Update tts.py

tts.py

@@ -1,128 +1,128 @@
-import os
-import base64
-import json
-import streamlit as st
-from sarvamai import SarvamAI
-from typing import List, Dict, Optional
-
-
-client = None
-try:
-    api_key = os.environ("SARVAM_API_KEY")
-    if api_key:
-        client = SarvamAI(api_subscription_key=api_key)
-        print("✅ Sarvam AI client for TTS (Bulbul) initialized successfully.")
-    else:
-        print("⚠️ Warning: SARVAM_API_KEY not found.")
-except Exception as e:
-    print(f"❌ Error initializing Sarvam AI client: {e}")
-
-# --- Language Mapping ---
-LANGUAGE_CODE_MAP = {
-    "hindi": "hi-IN", "bengali": "bn-IN", "tamil": "ta-IN", "telugu": "te-IN",
-    "gujarati": "gu-IN", "kannada": "kn-IN", "malayalam": "ml-IN", "marathi": "mr-IN",
-    "punjabi": "pa-IN", "odia": "od-IN", "english": "en-IN",
-}
-
-def get_language_code(language_name: str) -> Optional[str]:
-    return LANGUAGE_CODE_MAP.get(language_name.lower())
-
-def generate_audio_from_text(
-    text: str,
-    language_name: str,
-    gender: str,
-    output_file_path: str
-) -> bool:
-    """
-    Generates an audio file from a text string using the Sarvam "Bulbul" TTS API
-    with a specified gender and pace for the voice.
-    """
-    if not client: return False
-    lang_code = get_language_code(language_name)
-    if not lang_code:
-        print(f"❌ Language '{language_name}' is not supported. Skipping.")
-        return False
-
-    if gender.lower() == "male":
-        speaker_name = "abhilash"
-        pace_value = 1.0
-    else:
-        speaker_name = "anushka"
-        pace_value = 0.9
-
-    print(f"--- 🎤 Generating audio for chunk: '{text[:50]}...' in {language_name} (Voice: {speaker_name}, Pace: {pace_value}) ---")
-
-    try:
-        response = client.text_to_speech.convert(
-            text=text,
-            model="bulbul:v2",
-            target_language_code=lang_code,
-            speaker=speaker_name,
-            pace=pace_value, # Use the selected pace
-            speech_sample_rate=22050,
-            enable_preprocessing=True
-        )
-
-        combined_audio_b64 = "".join(response.audios)
-        audio_data = base64.b64decode(combined_audio_b64)
-
-        with open(output_file_path, "wb") as f:
-            f.write(audio_data)
-
-        print(f"✅ Audio saved to {output_file_path}")
-        return True
-
-    except Exception as e:
-        print(f"❌ An error occurred during the Sarvam TTS API call: {e}")
-        return False
-
-def generate_all_audio_from_file(
-    json_path: str,
-    target_language: str,
-    gender: str,
-    output_dir: str = "generated_audio",
-    output_json_path: str = "multimedia_data_final.json"
-) -> List[Dict[str, str]]:
-    """
-    Reads data from a JSON, generates audio with a specific gender, and saves a final JSON.
-    """
-    try:
-        with open(json_path, 'r', encoding='utf-8') as f:
-            multimedia_data = json.load(f)
-    except (FileNotFoundError, json.JSONDecodeError) as e:
-        print(f"❌ Error reading or parsing {json_path}: {e}")
-        return []
-
-    os.makedirs(output_dir, exist_ok=True)
-
-    for i, item in enumerate(multimedia_data):
-        audio_text = item.get("audio_text")
-        if not audio_text:
-            item["audio_path"] = None
-            continue
-
-        file_path = os.path.join(output_dir, f"audio_{i:03d}.mp3")
-        success = generate_audio_from_text(audio_text, target_language, gender, file_path)
-        item["audio_path"] = file_path if success else None
-
-    with open(output_json_path, 'w', encoding='utf-8') as f:
-        json.dump(multimedia_data, f, indent=2, ensure_ascii=False)
-    print(f"\n--- ✅ Audio generation finished. Final data saved to {output_json_path}. ---")
-
-    return multimedia_data
-
-# Example Usage
-# if __name__ == '__main__':
-#     json_input_file = "multimedia_data_with_images.json"
-#     if not os.path.exists(json_input_file):
-#         print(f"❌ Error: Input file '{json_input_file}' not found.")
-#         print("Please run image_generation.py first to generate it.")
