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# Necessary imports | |
import os | |
from langchain.llms import OpenAI | |
from langchain.prompts import PromptTemplate | |
from langchain.chains import LLMChain | |
from langchain.chains import SimpleSequentialChain | |
from prompts import prompt_transcribe, prompt_command | |
# Initializing OpenAI as the large language model | |
llm = OpenAI(temperature=0.0) | |
def get_transcription(text): | |
# Transcription prompt | |
transcribe_prompt = PromptTemplate( | |
input_variables=["text"], | |
template=prompt_transcribe | |
) | |
# Creating transcription chain | |
sentence_chain = LLMChain(llm=llm, | |
prompt=transcribe_prompt, | |
output_key="sentence") | |
return sentence_chain | |
# Method takes in the transcription chain to link them together with a sequential chain, which is then returned. | |
def format_command(chain): | |
# Prompt Creation | |
command = PromptTemplate( | |
input_variables=["sentence"], | |
template=prompt_command | |
) | |
# Chain Creation | |
command_chain = LLMChain(llm=llm, prompt=command, output_key="output") | |
# Initializing chain needed to connect using the parameters | |
sentence_chain = chain | |
# Connecting the two created chains via the SimpleSequentialChain. | |
sentence_command_chain = SimpleSequentialChain( | |
chains=[sentence_chain, command_chain], verbose=True | |
) | |
# Returning the new combined chain | |
return sentence_command_chain | |
def to_file(text): | |
f = open("commands.txt", "w") | |
f.write(text) | |
f.close() | |
# Method to get the actual formatted command | |
def get_command(text): | |
command = format_command(get_transcription(text)) | |
to_file(command.run(text)) | |
return command.run(text) | |