Duplicate from DataScienceEngineering/4-GeneratorCalcPipe

Co-authored-by: Aaron C Wacker <awacke1@users.noreply.huggingface.co>

.gitattributes

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README.md

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+---
+title: 🧠Generator Calc Writer📖💾 Gradio
+emoji: 3-Gen📖
+colorFrom: indigo
+colorTo: red
+sdk: gradio
+sdk_version: 3.4.1
+app_file: app.py
+pinned: false
+license: apache-2.0
+duplicated_from: DataScienceEngineering/4-GeneratorCalcPipe
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

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())})
+        # uncomment line below to begin saving your changes
+        #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")
+
+examples = [
+    ["Asynchronous Telemedicine", "multiply", "Provide remote care services live addressing provider shortages"],
+    ["Ambient and emotion AI", "multiply", "rtificial intelligence showing empathy and compassion, reducing biases making us feel cared for and assist lifestyle"],
+    ["import gradio as gr", "multiply", "import streamlit as st"],
+    ["Skin Patch", "multiply", "Allow technology to measure blood pressure, glucose, reducing huge bulky devices"],
+    ["Affordable vein scanner", "multiply", "View veins through skin"],
+    ["Synthetic medical records", "multiply", "Create synthetic medical records using GANS trained to create synthetic data"],
+    ["Blood draw devices used in clinical trials", "multiply", "So you dont have to go to physical location, engagement during trials"],
+    ["Smart TVs being used for remote care", "multiply", "Video chat and recordings for remote care consultations"],
+    ["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."],
+    ["What type of shoes do ninjas wear?  Sneakers", "add", "Can a ninja bring a ninja star into the airport?  Shuriken."],
+    ["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."]
+]
+
+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