Create app.py

app.py

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+import gradio as gr
+import random
+
+import requests
+
+# Template
+title = "A conversation with Gandalf (GPTJ-6B) 🧙"
+description = ""
+article = """<img src='http://www.simoninithomas.com/test/gandalf.jpg', alt="Gandalf"/>"""
+theme="huggingface"
+examples = [[0.9, 1.1, 50, "Hey Gandalf! How are you?"], [0.9, 1.1, 50, "Hey Gandalf, why you didn't use the great eagles to fly Frodo to Mordor?"]]
+
+# GPT-J-6B API
+API_URL = "https://api-inference.huggingface.co/models/EleutherAI/gpt-j-6B"
+def query(payload):
+  response = requests.post(API_URL, json=payload)
+  return response.json()
+context_setup = "The following is a conversation with Gandalf, the mage of 'the Lord of the Rings'"
+context=context_setup
+interlocutor_names = ["Human", "Gandalf"]
+
+# Builds the prompt from what previously happened 
+def build_prompt(conversation, context):
+  prompt = context + "\n"
+  for user_msg, resp_msg in conversation:
+      line = "\n- " + interlocutor_names[0] + ":" + user_msg
+      prompt += line
+      line = "\n- " + interlocutor_names[1] + ":" + resp_msg
+      prompt += line
+  prompt += ""
+  return prompt
+
+# Attempt to recognize what the model said, if it used the correct format
+def clean_chat_output(txt, prompt):
+  delimiter = "\n- "+interlocutor_names[0]
+  output = txt.replace(prompt, '')
+  output = output[:output.find(delimiter)]
+  return output
+
+
+def chat(top_p, temperature, max_new_tokens, message):
+    history = gr.get_state() or []
+    history.append((message, ""))
+    gr.set_state(history)
+    conversation = history
+    prompt = build_prompt(conversation, context)
+    
+    # Build JSON
+    json_ = {"inputs": prompt,
+         "parameters":
+         {
+        "top_p": top_p,
+        "temperature": temperature,
+        "max_new_tokens": max_new_tokens,
+        "return_full_text": False
+        }}
+       
+    output = query(json_)
+    output = output[0]['generated_text']
+    answer = clean_chat_output(output, prompt)
+    response = answer
+    history[-1] = (message, response)
+    gr.set_state(history)
+    html = "<div class='chatbot'>"
+    for user_msg, resp_msg in history:
+        html += f"<div class='user_msg'>{user_msg}</div>"
+        html += f"<div class='resp_msg'>{resp_msg}</div>"
+    html += "</div>"
+    return html
+
+iface = gr.Interface(
+        chat, 
+        [ 
+            gr.inputs.Slider(minimum=0.5, maximum=1, step=0.05, default=0.9, label="top_p"),
+            gr.inputs.Slider(minimum=0.5, maximum=1.5, step=0.1, default=1.1, label="temperature"),
+            gr.inputs.Slider(minimum=20, maximum=250, step=10, default=50, label="max_new_tokens"),
+            "text",
+        ],
+     "html", css="""
+    .chatbox {display:flex;flex-direction:column}
+    .user_msg, .resp_msg {padding:4px;margin-bottom:4px;border-radius:4px;width:80%}
+    .user_msg {background-color:cornflowerblue;color:white;align-self:start}
+    .resp_msg {background-color:lightgray;align-self:self-end}
+""", allow_screenshot=True, 
+allow_flagging=True,
+title=title,
+article=article,
+theme=theme,
+examples=examples)
+
+if __name__ == "__main__":
+  iface.launch()