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import streamlit as st
from PIL import Image
import io
import base64
import uuid
from gtts import gTTS
import google.generativeai as genai
from io import BytesIO  # Import BytesIO

# Set your API key
api_key = "AIzaSyC70u1sN87IkoxOoIj4XCAPw97ae2LZwNM"  # Replace with your actual API key
genai.configure(api_key=api_key)

# Configure the generative AI model
generation_config = genai.GenerationConfig(
    temperature=0.9,
    max_output_tokens=3000
)

# Safety settings configuration
safety_settings = [
    {
        "category": "HARM_CATEGORY_DANGEROUS_CONTENT",
        "threshold": "BLOCK_NONE",
    },
    {
        "category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
        "threshold": "BLOCK_NONE",
    },
    {
        "category": "HARM_CATEGORY_HATE_SPEECH",
        "threshold": "BLOCK_NONE",
    },
    {
        "category": "HARM_CATEGORY_HARASSMENT",
        "threshold": "BLOCK_NONE",
    },
]

# Initialize session state
if 'chat_history' not in st.session_state:
    st.session_state['chat_history'] = []
if 'file_uploader_key' not in st.session_state:
    st.session_state['file_uploader_key'] = str(uuid.uuid4())

st.title("Gemini Chatbot")

# Helper functions for image processing and chat history management
def get_image_base64(image):
    image = image.convert("RGB")
    buffered = io.BytesIO()
    image.save(buffered, format="JPEG")
    img_str = base64.b64encode(buffered.getvalue()).decode()
    return img_str

def clear_conversation():
    st.session_state['chat_history'] = []
    st.session_state['file_uploader_key'] = str(uuid.uuid4())

def display_chat_history():
    for entry in st.session_state['chat_history']:
        role = entry["role"]
        parts = entry["parts"][0]
        if 'text' in parts:
            st.markdown(f"{role.title()}: {parts['text']}")
        elif 'data' in parts:
            st.image(Image.open(io.BytesIO(base64.b64decode(parts['data']))), caption='Uploaded Image')

def get_chat_history_str():
    chat_history_str = "\n".join(
        f"{entry['role'].title()}: {part['text']}" if 'text' in part
        else f"{entry['role'].title()}: (Image)"
        for entry in st.session_state['chat_history']
        for part in entry['parts']
    )
    return chat_history_str

# Send message function with TTS integration
def send_message():
    user_input = st.session_state.user_input
    uploaded_files = st.session_state.uploaded_files
    prompts = []
    prompt_parts = []

    # Populate the prompts list with the existing chat history
    for entry in st.session_state['chat_history']:
        for part in entry['parts']:
            if 'text' in part:
                prompts.append(part['text'])
            elif 'data' in part:
                # Add the image in base64 format to prompt_parts for vision model
                prompt_parts.append({"data": part['data'], "mime_type": "image/jpeg"})
                prompts.append("[Image]")

    # Append the user input to the prompts list
    if user_input:
        prompts.append(user_input)
        st.session_state['chat_history'].append({"role": "user", "parts": [{"text": user_input}]})
        # Also add the user text input to prompt_parts
        prompt_parts.append({"text": user_input})

    # Handle uploaded files
    if uploaded_files:
        for uploaded_file in uploaded_files:
            base64_image = get_image_base64(Image.open(uploaded_file))
            prompts.append("[Image]")
            prompt_parts.append({"data": base64_image, "mime_type": "image/jpeg"})
            st.session_state['chat_history'].append({
                "role": "user",
                "parts": [{"mime_type": uploaded_file.type, "data": base64_image}]
            })

    # Determine if vision model should be used
    use_vision_model = any(part.get('mime_type') == 'image/jpeg' for part in prompt_parts)

    # Set up the model and generate a response
    model_name = 'gemini-pro-vision' if use_vision_model else 'gemini-pro'
    model = genai.GenerativeModel(
        model_name=model_name,
        generation_config=generation_config,
        safety_settings=safety_settings
    )
    chat_history_str = "\n".join(prompts)
    if use_vision_model:
        # Include text and images for vision model
        generated_prompt = {"role": "user", "parts": prompt_parts}
    else:
        # Include text only for standard model
        generated_prompt = {"role": "user", "parts": [{"text": chat_history_str}]}

    response = model.generate_content([generated_prompt])
    response_text = response.text if hasattr(response, "text") else "No response text found."

    # After generating the response from the model, append it to the chat history
    if response_text:
        st.session_state['chat_history'].append({"role": "model", "parts":[{"text": response_text}]})

        # Convert the response text to speech
        tts = gTTS(text=response_text, lang='en')
        tts_file = BytesIO()
        tts.write_to_fp(tts_file)
        tts_file.seek(0)
        st.audio(tts_file, format='audio/mp3')

    # Clear the input fields after sending the message
    st.session_state.user_input = ''
    st.session_state.uploaded_files = []
    st.session_state.file_uploader_key = str(uuid.uuid4())

    # Display the updated chat history
    display_chat_history()

# User input text area
user_input = st.text_area(
    "Enter your message here:",
    value="",
    key="user_input"
)

# File uploader for images
uploaded_files = st.file_uploader(
    "Upload images:",
    type=["png", "jpg", "jpeg"],
    accept_multiple_files=True,
    key=st.session_state.file_uploader_key
)

# Send message button
send_button = st.button(
    "Send",
    on_click=send_message
)

# Clear conversation button
clear_button = st.button("Clear Conversation", on_click=clear_conversation)

# Function to download the chat history as a text file
def download_chat_history():
    chat_history_str = get_chat_history_str()
    return chat_history_str

# Download button for the chat history
download_button = st.download_button(
    label="Download Chat",
    data=download_chat_history(),
    file_name="chat_history.txt",
    mime="text/plain"
)

# Ensure the file_uploader widget state is tied to the randomly generated key
st.session_state.uploaded_files = uploaded_files

# JavaScript to capture the Ctrl+Enter event and trigger a button click
st.markdown(
    """
    <script>
    document.addEventListener('DOMContentLoaded', (event) => {
        document.querySelector('.stTextArea textarea').addEventListener('keydown', function(e) {
            if (e.key === 'Enter' && e.ctrlKey) {
                document.querySelector('.stButton > button').click();
                e.preventDefault();
            }
        });
    });
    </script>
    """,
    unsafe_allow_html=True
)