TutorTask696: Align code with coding guidelines

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Author: indrayudd

agentic_eda/jupyterlab_extension_backend/README.md

@@ -0,0 +1,19 @@
+# JupyterLab Extension Backend
+
+Run the backend entrypoint from this directory:
+
+```bash
+cd /Users/indro/src/tutorials1/agentic_eda/jupyterlab_extension_backend
+python -m src.main \
+  --mode integrity \
+  --path /Users/indro/src/tutorials1/agentic_eda/jupyterlab_extension_backend/datasets/T1_slice.csv
+```
+
+If you run from a different directory, set `PYTHONPATH`:
+
+```bash
+PYTHONPATH=/Users/indro/src/tutorials1/agentic_eda/jupyterlab_extension_backend \
+python -m src.main \
+  --mode integrity \
+  --path /Users/indro/src/tutorials1/agentic_eda/jupyterlab_extension_backend/datasets/T1_slice.csv
+```

agentic_eda/jupyterlab_extension_backend/config/config.py

@@ -1,133 +1,128 @@
-import os
+"""
+Import as:
+
+import config.config as cconf
+"""
+
 import dataclasses
 import functools
-import pydantic
+import os
 
 import dotenv
+import langchain_anthropic
+import langchain_google_genai
 import langchain_openai
-import langchain_anthropic # ChatAnthropic
-import langchain_google_genai # ChatGoogleGenerativeAI
-# import langchain_groq # ChatGroq
-# import langchain_mistralai # ChatMistralAI
-# import langchain_ollama # ChatOllama
-
+import pydantic
 
 dataclass = dataclasses.dataclass
 lru_cache = functools.lru_cache
 ChatOpenAI = langchain_openai.ChatOpenAI
 ChatAnthropic = langchain_anthropic.ChatAnthropic
 ChatGoogleGenerativeAI = langchain_google_genai.ChatGoogleGenerativeAI
-# ChatGroq = langchain_groq.ChatGroq
-# ChatMistralAI = langchain_mistralai.ChatMistralAI
-# ChatOllama = langchain_ollama.ChatOllama
 SecretStr = pydantic.SecretStr
 
-# Load Variables
 dotenv.load_dotenv()
 
 
-# Immutable data class
 @dataclass(frozen=True)
 class Settings:
+    """
+    Store model provider settings.
+    """
+
     provider: str
     model: str
     temperature: float
     timeout: float
     max_retries: int
 
-def _need(name:str) -> str:
-    v = os.getenv(name)
-    if v is None or v == "":
+
+def _need(name: str) -> str:
+    """
+    Read a required environment variable.
+
+    :param name: environment variable name
+    :return: environment variable value
+    """
+    value = os.getenv(name)
+    if value is None or value == "":
         raise RuntimeError(f"Missing required environment variable: {name}")
-    return v
+    return value
+
 
 @lru_cache(maxsize=1)
 def get_settings() -> Settings:
-    return Settings(
+    """
+    Build settings from environment variables.
+
+    :return: configured settings
+    """
+    settings = Settings(
         provider=os.getenv("LLM_PROVIDER", "openai"),
         model=os.getenv("LLM_MODEL", "gpt-5-nano"),
         temperature=float(os.getenv("LLM_TEMP", 0.2)),
         timeout=float(os.getenv("LLM_TIMEOUT", 60)),
         max_retries=int(os.getenv("LLM_MAX_RETRIES", 2)),
-
     )
+    return settings
 
-@lru_cache(maxsize=1)
-def get_chat_model(model=get_settings().model):
-    s = get_settings()
-
-    # OpenAI-adjacent
 
-    if s.provider == "openai":
-
-        # READ API KEY.
+@lru_cache(maxsize=1)
+def get_chat_model(*, model: str | None = None) -> object:
+    """
+    Build the configured chat model client.
+
+    :param model: optional model override
+    :return: langchain chat model client
+    """
+    settings = get_settings()
+    model_name = settings.model if model is None else model
+    provider = settings.provider
+    if provider == "openai":
         _need("OPENAI_API_KEY")
-
-        # Return the chatmodel
-
-        return ChatOpenAI(
-            model=s.model,
-            temperature=s.temperature,
-            timeout=s.timeout,
-            max_retries=s.max_retries,
+        chat_model = ChatOpenAI(
+            model=model_name,
+            temperature=settings.temperature,
+            timeout=settings.timeout,
+            max_retries=settings.max_retries,
         )
-    
-    if s.provider == "openai_compatible":
-
-        # Secrets.
+    elif provider == "openai_compatible":
         base_url = _need("OPENAI_COMPAT_BASE_URL")
         api_key = _need("OPENAI_COMPAT_API_KEY")
-        return ChatOpenAI(
-            model=model,
+        chat_model = ChatOpenAI(
+            model=model_name,
             base_url=base_url,
             api_key=SecretStr(api_key),
-            temperature=s.temperature,
-            timeout=s.timeout,
-            max_retries=s.max_retries,
-
+            temperature=settings.temperature,
+            timeout=settings.timeout,
+            max_retries=settings.max_retries,
         )
-    
-    if s.provider == "azure_openai_v1":
-
-        # Secrets.
+    elif provider == "azure_openai_v1":
         azure_base = _need("AZURE_OPENAI_BASE_URL")
         azure_key = SecretStr(_need("AZURE_OPENAI_API_KEY"))
-
-        return ChatOpenAI(
-            model=s.model,
+        chat_model = ChatOpenAI(
+            model=model_name,
             base_url=azure_base,
             api_key=azure_key,
-            temperature=s.temperature,
-            timeout=s.timeout,
-            max_retries=s.max_retries,
-
+            temperature=settings.temperature,
+            timeout=settings.timeout,
+            max_retries=settings.max_retries,
         )
-
-    # Anthropic 
-    
-    if s.provider == "anthropic":
-
-        # Secrets.
-        _need("ANTHROPIC_API_KEY") 
-        return ChatAnthropic(
-            model_name=s.model,
-            temperature=s.temperature,
-            timeout=s.timeout,
-            max_retries=s.max_retries,
-            stop=None
-            )
-    
-    # Google
-    if s.provider in ("google", "gemini", "google_genai"):
-        # Secrets.
+    elif provider == "anthropic":
+        _need("ANTHROPIC_API_KEY")
+        chat_model = ChatAnthropic(
+            model_name=model_name,
+            temperature=settings.temperature,
+            timeout=settings.timeout,
+            max_retries=settings.max_retries,
+            stop=None,
+        )
+    elif provider in ("google", "gemini", "google_genai"):
         _need("GOOGLE_API_KEY")
-        return ChatGoogleGenerativeAI(
-            model=s.model,
-            temperature=s.temperature,
+        chat_model = ChatGoogleGenerativeAI(
+            model=model_name,
+            temperature=settings.temperature,
         )
-
-
-
-
-    
-    raise ValueError("TODO(*): expand support!")
+    else:
+        raise ValueError(f"Unsupported provider='{provider}'")
+    return chat_model