app.py

import os
import json
import re
import gradio as gr
import asyncio
import logging
import torch
from serpapi import GoogleSearch
from pydantic import BaseModel
from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.conditions import HandoffTermination, TextMentionTermination
from autogen_agentchat.teams import Swarm
from autogen_agentchat.ui import Console
from autogen_agentchat.messages import TextMessage, HandoffMessage, StructuredMessage
from autogen_ext.models.anthropic import AnthropicChatCompletionClient
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.models.ollama import OllamaChatCompletionClient
import traceback
import soundfile as sf
import tempfile
from pydub import AudioSegment
from TTS.api import TTS

# Set up logging
logging.basicConfig(
    level=logging.DEBUG,
    format="%(asctime)s - %(levelname)s - %(message)s",
    handlers=[
        logging.FileHandler("lecture_generation.log"),
        logging.StreamHandler()
    ]
)
logger = logging.getLogger(__name__)

# Set up environment
OUTPUT_DIR = os.path.join(os.getcwd(), "outputs")  # Fallback for local dev
os.makedirs(OUTPUT_DIR, exist_ok=True)
logger.info(f"Using output directory: {OUTPUT_DIR}")
os.environ["COQUI_TOS_AGREED"] = "1"

# Initialize TTS model at the top
try:
    device = "cuda" if torch.cuda.is_available() else "cpu"
    tts = TTS("tts_models/multilingual/multi-dataset/xtts_v2").to(device)
    logger.info("TTS model initialized on %s", device)
except Exception as e:
    logger.error("Failed to initialize TTS model: %s", str(e))
    tts = None

# Define Pydantic model for slide data
class Slide(BaseModel):
    title: str
    content: str

class SlidesOutput(BaseModel):
    slides: list[Slide]

# Define search_web tool using SerpApi
def search_web(query: str, serpapi_key: str) -> str:
    try:
        params = {
            "q": query,
            "engine": "google",
            "api_key": serpapi_key,
            "num": 5
        }
        search = GoogleSearch(params)
        results = search.get_dict()
        
        if "error" in results:
            logger.error("SerpApi error: %s", results["error"])
            return None
        
        if "organic_results" not in results or not results["organic_results"]:
            logger.info("No search results found for query: %s", query)
            return None
        
        formatted_results = []
        for item in results["organic_results"][:5]:
            title = item.get("title", "No title")
            snippet = item.get("snippet", "No snippet")
            link = item.get("link", "No link")
            formatted_results.append(f"Title: {title}\nSnippet: {snippet}\nLink: {link}\n")
        
        formatted_output = "\n".join(formatted_results)
        logger.info("Successfully retrieved search results for query: %s", query)
        return formatted_output
    
    except Exception as e:
        logger.error("Unexpected error during search: %s", str(e))
        return None

# Define helper function for progress HTML
def html_with_progress(label, progress):
    return f"""
    <div style="display: flex; flex-direction: column; justify-content: center; align-items: center; height: 100%; min-height: 700px; padding: 20px; text-align: center; border: 1px solid #ddd; border-radius: 8px;">
        <div style="width: 70%; background-color: #FFFFFF; border-radius: 80px; overflow: hidden; margin-bottom: 20px;">
            <div style="width: {progress}%; height: 15px; background-color: #4CAF50; border-radius: 80px;"></div>
        </div>
        <h2 style="font-style: italic; color: #555;">{label}</h2>
    </div>
    """

# Function to get model client based on selected service
def get_model_client(service, api_key):
    if service == "OpenAI-gpt-4o-2024-08-06":
        return OpenAIChatCompletionClient(model="gpt-4o-2024-08-06", api_key=api_key)
    elif service == "Anthropic-claude-3-sonnet-20240229":
        return AnthropicChatCompletionClient(model="claude-3-sonnet-20240229", api_key=api_key)
    elif service == "Google-gemini-1.5-flash":
        return OpenAIChatCompletionClient(model="gemini-1.5-flash", api_key=api_key)
    elif service == "Ollama-llama3.2":
        return OllamaChatCompletionClient(model="llama3.2")
    else:
        raise ValueError("Invalid service")

