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import whisper | |
from langchain.llms import OpenAI | |
from langchain.agents import initialize_agent | |
from langchain.agents.agent_toolkits import ZapierToolkit | |
from langchain.utilities.zapier import ZapierNLAWrapper | |
import os | |
os.environ["OPENAI_API_KEY"] = "" | |
os.environ["ZAPIER_NLA_API_KEY"] = "" | |
def email_summary(file): | |
llm = OpenAI(temperature=0) | |
# Initializing zapier | |
zapier = ZapierNLAWrapper() | |
toolkit = ZapierToolkit.from_zapier_nla_wrapper(zapier) | |
# The agent used here is a "zero-shot-react-description" agent. | |
# Zero-shot means the agent functions on the current action only — it has no memory. | |
# It uses the ReAct framework to decide which tool to use, based solely on the tool's description. | |
agent = initialize_agent(toolkit.get_tools(), llm, agent="zero-shot-react-description", verbose=True) | |
# specify a model, here its BASE | |
model = whisper.load_model("base") | |
# transcribe audio file | |
result = model.transcribe(file) | |
print(result["text"]) | |
# Send email using zapier | |
agent.run("Send an Email to vmalapaka@umass.edu via gmail summarizing the following text provided below : "+result["text"]) | |