Update utils.py

utils.py

@@ -1,79 +1,18 @@
-from groq import Groq
-from pydantic import BaseModel, ValidationError
-from typing import List, Literal
-import os
-import tiktoken
-import tempfile
-import json
-import re
-from transformers import pipeline
-import torch
-import soundfile as sf
-
-groq_client = Groq(api_key=os.environ["GROQ_API_KEY"])
-tokenizer = tiktoken.get_encoding("cl100k_base")
-
-# Initialize TTS pipelines
-tts_male = pipeline("text-to-speech", model="microsoft/speecht5_tts", device="cpu")
-tts_female = pipeline("text-to-speech", model="microsoft/speecht5_tts", device="cpu")
-
-# Load speaker embeddings
-male_embedding = torch.load("https://huggingface.co/microsoft/speecht5_tts/resolve/main/en_speaker_1.pt")
-female_embedding = torch.load("https://huggingface.co/microsoft/speecht5_tts/resolve/main/en_speaker_9.pt")
-
-class DialogueItem(BaseModel):
-    speaker: Literal["John", "Sarah"]  # Changed from "Host" and "Guest" to "John" and "Sarah"
-    text: str
-
-class Dialogue(BaseModel):
-    dialogue: List[DialogueItem]
-
-def truncate_text(text, max_tokens=2048):
-    tokens = tokenizer.encode(text)
-    if len(tokens) > max_tokens:
-        return tokenizer.decode(tokens[:max_tokens])
-    return text
-
-def generate_script(system_prompt: str, input_text: str, tone: str):
-    input_text = truncate_text(input_text)
-    prompt = f"{system_prompt}\nTONE: {tone}\nINPUT TEXT: {input_text}"
-    
-    response = groq_client.chat.completions.create(
-        messages=[
-            {"role": "system", "content": prompt},
-        ],
-        model="llama-3.1-70b-versatile",
-        max_tokens=2048,
-        temperature=0.7
-    )
-    
-    content = response.choices[0].message.content
-    content = re.sub(r'```json\s*|\s*```', '', content)
-    
-    try:
-        json_data = json.loads(content)
-        dialogue = Dialogue.model_validate(json_data)
-    except json.JSONDecodeError as json_error:
-        match = re.search(r'\{.*\}', content, re.DOTALL)
-        if match:
-            try:
-                json_data = json.loads(match.group())
-                dialogue = Dialogue.model_validate(json_data)
-            except (json.JSONDecodeError, ValidationError) as e:
-                raise ValueError(f"Failed to parse dialogue JSON: {e}\nContent: {content}")
-        else:
-            raise ValueError(f"Failed to find valid JSON in the response: {content}")
-    except ValidationError as e:
-        raise ValueError(f"Failed to validate dialogue structure: {e}\nContent: {content}")
-    
-    return dialogue
-
-def generate_audio(text: str, speaker: str) -> str:
-    if speaker == "John":
-        speech = tts_male(text, speaker_embeddings=male_embedding)
-    else:  # Sarah
-        speech = tts_female(text, speaker_embeddings=female_embedding)
-    
-    with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as temp_audio:
-        sf.write(temp_audio.name, speech["audio"], speech["sampling_rate"])
-        return temp_audio.name
+runtime error
+Exit code: 1. Reason: Traceback (most recent call last):
+  File "/home/user/app/app.py", line 2, in <module>
+    from utils import generate_script, generate_audio, truncate_text
+  File "/home/user/app/utils.py", line 17, in <module>
+    tts_male = pipeline("text-to-speech", model="microsoft/speecht5_tts", device="cpu")
+  File "/usr/local/lib/python3.10/site-packages/transformers/pipelines/__init__.py", line 999, in pipeline
+    tokenizer = AutoTokenizer.from_pretrained(
+  File "/usr/local/lib/python3.10/site-packages/transformers/models/auto/tokenization_auto.py", line 907, in from_pretrained
+    return tokenizer_class.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs)
+  File "/usr/local/lib/python3.10/site-packages/transformers/utils/import_utils.py", line 1637, in __getattribute__
+    requires_backends(cls, cls._backends)
+  File "/usr/local/lib/python3.10/site-packages/transformers/utils/import_utils.py", line 1625, in requires_backends
+    raise ImportError("".join(failed))
+ImportError: 
+SpeechT5Tokenizer requires the SentencePiece library but it was not found in your environment. Checkout the instructions on the
+installation page of its repo: https://github.com/google/sentencepiece#installation and follow the ones
+that match your environment. Please note that you may need to restart your runtime after installation.