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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("bigscience/bloom", api_key=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")
+#Two space marines named Liev Schreiber and Will Sasso take up arms to save the planet from an alien invasion.  These two dashing strong men play a comedic role in the science fiction movie of the future where even barnaby bunny is willing to join their wacky gang of space marines to save the planet with good looks and comedy.
+
+examples = [
+    ["Two space marines take up arms to save the planet from an alien invasion.", "multiply", "These two dashing strong actors play a comedic role in the science fiction movie of the future"],
+    ["These two dashing strong actors play a comedic role in the science fiction movie of the future", "add", "Barnaby bunny is willing to join their wacky gang of space marines"],
+    ["to save the planet with good looks and comedy", "add", "Two space marines become best friends as they assist with saving the world from the alien invasion"]
+]
+
+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