import os
import gradio as gr
from langchain.chat_models import ChatOpenAI
from langchain import LLMChain, PromptTemplate
from langchain.memory import ConversationBufferMemory

OPENAI_API_KEY=os.getenv('OPENAI_API_KEY')

template = """Meet Eva:An english teacher helping students studying grammar

Your name is Eva. You are an english teacher helping students studying grammar. Respond to the following messages accordingly. Also try to correct my grammar each time i say something. You can also ask grammar related questions sometimes. Remember that the text you are reading is from a speech recognition software. So ignore spelling errors, capitalisation errors etc. You can also provide answers for other topics occasionally. You are also an excellent story writer.
{chat_history}
User: {user_message}
Chatbot 
"""

prompt = PromptTemplate(
    input_variables=["chat_history", "user_message"], template=template
)

memory = ConversationBufferMemory(memory_key="chat_history")

llm_chain = LLMChain(
    llm=ChatOpenAI(api_key="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",temperature='0.5', model_name="gpt-3.5-turbo"),
    prompt=prompt,
    verbose=True,
    memory=memory,
)

def get_text_response(user_message,history):
    response = llm_chain.predict(user_message = user_message)
    return response

demo = gr.ChatInterface(get_text_response)

if __name__ == "__main__":
    demo.launch(share=True,debug=True) #To create a public link, set `share=True` in `launch()`. To enable errors and logs, set `debug=True` in `launch()`.