refactor: replace .getenv with .environ

app.py

@@ -10,11 +10,11 @@ import base64
 from memory_store import MemoryStore
 import logging
 
-load_dotenv()
-dsn = os.getenv("DB_URL")
-schema = os.getenv("DB_SCHEMA")
-
-print("DEBUG: DB_URL =", os.getenv("DB_URL"))
+# load_dotenv()
+# dsn = os.environ["DB_URL"]
+# schema = os.environ["DB_SCHEMA"]
+#
+# print("DEBUG: DB_URL =", os.environ["DB_URL"])
 
 # ======================================= Load DB configs
 def load_db_configs():
@@ -45,7 +45,7 @@ async def run_agent(request, history=None):
         # Handle image processing
         image_path = ""
         load_dotenv()
-        PANDAS_EXPORTS_PATH = os.getenv("PANDAS_EXPORTS_PATH", "exports/charts")
+        PANDAS_EXPORTS_PATH = os.environ["PANDAS_EXPORTS_PATH"]
         
         # Ensure the exports directory exists
         os.makedirs(PANDAS_EXPORTS_PATH, exist_ok=True)

langchain_mcp_client.py

@@ -39,16 +39,16 @@ async def lc_mcp_exec(request: str, history=None) -> Tuple[str, list]:
 
         # Initialize the LLM for OpenAI
         # llm = init_chat_model(
-        #     model_provider=os.getenv("OPENAI_MODEL_PROVIDER"), 
-        #     model=os.getenv("OPENAI_MODEL"), 
-        #     api_key=os.getenv("OPENAI_API_KEY")
+        #     model_provider=os.environ["OPENAI_MODEL_PROVIDER"],
+        #     model=os.environ["OPENAI_MODEL"],
+        #     api_key=os.environ["OPENAI_API_KEY"]
         # )
 
         # Initialize the LLM for Gemini
         llm = init_chat_model(
-            model_provider=os.getenv("GEMINI_MODEL_PROVIDER"), 
-            model=os.getenv("GEMINI_MODEL"), 
-            api_key=os.getenv("GEMINI_API_KEY")
+            model_provider=os.environ["GEMINI_MODEL_PROVIDER"],
+            model=os.environ["GEMINI_MODEL"],
+            api_key=os.environ["GEMINI_API_KEY"]
         )
 
         # Initialize the MCP client

postgre_mcp_server.py

@@ -40,10 +40,10 @@ async def db_lifespan(server: FastMCP) -> AsyncIterator[DbContext]:
     """Manage database connection lifecycle"""
     # Initialize DB connection from environment variables
     load_dotenv()
-    dsn = os.getenv("DB_URL")
-    schema = os.getenv("DB_SCHEMA")
+    dsn = os.environ["DB_URL"]
+    schema = os.environ["DB_SCHEMA"]
     
-    print("DEBUG: DB_URL =", os.getenv("DB_URL"))
+    print("DEBUG: DB_URL =", os.environ["DB_URL"])
 
     pool = await asyncpg.create_pool(
         dsn,
@@ -327,7 +327,7 @@ async def list_tables() -> str:
 async def get_table_schema(table_name: str) -> str:
     """Get schema information for a specific table"""
     try:
-        schema = os.getenv("DB_SCHEMA")
+        schema = os.environ["DB_SCHEMA"]
 
         async with db_lifespan(mcp) as db_ctx:
             columns = await get_table_schema_info(db_ctx.pool, schema, table_name)
@@ -350,7 +350,7 @@ def get_foreign_keys(table_name: str) -> str:
         table_name: The name of the table to get foreign keys from
         schema: The schema name (defaults to 'public')
     """
-    schema = os.getenv("DB_SCHEMA")
+    schema = os.environ["DB_SCHEMA"]
 
     sql = """
     SELECT 
@@ -380,7 +380,7 @@ def get_foreign_keys(table_name: str) -> str:
 async def get_all_schemas() -> str:
     """Get schema information for all tables in the database"""
     try:
-        schema = os.getenv("DB_SCHEMA")
+        schema = os.environ["DB_SCHEMA"]
 
         async with db_lifespan(mcp) as db_ctx:
             tables = await get_all_tables(db_ctx.pool, db_ctx.schema)
@@ -450,7 +450,7 @@ async def generate_analytical_query(table_name: str) -> list[PromptMessage]:
         table_name: The name of the table to generate analytical queries for
     """
     load_dotenv()
-    schema = os.getenv("DB_SCHEMA")
+    schema = os.environ["DB_SCHEMA"]
     try:
         async with db_lifespan(mcp) as db_ctx:
             pool = db_ctx.pool
@@ -631,14 +631,14 @@ async def visualize_results(json_data: dict, vis_prompt: str) -> str:
 
         # Load api key
         load_dotenv()
-        api_key = os.environ.get("PANDAS_KEY")
+        api_key = os.environ["PANDAS_KEY"]
         pai.api_key.set(api_key)
 
         # Generate visualization
         df_ai.chat(vis_prompt)
 
         # Get the visualization path
-        PANDAS_EXPORTS_PATH = os.getenv("PANDAS_EXPORTS_PATH")
+        PANDAS_EXPORTS_PATH = os.environ["PANDAS_EXPORTS_PATH"]
         generated_files = [f for f in os.listdir(PANDAS_EXPORTS_PATH) if f.startswith("temp_chart")]
         if generated_files:
             visualization_path = os.path.join(PANDAS_EXPORTS_PATH, generated_files[0])