mirror of
https://github.com/thorstenMueller/Thorsten-Voice.git
synced 2024-11-21 23:43:12 +01:00
59 lines
2.0 KiB
Python
59 lines
2.0 KiB
Python
# Script is originally taken from https://github.com/imartinez/privateGPT/blob/main/privateGPT.py
|
|
# and i've added some STT and TTS stuff.
|
|
# See full tutorial on my "Thorsten-Voice" Youtube channel: https://youtu.be/qBs85JNyY7I
|
|
|
|
from dotenv import load_dotenv
|
|
from langchain.chains import RetrievalQA
|
|
from langchain.embeddings import HuggingFaceEmbeddings
|
|
from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
|
|
from langchain.vectorstores import Chroma
|
|
from langchain.llms import GPT4All, LlamaCpp
|
|
import os
|
|
from constants import CHROMA_SETTINGS
|
|
|
|
import whisper
|
|
from TTS.api import TTS
|
|
|
|
##############################
|
|
# Whisper for local STT part #
|
|
##############################
|
|
|
|
model = whisper.load_model("base")
|
|
result = model.transcribe("input.wav")
|
|
query = result["text"]
|
|
|
|
##################################
|
|
# PrivateGPT for query documents #
|
|
##################################
|
|
load_dotenv()
|
|
|
|
embeddings_model_name = os.environ.get("EMBEDDINGS_MODEL_NAME")
|
|
persist_directory = os.environ.get('PERSIST_DIRECTORY')
|
|
|
|
model_type = os.environ.get('MODEL_TYPE')
|
|
print("Model type: " + model_type)
|
|
model_path = os.environ.get('MODEL_PATH')
|
|
print("Model path: " + model_path)
|
|
model_n_ctx = os.environ.get('MODEL_N_CTX')
|
|
target_source_chunks = int(os.environ.get('TARGET_SOURCE_CHUNKS',4))
|
|
|
|
embeddings = HuggingFaceEmbeddings(model_name=embeddings_model_name)
|
|
db = Chroma(persist_directory=persist_directory, embedding_function=embeddings, client_settings=CHROMA_SETTINGS)
|
|
retriever = db.as_retriever(search_kwargs={"k": target_source_chunks})
|
|
llm = GPT4All(model=model_path, n_ctx=model_n_ctx, backend='gptj', callbacks=None, verbose=False)
|
|
qa = RetrievalQA.from_chain_type(llm=llm, chain_type="stuff", retriever=retriever, return_source_documents=False)
|
|
|
|
print("")
|
|
print(">> Asking my documents: " + query)
|
|
print("")
|
|
|
|
res = qa(query)
|
|
print("")
|
|
|
|
############################
|
|
# Coqui for local TTS part #
|
|
############################
|
|
os.environ["TOKENIZERS_PARALLELISM"] = "false"
|
|
tts = TTS(model_name="tts_models/en/ljspeech/vits--neon")
|
|
tts.tts_to_file(text=res['result'])
|