# Helper function to clean script text
def clean_script_text(script):
    if not script or not isinstance(script, str):
        logger.error("Invalid script input: %s", script)
        return None
    
    script = re.sub(r"\*\*Slide \d+:.*?\*\*", "", script)
    script = re.sub(r"\[.*?\]", "", script)
    script = re.sub(r"Title:.*?\n|Content:.*?\n", "", script)
    script = script.replace("humanlike", "human-like").replace("problemsolving", "problem-solving")
    script = re.sub(r"\s+", " ", script).strip()
    
    if len(script) < 10:
        logger.error("Cleaned script too short (%d characters): %s", len(script), script)
        return None
    
    logger.info("Cleaned script: %s", script)
    return script

# Helper function to validate and convert speaker audio
async def validate_and_convert_speaker_audio(speaker_audio):
    if not speaker_audio or not os.path.exists(speaker_audio):
        logger.warning("Speaker audio file does not exist: %s. Using default voice.", speaker_audio)
        default_voice = os.path.join(os.path.dirname(__file__), "feynman.mp3")
        if os.path.exists(default_voice):
            speaker_audio = default_voice
        else:
            logger.error("Default voice not found. Cannot proceed with TTS.")
            return None
    
    try:
        ext = os.path.splitext(speaker_audio)[1].lower()
        if ext == ".mp3":
            logger.info("Converting MP3 to WAV: %s", speaker_audio)
            audio = AudioSegment.from_mp3(speaker_audio)
            audio = audio.set_channels(1).set_frame_rate(22050)
            with tempfile.NamedTemporaryFile(suffix=".wav", delete=False, dir=OUTPUT_DIR) as temp_file:
                audio.export(temp_file.name, format="wav")
                speaker_wav = temp_file.name
        elif ext == ".wav":
            speaker_wav = speaker_audio
        else:
            logger.error("Unsupported audio format: %s", ext)
            return None
        
        data, samplerate = sf.read(speaker_wav)
        if samplerate < 16000 or samplerate > 48000:
            logger.error("Invalid sample rate for %s: %d Hz", speaker_wav, samplerate)
            return None
        if len(data) < 16000:
            logger.error("Speaker audio too short: %d frames", len(data))
            return None
        if data.ndim == 2:
            logger.info("Converting stereo WAV to mono: %s", speaker_wav)
            data = data.mean(axis=1)
            with tempfile.NamedTemporaryFile(suffix=".wav", delete=False, dir=OUTPUT_DIR) as temp_file:
                sf.write(temp_file.name, data, samplerate)
                speaker_wav = temp_file.name
        
        logger.info("Validated speaker audio: %s", speaker_wav)
        return speaker_wav
    
    except Exception as e:
        logger.error("Failed to validate or convert speaker audio %s: %s", speaker_audio, str(e))
        return None

# Helper function to generate audio using Coqui TTS API
def generate_xtts_audio(tts, text, speaker_wav, output_path):
    if not tts:
        logger.error("TTS model not initialized")
        return False
    try:
        tts.tts_to_file(text=text, speaker_wav=speaker_wav, language="en", file_path=output_path)
        logger.info("Generated audio for %s", output_path)
        return True
    except Exception as e:
        logger.error("Failed to generate audio for %s: %s", output_path, str(e))
        return False

# Helper function to extract JSON from messages
def extract_json_from_message(message):
    if isinstance(message, TextMessage):
        content = message.content
        logger.debug("Extracting JSON from TextMessage: %s", content)
        if not isinstance(content, str):
            logger.warning("TextMessage content is not a string: %s", content)
            return None
        
        pattern = r"```json\s*(.*?)\s*```"
        match = re.search(pattern, content, re.DOTALL)
        if match:
            try:
                json_str = match.group(1).strip()
                logger.debug("Found JSON in code block: %s", json_str)
                return json.loads(json_str)
            except json.JSONDecodeError as e:
                logger.error("Failed to parse JSON from code block: %s", e)
        
        json_patterns = [
            r"\[\s*\{.*?\}\s*\]",
            r"\{\s*\".*?\"\s*:.*?\}",
        ]
        
        for pattern in json_patterns:
            match = re.search(pattern, content, re.DOTALL)
            if match:
                try:
                    json_str = match.group(0).strip()
                    logger.debug("Found JSON with pattern %s: %s", pattern, json_str)
                    return json.loads(json_str)
                except json.JSONDecodeError as e:
                    logger.error("Failed to parse JSON with pattern %s: %s", pattern, e)
        
        try:
            for i in range(len(content)):
                for j in range(len(content), i, -1):
                    substring = content[i:j].strip()
                    if (substring.startswith('{') and substring.endswith('}')) or \
                       (substring.startswith('[') and substring.endswith(']')):
                        try:
                            parsed = json.loads(substring)
                            if isinstance(parsed, (list, dict)):
                                logger.info("Found JSON in substring: %s", substring)
                                return parsed
                        except json.JSONDecodeError:
                            continue
        except Exception as e:
            logger.error("Error in JSON substring search: %s", e)
        
        logger.warning("No JSON found in TextMessage content")
        return None
    
    elif isinstance(message, StructuredMessage):
        content = message.content
        logger.debug("Extracting JSON from StructuredMessage: %s", content)
        try:
            if isinstance(content, BaseModel):
                content_dict = content.dict()
                return content_dict.get("slides", content_dict)
            return content
        except Exception as e:
            logger.error("Failed to extract JSON from StructuredMessage: %s, Content: %s", e, content)
            return None
    
