Update appv2.py

appv2.py

@@ -1,153 +1,141 @@
-from __future__ import annotations
-
-from langchain_core.output_parsers import StrOutputParser
-from langchain_core.prompts import PromptTemplate
-from langchain_community.llms import LlamaCpp
-
-import ast
-import atexit
-import os
-import re
-import sys
-
-FENCE_RE = re.compile(r"```(?:python)?\s*([\s\S]*?)\s*```", flags=re.IGNORECASE)
-TRAILING_PARENS_RE = re.compile(r"\)\)\s*$", flags=re.MULTILINE)
-
-# Install (Python env):
-# - pip install langchain langchain-community
-# - pip install llama-cpp-python
-# - pip install gpt4all   (optional: if using LLM_BACKEND=gpt4all) $env:LLM_BACKEND='gpt4all'
-
-
-def _force_utf8_stdio() -> None:
-    try:
-        if hasattr(sys.stdout, "reconfigure"):
-            sys.stdout.reconfigure(encoding="utf-8")
-        if hasattr(sys.stderr, "reconfigure"):
-            sys.stderr.reconfigure(encoding="utf-8")
-    except Exception:
-        pass
-
-# =====================
-# Config
-# =====================
-MODEL_FILE = "Cube-Python_v2.gguf"
-N_CTX = 4096
-TEMPERATURE = 0.1
-N_GPU_LAYERS = -1  # llama.cpp: -1 = try push all to GPU, set 0 to force CPU
-
-LLM_BACKEND = os.getenv("LLM_BACKEND", "llamacpp").strip().lower()
-MAX_FIX_ATTEMPTS = 2
-
-def load_llm():
-    base_path = os.path.dirname(os.path.abspath(__file__))
-    model_path = os.path.join(base_path, MODEL_FILE)
-    
-    if not os.path.exists(model_path):
-        raise FileNotFoundError(f"Không tìm thấy file model tại: {model_path}")
-
-    if LLM_BACKEND in {"gpt4all", "gpt4allcpp"}:
-        try:
-            from langchain_community.llms import GPT4All
-        except Exception as e:
-            raise RuntimeError(
-                "Chưa cài GPT4All cho LangChain. Cài bằng:\n"
-                "  pip install gpt4all langchain-community\n"
-                f"Chi tiết: {e}"
-            )
-
-        return GPT4All(model=model_path, temp=TEMPERATURE, verbose=False)
-
-    return LlamaCpp(
-        model_path=model_path,
-        n_gpu_layers=N_GPU_LAYERS,
-        n_ctx=N_CTX,
-        temperature=TEMPERATURE,
-        verbose=False,  # Tắt log rác
-    )
-
-def close_llm_safely(llm):
-    try:
-        client = getattr(llm, "client", None)
-        close = getattr(client, "close", None)
-        if callable(close):
-            close()
-    except Exception:
-        pass
-
-def extract_python_code(text: str) -> str:
-    if not text:
-        return ""
-
-    m = FENCE_RE.search(text)
-    if m:
-        return m.group(1).strip()
-
-    return text.strip()
-
-def _syntax_error_message(code: str) -> str | None:
-    try:
-        ast.parse(code)
-        return None
-    except SyntaxError:
-        # Re-parse to get rich info (cheap vs model inference, and avoids duplicate logic).
-        try:
-            ast.parse(code)
-            return None
-        except SyntaxError as e:
-            line = (e.text or "").strip()
-            where = f"line {e.lineno}, col {e.offset}" if e.lineno and e.offset else "unknown location"
-            return f"{e.msg} ({where}). Offending line: {line}"
-
-
-def is_valid_python(code: str) -> bool:
-    return _syntax_error_message(code) is None
-
-
-def generate_code(chain, question: str) -> str:
-    raw = chain.invoke({"question": question})
-    code = extract_python_code(raw)
-
-    for _ in range(MAX_FIX_ATTEMPTS):
-        err = _syntax_error_message(code)
-        if err is None:
-            return code
-
-        raw = chain.invoke(
-            {
-                "question": (
-                    "Output trước bị sai cú pháp Python.\n"
-                    f"Lỗi: {err}\n\n"
-                    f"Output trước:\n{raw}\n\n"
-                    "Hãy trả lại code Python ĐÚNG cú pháp, chỉ code, không markdown."
-                )
-            }
-        )
-        code = extract_python_code(raw)
-
-    code2 = TRAILING_PARENS_RE.sub(")", code)
-    return code2 if is_valid_python(code2) else code
-
-template = """[INST] Bạn là một trợ lý AI chuyên nghiệp về lập trình Python.
-Hãy viết code Python chất lượng cao để giải quyết yêu cầu sau.
-Chỉ trả lời bằng code Python thuần (KHÔNG markdown, KHÔNG giải thích).
-Yêu cầu: {question} [/INST]"""
-
-prompt = PromptTemplate(input_variables=["question"], template=template)
-
-_force_utf8_stdio()
-llm = load_llm()
-atexit.register(close_llm_safely, llm)
-chain = prompt | llm | StrOutputParser()
-
-question = '''
-Write a Python program that extracts all email addresses from a given text.
