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Create app.py
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app.py
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import streamlit as st
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from langchain.schema.runnable import RunnablePassthrough
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from langchain.memory import ConversationBufferWindowMemory
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from langchain.agents import AgentExecutor
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from langchain.agents.format_scratchpad import format_to_openai_functions
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import wikipedia
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from langchain.tools.render import format_tool_to_openai_function
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from langchain.prompts import MessagesPlaceholder
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from langchain.agents.output_parsers import OpenAIFunctionsAgentOutputParser
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from langchain.chat_models import ChatOpenAI
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from langchain.prompts import ChatPromptTemplate
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from langchain.agents import tool
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import requests
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import datetime,os
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from langchain.pydantic_v1 import BaseModel,Field
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st.set_page_config(page_title="ChatBot", page_icon="🤖")
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st.header('Agent ChatBot')
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st.write('Allows users to interact with the ChatGPT,Wikipedia and fetch current weather temperature of any place.')
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if "messages" not in st.session_state:
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st.session_state["messages"] = [{"role":"assistant","content":"Hello! How can I assist you today?"}]
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chat_model = ChatOpenAI(model="gpt-3.5-turbo-1106",
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streaming=True,)
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# Define the input schema
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class OpenMeteoInput(BaseModel):
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latitude: float = Field(..., description="Latitude of the location to fetch weather data for")
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longitude: float = Field(..., description="Longitude of the location to fetch weather data for")
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@tool(args_schema=OpenMeteoInput)
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def get_current_temperature(latitude: float, longitude: float) -> dict:
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"""Fetch current temperature for given coordinates."""
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BASE_URL = "https://api.open-meteo.com/v1/forecast"
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# Parameters for the request
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params = {
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'latitude': latitude,
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'longitude': longitude,
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'hourly': 'temperature_2m',
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'forecast_days': 1,
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}
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# Make the request
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response = requests.get(BASE_URL, params=params)
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if response.status_code == 200:
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results = response.json()
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else:
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return f"API Request failed with status code: {response.status_code}"
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current_utc_time = datetime.datetime.utcnow()
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time_list = [datetime.datetime.fromisoformat(time_str.replace('Z', '+00:00')) for time_str in results['hourly']['time']]
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temperature_list = results['hourly']['temperature_2m']
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closest_time_index = min(range(len(time_list)), key=lambda i: abs(time_list[i] - current_utc_time))
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current_temperature = temperature_list[closest_time_index]
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return f'The current temperature is {current_temperature}°C'
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@tool
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def SearchWikiPedia(query: str):
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"Serach wikipedia and get page summaries."
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page_titles = wikipedia.search(query)
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summaries = []
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for page_title in page_titles[: 3]:
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try:
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wiki_page = wikipedia.page(title=page_title,auto_suggest=False)
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summaries.append(f"Page: {wiki_page.title}\nSummary: {wiki_page.summary}")
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except Exception:
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pass
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if not summaries:
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return "No Good WikiPedia Search results found."
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return "\n\n".join(summaries)
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tools = [get_current_temperature,SearchWikiPedia]
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functions = [format_tool_to_openai_function(t) for t in tools]
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model_with_function = chat_model.bind(functions = functions)
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prompt = ChatPromptTemplate.from_messages([("system","You are helpfull assistant.You can query from wikipedia if you donot know the answer of user query also you can check current weather temperature of any place."),
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MessagesPlaceholder(variable_name="chat_history"),
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("user","{user_input}"),
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MessagesPlaceholder(variable_name="agent_scratchpad")])
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chain = prompt | model_with_function | OpenAIFunctionsAgentOutputParser()
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agent_chain = RunnablePassthrough.assign(
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agent_scratchpad = lambda x: format_to_openai_functions(x['intermediate_steps'])
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) | chain
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for msg in st.session_state["messages"]:
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st.chat_message(msg["role"]).write(msg["content"])
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@st.cache_resource
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def main():
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memory=ConversationBufferWindowMemory(return_messages=True,memory_key="chat_history",k=54)
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return AgentExecutor(agent=agent_chain,tools=tools,memory=memory)
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def _main():
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if user_input:= st.chat_input("Send Message To GPT..."):
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st.chat_message("user").write(user_input)
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st.session_state.messages.append({"role":"user","content":user_input})
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response = main().invoke({'user_input':user_input})
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with st.chat_message("assistant"):
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st.write(response["output"])
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st.session_state.messages.append({"role":"assistant","content":response["output"]})
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try:
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_main()
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except Exception as error:
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st.error(error)
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