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| # app.py | |
| import streamlit as st | |
| import time | |
| import re | |
| import os | |
| import tempfile | |
| import pypdf | |
| from pydub import AudioSegment, effects | |
| import difflib | |
| from utils import ( | |
| generate_script, | |
| generate_audio_mp3, | |
| truncate_text, | |
| extract_text_from_url, | |
| transcribe_youtube_video, | |
| research_topic, | |
| mix_with_bg_music, | |
| DialogueItem | |
| ) | |
| from prompts import SYSTEM_PROMPT | |
| # NEW: For Q&A | |
| from qa import transcribe_audio_deepgram, handle_qa_exchange | |
| MAX_QA_QUESTIONS = 5 # up to 5 voice/text questions | |
| def parse_user_edited_transcript(edited_text: str, host_name: str, guest_name: str): | |
| pattern = r"\*\*(.+?)\*\*:\s*(.+)" | |
| matches = re.findall(pattern, edited_text) | |
| items = [] | |
| if not matches: | |
| raw_name = host_name or "Jane" | |
| text_line = edited_text.strip() | |
| speaker = "Jane" | |
| if raw_name.lower() == guest_name.lower(): | |
| speaker = "John" | |
| item = DialogueItem( | |
| speaker=speaker, | |
| display_speaker=raw_name, | |
| text=text_line | |
| ) | |
| items.append(item) | |
| return items | |
| for (raw_name, text_line) in matches: | |
| if raw_name.lower() == host_name.lower(): | |
| speaker = "Jane" | |
| elif raw_name.lower() == guest_name.lower(): | |
| speaker = "John" | |
| else: | |
| speaker = "Jane" | |
| item = DialogueItem( | |
| speaker=speaker, | |
| display_speaker=raw_name, | |
| text=text_line | |
| ) | |
| items.append(item) | |
| return items | |
| def regenerate_audio_from_dialogue(dialogue_items, custom_bg_music_path=None): | |
| audio_segments = [] | |
| transcript = "" | |
| crossfade_duration = 50 # ms | |
| for item in dialogue_items: | |
| audio_file = generate_audio_mp3(item.text, item.speaker) | |
| seg = AudioSegment.from_file(audio_file, format="mp3") | |
| audio_segments.append(seg) | |
| transcript += f"**{item.display_speaker}**: {item.text}\n\n" | |
| os.remove(audio_file) | |
| if not audio_segments: | |
| return None, "No audio segments were generated." | |
| combined_spoken = audio_segments[0] | |
| for seg in audio_segments[1:]: | |
| combined_spoken = combined_spoken.append(seg, crossfade=crossfade_duration) | |
| final_mix = mix_with_bg_music(combined_spoken, custom_bg_music_path) | |
| with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as temp_audio: | |
| final_mix.export(temp_audio.name, format="mp3") | |
| final_mp3_path = temp_audio.name | |
| with open(final_mp3_path, "rb") as f: | |
| audio_bytes = f.read() | |
| os.remove(final_mp3_path) | |
| return audio_bytes, transcript | |
| def generate_podcast( | |
| file, | |
| url, | |
| video_url, | |
| research_topic_input, | |
| tone, | |
| length_minutes, | |
| host_name, | |
| host_desc, | |
| guest_name, | |
| guest_desc, | |
| user_specs, | |
| sponsor_content, | |
| sponsor_style, | |
| custom_bg_music_path | |
| ): | |
| sources = [bool(file), bool(url), bool(video_url), bool(research_topic_input)] | |
| if sum(sources) > 1: | |
| return None, "Provide only one input (PDF, URL, YouTube, or Topic)." | |
| if not any(sources): | |
| return None, "Please provide at least one source." | |
| text = "" | |
| if file: | |
| try: | |
| if not file.name.lower().endswith('.pdf'): | |
| return None, "Please upload a PDF file." | |
| reader = pypdf.PdfReader(file) | |
| text = " ".join(page.extract_text() for page in reader.pages if page.extract_text()) | |
| except Exception as e: | |
