# import streamlit as st
# import os
# import time

# import google.generativeai as genai

# secret_key = os.getenv("SECRET_KEY")
# genai.configure(api_key=secret_key)

# def upload_to_gemini(path, mime_type=None):
#   file = genai.upload_file(path, mime_type=mime_type)
#   print(f"Uploaded file '{file.display_name}' as: {file.uri}")
#   return file

# def wait_for_files_active(files):
#   for name in (file.name for file in files):
#     file = genai.get_file(name)
#     while file.state.name == "PROCESSING":
#       time.sleep(10)
#       file = genai.get_file(name)
#     if file.state.name != "ACTIVE":
#       raise Exception(f"File {file.name} failed to process")


# model = genai.GenerativeModel(
#   model_name="gemini-1.5-pro"
# )

# # files = [
# #   upload_to_gemini("American Museum of Natural History Tour - 5 Min", mime_type="video/mp4"),
# # ]

# uploaded_file = st.file_uploader("Upload a video file", type=["mp4", "avi", "mov"])

# if uploaded_file:
#     files = [
#       upload_to_gemini(uploaded_file, mime_type="video/mp4"),
#     ]
    
#     wait_for_files_active(files)
    
#     chat_session = model.start_chat()

#     input=st.text_input("Input Prompt: ",key="input")  
    
#     response = chat_session.send_message(input)
    
    
#     st.write(response.text)

# import streamlit as st
# import os
# import time
# import tempfile
# import google.generativeai as genai

# secret_key = os.getenv("SECRET_KEY")
# genai.configure(api_key=secret_key)

# def upload_to_gemini(path, mime_type=None):
#     file = genai.upload_file(path, mime_type=mime_type)
#     print(f"Uploaded file '{file.display_name}' as: {file.uri}")
#     return file

# def wait_for_files_active(files):
#     for name in (file.name for file in files):
#         file = genai.get_file(name)
#         while file.state.name == "PROCESSING":
#             time.sleep(10)
#             file = genai.get_file(name)
#         if file.state.name != "ACTIVE":
#             raise Exception(f"File {file.name} failed to process")

# model = genai.GenerativeModel(
#     model_name="gemini-1.5-pro"
# )

# uploaded_file = st.file_uploader("Upload a video file", type=["mp4", "avi", "mov"])

# if uploaded_file:
#     with tempfile.NamedTemporaryFile(delete=False) as temp_file:
#         temp_file.write(uploaded_file.read())
#         temp_file_path = temp_file.name

#     try:
#         files = [
#             upload_to_gemini(temp_file_path, mime_type="video/mp4"),
#         ]
        
#         wait_for_files_active(files)
        
#         chat_session = model.start_chat()
        
#         input = st.text_input("Input Prompt: ", key="input")
        
#         if input:
#             response = chat_session.send_message(input)
#             st.write(response.text)
#     finally:
#         os.remove(temp_file_path)  # Ensure the temporary file is deleted

# import streamlit as st
# import os
# import time
# import tempfile
# import google.generativeai as genai

# secret_key = os.getenv("SECRET_KEY")
# genai.configure(api_key=secret_key)

# def upload_to_gemini(path, mime_type=None):
#     file = genai.upload_file(path, mime_type=mime_type)
#     print(f"Uploaded file '{file.display_name}' as: {file.uri}")
#     return file

# def wait_for_files_active(files):
#     for name in (file.name for file in files):
#         file = genai.get_file(name)
#         while file.state.name == "PROCESSING":
#             time.sleep(10)
#             file = genai.get_file(name)
#         if file.state.name != "ACTIVE":
#             raise Exception(f"File {file.name} failed to process")

# model = genai.GenerativeModel(
#     model_name="gemini-1.5-pro"
# )

# uploaded_file = st.file_uploader("Upload a video file", type=["mp4", "avi", "mov"])

# if uploaded_file:
#     with tempfile.NamedTemporaryFile(delete=False) as temp_file:
#         temp_file.write(uploaded_file.read())
#         temp_file_path = temp_file.name

#     try:
#         file = upload_to_gemini(temp_file_path, mime_type="video/mp4")
        
#         wait_for_files_active([file])
        
#         chat_session = model.start_chat()
        
#         input = st.text_input("Input Prompt: ", key="input")
        
#         if input:
#             response = chat_session.send_message(input)
#             st.write(response.text)
        
#         st.write(f"Uploaded video file: [View Video]({file.uri})")
#     finally:
#         os.remove(temp_file_path)  # Ensure the temporary file is deleted

# streamlit_app.py

import os
import time
import streamlit as st
import google.generativeai as genai

# Configure the API key for Google Generative AI
secret_key = os.getenv("SECRET_KEY")
genai.configure(api_key=secret_key)

def upload_to_gemini(path, mime_type=None):
    """Uploads the given file to Gemini."""
    file = genai.upload_file(path, mime_type=mime_type)
    st.write(f"Uploaded file '{file.display_name}' as: {file.uri}")
    return file

def wait_for_files_active(files):
    """Waits for the given files to be active."""
    st.write("Waiting for file processing...")
    for name in (file.name for file in files):
        file = genai.get_file(name)
        while file.state.name == "PROCESSING":
            st.write(".", end="", flush=True)
            time.sleep(10)
            file = genai.get_file(name)
        if file.state.name != "ACTIVE":
            raise Exception(f"File {file.name} failed to process")
    st.write("...all files ready")
    st.write()

# Define the Streamlit interface
st.title("Video Upload for Generative AI Processing")
uploaded_file = st.file_uploader("Upload a video file", type=["mp4"])

if uploaded_file is not None:
    # Save the uploaded file locally
    video_path = os.path.join("", uploaded_file.name)
    with open(video_path, "wb") as f:
        f.write(uploaded_file.getbuffer())
    st.success(f"Saved file: {uploaded_file.name}")

    # Upload the video to Gemini
    files = [
        upload_to_gemini(video_path, mime_type="video/mp4"),
    ]

    # Wait for the file to become active
    wait_for_files_active(files)

    # Create the generative model
    generation_config = {
        "temperature": 1,
        "top_p": 0.95,
        "top_k": 64,
        "max_output_tokens": 8192,
        "response_mime_type": "text/plain",
    }
    safety_settings = [
        {
            "category": "HARM_CATEGORY_HARASSMENT",
            "threshold": "BLOCK_MEDIUM_AND_ABOVE",
        },
        {
            "category": "HARM_CATEGORY_HATE_SPEECH",
            "threshold": "BLOCK_MEDIUM_AND_ABOVE",
        },
        {
            "category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
            "threshold": "BLOCK_MEDIUM_AND_ABOVE",
        },
        {
            "category": "HARM_CATEGORY_DANGEROUS_CONTENT",
            "threshold": "BLOCK_MEDIUM_AND_ABOVE",
        },
    ]
    model = genai.GenerativeModel(
        model_name="gemini-1.5-pro",
        safety_settings=safety_settings,
        generation_config=generation_config,
    )

    # Start a chat session
    chat_session = model.start_chat(
        history=[
            {
                "role": "user",
                "parts": ["summarise video"],
            },
            {
                "role": "user",
                "parts": [files[0].uri],
            },
        ]
    )

    # Send a message to the chat session
    response = chat_session.send_message("INSERT_INPUT_HERE")

    # Display the response
    st.write("Response from the model:")
    st.write(response.text)