go again

app.py

@@ -63,7 +63,7 @@ example = r"""{
 
 
 @spaces.GPU
-def infer(var_name, code):
+def infer(code):
 
     splitcode = code.splitlines()
     bodyvars = [v['name'] for v in prep_decompiled.extract_comments(splitcode) if "name" in v]
@@ -71,11 +71,16 @@ def infer(var_name, code):
     vars = argvars + bodyvars
     #comments = prep_decompiled.extract_comments(splitcode)
     #sig = prep_decompiled.parse_signature(splitcode)
-    print(f"vars {vars}")
+    #print(f"vars {vars}")
+
+    varstring = ", ".join([f"`{v}`" for v in vars])
+
+    prompt = f"What are the original name and data types of variables {varstring}?\n```{code}\n```"
+
+    var_name = vars[0]
 
-    #line = json.loads(input)
-    #first_token = line["output"].split(":")[0]
     prompt = code + var_name + ":"
+    print(prompt)
 
     input_ids = tokenizer.encode(prompt, return_tensors="pt").cuda()[:, : 8192 - 1024]
     output = vardecoder_model.generate(
@@ -95,16 +100,16 @@ def infer(var_name, code):
     )
 
     output = var_name + ":" + output
-    return output
+    return output, varstring
 
 
 demo = gr.Interface(
     fn=infer,
     inputs=[
-        gr.Text(label="First Token", value="a1"),
         gr.Textbox(lines=10, value=json.loads(example)['input']),
     ],
-    outputs=gr.Text(label="Var Decoder Output"),
+    outputs=[gr.Text(label="Var Decoder Output"),
+             gr.Text(label="Generated Variable List")],
     description=description
 )
 demo.launch()