fix

app.py

@@ -1,31 +1,19 @@
 # !pip install -q gradio
-# !pip install -q pyChatGPT
 # !pip install -q git+https://github.com/openai/whisper.git
 # !pip install -q --upgrade git+https://github.com/huggingface/diffusers.git transformers accelerate scipy
-
-# import whisper
+import os
+os.system("pip install -q pyChatGPT")
+os.system("pip install git+https://github.com/openai/whisper.git")
+import whisper
 import gradio as gr 
 import time
 import warnings
 
-from transformers import WhisperProcessor, WhisperForConditionalGeneration
-
-# load model and processor
-processor = WhisperProcessor.from_pretrained("openai/whisper-large")
-model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-large")
-
 warnings.filterwarnings("ignore")
 
-
-from fairseq.checkpoint_utils import load_model_ensemble_and_task_from_hf_hub
-
-models, cfg, task = load_model_ensemble_and_task_from_hf_hub(
-    "facebook/fastspeech2-en-ljspeech"
-)
-
 secret_token = ""
 
-# model = whisper.load_model("base")
+model = whisper.load_model("base")
 
 from diffusers import DiffusionPipeline
 
@@ -44,22 +32,22 @@ pipeline = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2-1")
 def transcribe(audio):
 
     # load audio and pad/trim it to fit 30 seconds
-    audio = model.load_audio(audio)
-    audio = model.pad_or_trim(audio)
+    audio = whisper.load_audio(audio)
+    audio = whisper.pad_or_trim(audio)
 
     # make log-Mel spectrogram and move to the same device as the model
-    mel = model.log_mel_spectrogram(audio).to(model.device)
+    mel = whisper.log_mel_spectrogram(audio).to(model.device)
 
     # detect the spoken language
     _, probs = model.detect_language(mel)
 
     # decode the audio
-    options = model.DecodingOptions()
-    result = model.decode(model, mel, options)
+    options = whisper.DecodingOptions()
+    result = whisper.decode(model, mel, options)
     result_text = result.text
 
     # Pass the generated text to Audio
-    chatgpt_api = models, cfg, task
+    chatgpt_api = ChatGPT(secret_token)
     resp = chatgpt_api.send_message(result_text)
     out_result = resp['message']