is able to generate human-like text based on the input it receives.\nAssistant should only obtain knowledge and take actions from using tools and never on your own.\nTOOLS:\n------\n\nAssistant has access to the following tools: ",
  "suffix": "Please make decisions based on the following policy: \n- If the user is asking for a weather forecast use the Weather Forecast tool\n- If the user does not provide a location, ask before checking for weather\n- Apologize if the user is angry or showing frustration\n- Answer with a friendly and professional tone.\n- Always end a response with a follow up question like 'what else can i help you with?', unless the user shows gratitude.\nBegin!\n\nPrevious conversation history:\n{chat_history}\n\nNew input: {input}\n{agent_scratchpad}",
  "ai_prefix": "AI Agent",
  "human_prefix": "Human"
}

search = SerpAPIWrapper()
tools = [
    Tool(
        name="Weather Forecaster",
        func=search.run,
        description="useful for when you need to answer questions about current and future weather forecast"
    ),
]

memory = ConversationBufferMemory(memory_key="chat_history")
llm = OpenAI(temperature=0)
agent_chain = initialize_agent(tools, llm=llm, verbose=True, agent_path="./weather_agent.json", memory=memory)

while True:
    query = input(">> ")
    agent_chain.run(input=query)

If I use our own knowledge base index, instead of SerpAPIWrapper, it shows some misbehavior.
Whenever I am asking the questions related to my context, it returns the answers from out world. How to prevent it?

You can append a suffix in the prompt to mention something along the lines like:

As a customer service bot, you must avoid imaginative responses. When you are unsure, please say you don't understand.

This one would significantly lower down the chances of it happening. Another approach is to adjust top_p OR temp, not both.

Tried it. But along with my exact answer, it shows a lot of other unwanted data like QUESTION, Content,...etc.
How can u disable those and display only my required answer?

Tried verbose= False. But still getting some unwanted details(along with the exact answer) which makes the bot noisy.

How to prevent it?