-Input:
-A text: "Contact us at support@nlp.com or info@textprocessing.ai for more details."
-Desired Output:
-['support@nlp.com', 'info@textprocessing.ai']'''
-
-try:
-    print(generate_code(chain, question))
-finally:
+from __future__ import annotations
+
+from langchain_core.output_parsers import StrOutputParser
+from langchain_core.prompts import PromptTemplate
+
+import ast
+import atexit
+import os
+import re
+import sys
+
+FENCE_RE = re.compile(r"```(?:python)?\s*([\s\S]*?)\s*```", flags=re.IGNORECASE)
+TRAILING_PARENS_RE = re.compile(r"\)\)\s*$", flags=re.MULTILINE)
+
+# Install (Python env):
+# - pip install langchain langchain-community
+# - pip install gpt4all
+
+
+def _force_utf8_stdio() -> None:
+    try:
+        if hasattr(sys.stdout, "reconfigure"):
+            sys.stdout.reconfigure(encoding="utf-8")
+        if hasattr(sys.stderr, "reconfigure"):
+            sys.stderr.reconfigure(encoding="utf-8")
+    except Exception:
+        pass
+
+# =====================
+# Config
+# =====================
+MODEL_FILE = "Cube-Python_v2.gguf"
+N_CTX = 4096
+TEMPERATURE = 0.1
+N_GPU_LAYERS = -1  # llama.cpp: -1 = try push all to GPU, set 0 to force CPU
+
+MAX_FIX_ATTEMPTS = 2
+
+def load_llm():
+    base_path = os.path.dirname(os.path.abspath(__file__))
+    model_path = os.path.join(base_path, MODEL_FILE)
+    
+    if not os.path.exists(model_path):
+        raise FileNotFoundError(f"Không tìm thấy file model tại: {model_path}")
+
+    try:
+        from langchain_community.llms import GPT4All
+    except Exception as e:
+        raise RuntimeError(
+            "Chưa cài GPT4All cho LangChain. Cài bằng:\n"
+            "  pip install gpt4all langchain-community\n"
+            f"Chi tiết: {e}"
+        )
+
+    return GPT4All(model=model_path, temp=TEMPERATURE, verbose=False)
+
+def close_llm_safely(llm):
+    try:
+        client = getattr(llm, "client", None)
+        close = getattr(client, "close", None)
+        if callable(close):
+            close()
+    except Exception:
+        pass
+
+def extract_python_code(text: str) -> str:
+    if not text:
+        return ""
+
+    m = FENCE_RE.search(text)
+    if m:
+        return m.group(1).strip()
+
+    return text.strip()
+
+def _syntax_error_message(code: str) -> str | None:
+    try:
+        ast.parse(code)
+        return None
+    except SyntaxError:
+        # Re-parse to get rich info (cheap vs model inference, and avoids duplicate logic).
+        try:
+            ast.parse(code)
+            return None
+        except SyntaxError as e:
+            line = (e.text or "").strip()
+            where = f"line {e.lineno}, col {e.offset}" if e.lineno and e.offset else "unknown location"
+            return f"{e.msg} ({where}). Offending line: {line}"
+
+
+def is_valid_python(code: str) -> bool:
+    return _syntax_error_message(code) is None
+
+
+def generate_code(chain, question: str) -> str:
+    raw = chain.invoke({"question": question})
+    code = extract_python_code(raw)
+
+    for _ in range(MAX_FIX_ATTEMPTS):
+        err = _syntax_error_message(code)
+        if err is None:
+            return code
+
+        raw = chain.invoke(
+            {
+                "question": (
+                    "Output trước bị sai cú pháp Python.\n"
+                    f"Lỗi: {err}\n\n"
+                    f"Output trước:\n{raw}\n\n"
+                    "Hãy trả lại code Python ĐÚNG cú pháp, chỉ code, không markdown."
+                )
+            }
+        )
+        code = extract_python_code(raw)
+
+    code2 = TRAILING_PARENS_RE.sub(")", code)
+    return code2 if is_valid_python(code2) else code
+
+template = """[INST] Bạn là một trợ lý AI chuyên nghiệp về lập trình Python.
+Hãy viết code Python chất lượng cao để giải quyết yêu cầu sau.
+Chỉ trả lời bằng code Python thuần (KHÔNG markdown, KHÔNG giải thích).
+Yêu cầu: {question} [/INST]"""
+
+prompt = PromptTemplate(input_variables=["question"], template=template)
+
+_force_utf8_stdio()
+llm = load_llm()
+atexit.register(close_llm_safely, llm)
+chain = prompt | llm | StrOutputParser()
+
+question = '''
+Write a Python program that extracts all email addresses from a given text.
+Input:
+A text: "Contact us at support@nlp.com or info@textprocessing.ai for more details."
+Desired Output:
+['support@nlp.com', 'info@textprocessing.ai']'''
+
+try:
+    print(generate_code(chain, question))
+finally:
     close_llm_safely(llm)