last

app.py

@@ -1,18 +1,48 @@
 import random
+import re
 import gradio as gr
+import requests
+from transformers import AutoModelForCausalLM, AutoTokenizer
 
-code = 'def hello_world(): return "Hello, world!" print(hello_world())'
+model = AutoModelForCausalLM.from_pretrained(
+    'parsak/codegen-350M-mono-lora-instruction',
+)
+tokenizer = AutoTokenizer.from_pretrained('Salesforce/codegen-350M-mono')
 
-def prompt(message, history):
-    return gr.Code(value=code,language="python")
+tokenizer.pad_token_id = 0  # different to <eos>
+tokenizer.padding_side = "left"  # Allow batched inference
+
+def extract_code(input_text):
+    pattern = r"'''py\n(.*?)'''"
+    match = re.search(pattern, input_text, re.DOTALL)
+    
+    if match:
+        return match.group(1)
+    else:
+        return None  # Return None if no match is found
+
+def generate_code(input_text):
+    input_ids = tokenizer(input_text, return_tensors="pt").input_ids
+    generated_ids = model.generate(input_ids, max_length=128)
+    result = tokenizer.decode(generated_ids[0], skip_special_tokens=True)
+    return extract_code(result)
+
+def respond(message, chat_history, additional_inputs):
+    return  f"Here's an example code:\n\n```python\n{generate_code(message)}\n```" 
+
+
+
+
+
+
+gr.ChatInterface(respond,
+        retry_btn= gr.Button(value="Retry"), 
+        undo_btn=None, clear_btn=gr.Button(value="Clear"),
+        additional_inputs=[
+            gr.Dropdown(["annen", "baban"])
+        ]
+        ).launch()
 
-demo = gr.ChatInterface(prompt,
-    title="codeBot",
-    description="Ask me a question",
-    retry_btn="Retry",
-    undo_btn=None,
-    clear_btn="Clear")
 
 
 
-demo.launch()