Initial commit

app.py

@@ -25,22 +25,22 @@ logger.debug("Loading CodeT5-base model")
 try:
     code_tokenizer = AutoTokenizer.from_pretrained("Salesforce/codeT5-base", cache_dir="/tmp/hf_cache")
     code_model = AutoModelForSeq2SeqLM.from_pretrained("Salesforce/codeT5-base", cache_dir="/tmp/hf_cache")
-    code_gen = pipeline("text2text-generation", model=code_model, tokenizer=code_tokenizer, max_length=512, device=-1)
+    code_gen = pipeline("text2text-generation", model=code_model, tokenizer=code_tokenizer, max_length=768, device=-1)
     logger.debug("CodeT5-base model loaded")
 except Exception as e:
     logger.error(f"Failed to load CodeT5-base: {e}")
     raise
 
 # لود مدل ترجمه
-logger.debug("Loading Helsinki-NLP/opus-mt-fa-en model")
+logger.debug("Loading Helsinki-NLP/opus-mt-fas-en model")
 try:
-    translate_tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-fa-en", cache_dir="/tmp/hf_cache")
-    translate_model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-fa-en", cache_dir="/tmp/hf_cache")
+    translate_tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-fas-en", cache_dir="/tmp/hf_cache")
+    translate_model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-fas-en", cache_dir="/tmp/hf_cache")
     translate_gen = pipeline("translation", model=translate_model, tokenizer=translate_tokenizer, max_length=300)
-    logger.debug("Helsinki-NLP/opus-mt-fa-en model loaded")
+    logger.debug("Helsinki-NLP/opus-mt-fas-en model loaded")
 except Exception as e:
     logger.error(f"Failed to load translation model: {e}")
-    raise
+    translate_gen = None  # Fallback: اگه مدل ترجمه لود نشد، از ورودی خام استفاده می‌کنیم
 
 # آزادسازی حافظه
 import gc
@@ -82,8 +82,7 @@ def save_to_memory(user_input, task_type, prompt, response):
             logger.debug("Saved to DB")
     except Exception as e:
         logger.error(f"DB Save Error: {e}")
-        # نذار خطای دیتابیس جلوی ادامه کار رو بگیره
-        pass
+        pass  # نذار خطای دیتابیس جلوی ادامه کار رو بگیره
 
 # دریافت تاریخچه
 def get_history():
@@ -113,11 +112,14 @@ def get_history():
 def debug_models(text, language):
     logger.debug(f"Debugging models with input: {text}, language: {language}")
     try:
-        translated = translate_gen(text, max_length=300)[0]['translation_text']
+        if translate_gen:
+            translated = translate_gen(text, max_length=300)[0]['translation_text']
+        else:
+            translated = text  # Fallback: اگه ترجمه کار نکرد، از ورودی خام استفاده کن
         logger.debug(f"Translated text: {translated}")
         prompt = f"Write a complete, correct, and well-explained code in {language} to: {translated}"
         logger.debug(f"Generated prompt: {prompt}")
-        code_output = code_gen(prompt, max_length=512, num_beams=5)[0]['generated_text']
+        code_output = code_gen(prompt, max_length=768, num_beams=5, do_sample=False)[0]['generated_text']
         logger.debug(f"Generated code: {code_output}")
         return f"Debug: Translation: {translated}\nPrompt: {prompt}\nCode: {code_output}"
     except Exception as e:
@@ -128,19 +130,24 @@ def debug_models(text, language):
 def translate_and_prompt(text, language):
     logger.debug(f"Translating input: {text}")
     try:
-        translated = translate_gen(text, max_length=300)[0]['translation_text']
+        if translate_gen:
+            translated = translate_gen(text, max_length=300)[0]['translation_text']
+        else:
+            translated = text  # Fallback: اگه ترجمه کار نکرد، از ورودی خام استفاده کن
         logger.debug(f"Translated text: {translated}")
         prompt = f"Write a complete, correct, and well-explained code in {language} to: {translated}"
         return prompt
     except Exception as e:
         logger.error(f"Translation error: {e}")
-        return f"Translation error: {e}"
+        prompt = f"Write a complete, correct, and well-explained code in {language} to: {text}"
+        logger.debug(f"Fallback prompt: {prompt}")
+        return prompt
 
 # تولید کد
 def generate_code(prompt):
     logger.debug(f"Generating code with prompt: {prompt}")
     try:
-        result = code_gen(prompt, max_length=512, num_beams=5, do_sample=False)
+        result = code_gen(prompt, max_length=768, num_beams=5, do_sample=False)
         code_output = result[0]['generated_text']
         if not code_output.strip():
             logger.warning("Generated code is empty")