-#     else:
-#         target_language_for_story = "English"
-#         target_gender_for_story = "male" # Change to "male" to test the other voice
-
-#         generate_all_audio_from_file(
-#             json_path=json_input_file,
-#             target_language=target_language_for_story,
-#             gender=target_gender_for_story
+import os
+import base64
+import json
+import streamlit as st
+from sarvamai import SarvamAI
+from typing import List, Dict, Optional
+
+
+client = None
+try:
+    api_key = st.secrets.get("SARVAM_API_KEY") or os.getenv("SARVAM_API_KEY")
+    if api_key:
+        client = SarvamAI(api_subscription_key=api_key)
+        print("✅ Sarvam AI client for TTS (Bulbul) initialized successfully.")
+    else:
+        print("⚠️ Warning: SARVAM_API_KEY not found.")
+except Exception as e:
+    print(f"❌ Error initializing Sarvam AI client: {e}")
+
+# --- Language Mapping ---
+LANGUAGE_CODE_MAP = {
+    "hindi": "hi-IN", "bengali": "bn-IN", "tamil": "ta-IN", "telugu": "te-IN",
+    "gujarati": "gu-IN", "kannada": "kn-IN", "malayalam": "ml-IN", "marathi": "mr-IN",
+    "punjabi": "pa-IN", "odia": "od-IN", "english": "en-IN",
+}
+
+def get_language_code(language_name: str) -> Optional[str]:
+    return LANGUAGE_CODE_MAP.get(language_name.lower())
+
+def generate_audio_from_text(
+    text: str,
+    language_name: str,
+    gender: str,
+    output_file_path: str
+) -> bool:
+    """
+    Generates an audio file from a text string using the Sarvam "Bulbul" TTS API
+    with a specified gender and pace for the voice.
+    """
+    if not client: return False
+    lang_code = get_language_code(language_name)
+    if not lang_code:
+        print(f"❌ Language '{language_name}' is not supported. Skipping.")
+        return False
+
+    if gender.lower() == "male":
+        speaker_name = "abhilash"
+        pace_value = 1.0
+    else:
+        speaker_name = "anushka"
+        pace_value = 0.9
+
+    print(f"--- 🎤 Generating audio for chunk: '{text[:50]}...' in {language_name} (Voice: {speaker_name}, Pace: {pace_value}) ---")
+
+    try:
+        response = client.text_to_speech.convert(
+            text=text,
+            model="bulbul:v2",
+            target_language_code=lang_code,
+            speaker=speaker_name,
+            pace=pace_value, # Use the selected pace
+            speech_sample_rate=22050,
+            enable_preprocessing=True
+        )
+
+        combined_audio_b64 = "".join(response.audios)
+        audio_data = base64.b64decode(combined_audio_b64)
+
+        with open(output_file_path, "wb") as f:
+            f.write(audio_data)
+
+        print(f"✅ Audio saved to {output_file_path}")
+        return True
+
+    except Exception as e:
+        print(f"❌ An error occurred during the Sarvam TTS API call: {e}")
+        return False
+
+def generate_all_audio_from_file(
+    json_path: str,
+    target_language: str,
+    gender: str,
+    output_dir: str = "generated_audio",
+    output_json_path: str = "multimedia_data_final.json"
+) -> List[Dict[str, str]]:
+    """
+    Reads data from a JSON, generates audio with a specific gender, and saves a final JSON.
+    """
+    try:
+        with open(json_path, 'r', encoding='utf-8') as f:
+            multimedia_data = json.load(f)
+    except (FileNotFoundError, json.JSONDecodeError) as e:
+        print(f"❌ Error reading or parsing {json_path}: {e}")
+        return []
+
+    os.makedirs(output_dir, exist_ok=True)
+
+    for i, item in enumerate(multimedia_data):
+        audio_text = item.get("audio_text")
+        if not audio_text:
+            item["audio_path"] = None
+            continue
+
+        file_path = os.path.join(output_dir, f"audio_{i:03d}.mp3")
+        success = generate_audio_from_text(audio_text, target_language, gender, file_path)
+        item["audio_path"] = file_path if success else None
+
+    with open(output_json_path, 'w', encoding='utf-8') as f:
+        json.dump(multimedia_data, f, indent=2, ensure_ascii=False)
+    print(f"\n--- ✅ Audio generation finished. Final data saved to {output_json_path}. ---")
+
+    return multimedia_data
+
+# Example Usage
+# if __name__ == '__main__':
+#     json_input_file = "multimedia_data_with_images.json"
+#     if not os.path.exists(json_input_file):
+#         print(f"❌ Error: Input file '{json_input_file}' not found.")
+#         print("Please run image_generation.py first to generate it.")
+#     else:
+#         target_language_for_story = "English"
+#         target_gender_for_story = "male" # Change to "male" to test the other voice
+
+#         generate_all_audio_from_file(
+#             json_path=json_input_file,
+#             target_language=target_language_for_story,
+#             gender=target_gender_for_story
 #         )