| return None, f"Error reading PDF: {str(e)}" | |
| elif url: | |
| try: | |
| text = extract_text_from_url(url) | |
| if not text: | |
| return None, "Failed to extract text from URL." | |
| except Exception as e: | |
| return None, f"Error extracting text from URL: {str(e)}" | |
| elif video_url: | |
| try: | |
| text = transcribe_youtube_video(video_url) | |
| if not text: | |
| return None, "Failed to transcribe YouTube video." | |
| except Exception as e: | |
| return None, f"Error transcribing YouTube video: {str(e)}" | |
| elif research_topic_input: | |
| try: | |
| text = research_topic(research_topic_input) | |
| if not text: | |
| return None, f"Sorry, no information found on '{research_topic_input}'." | |
| except Exception as e: | |
| return None, f"Error researching topic: {str(e)}" | |
| from utils import truncate_text | |
| text = truncate_text(text) | |
| extra_instructions = [] | |
| if host_name or guest_name: | |
| host_line = f"Host: {host_name or 'Jane'} - {host_desc or 'a curious host'}." | |
| guest_line = f"Guest: {guest_name or 'John'} - {guest_desc or 'an expert'}." | |
| extra_instructions.append(f"{host_line}\n{guest_line}") | |
| if user_specs.strip(): | |
| extra_instructions.append(f"Additional User Instructions: {user_specs}") | |
| if sponsor_content.strip(): | |
| extra_instructions.append( | |
| f"Sponsor Content Provided (should be under ~30 seconds):\n{sponsor_content}" | |
| ) | |
| from prompts import SYSTEM_PROMPT | |
| combined_instructions = "\n\n".join(extra_instructions).strip() | |
| full_prompt = SYSTEM_PROMPT | |
| if combined_instructions: | |
| full_prompt += f"\n\n# Additional Instructions\n{combined_instructions}\n" | |
| from utils import generate_script, generate_audio_mp3, mix_with_bg_music | |
| try: | |
| script = generate_script( | |
| full_prompt, | |
| text, | |
| tone, | |
| f"{length_minutes} Mins", | |
| host_name=host_name or "Jane", | |
| guest_name=guest_name or "John", | |
| sponsor_style=sponsor_style, | |
| sponsor_provided=bool(sponsor_content.strip()) | |
| ) | |
| except Exception as e: | |
| return None, f"Error generating script: {str(e)}" | |
| audio_segments = [] | |
| transcript = "" | |
| crossfade_duration = 50 | |
| try: | |
| for item in script.dialogue: | |
| audio_file = generate_audio_mp3(item.text, item.speaker) | |
| seg = AudioSegment.from_file(audio_file, format="mp3") | |
| audio_segments.append(seg) | |
| transcript += f"**{item.display_speaker}**: {item.text}\n\n" | |
| os.remove(audio_file) | |
| if not audio_segments: | |
| return None, "No audio segments generated." | |
| combined_spoken = audio_segments[0] | |
| for seg in audio_segments[1:]: | |
| combined_spoken = combined_spoken.append(seg, crossfade=crossfade_duration) | |
| final_mix = mix_with_bg_music(combined_spoken, custom_bg_music_path) | |
| with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as temp_audio: | |
| final_mix.export(temp_audio.name, format="mp3") | |
| final_mp3_path = temp_audio.name | |
| with open(final_mp3_path, "rb") as f: | |
| audio_bytes = f.read() | |
| os.remove(final_mp3_path) | |
| return audio_bytes, transcript | |
| except Exception as e: | |
| return None, f"Error generating audio: {str(e)}" | |
| def highlight_differences(original: str, edited: str) -> str: | |
| matcher = difflib.SequenceMatcher(None, original.split(), edited.split()) | |
| highlighted = [] | |
| for opcode, i1, i2, j1, j2 in matcher.get_opcodes(): | |
| if opcode == 'equal': | |
| highlighted.extend(original.split()[i1:i2]) | |
