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app.py

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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()

requirements.txt

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+transformers