    elif isinstance(message, HandoffMessage):
        logger.debug("Extracting JSON from HandoffMessage context")
        for ctx_msg in message.context:
            if hasattr(ctx_msg, "content"):
                content = ctx_msg.content
                logger.debug("HandoffMessage context content: %s", content)
                if isinstance(content, str):
                    pattern = r"```json\s*(.*?)\s*```"
                    match = re.search(pattern, content, re.DOTALL)
                    if match:
                        try:
                            return json.loads(match.group(1))
                        except json.JSONDecodeError as e:
                            logger.error("Failed to parse JSON from HandoffMessage: %s", e)
                    
                    json_patterns = [
                        r"\[\s*\{.*?\}\s*\]",
                        r"\{\s*\".*?\"\s*:.*?\}",
                    ]
                    
                    for pattern in json_patterns:
                        match = re.search(pattern, content, re.DOTALL)
                        if match:
                            try:
                                return json.loads(match.group(0))
                            except json.JSONDecodeError as e:
                                logger.error("Failed to parse JSON with pattern %s: %s", pattern, e)
                elif isinstance(content, dict):
                    return content.get("slides", content)
        
        logger.warning("No JSON found in HandoffMessage context")
        return None
    
    logger.warning("Unsupported message type for JSON extraction: %s", type(message))
    return None

# Function to generate Markdown slides
def generate_markdown_slides(slides, title, speaker="Prof. AI Feynman", date="April 26th, 2025"):
    try:
        markdown_slides = []
        for i, slide in enumerate(slides):
            slide_number = i + 1
            content = slide['content']
            
            # First slide has no header/footer, others have header and footer
            if i == 0:
                slide_md = f"""
# {slide['title']}
{content}

**{speaker}**  
*{date}*
"""
            else:
                slide_md = f"""
##### Slide {slide_number}, {slide['title']}
{content}

, {title} {speaker}, {date}
"""
            markdown_slides.append(slide_md.strip())
        
        logger.info(f"Generated Markdown slides for: {title}: {markdown_slides}")
        return markdown_slides
    except Exception as e:
        logger.error(f"Failed to generate Markdown slides: {str(e)}")
        logger.error(traceback.format_exc())
        return None

# Async function to update audio preview
async def update_audio_preview(audio_file):
    if audio_file:
        logger.info("Updating audio preview for file: %s", audio_file)
        return audio_file
    return None

# Async function to generate lecture materials and audio
async def on_generate(api_service, api_key, serpapi_key, title, lecture_content_description, lecture_type, speaker_audio, num_slides):
    model_client = get_model_client(api_service, api_key)
    
    total_slides = num_slides  # Use exactly the number of slides from input
    
    research_agent = AssistantAgent(
        name="research_agent",
        model_client=model_client,
        handoffs=["slide_agent"],
        system_message="You are a Research Agent. Use the search_web tool to gather information on the topic and keywords from the initial message. Summarize the findings concisely in a single message, then use the handoff_to_slide_agent tool to pass the task to the Slide Agent. Do not produce any other output.",
        tools=[search_web]
    )
    slide_agent = AssistantAgent(
        name="slide_agent",
        model_client=model_client,
        handoffs=["script_agent"],
        system_message=f"""
You are a Slide Agent. Using the research from the conversation history and the specified number of slides ({total_slides}), generate exactly {total_slides} content slides. Output ONLY a JSON array wrapped in ```json ... ``` in a TextMessage, where each slide is an object with 'title' and 'content' keys. Do not include any explanatory text, comments, or other messages. Ensure the JSON is valid and contains exactly {total_slides} slides before proceeding. After outputting the JSON, use the handoff_to_script_agent tool to pass the task to the Script Agent.
Example output for 2 slides:
```json
[
    {{"title": "Slide 1", "content": "Content for slide 1"}},
    {{"title": "Slide 2", "content": "Content for slide 2"}}
]
```""",
        output_content_type=None,
        reflect_on_tool_use=False
    )
    script_agent = AssistantAgent(
        name="script_agent",
        model_client=model_client,
        handoffs=["feynman_agent"],
        system_message=f"""
You are a Script Agent. Access the JSON array of {total_slides} slides from the conversation history. Generate a narration script (1-2 sentences) for each of the {total_slides} slides, summarizing its content in a clear, academically inclined tone as a professor would deliver it. Avoid using non-verbal fillers such as "um," "you know," or "like." Output ONLY a JSON array wrapped in ```json ... ``` with exactly {total_slides} strings, one script per slide, in the same order. Ensure the JSON is valid and complete. After outputting, use the handoff_to_feynman_agent tool. If scripts cannot be generated, retry once.
Example for 3 slides:
```json
[
    "Hello everyone, welcome to Agents 101. I am Jaward, your primary instructor for this course.",
    "Today, we will cover the syllabus for this semester, providing a gentle introduction to AI agents.",
    "Let us define what an AI agent is: it refers to a system or program capable of autonomously performing tasks on behalf of a user or another system."
]
```""",
        output_content_type=None,
        reflect_on_tool_use=False
    )
    feynman_agent = AssistantAgent(
        name="feynman_agent",
        model_client=model_client,
        handoffs=[],
        system_message=f"""
You are Agent Feynman. Review the slides and scripts from the conversation history to ensure coherence, completeness, and that exactly {total_slides} slides and {total_slides} scripts are received. Output a confirmation message summarizing the number of slides and scripts received. If slides or scripts are missing, invalid, or do not match the expected count ({total_slides}), report the issue clearly. Use 'TERMINATE' to signal completion.
Example: 'Received {total_slides} slides and {total_slides} scripts. Lecture is coherent. TERMINATE'
""")
    
