Spaces:
Configuration error
Configuration error
""" | |
utils.py | |
Functions: | |
- get_script: Get the dialogue from the LLM. | |
- call_llm: Call the LLM with the given prompt and dialogue format. | |
- get_audio: Get the audio from the TTS model from HF Spaces. | |
""" | |
import os | |
import requests | |
from gradio_client import Client | |
from openai import OpenAI | |
from pydantic import ValidationError | |
MODEL_ID = "accounts/fireworks/models/llama-v3p1-405b-instruct" | |
JINA_URL = "https://r.jina.ai/" | |
client = OpenAI( | |
base_url="https://api.fireworks.ai/inference/v1", | |
api_key=os.getenv("FIREWORKS_API_KEY"), | |
) | |
hf_client = Client("mrfakename/MeloTTS") | |
def generate_script(system_prompt: str, input_text: str, output_model): | |
"""Get the dialogue from the LLM.""" | |
# Load as python object | |
try: | |
response = call_llm(system_prompt, input_text, output_model) | |
dialogue = output_model.model_validate_json( | |
response.choices[0].message.content | |
) | |
except ValidationError as e: | |
error_message = f"Failed to parse dialogue JSON: {e}" | |
system_prompt_with_error = f"{system_prompt}\n\nPlease return a VALID JSON object. This was the earlier error: {error_message}" | |
response = call_llm(system_prompt_with_error, input_text, output_model) | |
dialogue = output_model.model_validate_json( | |
response.choices[0].message.content | |
) | |
return dialogue | |
def call_llm(system_prompt: str, text: str, dialogue_format): | |
"""Call the LLM with the given prompt and dialogue format.""" | |
response = client.chat.completions.create( | |
messages=[ | |
{"role": "system", "content": system_prompt}, | |
{"role": "user", "content": text}, | |
], | |
model=MODEL_ID, | |
max_tokens=16_384, | |
temperature=0.1, | |
response_format={ | |
"type": "json_object", | |
"schema": dialogue_format.model_json_schema(), | |
}, | |
) | |
return response | |
def parse_url(url: str) -> str: | |
"""Parse the given URL and return the text content.""" | |
full_url = f"{JINA_URL}{url}" | |
response = requests.get(full_url, timeout=60) | |
return response.text | |
def generate_audio(text: str, speaker: str, language: str) -> bytes: | |
"""Get the audio from the TTS model from HF Spaces and adjust pitch if necessary.""" | |
if speaker == "Guest": | |
accent = "EN-US" if language == "EN" else language | |
speed = 0.9 | |
else: # host | |
accent = "EN-Default" if language == "EN" else language | |
speed = 1 | |
if language != "EN" and speaker != "Guest": | |
speed = 1.1 | |
# Generate audio | |
result = hf_client.predict( | |
text=text, language=language, speaker=accent, speed=speed, api_name="/synthesize" | |
) | |
return result | |