t

app.py

@@ -1,4 +1,5 @@
 
+import requests
 import gradio as gr
 # # from transformers import AutoModelForCausalLM, AutoTokenizer
 
@@ -11,18 +12,20 @@ import gradio as gr
 # try:
 #     from transformers import AutoModelForCausalLM, AutoTokenizer
 #     tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-j-6B")
-    
+
 #     # "EluttherAI" on this line and for the next occurence only
 #     # tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-j-6B")
 #     # model = AutoModelForCausalLM.from_pretrained("EleutherAI/gpt-j-6B")
 # except Exception as e:
 #     ex = e
 
-temperature = gr.inputs.Slider(minimum=0, maximum=1.5, step=0.1, default=0.9, label="temperature")
-top_p = gr.inputs.Slider(minimum=0, maximum=1.0, step=0.1, default=0.9, label="top_p")
+temperature = gr.inputs.Slider(
+    minimum=0, maximum=1.5, default=0.9, label="temperature")
+top_p = gr.inputs.Slider(minimum=0, maximum=1.0,
+                          default=0.9, label="top_p")
 
-import requests
-def f(text):
+
+def f(text, temperature, top_p):    
     try:
         # http://api.vicgalle.net:5000/docs#/default/generate_generate_post
         # https://pythonrepo.com/repo/vicgalle-gpt-j-api-python-natural-language-processing
@@ -33,14 +36,18 @@ def f(text):
             "temperature": temperature,
             "top_p": top_p,
         }
-        response = requests.post("http://api.vicgalle.net:5000/generate", params=payload).json()
+        response = requests.post(
+            "http://api.vicgalle.net:5000/generate", params=payload).json()
 
     except Exception as e:
         return "error: \n"+str(e)
     return response['text']
 
 
-iface = gr.Interface(fn=f, inputs=["text", temperature, top_p], outputs="text")
+iface = gr.Interface(f, [
+    "text",
+    temperature,
+    top_p], outputs="text")
 iface.launch(enable_queue=True)
 
 # all below works but testing