diff --git a/.env.dist b/.env.dist
index e9743d9..72768ba 100644
--- a/.env.dist
+++ b/.env.dist
@@ -1 +1,5 @@
 GOOGLE_APPLICATION_CREDENTIALS=credentials.json
+PORT=8000
+HOST=0.0.0.0
+BASIC_AUTH_USERNAME=admin
+BASIC_AUTH_PASSWORD=admin
\ No newline at end of file
diff --git a/app.py b/app.py
index 2c5dd2d..9de7fe9 100644
--- a/app.py
+++ b/app.py
@@ -1,12 +1,21 @@
+"""FastAPI application for Akern-Genai project.
+
+This module provides the web application with WebSocket support
+for streaming responses from the Gemini model.
+"""
+
 import os
 import logging
 from typing import Annotated
+
 from fastapi import FastAPI, Request, WebSocket, Depends, HTTPException, status
 from fastapi.security import HTTPBasic, HTTPBasicCredentials
 from fastapi.templating import Jinja2Templates
 from fastapi.staticfiles import StaticFiles
+
 from main import generate
 
+# Configure logging format and level
 logging.basicConfig(
     level=logging.INFO,
     format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
@@ -15,20 +24,26 @@ logging.basicConfig(
 
 logger = logging.getLogger(__name__)
 
+# Static files configuration
+STATIC_DIR: str = "static"
+TEMPLATES_DIR: str = "templates"
 
-STATIC_DIR = "static"
-TEMPLATES_DIR = "templates"
-
+# Security configuration
 security = HTTPBasic()
 
 
-app = FastAPI()
-app.mount(f"/{STATIC_DIR}", StaticFiles(directory=STATIC_DIR), name="static")
+def verify_credentials(credentials: HTTPBasicCredentials = Depends(security)) -> str:
+    """Verify HTTP Basic credentials against environment variables.
 
-templates = Jinja2Templates(directory=os.path.join(STATIC_DIR, TEMPLATES_DIR))
+    Args:
+        credentials: HTTP Basic authentication credentials.
 
+    Returns:
+        str: The authenticated username.
 
-def verify_credentials(credentials: HTTPBasicCredentials = Depends(security)):
+    Raises:
+        HTTPException: If credentials are invalid.
+    """
     correct_username = os.getenv("BASIC_AUTH_USERNAME")
     correct_password = os.getenv("BASIC_AUTH_PASSWORD")
 
@@ -44,13 +59,34 @@ def verify_credentials(credentials: HTTPBasicCredentials = Depends(security)):
     return credentials.username
 
 
+# Initialize FastAPI application
+app = FastAPI()
+app.mount(f"/{STATIC_DIR}", StaticFiles(directory=STATIC_DIR), name="static")
+
+templates = Jinja2Templates(directory=os.path.join(STATIC_DIR, TEMPLATES_DIR))
+
+
 @app.get("/")
 async def home(request: Request, username: Annotated[str, Depends(verify_credentials)]):
+    """Render the main index page.
+
+    Args:
+        request: The incoming request object.
+        username: The authenticated username from HTTP Basic auth.
+
+    Returns:
+        TemplateResponse: The rendered HTML template.
+    """
     return templates.TemplateResponse("index.html", {"request": request})
 
 
 @app.websocket("/ws")
 async def websocket_endpoint(websocket: WebSocket):
+    """Handle WebSocket connections for streaming responses.
+
+    Args:
+        websocket: The WebSocket connection.
+    """
     await websocket.accept()
     while True:
         data = await websocket.receive_text()
diff --git a/main.py b/main.py
index f10a67e..eb2ab9a 100644
--- a/main.py
+++ b/main.py
@@ -1,19 +1,39 @@
+"""Google Gemini API integration for Akern-Genai project.
+
+This module provides functionality to generate content using Google's Gemini model
+with Vertex AI RAG (Retrieval-Augmented Generation) support.
+"""
+
 from google import genai
 from google.genai import types
 from dotenv import load_dotenv
 
-
+# Load environment variables from .env file
 load_dotenv()
 
-CORPUS = "projects/520464122471/locations/europe-west3/ragCorpora/2305843009213693952"
+# Vertex AI RAG Corpus resource path
+CORPUS: str = "projects/520464122471/locations/europe-west3/ragCorpora/2305843009213693952"
+
+# Gemini model name
+GEMINI_MODEL: str = "gemini-3-pro-preview"
 
 
 def generate(prompt: str):
+    """Generate content using Gemini model with RAG retrieval.
+
+    This function creates a streaming response from the Gemini model,
+    augmented with content from the configured RAG corpus.
+
+    Args:
+        prompt: The user's input prompt to generate content for.
+
+    Yields:
+        str: Text chunks from the generated response.
+    """
     client = genai.Client(
         vertexai=True,
     )
 
-    model = "gemini-3-pro-preview"
     contents = [
         types.Content(role="user", parts=[types.Part.from_text(text=prompt)]),
     ]
@@ -21,7 +41,8 @@ def generate(prompt: str):
         types.Tool(
             retrieval=types.Retrieval(
                 vertex_rag_store=types.VertexRagStore(
-                    rag_resources=[types.VertexRagStoreRagResource(rag_corpus=CORPUS)],
+                    rag_resources=[
+                        types.VertexRagStoreRagResource(rag_corpus=CORPUS)],
                 )
             )
         )
@@ -32,14 +53,16 @@ def generate(prompt: str):
         top_p=0.95,
         max_output_tokens=65535,
         safety_settings=[
-            types.SafetySetting(category="HARM_CATEGORY_HATE_SPEECH", threshold="OFF"),
+            types.SafetySetting(
+                category="HARM_CATEGORY_HATE_SPEECH", threshold="OFF"),
             types.SafetySetting(
                 category="HARM_CATEGORY_DANGEROUS_CONTENT", threshold="OFF"
             ),
             types.SafetySetting(
                 category="HARM_CATEGORY_SEXUALLY_EXPLICIT", threshold="OFF"
             ),
-            types.SafetySetting(category="HARM_CATEGORY_HARASSMENT", threshold="OFF"),
+            types.SafetySetting(
+                category="HARM_CATEGORY_HARASSMENT", threshold="OFF"),
         ],
         tools=tools,
         thinking_config=types.ThinkingConfig(
@@ -48,7 +71,7 @@ def generate(prompt: str):
     )
 
     for chunk in client.models.generate_content_stream(
-        model=model,
+        model=GEMINI_MODEL,
         contents=contents,
         config=generate_content_config,
     ):