code_base.txt

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 json


# Step 1: Please add environment api keys for SerpAPI and OpenAI
os.environ["OPENAI_API_KEY"] = ""
os.environ["SERPAPI_API_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"
}

# Define the path to the local file where you want to save the JSON data
file_path = "/content/weather_agent.json"

# Write the JSON data to the file
with open(file_path, "w") as json_file:
    json.dump(weather_agent, json_file, indent=2)

print(f"JSON data has been saved to {file_path}")

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="/content/weather_agent.json", 
                               memory=memory)

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