    swarm = Swarm(
        participants=[research_agent, slide_agent, script_agent, feynman_agent],
        termination_condition=HandoffTermination(target="user") | TextMentionTermination("TERMINATE")
    )
    
    progress = 0
    label = "Research: in progress..."
    yield (
        html_with_progress(label, progress),
        []
    )
    await asyncio.sleep(0.1)
    
    initial_message = f"""
    Lecture Title: {title}
    Lecture Content Description: {lecture_content_description}
    Audience: {lecture_type}
    Number of Slides: {total_slides}
    Please start by researching the topic, or proceed without research if search is unavailable.
    """
    logger.info("Starting lecture generation for title: %s with %d slides", title, total_slides)
    
    slides = None
    scripts = None
    error_html = """
    <div style="display: flex; flex-direction: column; justify-content: center; align-items: center; height: 100%; min-height: 700px; padding: 20px; text-align: center; border: 1px solid #ddd; border-radius: 8px;">
        <h2 style="color: #d9534f;">Failed to generate lecture materials</h2>
        <p style="margin-top: 20px;">Please try again with different parameters or a different model.</p>
    </div>
    """
    
    try:
        logger.info("Research Agent starting...")
        if serpapi_key:
            task_result = await Console(swarm.run_stream(task=initial_message))
        else:
            logger.warning("No SerpApi key provided, bypassing research phase")
            task_result = await Console(swarm.run_stream(task=f"{initial_message}\nNo search available, proceed with slide generation."))
        logger.info("Swarm execution completed")
        
        slide_retry_count = 0
        script_retry_count = 0
        max_retries = 2
        
        for message in task_result.messages:
            source = getattr(message, 'source', getattr(message, 'sender', None))
            logger.debug("Processing message from %s, type: %s", source, type(message))
            
            if isinstance(message, HandoffMessage):
                logger.info("Handoff from %s to %s", source, message.target)
                if source == "research_agent" and message.target == "slide_agent":
                    progress = 25
                    label = "Slides: generating..."
                    yield (
                        html_with_progress(label, progress),
                        []
                    )
                    await asyncio.sleep(0.1)
                elif source == "slide_agent" and message.target == "script_agent":
                    if slides is None:
                        logger.warning("Slide Agent handoff without slides JSON")
                        extracted_json = extract_json_from_message(message)
                        if extracted_json:
                            slides = extracted_json
                            logger.info("Extracted slides JSON from HandoffMessage context: %s", slides)
                    if slides is None or len(slides) != total_slides:
                        if slide_retry_count < max_retries:
                            slide_retry_count += 1
                            logger.info("Retrying slide generation (attempt %d/%d)", slide_retry_count, max_retries)
                            retry_message = TextMessage(
                                content=f"Please generate exactly {total_slides} slides as per your instructions.",
                                source="user",
                                recipient="slide_agent"
                            )
                            task_result.messages.append(retry_message)
                            continue
                    progress = 50
                    label = "Scripts: generating..."
                    yield (
                        html_with_progress(label, progress),
                        []
                    )
                    await asyncio.sleep(0.1)
                elif source == "script_agent" and message.target == "feynman_agent":
                    if scripts is None:
                        logger.warning("Script Agent handoff without scripts JSON")
                        extracted_json = extract_json_from_message(message)
                        if extracted_json:
                            scripts = extracted_json
                            logger.info("Extracted scripts JSON from HandoffMessage context: %s", scripts)
                    progress = 75
                    label = "Review: in progress..."
                    yield (
                        html_with_progress(label, progress),
                        []
                    )
                    await asyncio.sleep(0.1)
            
