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app.py

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+import gradio as gr
+import requests
+import os 
+
+##Bloom
+API_URL = "https://api-inference.huggingface.co/models/bigscience/bloom"
+headers = {"Authorization": "Bearer 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"}
+
+#def query(payload):
+#	response = requests.post(API_URL, headers=headers, json=payload)
+#	return response.json()
+	
+#output = query({
+#	"inputs": "Can you please let us know more details about your ",
+#})
+
+
+# GPT-J-6B API
+#API_URL = "https://api-inference.huggingface.co/models/EleutherAI/gpt-j-6B"
+#HF_TOKEN = os.environ["HF_TOKEN"]
+#headers = {"Authorization": f"Bearer {HF_TOKEN}"}
+
+prompt = """
+word: risk
+poem using word: And then the day came,
+when the risk
+to remain tight
+in a bud
+was more painful
+than the risk
+it took
+to blossom.
+word: bird
+poem using word: She sights a bird, she chuckles
+She flattens, then she crawls
+She runs without the look of feet
+Her eyes increase to Balls.
+word: """
+
+examples = [["river"], ["night"], ["trees"],["table"],["laughs"]]
+
+
+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>Generate Short Poem along with an Illustration</center></h1>")
+  gr.Markdown(
+        """Enter a single word you would want GPTJ-6B to write Poetry 🎤 on. A Space by [Yuvraj Sharma](https://huggingface.co/ysharma)."""
+        )
+  gr.Markdown("""<div>Generate an illustration 🎨 provided by Latent Diffusion model.</div><div>GPJ-6B is a 6 Billion parameter autoregressive language model. It generates the Poem based on how it has been 'prompt-engineered' 🤗 The complete text of generated poem then goes in as a prompt to the amazing Latent Diffusion Art space by <a href='https://huggingface.co/spaces/multimodalart/latentdiffusion' target='_blank'>Multimodalart</a>.</div>Please note that some of the Poems/Illustrations might not look at par, and well, this is what happens when you can't 'cherry-pick' and post 😁 <div> Some of the example words that you can use are 'river', 'night', 'trees', 'table', 'laughs' or maybe on similar lines to get best results!"""
+    )
+  with gr.Row():
+    input_word = gr.Textbox(placeholder="Enter a word here to create a Poem on..")
+    poem_txt = gr.Textbox(lines=7)
+    output_image = gr.Image(type="filepath", shape=(256,256))
+  
+  b1 = gr.Button("Generate Poem")
+  b2 = gr.Button("Generate Image")
+
+  b1.click(poem_generate, input_word, poem_txt)
+  b2.click(poem_to_image, poem_txt, output_image)
+  #examples=examples
+
+demo.launch(enable_queue=True, debug=True)