import os import time from langchain_core.pydantic_v1 import BaseModel, Field from fastapi import FastAPI, HTTPException, Query, Request from fastapi.responses import StreamingResponse 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 from TextGen.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 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 Message(BaseModel): npc: str | None = None messages: List[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", "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)) @app.post("/generate_voice") async def generate_voice(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 = 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, ) 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)) @app.get("/generate_song") async def generate_song(text: str): try: data = custom_generate_audio({ "prompt": f"{text}", "make_instrumental": False, "wait_audio": False }) ids = f"{data[0]['id']},{data[1]['id']}" print(f"ids: {ids}") for _ in range(60): data = get_audio_information(ids) if data[0]["status"] == 'streaming': print(f"{data[0]['id']} ==> {data[0]['audio_url']}") print(f"{data[1]['id']} ==> {data[1]['audio_url']}") break # sleep 5s time.sleep(5) except: print("Error")