            elif source == "research_agent" and isinstance(message, TextMessage) and "handoff_to_slide_agent" in message.content:
                logger.info("Research Agent completed research")
                progress = 25
                label = "Slides: generating..."
                yield (
                    html_with_progress(label, progress),
                    []
                )
                await asyncio.sleep(0.1)
            
            elif source == "slide_agent" and isinstance(message, (TextMessage, StructuredMessage)):
                logger.debug("Slide Agent message received")
                extracted_json = extract_json_from_message(message)
                if extracted_json:
                    slides = extracted_json
                    logger.info("Slide Agent generated %d slides: %s", len(slides), slides)
                    if len(slides) != total_slides:
                        if slide_retry_count < max_retries:
                            slide_retry_count += 1
                            logger.info("Retrying slide generation (attempt %d/%d)", slide_retry_count, max_retries)
                            retry_message = TextMessage(
                                content=f"Please generate exactly {total_slides} slides as per your instructions.",
                                source="user",
                                recipient="slide_agent"
                            )
                            task_result.messages.append(retry_message)
                            continue
                    for i, slide in enumerate(slides):
                        content_file = os.path.join(OUTPUT_DIR, f"slide_{i+1}_content.txt")
                        try:
                            with open(content_file, "w", encoding="utf-8") as f:
                                f.write(slide["content"])
                            logger.info("Saved slide content to %s", content_file)
                        except Exception as e:
                            logger.error("Error saving slide content to %s: %s", content_file, str(e))
                    progress = 50
                    label = "Scripts: generating..."
                    yield (
                        html_with_progress(label, progress),
                        []
                    )
                    await asyncio.sleep(0.1)
                else:
                    logger.warning("No JSON extracted from slide_agent message")
                    if slide_retry_count < max_retries:
                        slide_retry_count += 1
                        logger.info("Retrying slide generation (attempt %d/%d)", slide_retry_count, max_retries)
                        retry_message = TextMessage(
                            content=f"Please generate exactly {total_slides} slides as per your instructions.",
                            source="user",
                            recipient="slide_agent"
                        )
                        task_result.messages.append(retry_message)
                        continue
            
            elif source == "script_agent" and isinstance(message, (TextMessage, StructuredMessage)):
                logger.debug("Script Agent message received")
                extracted_json = extract_json_from_message(message)
                if extracted_json:
                    scripts = extracted_json
                    logger.info("Script Agent generated scripts for %d slides: %s", len(scripts), scripts)
                    for i, script in enumerate(scripts):
                        script_file = os.path.join(OUTPUT_DIR, f"slide_{i+1}_script.txt")
                        try:
                            with open(script_file, "w", encoding="utf-8") as f:
                                f.write(script)
                            logger.info("Saved script to %s", script_file)
                        except Exception as e:
                            logger.error("Error saving script to %s: %s", script_file, str(e))
                    progress = 75
                    label = "Scripts generated and saved. Reviewing..."
                    yield (
                        html_with_progress(label, progress),
                        []
                    )
                    await asyncio.sleep(0.1)
                else:
                    logger.warning("No JSON extracted from script_agent message")
                    if script_retry_count < max_retries:
                        script_retry_count += 1
                        logger.info("Retrying script generation (attempt %d/%d)", script_retry_count, max_retries)
                        retry_message = TextMessage(
                            content=f"Please generate exactly {total_slides} scripts for the {total_slides} slides as per your instructions.",
                            source="user",
                            recipient="script_agent"
                        )
                        task_result.messages.append(retry_message)
                        continue
            
            elif source == "feynman_agent" and isinstance(message, TextMessage) and "TERMINATE" in message.content:
                logger.info("Feynman Agent completed lecture review: %s", message.content)
                progress = 90
                label = "Lecture materials ready. Generating audio..."
                yield (
                    html_with_progress(label, progress),
                    []
                )
                await asyncio.sleep(0.1)
        
        logger.info("Slides state: %s", "Generated" if slides else "None")
        logger.info("Scripts state: %s", "Generated" if scripts else "None")
        if not slides or not scripts:
            error_message = f"Failed to generate {'slides and scripts' if not slides and not scripts else 'slides' if not slides else 'scripts'}"
            error_message += f". Received {len(slides) if slides else 0} slides and {len(scripts) if scripts else 0} scripts."
            logger.error("%s", error_message)
            logger.debug("Dumping all messages for debugging:")
            for msg in task_result.messages:
                source = getattr(msg, 'source', getattr(msg, 'sender', None))
                logger.debug("Message from %s, type: %s, content: %s", source, type(msg), msg.to_text() if hasattr(msg, 'to_text') else str(msg))
            yield (
                f"""
                <div style="display: flex; flex-direction: column; justify-content: center; align-items: center; height: 100%; min-height: 700px; padding: 20px; text-align: center; border: 1px solid #ddd; border-radius: 8px;">
                    <h2 style="color: #d9534f;">{error_message}</h2>
                    <p style="margin-top: 20px;">Please try again with a different model or adjust your inputs.</p>
                </div>
                """,
                []
            )
            return
        