| elif opcode in ('replace', 'insert'): | |
| added_words = edited.split()[j1:j2] | |
| highlighted.extend([f'<span style="color:red">{word}</span>' for word in added_words]) | |
| elif opcode == 'delete': | |
| pass | |
| return ' '.join(highlighted) | |
| def main(): | |
| st.set_page_config( | |
| page_title="MyPod v2: AI-Powered Podcast Magic", | |
| layout="centered" | |
| ) | |
| # Inject custom CSS for styling adjustments | |
| st.markdown(""" | |
| <style> | |
| /* Shrink file uploader button */ | |
| .stFileUploader>div>div>div { | |
| transform: scale(0.9); | |
| } | |
| /* Remove any custom radio button styling to revert to original layout */ | |
| /* Footer styling */ | |
| footer { | |
| text-align: center; | |
| padding: 1em 0; | |
| font-size: 0.8em; | |
| color: #888; | |
| } | |
| </style> | |
| """, unsafe_allow_html=True) | |
| logo_col, title_col = st.columns([1, 10]) | |
| with logo_col: | |
| st.image("logomypod.jpg", width=70) # Increased size by ~15% | |
| with title_col: | |
| st.markdown("## MyPod v2: AI-Powered Podcast Magic") | |
| # Reinstated welcome section | |
| st.markdown(""" | |
| Welcome to **MyPod**, your go-to AI-powered podcast generator! 🎉 | |
| MyPod transforms your documents, webpages, YouTube videos, or research topics into a more human-sounding, conversational podcast. | |
| Select a tone and a duration range. The output script will be on-topic, concise, and respect your chosen length. | |
| """) | |
| # "How to Use" as an expander with enumerated list and larger text | |
| with st.expander("How to Use"): | |
| st.markdown(""" | |
| <ol style="font-size:18px;"> | |
| <li>Provide one source: PDF Files, Website URL, YouTube videos, or a Topic to Research.</li> | |
| <li>Choose the tone and the target duration.</li> | |
| <li>Add custom names and descriptions for the speakers if you wish.</li> | |
| <li>Add sponsored content as a separate break or blended into the script.</li> | |
| <li>Click 'Generate Podcast' to produce your podcast.</li> | |
| <li>Post generation you can edit the transcript and re-generate the audio with your edits if needed.</li> | |
| <li>Ask Follow-up Questions via text or voice and get immediate answers.</li> | |
| </ol> | |
| """, unsafe_allow_html=True) | |
| # Retained text below "How to Use" | |
| st.markdown(""" | |
| **Research a Topic:** If it's too niche or specific, you might not get the desired outcome. | |
| **Token Limit:** Up to ~2,048 tokens are supported. Long inputs may be truncated. | |
| **Note:** YouTube videos will only work if they have captions built in. | |
| ⏳**Please be patient while your podcast is being generated.** This process involves content analysis, script creation, and high-quality audio synthesis, which may take a few minutes. | |
| 🔥 **Ready to create your personalized podcast?** Give it a try now and let the magic happen! 🔥 | |
| """) | |
| # Original placement of input options | |
| col1, col2 = st.columns(2) | |
| with col1: | |
| file = st.file_uploader("Upload File (.pdf only)", type=["pdf"]) | |
| url = st.text_input("Or Enter Website URL") | |
| video_url = st.text_input("Or Enter YouTube Link (Captioned videos)") | |
| with col2: | |
| research_topic_input = st.text_input("Or Research a Topic") | |
| tone = st.radio("Tone", ["Casual", "Formal", "Humorous", "Youthful"], index=0) | |
| length_minutes = st.slider("Podcast Length (in minutes)", 1, 60, 3) | |
| st.markdown("### Customize Your Podcast (New Features)") | |
| with st.expander("Set Host & Guest Names/Descriptions (Optional)"): | |
