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import gradio as gr
import os
# PersistDataset -----
import os
import csv
import gradio as gr
from gradio import inputs, outputs
import huggingface_hub
from huggingface_hub import Repository, hf_hub_download, upload_file
from datetime import datetime
# created new dataset as awacke1/MindfulStory.csv
DATASET_REPO_URL = "https://huggingface.co/datasets/awacke1/MindfulStory.csv"
DATASET_REPO_ID = "awacke1/MindfulStory.csv"
DATA_FILENAME = "MindfulStory.csv"
DATA_FILE = os.path.join("data", DATA_FILENAME)
HF_TOKEN = os.environ.get("HF_TOKEN")
# Download dataset repo using hub download
try:
hf_hub_download(
repo_id=DATASET_REPO_ID,
filename=DATA_FILENAME,
cache_dir=DATA_DIRNAME,
force_filename=DATA_FILENAME
)
except:
print("file not found")
def AIMemory(title: str, story: str):
if title and story:
with open(DATA_FILE, "a") as csvfile:
writer = csv.DictWriter(csvfile, fieldnames=["title", "story", "time"])
writer.writerow({"title": title, "story": story, "time": str(datetime.now())})
commit_url = repo.push_to_hub()
return ""
# Set up cloned dataset from repo for operations
repo = Repository(
local_dir="data", clone_from=DATASET_REPO_URL, use_auth_token=HF_TOKEN
)
generator1 = gr.Interface.load("huggingface/gpt2-large", api_key=HF_TOKEN)
generator2 = gr.Interface.load("huggingface/EleutherAI/gpt-neo-2.7B", api_key=HF_TOKEN)
generator3 = gr.Interface.load("huggingface/EleutherAI/gpt-j-6B", api_key=HF_TOKEN)
def calculator(intro, operator, outro):
if operator == "add":
output = generator2(intro) + generator3(outro)
title = intro + " " + outro
saved = AIMemory(title, output)
return output
elif operator == "subtract":
output = generator2(outro) + generator3(intro)
title = outro + " " + intro
saved = AIMemory(title, output)
output = output.replace(intro, "").replace(outro, "")
return output
elif operator == "multiply":
output = generator1(intro) + generator2(outro) + generator3(intro)
title = intro + " " + outro + " " + intro
saved = AIMemory(title, output)
return output
elif operator == "divide":
output = generator1(outro) + generator2(intro) + generator3(outro)
title = outro + " " + intro + " " + outro
saved = AIMemory(title, output)
output = output.replace(intro, "").replace(outro, "")
return output
#with open('Mindfulness.txt', 'r') as file:
# context = file.read()
#contextBox = gr.Textbox(lines=3, default=context, label="Story starter")
examples = [
["Music and art make me feel", "add", "Path to Health and Happiness"],
["Feel better each day when you awake by", "add", "Mental Body Scan"],
["Feel better physically by", "add", "Stretch, Calm, Breath"],
["Practicing mindfulness each day", "add", "Walk Feel"],
["Be happier by", "add", "Brain gamification"],
["Meditation can improve health", "add", "Deep Breaths"],
["Spending time outdoors", "add", "Find Joy"],
["Stress is relieved by quieting your mind, getting exercise and time with nature", "add", "Relieve Pain"],
["Break the cycle of stress and anxiety", "add", "Yoga and Meditation"],
["Feel calm in stressful situations", "add", "Neocortex Tools and Techniques"],
["Deal with work pressure", "add", "Strengthen Attention"],
["Learn to reduce feelings of overwhelmed", "add", "Easy Daily Activities"]
]
demo = gr.Interface(
calculator,
[
"text",
gr.Radio(["add", "subtract", "multiply", "divide"]),
"text"
],
"text",
examples=examples,
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",
live=True,
)
demo.launch() |