Delete script_generator.py

script_generator.py

@@ -1,212 +0,0 @@
-import os
-import gradio as gr
-import wikipediaapi
-from groq import Groq
-import torch
-from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer
-from deep_translator import GoogleTranslator
-import yake
-from datetime import datetime
-import shutil
-import glob
-
-# ✅ Set API Key
-# os.environ["GROQ_API_KEY"] = "your_api_key_here"
-# client = Groq(api_key=os.environ["GROQ_API_KEY"])
-
-# ✅ Set API Key
-os.environ["GROQ_API_KEY"] = "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"    # Replace with your API key
-client = Groq(api_key=os.environ["GROQ_API_KEY"])
-
-# # ✅ Load M2M-100 Model
-# model_name = "facebook/m2m100_418M"
-# tokenizer = M2M100Tokenizer.from_pretrained(model_name)
-# model = M2M100ForConditionalGeneration.from_pretrained(model_name)
-
-def fetch_wikipedia_summary(topic):
-    wiki_wiki = wikipediaapi.Wikipedia(
-        user_agent="EducationalScriptApp/1.0",
-        language="en"
-    )
-    page = wiki_wiki.page(topic)
-    return page.summary if page.exists() else "No Wikipedia summary available."
-
-def generate_script(topic, duration):
-    try:
-        factual_content = fetch_wikipedia_summary(topic)
-        words_per_minute = 130
-        target_words = duration * words_per_minute
-
-        response = client.chat.completions.create(
-            messages=[{"role": "user", "content": f"Format the following factual content into a well-structured educational script in English with approximately {target_words} words: \n{factual_content}"}],
-            model="llama-3.3-70b-versatile"
-        )
-        return response.choices[0].message.content
-    except Exception as e:
-        return f"❌ Error in script generation: {str(e)}"
-
-
-# ✅ Function to Extract Keywords Using YAKE
-def extract_keywords(script):
-    try:
-        kw_extractor = yake.KeywordExtractor(
-            lan="en",  # Language
-            n=3,  # Max number of words in a keyword phrase (trigrams)
-            dedupLim=0.9,  # Reduce redundant phrases
-            # top=10  # Extract top 10 keywords
-        )
-
-        keywords = kw_extractor.extract_keywords(script)
-        return ", ".join([kw[0] for kw in keywords])  # ✅ Extract only the keyword text
-    except Exception as e:
-        return f"❌ Error extracting keywords: {str(e)}"
-
-
-def save_keywords_file(keywords, topic):
-    today = datetime.today().strftime('%Y_%b_%d')
-    filename = f"Keywords/{topic}_Keyword_{today}.txt"
-    os.makedirs(os.path.dirname(filename), exist_ok=True)
-    with open(filename, "w", encoding="utf-8") as f:
-        f.write(keywords)
-    return filename
-
-
-# # ✅ Function to Translate English Script to Urdu
-# def translate_to_urdu(english_script):
-#     try:
-#         google_translation = GoogleTranslator(source='en', target='ur').translate(english_script)
-#         tokenizer.src_lang = "en"
-#         max_length = 500
-#         input_chunks = [google_translation[i:i+max_length] for i in range(0, len(google_translation), max_length)]
-#         refined_chunks = []
-#         for chunk in input_chunks:
-#             inputs = tokenizer(chunk, return_tensors="pt", truncation=True, max_length=1024).to(model.device)
-#             translated_tokens = model.generate(
-#                 **inputs,
-#                 max_length=1024,
-#                 no_repeat_ngram_size=2,
-#                 forced_bos_token_id=tokenizer.get_lang_id("ur"),
-#                 num_beams=2
-#             )
-#             refined_chunks.append(tokenizer.batch_decode(translated_tokens, skip_special_tokens=True)[0])
-#         return " ".join(refined_chunks)
-#     except Exception as e:
-#         return f"❌ Error in translation: {str(e)}"
-
-
-def translate_to_urdu(english_script):
-    try:
-        # ✅ Define a max chunk size (Google Translator has a limit)
-        max_chunk_size = 4500  # Stay below 5000 to be safe
-        chunks = [english_script[i:i + max_chunk_size] for i in range(0, len(english_script), max_chunk_size)]
-
-        translated_chunks = []
-        for chunk in chunks:
-            translated_chunk = GoogleTranslator(source='en', target='ur').translate(chunk)
-            translated_chunks.append(translated_chunk)
-
-        return " ".join(translated_chunks)  # ✅ Join all translated chunks
-    except Exception as e:
-        return f"❌ Error in translation: {str(e)}"
-
-
-
-def save_english_file(content, topic):
-    today = datetime.today().strftime('%Y_%b_%d')  # Format: 2025_Feb_21
-    filename = f"English_Scripts/{topic}_Eng_{today}.txt"
-    os.makedirs(os.path.dirname(filename), exist_ok=True)  # Ensure directory exists
-    with open(filename, "w", encoding="utf-8") as f:
-        f.write(content)
-    return filename
-
-
-def save_urdu_file(content, topic):
-    today = datetime.today().strftime('%Y_%b_%d')
-    filename = f"Urdu_Scripts/{topic}_Urdu_{today}.txt"
-    os.makedirs(os.path.dirname(filename), exist_ok=True)
-    with open(filename, "w", encoding="utf-8") as f:
-        f.write(content)
-    return filename
-
-
-def save_final_urdu_file(topic, content):
-    date_str = datetime.now().strftime("%Y_%b_%d")
-    filename = f"Urdu_Final/{topic}_Urdu_Final_{date_str}.txt"  # ✅ Corrected file path
-    os.makedirs(os.path.dirname(filename), exist_ok=True)  # ✅ Ensure the directory exists
-    with open(filename, "w", encoding="utf-8") as f:
-        f.write(content)
-    return filename
-
-
-def finalize_process():
-    return "✅ Script Generation Completed Successfully!"
