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| import gradio as gr | |
| import os | |
| from transformers import pipeline | |
| title = "❤️🧠MindfulStory📖💾MemoryMaker" | |
| examples = [ | |
| ["Music and art make me feel"], | |
| ["Feel better each day when you awake by"], | |
| ["Feel better physically by"], | |
| ["Practicing mindfulness each day"], | |
| ["Be happier by"], | |
| ["Meditation can improve health"], | |
| ["Spending time outdoors"], | |
| ["Stress is relieved by quieting your mind, getting exercise and time with nature"], | |
| ["Break the cycle of stress and anxiety"], | |
| ["Feel calm in stressful situations"], | |
| ["Deal with work pressure"], | |
| ["Learn to reduce feelings of overwhelmed"] | |
| ] | |
| from gradio import inputs | |
| from gradio.inputs import Textbox | |
| from gradio import outputs | |
| # 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") | |
| # 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) | |
| SplitterInputBox = gr.inputs.Textbox(lines=5, label="Enter a sentence to get another sentence.") | |
| def AIMemory(name: str): | |
| if name and message: | |
| with open(DATA_FILE, "a") as csvfile: | |
| writer = csv.DictWriter(csvfile, fieldnames=["name", "message", "time"]) | |
| writer.writerow({"name": name, "message": message, "time": str(datetime.now())}) | |
| commit_url = repo.push_to_hub() | |
| return message | |
| with open('Mindfulness.txt', 'r') as file: | |
| context = file.read() | |
| #parallelModel = gr.Parallel(generator1, generator2, generator3, | |
| parallelModel = gr.Parallel(generator1, generator2, generator3, | |
| #inputs = SplitterInputBox, | |
| inputs=[ | |
| #gr.inputs.Textbox(lines=7, default=context, label=""), | |
| gr.inputs.Textbox(lines=3, default=context, label="Story starter")], | |
| examples=examples, | |
| title="Mindfulness Story Generation with Persistent Dataset Memory", | |
| description=f"Mindfulness Story Generation with Persistent Dataset Memory", | |
| article=f"Memory Dataset URL: [{DATASET_REPO_URL}]({DATASET_REPO_URL})" ) | |
| parallelModel.launch(share=False) |