initial commit

app.py

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+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+import gradio as gr
+
+tokenizer = AutoTokenizer.from_pretrained("natdon/DialoGPT_Michael_Scott")
+model = AutoModelForCausalLM.from_pretrained("natdon/DialoGPT_Michael_Scott")
+
+chat_history_ids = None
+step = 0
+
+
+def predict(input, chat_history_ids=chat_history_ids, step=step):
+    # encode the new user input, add the eos_token and return a tensor in Pytorch
+    new_user_input_ids = tokenizer.encode(
+        input + tokenizer.eos_token, return_tensors='pt')
+
+    # append the new user input tokens to the chat history
+    bot_input_ids = torch.cat(
+        [chat_history_ids, new_user_input_ids], dim=-1) if step > 0 else new_user_input_ids
+
+    # generated a response while limiting the total chat history to 1000 tokens,
+    chat_history_ids = model.generate(
+        bot_input_ids, max_length=1000,
+        pad_token_id=tokenizer.eos_token_id,
+        no_repeat_ngram_size=3,
+        do_sample=True,
+        top_k=100,
+        top_p=0.7,
+        temperature=0.8
+    )
+    step = step + 1
+    output = tokenizer.decode(
+        chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)
+    return output
+
+
+demo = gr.Blocks()
+
+with demo:
+    gr.Markdown(
+        """
+  <center>    
+  <img src="https://media3.giphy.com/media/l0amJzVHIAfl7jMDos/giphy.gif" alt="dialog" width="250" height="250">
+  
+  ## Speak with Michael by typing in the input box below.
+  </center>
+  """
+    )
+
+    with gr.Row():
+        with gr.Column():
+            inp = gr.Textbox(
+                label="Enter text to converse with Michael here:",
+                lines=1,
+                max_lines=1,
+                value="Wow this is hard",
+                placeholder="What do you think of Toby?",
+            )
+            btn = gr.Button("Submit")
+        out = gr.Textbox(lines=3)
+    # btn = gr.Button("Submit")
+    inp.submit(fn=predict, inputs=inp, outputs=out)
+    btn.click(fn=predict, inputs=inp, outputs=out)
+
+demo.launch()

requirements.txt

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+transformers
+torch