        if len(slides) != total_slides:
            logger.error("Expected %d slides, but received %d", total_slides, len(slides))
            yield (
                f"""
                <div style="display: flex; flex-direction: column; justify-content: center; align-items: center; height: 100%; min-height: 700px; padding: 20px; text-align: center; border: 1px solid #ddd; border-radius: 8px;">
                    <h2 style="color: #d9534f;">Incorrect number of slides</h2>
                    <p style="margin-top: 20px;">Expected {total_slides} slides, but generated {len(slides)}. Please try again.</p>
                </div>
                """,
                []
            )
            return
        
        if not isinstance(scripts, list) or not all(isinstance(s, str) for s in scripts):
            logger.error("Scripts are not a list of strings: %s", scripts)
            yield (
                f"""
                <div style="display: flex; flex-direction: column; justify-content: center; align-items: center; height: 100%; min-height: 700px; padding: 20px; text-align: center; border: 1px solid #ddd; border-radius: 8px;">
                    <h2 style="color: #d9534f;">Invalid script format</h2>
                    <p style="margin-top: 20px;">Scripts must be a list of strings. Please try again.</p>
                </div>
                """,
                []
            )
            return
        
        if len(scripts) != total_slides:
            logger.error("Mismatch between number of slides (%d) and scripts (%d)", len(slides), len(scripts))
            yield (
                f"""
                <div style="display: flex; flex-direction: column; justify-content: center; align-items: center; height: 100%; min-height: 700px; padding: 20px; text-align: center; border: 1px solid #ddd; border-radius: 8px;">
                    <h2 style="color: #d9534f;">Mismatch in slides and scripts</h2>
                    <p style="margin-top: 20px;">Generated {len(slides)} slides but {len(scripts)} scripts. Please try again.</p>
                </div>
                """,
                []
            )
            return
        
        markdown_slides = generate_markdown_slides(slides, title)
        if not markdown_slides:
            logger.error("Failed to generate Markdown slides")
            yield (
                f"""
                <div style="display: flex; flex-direction: column; justify-content: center; align-items: center; height: 100%; min-height: 700px; padding: 20px; text-align: center; border: 1px solid #ddd; border-radius: 8px;">
                    <h2 style="color: #d9534f;">Failed to generate slides</h2>
                    <p style="margin-top: 20px;">Please try again.</p>
                </div>
                """,
                []
            )
            return
        
        audio_files = []
        audio_urls = []
        validated_speaker_wav = await validate_and_convert_speaker_audio(speaker_audio)
        if not validated_speaker_wav:
            logger.error("Invalid speaker audio after conversion, skipping TTS")
            yield (
                f"""
                <div style="display: flex; flex-direction: column; justify-content: center; align-items: center; height: 100%; min-height: 700px; padding: 20px; text-align: center; border: 1px solid #ddd; border-radius: 8px;">
                    <h2 style="color: #d9534f;">Invalid speaker audio</h2>
                    <p style="margin-top: 20px;">Please upload a valid MP3 or WAV audio file and try again.</p>
                </div>
                """,
                []
            )
            return
        
        for i, script in enumerate(scripts):
            cleaned_script = clean_script_text(script)
            audio_file = os.path.join(OUTPUT_DIR, f"slide_{i+1}.mp3")
            script_file = os.path.join(OUTPUT_DIR, f"slide_{i+1}_script.txt")
            
            try:
                with open(script_file, "w", encoding="utf-8") as f:
                    f.write(cleaned_script or "")
                logger.info("Saved script to %s: %s", script_file, cleaned_script)
            except Exception as e:
                logger.error("Error saving script to %s: %s", script_file, str(e))
            
            if not cleaned_script:
                logger.error("Skipping audio for slide %d due to empty or invalid script", i + 1)
                audio_files.append(None)
                audio_urls.append(None)
                progress = 90 + ((i + 1) / len(scripts)) * 10
                label = f"Generated audio for slide {i + 1}/{len(scripts)}..."
                yield (
                    html_with_progress(label, progress),
                    []
                )
                await asyncio.sleep(0.1)
                continue
            
