src/streamlit_app.py

import os
os.environ["STREAMLIT_HOME"] = "/tmp/.streamlit"
import streamlit as st
from chat_langraph import system, workflow, HumanMessage, AIMessage, get_all_chat_ids, ToolMessage
import uuid
import speech_recognition as sr 
import base64
import pyttsx3 

st.set_page_config(layout="wide")
st.title("My Chatbot")

TEMP_DIR = "/tmp"
os.makedirs(TEMP_DIR, exist_ok=True)


# --- Helpers ---
if ("recognizer" not in st.session_state):
    st.session_state.recognizer = sr.Recognizer()
if ("speaker" not in st.session_state):
    st.session_state.speaker = pyttsx3.init()
st.session_state.tospeak = False

def set_title(messages):
    if messages:
        title = "New Chat"
        st.session_state.chat_dict[st.session_state.current_chat_id] = title


def set_config():
    return {"configurable": {"thread_id": st.session_state.current_chat_id}}


def load_session_state():
    if "chats" not in st.session_state:
        st.session_state.chats = get_all_chat_ids()
    if "current_chat_id" not in st.session_state:
        if len(st.session_state.chats) > 0:
            st.session_state.current_chat_id = st.session_state.chats[-1]
        else:
            new_id = str(uuid.uuid4())
            st.session_state.chats.append(new_id)
            st.session_state.current_chat_id = new_id
    if "chat_dict" not in st.session_state:
        st.session_state.chat_dict = {}


def render_sidebar():
    with st.sidebar:
        st.button("🎙️" , key="mic")
        st.title("Chats")
        if st.button("➕ New Chat"):
            new_id = str(uuid.uuid4())
            st.session_state.chats.append(new_id)
            st.session_state.current_chat_id = new_id
            config = {"configurable": {"thread_id": new_id}}
            workflow.update_state(config, {"messages": [system]})
            st.session_state.chat_dict[new_id] = "New Chat"
            st.rerun()
        for chat_id in st.session_state.chats:
            if st.button(st.session_state.chat_dict.get(chat_id, "New Chat"), key=chat_id):
                st.session_state.current_chat_id = chat_id


def create_download_link(file_path: str, label: str = None) -> str:
    """Generate HTML download link for a file."""
    if not os.path.exists(file_path):
        return ""
    try:
        with open(file_path, "rb") as f:
            data = f.read()
        b64 = base64.b64encode(data).decode()
        label = label or f"📥 Download {os.path.basename(file_path)}"
        href = f'<a href="data:file/octet-stream;base64,{b64}" download="{os.path.basename(file_path)}">{label}</a>'
        return href
    except Exception as e:
        return f"Error creating download link: {e}"





def loadchats():
    if "current_chat_id" not in st.session_state:
        return []
    config = {"configurable": {"thread_id": st.session_state.current_chat_id}}
    state = workflow.get_state(config)
    messages = state.values.get("messages", [])
    for message in messages:
        if(not message.content):
            continue 
        if isinstance(message, HumanMessage):
            with st.chat_message("human"):
                st.write(message.content)
        elif isinstance(message, AIMessage):
            with st.chat_message("assistant"):
                st.write(message.content)
        elif isinstance(message, ToolMessage):
            with st.chat_message("assistant"):
                st.info("Using Appropriate tool")
                if(message.name == "plot_graph" and "Filepath" in message.content):
                    st.image(message.content.split(":")[1] , "📊")
                if("Filepath" in message.content):
                    st.markdown(create_download_link(message.content.split(":")[1]) , True) 
                    
    return messages


# --- Main Chat Flow ---

load_session_state()
render_sidebar()

if "current_chat_id" in st.session_state:
    loadchats()
    user_input = st.chat_input("Your message:")
    if st.session_state.mic:
        st.session_state.tospeak = True
        with sr.Microphone() as source:
            try:
                st.toast("Listening ...")
                r = st.session_state.recognizer
                audio = r.listen(source , timeout = 200)
                text = r.recognize_google(audio)
                user_input = text
            except Exception as E:
                st.toast("Some Error Occoured Try again ...")    
    if user_input :
        with st.chat_message("human"):
            st.write(user_input)

        with st.chat_message("assistant"):
            response_placeholder = st.empty()
            full_response = ""
            tool_name = "" 
            tool_download_msg = ""
            for message, metadata in workflow.stream(
                {"messages": [system, HumanMessage(user_input)]},
                config={"configurable": {"thread_id": st.session_state.current_chat_id}},
                stream_mode="messages",
            ):
                tool_link = ""
                if isinstance(message, AIMessage):
                    full_response += message.content or ""
                    if(message.tool_calls):
                        tool_name = message.tool_calls[0]['name'] 
                elif isinstance(message, ToolMessage):
                    st.info("Using Appropriate tool")
                response_placeholder.markdown(full_response + " ")
            if(st.session_state.tospeak):
                st.session_state.speaker.say(full_response)
                st.session_state.runAndWait()
        st.rerun()