| host_name = st.text_input("Female Host Name (leave blank for 'Jane')") | |
| host_desc = st.text_input("Female Host Description (Optional)") | |
| guest_name = st.text_input("Male Guest Name (leave blank for 'John')") | |
| guest_desc = st.text_input("Male Guest Description (Optional)") | |
| user_specs = st.text_area("Any special instructions or prompts for the script? (Optional)", "") | |
| sponsor_content = st.text_area("Sponsored Content / Ad (Optional)", "") | |
| # Removed bold heading for Sponsor Integration Style | |
| sponsor_style = st.selectbox( | |
| "Sponsor Integration Style", | |
| ["Separate Break", "Blended"] | |
| ) | |
| custom_bg_music_file = st.file_uploader("Upload Custom Background Music (Optional)", type=["mp3", "wav"]) | |
| custom_bg_music_path = None | |
| if custom_bg_music_file: | |
| with tempfile.NamedTemporaryFile(delete=False, suffix=os.path.splitext(custom_bg_music_file.name)[1]) as tmp: | |
| tmp.write(custom_bg_music_file.read()) | |
| custom_bg_music_path = tmp.name | |
| if "audio_bytes" not in st.session_state: | |
| st.session_state["audio_bytes"] = None | |
| if "transcript" not in st.session_state: | |
| st.session_state["transcript"] = None | |
| if "transcript_original" not in st.session_state: | |
| st.session_state["transcript_original"] = None | |
| # For Q&A | |
| if "qa_count" not in st.session_state: | |
| st.session_state["qa_count"] = 0 | |
| if "conversation_history" not in st.session_state: | |
| st.session_state["conversation_history"] = "" | |
| generate_button = st.button("Generate Podcast") | |
| if generate_button: | |
| progress_bar = st.progress(0) | |
| progress_text = st.empty() | |
| progress_messages = [ | |
| "🔍 Analyzing your input...", | |
| "📝 Crafting the perfect script...", | |
| "🎙️ Generating high-quality audio...", | |
| "🎶 Adding the finishing touches..." | |
| ] | |
| progress_text.write(progress_messages[0]) | |
| progress_bar.progress(0) | |
| time.sleep(1.0) | |
| progress_text.write(progress_messages[1]) | |
| progress_bar.progress(25) | |
| time.sleep(1.0) | |
| progress_text.write(progress_messages[2]) | |
| progress_bar.progress(50) | |
| time.sleep(1.0) | |
| progress_text.write(progress_messages[3]) | |
| progress_bar.progress(75) | |
| time.sleep(1.0) | |
| audio_bytes, transcript = generate_podcast( | |
| file, | |
| url, | |
| video_url, | |
| research_topic_input, | |
| tone, | |
| length_minutes, | |
| host_name, | |
| host_desc, | |
| guest_name, | |
| guest_desc, | |
| user_specs, | |
| sponsor_content, | |
| sponsor_style, | |
| custom_bg_music_path | |
| ) | |
| progress_bar.progress(100) | |
| progress_text.write("✅ Done!") | |
| if audio_bytes is None: | |
| st.error(transcript) | |
| st.session_state["audio_bytes"] = None | |
| st.session_state["transcript"] = None | |
| st.session_state["transcript_original"] = None | |
| else: | |
| st.success("Podcast generated successfully!") | |
| st.session_state["audio_bytes"] = audio_bytes | |
| st.session_state["transcript"] = transcript | |
| st.session_state["transcript_original"] = transcript | |
| # Reset Q&A | |
| st.session_state["qa_count"] = 0 | |
| st.session_state["conversation_history"] = "" | |
| if st.session_state["audio_bytes"]: | |
| st.audio(st.session_state["audio_bytes"], format='audio/mp3') | |
| st.download_button( | |
| label="Download Podcast (MP3)", | |
| data=st.session_state["audio_bytes"], | |
| file_name="my_podcast.mp3", | |
| mime="audio/mpeg" | |
| ) | |
| st.markdown("### Generated Transcript (Editable)") | |
