v

app.py

@@ -1,6 +1,6 @@
-import streamlit as st
 import requests
 import os
+import gradio as gr
 import json
 
 def start_server():   
@@ -10,32 +10,27 @@ def start_server():
 if os.environ.get('SSTART') != "1":
     start_server()     
 
-st.set_page_config(
-    page_title="Incoder Example",
-    page_icon="👨‍💻",
+def completion(prompt,max_tokens,temperature,top_k,top_p):
+    req = f"http://0.0.0.0:8080?input_text={prompt}&top_p={top_p}&top_k={top_k}&temperature={temperature}&max_length={prompt}"
+    g = requests.get(req).json()
+    return g['text']
+
+demo = gr.Interface(
+       fn=completion, 
+       inputs=[
+               gr.inputs.Textbox(lines=10,placeholder='Write some code..'),
+               gr.inputs.Slider(10,200,10,100,'Max Tokens',False),
+               gr.inputs.Slider(0,1.0,0.1,1.0,'temperature',False),
+               gr.inputs.Slider(0,50,1,40,'top_k',True),
+               gr.inputs.Slider(0,1.0,0.1,0.9,'top_p',True)
+       ],
+       outputs="text",
+       theme='dark-huggingface',
+       title='Solo-Coder',
+       description='Build by Ansh and ❤️',
+       allow_flagging=False,
+ 
 )
 
-st.markdown("# 👨‍💻 Incoder Example")
-
-txt = st.text_area('Write code here', '''import os
-
-def remove_file(file):''', height=400)
-
-gen = st.button('Generate')
-
-c = st.code('')
-
-max_length = st.slider('max_length', 1, 2048, 128)
-top_k = st.slider('top_k', 0, 100, 50)
-top_p = st.slider('top_p', 0.0, 1.0, 0.9)
-temperature = st.slider('temperature', 0.0, 1.0, 0.6)
-num_beams = st.slider('num_beams', 1, 100, 1)
-repetition_penalty = st.slider('repetition_penalty', 1.0, 10.0, 1.0)
-
-
-if gen:
-    c.code('Generating...')
-    req = f"http://0.0.0.0:8080?input_text={txt}&top_p={top_p}&top_k={top_k}&temperature={temperature}&num_beams={num_beams}&repetition_penalty={repetition_penalty}&max_length={max_length}"
-    res = requests.get(req)
-    print('ok')
-    c.code(json.loads(res.text))
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

@@ -2,4 +2,5 @@ transformers
 fastapi
 uvicorn
 torch
-requests
+requests
+gradio

server.py

@@ -14,4 +14,4 @@ def read_root(input_text, max_length, top_p, top_k, num_beams, temperature, repe
     inpt = tokenizer.encode(input_text, return_tensors="pt")
     out = model.generate(inpt, max_length=int(max_length), top_p=float(top_p), top_k=float(top_k), temperature=float(temperature), num_beams=int(num_beams), repetition_penalty=float(repetition_penalty))
     res = tokenizer.decode(out[0])
-    return {res}
+    return {"text": res}