Spaces:
Sleeping
Sleeping
File size: 6,974 Bytes
3f66bfa 4d72b78 3f66bfa 77684f6 3f66bfa 4d72b78 3f66bfa 4d72b78 3f66bfa 4d72b78 3f66bfa 4d72b78 3f66bfa 4d72b78 3f66bfa 4d72b78 3f66bfa 4d72b78 3f66bfa 4d72b78 3f66bfa 4d72b78 3f66bfa 4d72b78 3f66bfa 4d72b78 3f66bfa 4d72b78 e1e87dc 3f66bfa 4d72b78 3f66bfa 4d72b78 3f66bfa e1e87dc 6e495b9 3f66bfa 4d72b78 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 | import re
import gradio as gr
import spaces
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
MODEL_ID = "shibsankardhara2/Qwen2.5-Coder-1.5B-Java-CSharp_V5"
print("Loading tokenizer...")
tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
if tokenizer.pad_token_id is None:
tokenizer.pad_token_id = tokenizer.eos_token_id
print("Loading model on CPU...")
model = AutoModelForCausalLM.from_pretrained(
MODEL_ID,
torch_dtype=torch.float16,
low_cpu_mem_usage=True,
)
model.eval()
print("Model loaded successfully.")
def add_java_hint(instruction: str) -> str:
instruction = instruction.strip()
if "java" in instruction.lower():
return instruction
return f"{instruction} Write the solution in Java."
def build_prompt(task: str, user_input: str) -> str:
user_input = user_input.strip()
if task == "Natural Language β Java":
return (
"### Instruction:\n\n"
f"{add_java_hint(user_input)}\n\n"
"### Response:\n\n"
)
return (
"### Instruction\n"
"Translate the following Java code into equivalent C#. "
"Write the solution in C#.\n\n"
"### Java\n"
f"{user_input}\n\n"
"### Response\n"
)
def clean_output(text: str) -> str:
text = text.strip()
fenced = re.search(
r"```(?:java|csharp|cs|c#)?\s*(.*?)```",
text,
flags=re.DOTALL | re.IGNORECASE,
)
if fenced:
text = fenced.group(1).strip()
stop_markers = [
"### Instruction:",
"### Instruction\n",
"### Java:",
"### Java\n",
"### Response:",
"### Response\n",
"<|im_start|>",
"<|im_end|>",
]
for marker in stop_markers:
if marker in text:
text = text.split(marker, 1)[0].strip()
return text
@spaces.GPU(duration=120)
def generate_code(task: str, user_input: str) -> str:
if not user_input or not user_input.strip():
return "Please enter a requirement or Java code."
prompt = build_prompt(task, user_input)
max_new_tokens = 300 if task == "Natural Language β Java" else 400
try:
model.to("cuda")
inputs = tokenizer(
prompt,
return_tensors="pt",
truncation=True,
max_length=2048,
).to("cuda")
with torch.inference_mode():
outputs = model.generate(
**inputs,
max_new_tokens=max_new_tokens,
do_sample=False,
pad_token_id=tokenizer.eos_token_id,
eos_token_id=tokenizer.eos_token_id,
)
generated_tokens = outputs[0][inputs["input_ids"].shape[1]:]
generated_text = tokenizer.decode(
generated_tokens,
skip_special_tokens=True,
)
code = _clean_csharp_output(generated_text)
if not code:
return "The model returned an empty response. Please try again."
language = "java" if task == "Natural Language β Java" else "csharp"
return f"```{language}\n{code}\n```"
except Exception as error:
return f"Generation failed: {type(error).__name__}: {error}"
finally:
model.to("cpu")
torch.cuda.empty_cache()
def update_input(task: str):
if task == "Natural Language β Java":
return gr.update(
label="Natural-language requirement",
placeholder=(
"Example: Write a Java method to check whether "
"a number is prime."
),
value="",
)
return gr.update(
label="Java code",
placeholder=(
"Example:\n"
"public static int factorial(int n) {\n"
" int result = 1;\n"
" for (int i = 2; i <= n; i++) {\n"
" result *= i;\n"
" }\n"
" return result;\n"
"}"
),
value="",
)
with gr.Blocks(title="Java and C# CodeGen") as demo:
gr.Markdown(
"""
# Java and C# CodeGen
Generate Java code from natural-language requirements or translate Java code
into equivalent C# using a fine-tuned Qwen2.5-Coder model.
"""
)
task = gr.Dropdown(
choices=[
"Natural Language β Java",
"Java β C#",
],
value="Natural Language β Java",
label="Select task",
)
user_input = gr.Textbox(
label="Natural-language requirement",
placeholder=(
"Example: Write a Java method to check whether "
"a number is prime."
),
lines=14,
)
generate_button = gr.Button(
"Generate Code",
variant="primary",
)
output = gr.Markdown()
task.change(
fn=update_input,
inputs=task,
outputs=user_input,
)
generate_button.click(
fn=generate_code,
inputs=[
task,
user_input,
],
outputs=output,
)
gr.Examples(
examples=[
[
"Natural Language β Java",
"Write a Java method to calculate factorial of a number using a loop.",
],
[
"Natural Language β Java",
"Write a Java method to reverse a string.",
],
[
"Java β C#",
"""public static int factorial(int n) {
int result = 1;
for (int i = 2; i <= n; i++) {
result *= i;
}
return result;
}""",
],
],
inputs=[
task,
user_input,
],
)
def _clean_csharp_output(code: str) -> str:
"""
Remove spurious `virtual` / `override` modifiers the model adds to bare
(class-less) method snippets.
The model was trained on C# methods that usually live inside a class, where
`public virtual ...` is common. When it translates a *standalone* Java method
it carries the `virtual` keyword over β but `virtual`/`override` are only
valid on members of a class, so on a bare snippet they are invalid C#.
We therefore strip them ONLY when the snippet has no enclosing type
declaration (class / struct / interface / record / enum).
"""
if re.search(r"\b(class|struct|interface|record|enum)\b", code):
return code # real type present β leave modifiers intact
# Drop 'virtual'/'override' after an access modifier: 'public virtual int' -> 'public int'.
code = re.sub(r"\b(public|private|protected|internal)\s+(?:virtual|override)\s+",
r"\1 ", code)
# Drop a leading 'virtual'/'override' with no access modifier.
code = re.sub(r"(^|\n)(\s*)(?:virtual|override)\s+", r"\1\2", code)
return code
if __name__ == "__main__":
demo.queue(
default_concurrency_limit=1,
max_size=10,
).launch() |