            max_audio_retries = 2
            for attempt in range(max_audio_retries + 1):
                try:
                    current_text = cleaned_script
                    if attempt > 0:
                        sentences = re.split(r"[.!?]+", cleaned_script)
                        sentences = [s.strip() for s in sentences if s.strip()][:2]
                        current_text = ". ".join(sentences) + "."
                        logger.info("Retry %d for slide %d with simplified text: %s", attempt, i + 1, current_text)
                    
                    success = generate_xtts_audio(tts, current_text, validated_speaker_wav, audio_file)
                    if not success:
                        raise RuntimeError("TTS generation failed")
                    
                    logger.info("Generated audio for slide %d: %s", i + 1, audio_file)
                    audio_files.append(audio_file)
                    # Use Gradio's file serving URL
                    audio_urls.append(f"/gradio_api/file={audio_file}")
                    progress = 90 + ((i + 1) / len(scripts)) * 10
                    label = f"Generated audio for slide {i + 1}/{len(scripts)}..."
                    yield (
                        html_with_progress(label, progress),
                        []
                    )
                    await asyncio.sleep(0.1)
                    break
                except Exception as e:
                    logger.error("Error generating audio for slide %d (attempt %d): %s\n%s", i + 1, attempt, str(e), traceback.format_exc())
                    if attempt == max_audio_retries:
                        logger.error("Max retries reached for slide %d, skipping", i + 1)
                        audio_files.append(None)
                        audio_urls.append(None)
                        progress = 90 + ((i + 1) / len(scripts)) * 10
                        label = f"Generated audio for slide {i + 1}/{len(scripts)}..."
                        yield (
                            html_with_progress(label, progress),
                            []
                        )
                        await asyncio.sleep(0.1)
                        break
        
        # Collect .txt files for download
        txt_files = [f for f in os.listdir(OUTPUT_DIR) if f.endswith('.txt')]
        txt_files.sort()  # Sort for consistent display
        txt_file_paths = [os.path.join(OUTPUT_DIR, f) for f in txt_files]
        
        # Generate audio timeline with playable audio elements
        audio_timeline = ""
        for i, audio_url in enumerate(audio_urls):
            if audio_url:
                audio_timeline += f'<audio id="audio-{i+1}" controls src="{audio_url}" style="display: inline-block; margin: 0 10px; width: 200px;"></audio>'
            else:
                audio_timeline += f'<span id="audio-{i+1}" style="display: inline-block; margin: 0 10px;">slide_{i+1}.mp3 (not generated)</span>'
        
        slides_info = json.dumps({"slides": markdown_slides, "audioFiles": audio_urls})
        
        html_output = f"""
        <script src="https://cdn.jsdelivr.net/npm/[email protected]/marked.min.js"></script>
        <div id="lecture-container" style="height: 700px; border: 1px solid #ddd; border-radius: 8px; display: flex; flex-direction: column; justify-content: space-between;">
            <div id="slide-content" style="flex: 1; overflow: auto; padding: 20px; text-align: center; background-color: #fff; color: #333;">
                <!-- Slides will be rendered here -->
            </div>
            <div style="padding: 20px; text-align: center;">
                <div style="display: flex; justify-content: center; margin-bottom: 10px;">
                    {audio_timeline}
                </div>
                <div style="display: flex; justify-content: center; margin-bottom: 10px;">
                    <button id="prev-btn" style="border-radius: 50%; width: 40px; height: 40px; margin: 0 5px; font-size: 1.2em; cursor: pointer;">⏮</button>
                    <button id="play-btn" style="border-radius: 50%; width: 40px; height: 40px; margin: 0 5px; font-size: 1.2em; cursor: pointer;">⏯</button>
                    <button id="next-btn" style="border-radius: 50%; width: 40px; height: 40px; margin: 0 5px; font-size: 1.2em; cursor: pointer;">⏭</button>
                    <button style="border-radius: 50%; width: 40px; height: 40px; margin: 0 5px; font-size: 1.2em; cursor: pointer;">☐</button>
                </div>
            </div>
        </div>
        <script>
            const lectureData = {slides_info};
            let currentSlide = 0;
            const totalSlides = lectureData.slides.length;
            let audioElements = [];

