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from pydantic import BaseModel
from fastapi import FastAPI, HTTPException, Query
from fastapi.responses import FileResponse
from fastapi.middleware.cors import CORSMiddleware
from langchain.chains import LLMChain
from langchain.prompts import PromptTemplate
from langchain_google_genai import (
ChatGoogleGenerativeAI,
HarmBlockThreshold,
HarmCategory,
)
from TextGen import app
my_hf_token=os.environ["HF_TOKEN"]
tts_client = Client("https://jofthomas-xtts.hf.space/--replicas/sxv98/",hf_token=my_hf_token)
class Generate(BaseModel):
text:str
def generate_text(prompt: str):
if prompt == "":
return {"detail": "Please provide a prompt."}
else:
prompt = PromptTemplate(template=prompt, input_variables=['Prompt'])
# Initialize the LLM
llm = ChatGoogleGenerativeAI(
model="gemini-pro",
safety_settings={
HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: HarmBlockThreshold.BLOCK_NONE,
},
)
llmchain = LLMChain(
prompt=prompt,
llm=llm
)
llm_response = llmchain.run({"Prompt": prompt})
return Generate(text=llm_response)
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
@app.get("/", tags=["Home"])
def api_home():
return {'detail': 'Welcome to FastAPI TextGen Tutorial!'}
@app.post("/api/generate", summary="Generate text from prompt", tags=["Generate"], response_model=Generate)
def inference(input_prompt: str):
return generate_text(prompt=input_prompt)
@app.get("/generate_wav")
async def generate_wav(text: str, language: str = "en"):
try:
# Use the Gradio client to generate the wav file
result = tts_client.predict(
text, # str in 'Text Prompt' Textbox component
language, # str in 'Language' Dropdown component
"./narator_out.wav", # str (filepath on your computer (or URL) of file) in 'Reference Audio' Audio component
"./narator_out.wav", # str (filepath on your computer (or URL) of file) in 'Use Microphone for Reference' Audio component
False, # bool in 'Use Microphone' Checkbox component
False, # bool in 'Cleanup Reference Voice' Checkbox component
False, # bool in 'Do not use language auto-detect' Checkbox component
True, # bool in 'Agree' Checkbox component
fn_index=1
)
# Get the path of the generated wav file
wav_file_path = result[1]
# Return the generated wav file as a response
return FileResponse(wav_file_path, media_type="audio/wav", filename="output.wav")
except Exception as e:
raise HTTPException(status_code=500, detail=str(e)) |