-
-
-def clear_old_files():
-    # ✅ Define all directories where files are stored
-    directories = ["English_Scripts", "Urdu_Scripts", "Urdu_Final", "Keywords"]
-
-    for directory in directories:
-        if os.path.exists(directory):  # ✅ Check if directory exists
-            files = glob.glob(f"{directory}/*")  # ✅ Get all files in the directory
-            for file in files:
-                try:
-                    os.remove(file)  # ✅ Delete each file
-                except Exception as e:
-                    print(f"❌ Error deleting {file}: {e}")
-
-    return "", "", "", "", ""  # ✅ Clear all textboxes in UI
-
-
-
-
-# ✅ Gradio UI
-with gr.Blocks() as app:
-    gr.Markdown("# 🎬 AI-Powered Educational Script Generator")
-
-    topic_input = gr.Textbox(label="Enter Topic")
-    duration_input = gr.Slider(minimum=1, maximum=30, step=1, label="Duration (minutes)")
-
-
-    generate_button = gr.Button("Generate English Script")
-    eng_output = gr.Textbox(label="Generated English Script", interactive=False)
-    download_english_button = gr.Button("Download English Script")
-    download_english_button.click(save_english_file, inputs=[eng_output, topic_input], outputs=[gr.File()])
-
-
-    # ✅ Keyword Extraction Section
-    extract_keywords_btn = gr.Button("🔑 Extract Keywords")
-    keyword_output = gr.Textbox(label="🔍 Extracted Keywords", interactive=True)
-    download_keywords_btn = gr.Button("⬇️ Download Keywords")
-    download_keywords_btn.click(save_keywords_file, inputs=[keyword_output, topic_input], outputs=[gr.File()])
-
-    translate_button = gr.Button("Generate Urdu Script")
-    urdu_output = gr.Textbox(label="Translated Urdu Script", interactive=False, rtl=True)
-    download_urdu_button = gr.Button("Download Urdu Script")
-    download_urdu_button.click(save_urdu_file, inputs=[urdu_output, topic_input], outputs=[gr.File()])
-
-    
-    final_edited_urdu_output = gr.Textbox(label="Edited Urdu Script", interactive=True, rtl=True)
-    download_final_urdu_button = gr.Button("Download Final Urdu Script")
-    download_final_urdu_button.click(save_final_urdu_file, inputs=[topic_input, final_edited_urdu_output], outputs=[gr.File()])
-
-
-    # ✅ Button Actions
-    # generate_button.click(generate_script, inputs=[topic_input, duration_input], outputs=[eng_output])
-    generate_button.click(generate_script, inputs=[topic_input, duration_input],  outputs=[eng_output])
-    extract_keywords_btn.click(extract_keywords, inputs=[eng_output], outputs=[keyword_output])
-    translate_button.click(translate_to_urdu, inputs=[eng_output], outputs=[urdu_output])
-
-    status_output = gr.Textbox(label="Status", interactive=False)
-    finalize_button = gr.Button("Finalize Process")
-    finalize_button.click(finalize_process, outputs=[status_output])
-
-    generate_button.click(
-    lambda topic, duration: (*clear_old_files(), generate_script(topic, duration)),  
-    inputs=[topic_input, duration_input],  
-    outputs=[keyword_output, urdu_output, final_edited_urdu_output, status_output]    )
-
-    
-
-
-app.launch()