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| import streamlit as st | |
| from streamlit_chat import message | |
| import os | |
| import uuid | |
| from dataclasses import dataclass | |
| from langchain.agents import load_tools, initialize_agent | |
| from langchain.llms import OpenAI | |
| from transformers import AutoModelForQuestionAnswering, AutoTokenizer | |
| class Message: | |
| text: str | |
| is_user: bool | |
| # Set streamlit page configuration | |
| st.set_page_config(page_title="Chat with wikipedia") | |
| with st.sidebar: | |
| st.title('Chat GPT using Langchain Agents to talk to Wikipedia') | |
| st.markdown(''' | |
| ## About | |
| This app is an OpenAi LLM-powered PDF chatbot built using: | |
| - [Streamlit](https://streamlit.io/) | |
| - [LangChain](https://python.langchain.com/) | |
| - [OpenAI](https://platform.openai.com/docs/models) LLM model | |
| ## How it works | |
| - Ask any question. It will try to use wikipedia api to get the result. (For ex: *Who is Madonna?*) | |
| - Ask a follow up question that would involve using some kind of mathematical operation (For ex: *Take Elton Johns age and multiply it with Madonnas age*) | |
| - The langchain agent will try to get the necessary information based on a tree of thought type of prompting | |
| ''') | |
| st.write('Made with 🤖 by [Cazimir Roman](https://cazimir.dev)') | |
| def load_app(): | |
| ## AGENT setup | |
| # llm = OpenAI(temperature=0) | |
| model_name = "deepset/roberta-base-squad2" | |
| tokenizer = AutoTokenizer.from_pretrained(model_name) | |
| llm = AutoModelForQuestionAnswering.from_pretrained(model_name) | |
| # llm = OpenAI(temperature=0) | |
| tools = load_tools(["llm-math", "wikipedia"], llm=llm) | |
| agent = initialize_agent(tools, llm, agent="zero-shot-react-description", verbose=True) | |
| ## AGENT setup | |
| if 'messages' not in st.session_state: | |
| st.session_state['messages'] = [Message(text="Hey, this is Botty. How can I help?", is_user=False)] | |
| if 'current_prompt' not in st.session_state: | |
| st.session_state['current_prompt'] = "" # Store the latest user input | |
| # Define function to submit user input | |
| def submit(): | |
| # Set current_prompt to the current value of prompt_input | |
| st.session_state.current_prompt = st.session_state.prompt_input | |
| # Clear prompt_input | |
| st.session_state.prompt_input = "" | |
| if st.session_state.current_prompt != "": | |
| user_query = st.session_state.current_prompt | |
| st.session_state.messages.append(Message(text=user_query, is_user=True)) | |
| # Get user query | |
| with st.spinner('AI is thinking...'): | |
| response = agent.run(user_query) | |
| st.session_state.messages.append(Message(text=response, is_user=False)) | |
| if len(st.session_state['messages']) != 0: | |
| for message_item in reversed(st.session_state['messages']): | |
| message(message_item.text, key=str(uuid.uuid4()), is_user=message_item.is_user) | |
| # Create a text input for user | |
| st.text_input('You: ', key='prompt_input', on_change=submit) | |
| def main(): | |
| container = st.container() | |
| with container: | |
| open_ai_key = os.getenv("OPENAI_API_KEY") | |
| api_key = container.text_input("Enter your OpenAI API key", type="password", value="" if open_ai_key == None else open_ai_key) | |
| st.write("Get your own Open AI API key from [here](https://platform.openai.com/account/api-keys)") | |
| submit = container.button("Submit") | |
| if open_ai_key: | |
| load_app() | |
| # submit button is pressed | |
| if submit: | |
| # check if api key length correct | |
| if len(api_key) == 51: | |
| os.environ["OPENAI_API_KEY"] = api_key | |
| load_app() | |
| else: | |
| st.error("Api key is not correct") | |
| if __name__ == '__main__': | |
| main() |