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Browse files- app.py +108 -0
- requirements (1).txt +1 -0
- requirements.txt +1 -0
app.py
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import gradio as gr
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import os
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# PersistDataset -----
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import os
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import csv
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import gradio as gr
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from gradio import inputs, outputs
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import huggingface_hub
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from huggingface_hub import Repository, hf_hub_download, upload_file
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from datetime import datetime
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# created new dataset as awacke1/MindfulStory.csv
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#DATASET_REPO_URL = "https://huggingface.co/datasets/awacke1/MindfulStory.csv"
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#DATASET_REPO_ID = "awacke1/MindfulStory.csv"
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#DATA_FILENAME = "MindfulStory.csv"
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#DATA_FILE = os.path.join("data", DATA_FILENAME)
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HF_TOKEN = os.environ.get("HF_TOKEN")
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# Download dataset repo using hub download
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#try:
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# hf_hub_download(
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# repo_id=DATASET_REPO_ID,
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# filename=DATA_FILENAME,
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# cache_dir=DATA_DIRNAME,
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# force_filename=DATA_FILENAME
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# )
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#except:
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# print("file not found")
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#def AIMemory(title: str, story: str):
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# if title and story:
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# with open(DATA_FILE, "a") as csvfile:
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# writer = csv.DictWriter(csvfile, fieldnames=["title", "story", "time"])
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# writer.writerow({"title": title, "story": story, "time": str(datetime.now())})
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# uncomment line below to begin saving your changes
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#commit_url = repo.push_to_hub()
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# return ""
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# Set up cloned dataset from repo for operations
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#repo = Repository(
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# local_dir="data", clone_from=DATASET_REPO_URL, use_auth_token=HF_TOKEN
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#)
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#generator1 = gr.Interface.load("bigscience/bloom", api_key=HF_TOKEN)
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generator1 = gr.Interface.load("huggingface/gpt2-large", api_key=HF_TOKEN)
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generator2 = gr.Interface.load("huggingface/EleutherAI/gpt-neo-2.7B", api_key=HF_TOKEN)
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generator3 = gr.Interface.load("huggingface/EleutherAI/gpt-j-6B", api_key=HF_TOKEN)
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def calculator(intro, operator, outro):
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if operator == "add":
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output = generator2(intro) + generator3(outro)
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title = intro + " " + outro
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# saved = AIMemory(title, output)
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return output
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elif operator == "subtract":
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output = generator2(outro) + generator3(intro)
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title = outro + " " + intro
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# saved = AIMemory(title, output)
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output = output.replace(intro, "").replace(outro, "")
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return output
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elif operator == "multiply":
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output = generator1(intro) + generator2(outro) + generator3(intro)
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title = intro + " " + outro + " " + intro
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# saved = AIMemory(title, output)
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return output
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elif operator == "divide":
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output = generator1(outro) + generator2(intro) + generator3(outro)
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title = outro + " " + intro + " " + outro
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# saved = AIMemory(title, output)
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output = output.replace(intro, "").replace(outro, "")
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return output
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#with open('Mindfulness.txt', 'r') as file:
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# context = file.read()
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#contextBox = gr.Textbox(lines=3, default=context, label="Story starter")
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examples = [
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["Asynchronous Telemedicine", "multiply", "Provide remote care services live addressing provider shortages"],
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["Ambient and emotion AI", "multiply", "rtificial intelligence showing empathy and compassion, reducing biases making us feel cared for and assist lifestyle"],
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["import gradio as gr", "multiply", "import streamlit as st"],
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["Skin Patch", "multiply", "Allow technology to measure blood pressure, glucose, reducing huge bulky devices"],
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["Affordable vein scanner", "multiply", "View veins through skin"],
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["Synthetic medical records", "multiply", "Create synthetic medical records using GANS trained to create synthetic data"],
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["Blood draw devices used in clinical trials", "multiply", "So you dont have to go to physical location, engagement during trials"],
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["Smart TVs being used for remote care", "multiply", "Video chat and recordings for remote care consultations"],
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["Why does a chicken coop have two doors? Because if had four doors it would be a chicken sedan!", "multiply", "Why did the chicken cross the park? To get to the other slide."],
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["What type of shoes do ninjas wear? Sneakers", "add", "Can a ninja bring a ninja star into the airport? Shuriken."],
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["To save the planet with good looks and comedy find your", "multiply", "Everybody laughed at me when I told them I was going to be a comedian. I thought well, thats not bad for a start."]
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]
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demo = gr.Interface(
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calculator,
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[
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"text",
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gr.Radio(["add", "subtract", "multiply", "divide"]),
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"text"
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],
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"text",
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examples=examples,
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article="Saved story memory dataset: https://huggingface.co/datasets/awacke1/MindfulStory.csv with available models to use from text gen: https://huggingface.co/models?pipeline_tag=text-generation&sort=downloads",
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live=True,
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)
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demo.launch()
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requirements (1).txt
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transformers
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requirements.txt
ADDED
@@ -0,0 +1 @@
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transformers
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