import streamlit as st
import os
from llama_index.llms.groq import Groq
import streamlit.components.v1 as components

# Ensure Streamlit config directory is set
os.environ["STREAMLIT_CONFIG_DIR"] = "/app/.streamlit"

class TextToSpeechChat:
    def __init__(self, api_key="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"):
        # Initialize the LLM
        self.llm = Groq(model="llama3-70b-8192", api_key=api_key)
        self.speech_enabled = st.session_state.get("speech_enabled", True)

    def speak_text(self, text):
        """Convert text to speech using browser's SpeechSynthesis API"""
        if not text.strip() or not self.speech_enabled:
            return
        try:
            safe_text = text.replace('"', '\\"').replace('\n', ' ')
            js_code = f"""
            <script>
                function speak(text) {{
                    const utterance = new SpeechSynthesisUtterance(text);
                    utterance.rate = 1.0;
                    utterance.volume = 0.9;
                    const voices = window.speechSynthesis.getVoices();
                    if (voices.length > 0) {{
                        utterance.voice = voices[0];
                    }}
                    window.speechSynthesis.speak(utterance);
                }}
                window.speechSynthesis.onvoiceschanged = function() {{
                    speak("{safe_text}");
                }};
                window.speechSynthesis.getVoices();
            </script>
            """
            components.html(js_code, height=0)
            st.write(f"🗣️ Speaking: {text}")
        except Exception as e:
            st.error(f"❌ Speech error: {e}")

    def get_llm_response(self, prompt):
        """Get response from LLM and speak paragraphs in real-time if enabled"""
        try:
            st.write("🤖 Generating response...")
            response = self.llm.stream_complete(prompt)
            full_response = ""
            buffer = ""
            
            response_container = st.empty()
            for r in response:
                delta = r.delta
                full_response += delta
                buffer += delta
                response_container.write(full_response, unsafe_allow_html=True)
                
                if self.speech_enabled and "\n\n" in buffer:
                    paragraphs = buffer.split("\n\n")
                    for paragraph in paragraphs[:-1]:
                        if paragraph.strip():
                            self.speak_text(paragraph.strip())
                    buffer = paragraphs[-1]
            
            if self.speech_enabled and buffer.strip():
                self.speak_text(buffer.strip())
            
            return full_response
        except Exception as e:
            error_msg = f"❌ Error getting LLM response: {e}"
            st.error(error_msg)
            if self.speech_enabled:
                self.speak_text(error_msg)
            return error_msg

def main(user_input):
    chat = TextToSpeechChat()
    response = chat.get_llm_response(user_input)
    return response

# Streamlit UI
st.title("Simple Streamlit UI")

# Speech toggle
if "speech_enabled" not in st.session_state:
    st.session_state.speech_enabled = True

st.checkbox("Enable Speech", value=st.session_state.speech_enabled, key="speech_enabled")

user_input = st.text_input("Enter something:")
if st.button("Submit"):
    st.write("You entered:", user_input)
    response = main(user_input)
    st.write("Response:", response)