Update app.py

app.py

@@ -1,292 +1,275 @@
-import os
-import uuid
-import json
-import time
-import gradio as gr
-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__":
-    try:
-        demo = launch_interface()
-        demo.launch(share=True)
-    except Exception as e:
-        logger.critical(f"App failed: {e}")
+import os
+import uuid
+
+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
+
+import gradio as gr
+
+import time
+import json
+
+import logging
+from dotenv import load_dotenv
+
+
+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"
+
+
+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)
+
+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:
+            langchain_history = []
+            for user, bot in history:
+                langchain_history.append(HumanMessage(content=user))
+                langchain_history.append(AIMessage(content=bot))
+
+            input_message = HumanMessage(content=user_message)
+            full_history = langchain_history + [input_message]
+
+            full_response = ""
+            config = {"configurable": {"thread_id": thread_id}}
+
+            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)}"
+
+
+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([])
+
+        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():
+            choices = []
+            for session_id in sessions:
+                if sessions[session_id]:
+                    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)
+
+            display_name = f"NEW: {new_id}"
+            updated_choices = [f"PREVIOUS: {k}" for k in sessions if sessions[k]] + [display_name]
+
+            return (
+                new_id,
+                [],
+                gr.update(choices=updated_choices, value=display_name),
+                display_name
+            )
+
+
+
+        def switch_chat(selected_display_id):
+            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):
+            if not message.strip():
+                yield history
+                return
+
+            history.append((message, ""))
+            yield history
+
+            full_response = ""
+            for chunk in chatbot.get_response(message, history[:-1], thread_id):
+                full_response = chunk
+                history[-1] = (message, full_response)
+                yield history
+
+            sessions[thread_id] = history
+            save_all_sessions(sessions)
+
+        def clear_current(thread_id):
+            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
+        )
+
+        msg.submit(
+            respond,
+            inputs=[msg, chatbot_ui, current_thread_id],
+            outputs=[chatbot_ui]
+        ).then(
+            lambda: "", None, msg
+        )
+
+        clear.click(
+            clear_current,
+            inputs=[current_thread_id],
+            outputs=[chatbot_ui]
+        )
+
+    return demo
+
+
+
+if __name__ == "__main__":
+    try:
+        demo = launch_interface()
+        demo.launch(share=True)
+    except Exception as e:
+        logger.critical(f"App failed: {e}")