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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
# API Key
os.environ["OPENAI_API_KEY"] = "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"
# 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)
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