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import json |
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import requests |
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import gradio as gr |
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import pandas as pd |
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import os |
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import openai |
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openai.api_key = os.environ.get('GPT_3_Token') |
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def openai_query( |
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recipient:str = "Employer", |
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len:int = 400, |
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recipient_name:str = "John Doe", |
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context:str = "", |
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input:str = "", |
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random_state:float = 0.85 |
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) -> str: |
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return openai.Completion.create( |
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engine='text-davinci-002', |
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prompt="Write a professional email to my " + recipient.lower() + " starting with Hello " + recipient_name + ", about the subject " + context + " and the email should be based on this draft: " + input, |
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temperature = random_state, |
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max_tokens= len, |
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frequency_penalty=0.25, |
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presence_penalty=0.75, |
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best_of=1 |
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).get("choices")[0]['text'].strip() |
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def query(payload, API_URL): |
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response = requests.request("POST", API_URL, json=payload) |
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return response.json() |
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def pre_query(recipient, recipient_name, sender, context, dates, input, model_id): |
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API_URL = "https://api-inference.huggingface.co/models/" + model_id |
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if model_id == "EleutherAI/gpt-neo-1.3B": |
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input_string = "Write a professional email to my " + recipient.lower() + " starting with Hello " + recipient_name + ", about the subject " + context + " and the email should be based on this draft: " + input |
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data = query({ |
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"inputs":input_string, |
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"parameters":{ |
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"wait_for_model": True} |
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}, API_URL) |
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return data[0]['generated_text'] |
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if model_id == "bigscience/bloom": |
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input_string = "Write a professional email to my " + recipient.lower() + " starting with Hello " + recipient_name + ", about the subject " + context + " and the email should be based on this draft: " + input + ": Hello " + recipient_name + ",\n\n" |
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data = query({ |
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"inputs":input_string, |
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"parameters":{"max_new_tokens":96, |
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"return_full_text": False, |
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"wait_for_model": True} |
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}, API_URL) |
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return "Hello " + recipient_name + ",\n\n" + data[0]['generated_text'].replace(input_string,'') |
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if model_id == "GPT-3": |
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return openai_query(recipient, 250, recipient_name, context, input) |
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return |
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demo = gr.Blocks() |
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with demo: |
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gr.Markdown( |
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""" |
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# <center> Email Assistant |
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Please fill out the fields below! |
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""") |
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with gr.Row(): |
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with gr.Column(): |
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with gr.Group(): |
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with gr.Row(): |
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sender = gr.Dropdown(["student", "professor", "employee", "employer", "coworker", "applicant", "recruiter"], label="I am a...") |
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recipient = gr.Dropdown(["student", "professor", "employee", "employer", "coworker", "applicant", "recruiter"], label="I am writing to my...") |
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recipient_name = gr.Textbox(label="Recipient Name", placeholder = "Their name is...") |
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subject = gr.Dropdown([ "Requesting a meeting", "Reporting conflict with scheduled meeting time", "Requesting clarification", "Requesting to leave early", "Requesting a leave of absence", "Requesting a letter of recommendation", "Requesting a referral for a job application"], label= "In this email, I am...") |
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dates = gr.Textbox(label="Relevant Dates", placeholder ="MM/DD/YYYY") |
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email = gr.Textbox(label="Input", lines=10, placeholder="Enter your Message Here!") |
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model_id = gr.Dropdown(["GPT-3", "EleutherAI/gpt-neo-1.3B", "bigscience/bloom"] ,label = "Choose a model") |
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submit_button = gr.Button("Generate my email!") |
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text_output = gr.Textbox(lines=10, label = "Email", placeholder = "Your generated email!", interactive = True) |
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input_list = [sender, recipient, recipient_name, subject, dates, email, model_id] |
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submit_button.click(pre_query, inputs = input_list, outputs=text_output) |
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demo.launch(debug=True) |
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