Update app.py

app.py

@@ -1,64 +1,292 @@
+import os
+import uuid
+import json
+import time
 import gradio as gr
-from huggingface_hub import InferenceClient
-
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
-
-
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
-
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
+import logging
+from dotenv import 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
+from langchain_core.messages import BaseMessage
+
+
+# === Logging & .env ===
+logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
+logger = logging.getLogger(__name__)
+load_dotenv()
+
+GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")
+if not GEMINI_API_KEY:
+    raise ValueError("Missing GEMINI_API_KEY")
+genai.configure(api_key=GEMINI_API_KEY)
+
+HISTORY_FILE = "chat_history.json"
+
+# === Persistent Storage ===
+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)
+
+# === Chatbot Class ===
+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 instead of answering something not correct.
+        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):
+        try:
+            # Convert string history into LangChain message objects
+            langchain_history = []
+            for user, bot in history:
+                langchain_history.append(HumanMessage(content=user))
+                langchain_history.append(AIMessage(content=bot))
+
+            # Add the new user message
+            input_message = HumanMessage(content=user_message)
+            full_history = langchain_history + [input_message]
+
+            full_response = ""
+            config = {"configurable": {"thread_id": thread_id}}
+
+            # Invoke the model with full conversation
+            response = self.app.invoke({"messages": full_history}, config)
+            complete_response = response["messages"][-1].content
+
+            for char in complete_response:
+                full_response += char
+                yield full_response
+                time.sleep(0.01)
+
+        except Exception as e:
+            logger.error(f"LangGraph Error: {e}")
+            yield f"⚠ Error: {type(e).__name__} — {str(e)}"
+
+
+# === Gradio UI ===
+chatbot = GeminiChatbot()
+sessions = load_all_sessions()
+
+
+def launch_interface():
+    with gr.Blocks(
+            theme=gr.themes.Base(),
+            css="""
+        body {
+            background-color: black;
+        }
+        .gr-block.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([])
+
+        # Initialize with first session or create new
+        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.keys()))
+            session_names.value = [f"PREVIOUS: {k}" for k in sessions.keys()]
+
+        def get_dropdown_choices():
+            """Get current dropdown choices including active sessions and new chat"""
+            choices = []
+            for session_id in sessions:
+                if sessions[session_id]:  # Only show sessions with history
+                    choices.append(f"PREVIOUS: {session_id}")
+            choices.append(f"NEW: {current_thread_id.value}")
+            return choices
+
+        with gr.Column():
+            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=320)
+
+        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")
+
+        def start_new_chat():
+            new_id = str(uuid.uuid4())
+            sessions[new_id] = []
+            save_all_sessions(sessions)
+
+            # Format for dropdown
+            display_name = f"NEW: {new_id}"
+            updated_choices = [f"PREVIOUS: {k}" for k in sessions if sessions[k]] + [display_name]
+
+            return (
+                new_id,  # thread ID state
+                [],  # history
+                gr.update(choices=updated_choices, value=display_name),  # update dropdown
+                display_name  # visible value
+            )
+
+
+
+        def switch_chat(selected_display_id):
+            """Switch between different chat sessions"""
+            if not selected_display_id:
+                return current_thread_id.value, [], ""
+
+            true_id = selected_display_id.split(": ", 1)[-1]
+            chat_history = sessions.get(true_id, [])
+            return true_id, chat_history, selected_display_id
+
+        def respond(message, history, thread_id):
+            """Generate response and update chat history"""
+            if not message.strip():
+                yield history
+                return
+
+            # Add user message to history
+            history.append((message, ""))
+            yield history
+
+            # Stream response
+            full_response = ""
+            for chunk in chatbot.get_response(message, history[:-1], thread_id):
+                full_response = chunk
+                history[-1] = (message, full_response)
+                yield history
+
+            # Save updated session
+            sessions[thread_id] = history
+            save_all_sessions(sessions)
+
+        def clear_current(thread_id):
+            """Clear current chat history"""
+            sessions[thread_id] = []
+            save_all_sessions(sessions)
+            return []
+
+        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,
+            inputs=[msg, chatbot_ui, current_thread_id],
+            outputs=[chatbot_ui]
+        ).then(
+            lambda: "", None, msg  # Clear input after sending
+        )
+
+        msg.submit(
+            respond,
+            inputs=[msg, chatbot_ui, current_thread_id],
+            outputs=[chatbot_ui]
+        ).then(
+            lambda: "", None, msg  # Clear input after sending
+        )
+
+        clear.click(
+            clear_current,
+            inputs=[current_thread_id],
+            outputs=[chatbot_ui]
+        )
+
+    return demo
+
 
 
+# === Run App ===
 if __name__ == "__main__":
-    demo.launch()
+    try:
+        demo = launch_interface()
+        demo.launch(share=True)
+    except Exception as e:
+        logger.critical(f"App failed: {e}")