app.py

import os
import uuid
import json
import time
import gradio as gr
import logging

# Load local .env only if it exists
from dotenv import load_dotenv
load_dotenv()

import google.generativeai as genai

from langgraph.graph import START, MessagesState, StateGraph
from langgraph.checkpoint.memory import MemorySaver
from langchain_core.messages import HumanMessage, AIMessage
from langchain_core.prompts.chat import (
    ChatPromptTemplate,
    SystemMessagePromptTemplate,
    MessagesPlaceholder,
    HumanMessagePromptTemplate,
)
from langchain_google_genai import ChatGoogleGenerativeAI

# === Logging ===
logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
logger = logging.getLogger(__name__)

# === Load API Key ===
os.environ["GOOGLE_API_KEY"] = os.getenv["GEMINI_API_KEY"]

# GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")
# if not GEMINI_API_KEY:
    #raise ValueError("GEMINI_API_KEY is missing. Set it as an environment variable or Hugging Face Secret.")

genai.configure(api_key=GEMINI_API_KEY)

# === Chat Storage ===
HISTORY_FILE = "chat_history.json"

def load_all_sessions():
    if os.path.exists(HISTORY_FILE):
        with open(HISTORY_FILE, "r", encoding="utf-8") as f:
            return json.load(f)
    return {}

def save_all_sessions(sessions):
    with open(HISTORY_FILE, "w", encoding="utf-8") as f:
        json.dump(sessions, f, indent=2)

sessions = load_all_sessions()

# === Gemini LLM Chatbot ===
class GeminiChatbot:
    def __init__(self):
        self.setup_model()

    def setup_model(self):
        system_template = """
        You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe.
        Your answers should be informative, engaging, and accurate. If a question doesn't make any sense, or isn't factually coherent, explain why.
        If you don't know the answer to a question, please don't share false information.
        """

        self.prompt = ChatPromptTemplate.from_messages([
            SystemMessagePromptTemplate.from_template(system_template),
            MessagesPlaceholder(variable_name="chat_history"),
            HumanMessagePromptTemplate.from_template("{input}")
        ])

        self.model = ChatGoogleGenerativeAI(
            model="gemini-2.0-flash",
            temperature=0.7,
            top_p=0.95,
            google_api_key=GEMINI_API_KEY,
            convert_system_message_to_human=True
        )

        def call_model(state: MessagesState):
            chat_history = state["messages"][:-1]
            user_input = state["messages"][-1].content
            formatted_messages = self.prompt.format_messages(chat_history=chat_history, input=user_input)
            response = self.model.invoke(formatted_messages)
            return {"messages": response}

        workflow = StateGraph(state_schema=MessagesState)
        workflow.add_node("model", call_model)
        workflow.add_edge(START, "model")

        self.memory = MemorySaver()
        self.app = workflow.compile(checkpointer=self.memory)

    def get_response(self, user_message, history, thread_id):
        from langchain_core.messages import HumanMessage, AIMessage

        try:
            # Format chat history for LangChain
            langchain_history = []
            for user, bot in history:
                langchain_history.append(HumanMessage(content=user))
                langchain_history.append(AIMessage(content=bot))

            input_msg = HumanMessage(content=user_message)
            full_history = langchain_history + [input_msg]
            config = {"configurable": {"thread_id": thread_id}}

            # Get final response
            response = self.app.invoke({"messages": full_history}, config)
            full_text = response["messages"][-1].content

            full_response = ""
            for char in full_text:
                full_response += char
                yield full_response
                time.sleep(0.01)

        except Exception as e:
            logger.error(f"Response error: {e}")
            yield f"⚠ Error: {type(e).__name__} — {str(e)}"


chatbot = GeminiChatbot()

# === Gradio UI ===
def launch_interface():
    with gr.Blocks(
        theme=gr.themes.Base(),
        css="""
        body { background-color: black; }
        .gr-textbox textarea { background-color: #2f2f2f; color: white; }
        .gr-chatbot { background-color: #2f2f2f; color: white; }
        .gr-button, .gr-dropdown {
            margin: 5px auto;
            display: block;
            width: 50%;
        }
        .gr-markdown h2 { text-align: center; color: white; }
        """
    ) as demo:
        demo.title = "LangChain Powered ChatBot"
        gr.Markdown("## LangChain Powered ChatBot")

        current_thread_id = gr.State()
        session_names = gr.State()
        history = gr.State([])

        if not sessions:
            new_id = str(uuid.uuid4())
            sessions[new_id] = []
            save_all_sessions(sessions)
            current_thread_id.value = new_id
            session_names.value = [f"NEW: {new_id}"]
        else:
            current_thread_id.value = next(iter(sessions))
            session_names.value = [f"PREVIOUS: {k}" for k in sessions if sessions[k]]

        def get_dropdown_choices():
            return [f"PREVIOUS: {k}" for k in sessions if sessions[k]] + [f"NEW: {current_thread_id.value}"]

        # UI
        new_chat_btn = gr.Button("New Chat", variant="primary")
        session_selector = gr.Dropdown(
            label="Chats",
            choices=get_dropdown_choices(),
            value=f"NEW: {current_thread_id.value}",
            interactive=True
        )

        chatbot_ui = gr.Chatbot(label="Conversation", height=350)

        with gr.Row():
            msg = gr.Textbox(placeholder="Ask a question...", container=False, scale=9)
            send = gr.Button("Send", variant="primary", scale=1)

        clear = gr.Button("Clear Current Chat")

        # === Event Functions ===
        def start_new_chat():
            new_id = str(uuid.uuid4())
            sessions[new_id] = []
            save_all_sessions(sessions)
            display = f"NEW: {new_id}"
            updated = [f"PREVIOUS: {k}" for k in sessions if sessions[k]] + [display]
            return new_id, [], gr.update(choices=updated, value=display), display

        def switch_chat(display_id):
            true_id = display_id.split(": ", 1)[-1]
            return true_id, sessions.get(true_id, []), display_id

        def respond(message, history, thread_id):
            if not message.strip():
                yield history
                return
            history.append((message, ""))
            yield history

            for chunk in chatbot.get_response(message, history[:-1], thread_id):
                history[-1] = (message, chunk)
                yield history

            sessions[thread_id] = history
            save_all_sessions(sessions)

        def clear_chat(thread_id):
            sessions[thread_id] = []
            save_all_sessions(sessions)
            return []

        # === Bind Events ===
        new_chat_btn.click(start_new_chat, outputs=[current_thread_id, chatbot_ui, session_selector, session_selector])
        session_selector.change(switch_chat, inputs=session_selector, outputs=[current_thread_id, chatbot_ui, session_selector])
        send.click(respond, [msg, chatbot_ui, current_thread_id], [chatbot_ui]).then(lambda: "", None, msg)
        msg.submit(respond, [msg, chatbot_ui, current_thread_id], [chatbot_ui]).then(lambda: "", None, msg)
        clear.click(clear_chat, inputs=[current_thread_id], outputs=[chatbot_ui])

    return demo

# === Run App ===
if __name__ == "__main__":
    try:
        demo = launch_interface()
        demo.launch()
    except Exception as e:
        logger.critical(f"App failed: {e}")