| edited_text = st.text_area( | |
| "Feel free to tweak lines, fix errors, or reword anything.", | |
| value=st.session_state["transcript"], | |
| height=300 | |
| ) | |
| if st.session_state["transcript_original"]: | |
| highlighted_transcript = highlight_differences( | |
| st.session_state["transcript_original"], | |
| edited_text | |
| ) | |
| st.markdown("### **Edited Transcript Highlights**", unsafe_allow_html=True) | |
| st.markdown(highlighted_transcript, unsafe_allow_html=True) | |
| if st.button("Regenerate Audio From Edited Text"): | |
| regen_bar = st.progress(0) | |
| regen_text = st.empty() | |
| regen_text.write("🔄 Regenerating your podcast with the edits...") | |
| regen_bar.progress(25) | |
| time.sleep(1.0) | |
| regen_text.write("🔧 Adjusting the script based on your changes...") | |
| regen_bar.progress(50) | |
| time.sleep(1.0) | |
| dialogue_items = parse_user_edited_transcript( | |
| edited_text, | |
| host_name or "Jane", | |
| guest_name or "John" | |
| ) | |
| new_audio_bytes, new_transcript = regenerate_audio_from_dialogue(dialogue_items, custom_bg_music_path) | |
| regen_bar.progress(75) | |
| time.sleep(1.0) | |
| if new_audio_bytes is None: | |
| regen_bar.progress(100) | |
| st.error(new_transcript) | |
| else: | |
| regen_bar.progress(100) | |
| regen_text.write("✅ Regeneration complete!") | |
| st.success("Regenerated audio below:") | |
| st.session_state["audio_bytes"] = new_audio_bytes | |
| st.session_state["transcript"] = new_transcript | |
| st.session_state["transcript_original"] = new_transcript | |
| st.audio(new_audio_bytes, format='audio/mp3') | |
| st.download_button( | |
| label="Download Edited Podcast (MP3)", | |
| data=new_audio_bytes, | |
| file_name="my_podcast_edited.mp3", | |
| mime="audio/mpeg" | |
| ) | |
| st.markdown("### Updated Transcript") | |
| st.markdown(new_transcript) | |
| # ----------------------- | |
| # POST-PODCAST Q&A Logic | |
| # ----------------------- | |
| st.markdown("## Post-Podcast Q&A") | |
| used_questions = st.session_state["qa_count"] | |
| remaining = MAX_QA_QUESTIONS - used_questions | |
| if remaining > 0: | |
| st.write(f"You can ask up to {remaining} more question(s).") | |
| typed_q = st.text_input("Type your follow-up question:") | |
| audio_q = st.audio_input("Or record an audio question (WAV)") | |
| if st.button("Submit Q&A"): | |
| if used_questions >= MAX_QA_QUESTIONS: | |
| st.warning("You have reached the Q&A limit.") | |
| else: | |
| question_text = typed_q.strip() | |
| if audio_q is not None: | |
| suffix = ".wav" | |
| with tempfile.NamedTemporaryFile(delete=False, suffix=suffix) as tmp: | |
| tmp.write(audio_q.read()) | |
| local_audio_path = tmp.name | |
| st.write("Transcribing your audio question...") | |
| audio_transcript = transcribe_audio_deepgram(local_audio_path) | |
| if audio_transcript: | |
| question_text = audio_transcript | |
| if not question_text: | |
| st.warning("No question found (text or audio).") | |
| else: | |
| st.write("Generating an answer...") | |
| ans_audio, ans_text = handle_qa_exchange(question_text) | |
| if ans_audio: | |
| st.audio(ans_audio, format="audio/mp3") | |
| st.markdown(f"**John**: {ans_text}") | |
| st.session_state["qa_count"] += 1 | |
| else: | |
| st.warning("No response could be generated.") | |
| else: | |
| st.write("You have used all 5 Q&A opportunities.") | |
| # Footer with updated text | |
| st.markdown("<footer>©2025 MyPod. All rights reserved.</footer>", unsafe_allow_html=True) | |
| if __name__ == "__main__": | |
| main() | |