            // Populate audio elements
            for (let i = 0; i < totalSlides; i++) {{
                const audio = document.getElementById(`audio-${{i+1}}`);
                audioElements.push(audio);
            }}

            function renderSlide() {{
                const slideContent = document.getElementById('slide-content');
                if (lectureData.slides[currentSlide]) {{
                    const markdownText = lectureData.slides[currentSlide];
                    const htmlContent = marked.parse(markdownText);
                    slideContent.innerHTML = htmlContent;
                    console.log("Rendering slide:", markdownText);
                    console.log("Rendered HTML:", htmlContent);
                }} else {{
                    slideContent.innerHTML = '<h2>No slide content available</h2>';
                    console.log("No slide content for index:", currentSlide);
                }}
            }}

            function updateSlide() {{
                renderSlide();
                audioElements.forEach(audio => {{
                    if (audio && audio.pause) {{
                        audio.pause();
                        audio.currentTime = 0;
                    }}
                }});
            }}

            function prevSlide() {{
                if (currentSlide > 0) {{
                    currentSlide--;
                    updateSlide();
                }}
            }}

            function nextSlide() {{
                if (currentSlide < totalSlides - 1) {{
                    currentSlide++;
                    updateSlide();
                }}
            }}

            function playAll() {{
                let index = 0;
                function playNext() {{
                    if (index >= totalSlides) return;
                    const audio = audioElements[index];
                    if (audio && audio.play) {{
                        audio.play().then(() => {{
                            audio.addEventListener('ended', () => {{
                                index++;
                                playNext();
                            }}, {{ once: true }});
                        }}).catch(e => {{
                            console.error('Audio play failed:', e);
                            index++;
                            playNext();
                        }});
                    }} else {{
                        index++;
                        playNext();
                    }}
                }}
                playNext();
            }}

            // Attach event listeners
            document.getElementById('prev-btn').addEventListener('click', prevSlide);
            document.getElementById('play-btn').addEventListener('click', playAll);
            document.getElementById('next-btn').addEventListener('click', nextSlide);

            // Initialize first slide
            renderSlide();
        </script>
        """
        logger.info("Lecture generation completed successfully")
        yield (
            html_output,
            txt_file_paths
        )
    
    except Exception as e:
        logger.error("Error during lecture generation: %s\n%s", str(e), traceback.format_exc())
        yield (
            f"""
            <div style="display: flex; flex-direction: column; justify-content: center; align-items: center; height: 100%; min-height: 700px; padding: 20px; text-align: center; border: 1px solid #ddd; border-radius: 8px;">
                <h2 style="color: #d9534f;">Error during lecture generation</h2>
                <p style="margin-top: 10px; font-size: 16px;">{str(e)}</p>
                <p style="margin-top: 20px;">Please try again or adjust your inputs.</p>
            </div>
            """,
            []
        )
        return

# Gradio interface
with gr.Blocks(title="Agent Feynman") as demo:
    gr.Markdown("# <center>Learn Anything With Professor AI Feynman</center>")
    with gr.Row():
        with gr.Column(scale=1):
            with gr.Group():
                title = gr.Textbox(label="Lecture Title", placeholder="e.g. Introduction to AI")
                lecture_content_description = gr.Textbox(label="Lecture Content Description", placeholder="e.g. Focus on recent advancements")
                lecture_type = gr.Dropdown(["Conference", "University", "High school"], label="Audience", value="University")
                api_service = gr.Dropdown(
                    choices=[
                        "OpenAI-gpt-4o-2024-08-06",
                        "Anthropic-claude-3-sonnet-20240229",
                        "Google-gemini-1.5-flash",
                        "Ollama-llama3.2"
                    ],
                    label="Model",
                    value="Google-gemini-1.5-flash"
                )
                api_key = gr.Textbox(label="Model Provider API Key", type="password", placeholder="Not required for Ollama")
                serpapi_key = gr.Textbox(label="SerpApi Key", type="password", placeholder="Enter your SerpApi key (optional)")
                num_slides = gr.Slider(1, 20, step=1, label="Number of Slides", value=3)
                speaker_audio = gr.Audio(label="Speaker sample audio (MP3 or WAV)", type="filepath", elem_id="speaker-audio")
                generate_btn = gr.Button("Generate Lecture")
        with gr.Column(scale=2):
            default_slide_html = """
            <div style="display: flex; flex-direction: column; justify-content: center; align-items: center; height: 100%; min-height: 700px; padding: 20px; text-align: center; border: 1px solid #ddd; border-radius: 8px;">
                <h2 style="font-style: italic; color: #555;">Waiting for lecture content...</h2>
                <p style="margin-top: 10px; font-size: 16px;">Please Generate lecture content via the form on the left first before lecture begins</p>
            </div>
            """
            slide_display = gr.HTML(label="Lecture Slides", value=default_slide_html)
            file_output = gr.File(label="Download Generated Files")
    
    speaker_audio.change(
        fn=update_audio_preview,
        inputs=speaker_audio,
        outputs=speaker_audio
    )
    
    generate_btn.click(
        fn=on_generate,
        inputs=[api_service, api_key, serpapi_key, title, lecture_content_description, lecture_type, speaker_audio, num_slides],
        outputs=[slide_display, file_output]
    )

if __name__ == "__main__":
    demo.launch(allowed_paths=[OUTPUT_DIR], max_file_size="5mb")