Create new file

app.py

@@ -0,0 +1,106 @@
+import gradio as gr
+import requests
+
+# GPT-J-6B API
+API_URL = "https://api-inference.huggingface.co/models/EleutherAI/gpt-j-6B"
+headers = {"Authorization": "Bearer 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"}
+prompt = """Oh, my life 
+is changing every day
+Every possible way
+And oh, my dreams, 
+it's never quite as it seems
+Never quite as it seems"""
+
+examples = [["mind"], ["memory"], ["sleep"],["wellness"],["nutrition"]]
+
+
+def poem2_generate(word):
+  p = word.lower() + "\n" + "poem using word: "
+  print(f"*****Inside poem_generate - Prompt is :{p}")
+  json_ = {"inputs": p,
+            "parameters":
+            {
+            "top_p": 0.9,
+          "temperature": 1.1,
+          "max_new_tokens": 50,
+          "return_full_text": False
+          }}
+  response = requests.post(API_URL, headers=headers, json=json_)
+  output = response.json()
+  print(f"If there was an error? Reason is : {output}")
+  output_tmp = output[0]['generated_text']
+  print(f"GPTJ response without splits is: {output_tmp}")
+  #poem = output[0]['generated_text'].split("\n\n")[0] # +"."
+  if "\n\n" not in output_tmp:
+    if output_tmp.find('.') != -1:
+      idx = output_tmp.find('.')
+      poem = output_tmp[:idx+1]
+    else:
+      idx = output_tmp.rfind('\n')
+      poem = output_tmp[:idx]
+  else:
+    poem = output_tmp.split("\n\n")[0] # +"."
+  poem = poem.replace('?','')
+  print(f"Poem being returned is: {poem}")
+  return poem
+  
+
+def poem_generate(word):
+
+  p = prompt + word.lower() + "\n" + "poem using word: "
+  print(f"*****Inside poem_generate - Prompt is :{p}")
+  json_ = {"inputs": p,
+            "parameters":
+            {
+            "top_p": 0.9,
+          "temperature": 1.1,
+          "max_new_tokens": 50,
+          "return_full_text": False
+          }}
+  response = requests.post(API_URL, headers=headers, json=json_)
+  output = response.json()
+  print(f"If there was an error? Reason is : {output}")
+  output_tmp = output[0]['generated_text']
+  print(f"GPTJ response without splits is: {output_tmp}")
+  #poem = output[0]['generated_text'].split("\n\n")[0] # +"."
+  if "\n\n" not in output_tmp:
+    if output_tmp.find('.') != -1:
+      idx = output_tmp.find('.')
+      poem = output_tmp[:idx+1]
+    else:
+      idx = output_tmp.rfind('\n')
+      poem = output_tmp[:idx]
+  else:
+    poem = output_tmp.split("\n\n")[0] # +"."
+  poem = poem.replace('?','')
+  print(f"Poem being returned is: {poem}")
+  return poem
+
+def poem_to_image(poem):
+  print("*****Inside Poem_to_image")
+  poem = " ".join(poem.split('\n'))
+  poem = poem + " oil on canvas."
+  steps, width, height, images, diversity = '50','256','256','1',15
+  img = gr.Interface.load("spaces/multimodalart/latentdiffusion")(poem, steps, width, height, images, diversity)[0]
+  return img
+
+demo = gr.Blocks()
+
+with demo:
+  gr.Markdown("<h1><center>Few Shot Learning for Text - Word Image Search</center></h1>")
+  gr.Markdown(
+        "https://huggingface.co/blog/few-shot-learning-gpt-neo-and-inference-api,  https://github.com/EleutherAI/the-pile"
+    )
+  with gr.Row():
+    input_word = gr.Textbox(lines=7, value=prompt)
+    poem_txt = gr.Textbox(lines=7)
+    output_image = gr.Image(type="filepath", shape=(256,256))
+  
+  b1 = gr.Button("Generate Text")
+  b2 = gr.Button("Generate Image")
+
+  b1.click(poem2_generate, input_word, poem_txt)
+  b2.click(poem_to_image, poem_txt, output_image)
+  examples=[["living, loving, feeling good"], ["I want to live.  I want to give."],["Ive been to Hollywood.  Ive been to Redwood"]]
+
+demo.launch(enable_queue=True, debug=True)