import os
import gradio as gr
from langchain.chains.llm import LLMChain
from langchain_core.prompts import PromptTemplate
from langchain.memory import ConversationBufferMemory
from langchain_openai import ChatOpenAI
from dotenv import load_dotenv

load_dotenv()

API = os.getenv("API_KEY")
if not API:
    raise ValueError("❌ Missing API_KEY environment variable!")

os.environ["OPENAI_API_KEY"] = API

llm = ChatOpenAI(model="gpt-4o-mini", temperature=0)

template = """
You are an expert code reviewer and security analyst specializing in vulnerability detection...
User: {user_message}
Chatbot:
"""

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

memory = ConversationBufferMemory(memory_key="chat_history")

llm_chain = LLMChain(
    llm=llm,
    prompt=prompt,
    memory=memory
)

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

demo = gr.ChatInterface(
    get_text_response,
    examples=[
        "What is a code vulnerability?",
        "What happens if a code is not secure?",
        "Give me secure coding tips."
    ],
    type='messages'
)

if __name__ == "__main__":
    demo.launch(share=True)