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import os
import time
from langchain_core.pydantic_v1 import BaseModel, Field
from fastapi import FastAPI, HTTPException, Query, Request
from fastapi.responses import StreamingResponse,Response
from fastapi.middleware.cors import CORSMiddleware
from langchain.chains import LLMChain
from langchain.prompts import PromptTemplate
from TextGen.suno import custom_generate_audio, get_audio_information,generate_lyrics
from TextGen.diffusion import generate_image
from coqui import predict
from langchain_google_genai import (
ChatGoogleGenerativeAI,
HarmBlockThreshold,
HarmCategory,
)
from TextGen import app
from gradio_client import Client, handle_file
from typing import List
from elevenlabs.client import ElevenLabs
from elevenlabs import stream
Eleven_client = ElevenLabs(
api_key=os.environ["ELEVEN_API_KEY"], # Defaults to ELEVEN_API_KEY
)
Last_message=None
class PlayLastMusic(BaseModel):
'''plays the lastest created music '''
Desicion: str = Field(
..., description="Yes or No"
)
class CreateLyrics(BaseModel):
f'''create some Lyrics for a new music'''
Desicion: str = Field(
..., description="Yes or No"
)
class CreateNewMusic(BaseModel):
f'''create a new music with the Lyrics previously computed'''
Name: str = Field(
..., description="tags to describe the new music"
)
class SongRequest(BaseModel):
prompt: str | None = None
tags: List[str] | None = None
class Message(BaseModel):
npc: str | None = None
messages: List[str] | None = None
class ImageGen(BaseModel):
prompt: str | None = None
class VoiceMessage(BaseModel):
npc: str | None = None
input: str | None = None
language: str | None = "en"
genre:str | None = "Male"
song_base_api=os.environ["VERCEL_API"]
my_hf_token=os.environ["HF_TOKEN"]
#tts_client = Client("Jofthomas/xtts",hf_token=my_hf_token)
main_npcs={
"Blacksmith":"./voices/Blacksmith.mp3",
"Herbalist":"./voices/female.mp3",
"Bard":"./voices/Bard_voice.mp3"
}
main_npc_system_prompts={
"Blacksmith":"You are a blacksmith in a video game",
"Herbalist":"You are an herbalist in a video game",
"Witch":"You are a witch in a video game. You are disguised as a potion seller in a small city where adventurers come to challenge the portal. You are selling some magic spells in a UI that the player only sees. Don't event too much lore and just follow the standard role of a merchant.",
"Bard":"You are a bard in a video game"
}
class Generate(BaseModel):
text:str
def generate_text(messages: List[str], npc:str):
print(npc)
if npc in main_npcs:
system_prompt=main_npc_system_prompts[npc]
else:
system_prompt="you're a character in a video game. Play along."
print(system_prompt)
new_messages=[{"role": "user", "content": system_prompt}]
for index, message in enumerate(messages):
if index%2==0:
new_messages.append({"role": "user", "content": message})
else:
new_messages.append({"role": "assistant", "content": message})
print(new_messages)
# Initialize the LLM
llm = ChatGoogleGenerativeAI(
model="gemini-1.5-pro-latest",
max_output_tokens=100,
temperature=1,
safety_settings={
HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: HarmBlockThreshold.BLOCK_NONE,
HarmCategory.HARM_CATEGORY_HARASSMENT: HarmBlockThreshold.BLOCK_NONE,
HarmCategory.HARM_CATEGORY_HATE_SPEECH: HarmBlockThreshold.BLOCK_NONE,
HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT: HarmBlockThreshold.BLOCK_NONE
},
)
if npc=="bard":
llm = llm.bind_tools([PlayLastMusic,CreateNewMusic,CreateLyrics])
llm_response = llm.invoke(new_messages)
print(llm_response)
return Generate(text=llm_response.content)
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
@app.get("/", tags=["Home"])
def api_home():
return {'detail': 'Everchanging Quest backend, nothing to see here'}
@app.post("/api/generate", summary="Generate text from prompt", tags=["Generate"], response_model=Generate)
def inference(message: Message):
return generate_text(messages=message.messages, npc=message.npc)
#Dummy function for now
def determine_vocie_from_npc(npc,genre):
if npc in main_npcs:
return main_npcs[npc]
else:
if genre =="Male":
"./voices/default_male.mp3"
if genre=="Female":
return"./voices/default_female.mp3"
else:
return "./voices/narator_out.wav"
@app.post("/generate_wav")
async def generate_wav(message: VoiceMessage):
# try:
# voice = determine_vocie_from_npc(message.npc, message.genre)
# audio_file_pth = handle_file(voice)
#
# Generator function to yield audio chunks
# async def audio_stream():
# result = tts_client.predict(
# prompt=message.input,
# language=message.language,
# audio_file_pth=audio_file_pth,
# mic_file_path=None,
# use_mic=False,
# voice_cleanup=False,
# no_lang_auto_detect=False,
# agree=True,
# api_name="/predict"
# )
# for sampling_rate, audio_chunk in result:
# yield audio_chunk.tobytes()
# await asyncio.sleep(0) # Yield control to the event loop
# Return the generated audio as a streaming response
# return StreamingResponse(audio_stream(), media_type="audio/wav")
# except Exception as e:
# raise HTTPException(status_code=500, detail=str(e))
return 200
@app.get("/generate_voice_eleven", response_class=StreamingResponse)
@app.post("/generate_voice_eleven", response_class=StreamingResponse)
def generate_voice_eleven(message: VoiceMessage = None):
global Last_message # Declare Last_message as global
if message is None:
message = Last_message
else:
Last_message = message
def audio_stream():
# Generate the audio stream from ElevenLabs
for chunk in Eleven_client.generate(text=message.input, stream=True):
yield chunk
return StreamingResponse(audio_stream(), media_type="audio/mpeg")
@app.get("/generate_voice_coqui", response_class=StreamingResponse)
@app.post("/generate_voice_coqui", response_class=StreamingResponse)
def generate_voice_coqui(message: VoiceMessage = None):
global Last_message
if message is None:
message = Last_message
else:
Last_message = message
def audio_stream():
voice = determine_vocie_from_npc(message.npc, message.genre)
result = predict(
prompt=message.input,
language=message.language,
audio_file_pth=voice,
mic_file_path=None,
use_mic=False,
voice_cleanup=False,
no_lang_auto_detect=False,
agree=True,
)
# Generate the audio stream from ElevenLabs
for chunk in result:
print("received : ",chunk)
yield chunk
return StreamingResponse(audio_stream(),media_type="audio/mpeg")
@app.get("/generate_song")
async def generate_song():
text="""You are a bard in a video game singing the tales of a little girl in red hood."""
song_lyrics=generate_lyrics({
"prompt": f"{text}",
})
data = custom_generate_audio({
"prompt": song_lyrics['text'],
"tags": "male bard",
"title":"Everchangin_Quest_song",
"wait_audio":True,
})
infos=get_audio_information(f"{data[0]['id']},{data[1]['id']}")
return infos
@app.post('/generate_image')
def Imagen(prompt:ImageGen=None):
image_bytes=generate_image(ImageGen.prompt)
return Response(content=image_bytes, media_type="image/png") |