(wip)replace space

tts.py

@@ -2,6 +2,8 @@ import os
 from dotenv import load_dotenv
 import random
 
+from fal_client import stream
+
 load_dotenv()
 
 ZEROGPU_TOKENS = os.getenv("ZEROGPU_TOKENS", "").split(",")
@@ -44,7 +46,7 @@ data = {"text": "string", "provider": "string", "model": "string"}
 
 def predict_index_tts(text, reference_audio_path=None):
     from gradio_client import Client, handle_file
-    client = Client("IndexTeam/IndexTTS",hf_token=os.getenv("HF_TOKEN"))
+    client = Client("kemuriririn/IndexTTS",hf_token=os.getenv("HF_TOKEN"))
     if reference_audio_path:
         prompt = handle_file(reference_audio_path)
     else:
@@ -92,12 +94,11 @@ def predict_cosyvoice_tts(text, reference_audio_path=None):
     prompt_text = recog_result if isinstance(recog_result, str) else str(recog_result)
     result = client.predict(
         tts_text=text,
-        mode_checkbox_group="3s Voice Clone",
         prompt_text=prompt_text,
         prompt_wav_upload=prompt_wav,
         prompt_wav_record=prompt_wav,
-        instruct_text="",
         seed=0,
+        stream=False,
         api_name="/generate_audio"
     )
     print("cosyvoice-2.0 result:", result)
@@ -123,7 +124,7 @@ def predict_maskgct(text, reference_audio_path=None):
 
 def predict_gpt_sovits_v2(text, reference_audio_path=None):
     from gradio_client import Client, file
-    client = Client("lj1995/GPT-SoVITS-v2")
+    client = Client("kemuriririn/GPT-SoVITS-v2",hf_token=os.getenv("HF_TOKEN"))
     if not reference_audio_path:
         raise ValueError("GPT-SoVITS-v2 需要 reference_audio_path")
     result = client.predict(