fix: update examples to use automatic env var support

Replace BrainusAI(api_key=os.getenv("BRAINUS_API_KEY")) with BrainusAI()
across async_patterns.py, batch_processing.py, error_handling.py,
fastapi_example.py, and flask_example.py. Remove unused import os.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

Author: 0xneobyte

examples/async_patterns.py

@@ -13,7 +13,6 @@
 
 import asyncio
 from brainus_ai import BrainusAI
-import os
 from typing import List, Dict
 
 
@@ -28,7 +27,7 @@ async def query_single(query: str, store_id: str = "default") -> Dict:
     Returns:
         Dict with query and result
     """
-    async with BrainusAI(api_key=os.getenv("BRAINUS_API_KEY")) as client:
+    async with BrainusAI() as client:
         result = await client.query(query=query, store_id=store_id)
         return {
             'query': query,
@@ -51,7 +50,7 @@ async def query_multiple(queries: List[str], store_id: str = "default") -> List[
     Returns:
         List of results
     """
-    async with BrainusAI(api_key=os.getenv("BRAINUS_API_KEY")) as client:
+    async with BrainusAI() as client:
         tasks = [
             client.query(query=q, store_id=store_id)
             for q in queries
@@ -103,7 +102,7 @@ async def query_with_fallback(query: str, fallback_stores: List[str]) -> Dict:
     Returns:
         Result from first successful store
     """
-    async with BrainusAI(api_key=os.getenv("BRAINUS_API_KEY")) as client:
+    async with BrainusAI() as client:
         for store_id in fallback_stores:
             try:
                 result = await client.query(query=query, store_id=store_id)

examples/batch_processing.py

@@ -16,7 +16,6 @@
 import pandas as pd
 from typing import List, Dict
 import asyncio
-import os
 from datetime import datetime
 
 
@@ -41,7 +40,7 @@ async def process_batch(
     results = []
     total_batches = (len(queries) + batch_size - 1) // batch_size
 
-    async with BrainusAI(api_key=os.getenv("BRAINUS_API_KEY")) as client:
+    async with BrainusAI() as client:
         for batch_num, i in enumerate(range(0, len(queries), batch_size), 1):
             batch = queries[i:i + batch_size]
 
@@ -150,7 +149,7 @@ async def process_with_progress(queries: List[str]) -> List[Dict]:
     """
     results = []
 
-    async with BrainusAI(api_key=os.getenv("BRAINUS_API_KEY")) as client:
+    async with BrainusAI() as client:
         for i, query in enumerate(queries, 1):
             try:
                 print(f"[{i}/{len(queries)}] Processing: {query[:50]}...")

examples/error_handling.py

@@ -20,7 +20,6 @@
     APIError
 )
 import asyncio
-import os
 from typing import Optional
 
 
@@ -35,7 +34,7 @@ async def basic_error_handling(query: str) -> Optional[dict]:
         Result dict or None on error
     """
     try:
-        async with BrainusAI(api_key=os.getenv("BRAINUS_API_KEY")) as client:
+        async with BrainusAI() as client:
             result = await client.query(query=query, store_id="default")
             return {
                 'answer': result.answer,
@@ -57,7 +56,7 @@ async def robust_query(query: str, max_retries: int = 3) -> Optional[dict]:
     Returns:
         Result dict or None on permanent failure
     """
-    async with BrainusAI(api_key=os.getenv("BRAINUS_API_KEY")) as client:
+    async with BrainusAI() as client:
         for attempt in range(max_retries):
             try:
                 result = await client.query(query=query, store_id="default")
@@ -138,7 +137,7 @@ async def query_with_fallback(query: str, fallback_answer: str = "Unable to proc
         Result dict with answer (from API or fallback)
     """
     try:
-        async with BrainusAI(api_key=os.getenv("BRAINUS_API_KEY")) as client:
+        async with BrainusAI() as client:
             result = await client.query(query=query, store_id="default")
             return {
                 'answer': result.answer,
@@ -184,7 +183,7 @@ async def validate_and_query(query: str) -> Optional[dict]:
 
     # Query with error handling
     try:
-        async with BrainusAI(api_key=os.getenv("BRAINUS_API_KEY")) as client:
+        async with BrainusAI() as client:
             result = await client.query(query=query, store_id="default")
             return {
                 'answer': result.answer,
@@ -210,7 +209,7 @@ async def batch_with_error_handling(queries: list[str]) -> list[dict]:
     """
     results = []
 
-    async with BrainusAI(api_key=os.getenv("BRAINUS_API_KEY")) as client:
+    async with BrainusAI() as client:
         for i, query in enumerate(queries, 1):
             print(f"\n[{i}/{len(queries)}] Processing: {query[:50]}...")
 

examples/fastapi_example.py

@@ -20,7 +20,6 @@
 from pydantic import BaseModel
 from typing import Optional, Dict, List
 from brainus_ai import BrainusAI, BrainusError
-import os
 from datetime import datetime
 
 app = FastAPI(
@@ -89,7 +88,7 @@ async def query_endpoint(
         HTTPException: On API errors
     """
     try:
-        async with BrainusAI(api_key=os.getenv("BRAINUS_API_KEY")) as client:
+        async with BrainusAI() as client:
             result = await client.query(
                 query=request.query,
                 store_id=request.store_id,

examples/flask_example.py

@@ -14,7 +14,6 @@
 
 from flask import Flask, request, jsonify
 from brainus_ai import BrainusAI, RateLimitError
-import os
 import asyncio
 
 app = Flask(__name__)
@@ -35,7 +34,7 @@ async def query_with_retry(query, store_id="default", max_retries=3):
     Raises:
         RateLimitError: If max retries exceeded
     """
-    async with BrainusAI(api_key=os.getenv("BRAINUS_API_KEY")) as client:
+    async with BrainusAI() as client:
         for attempt in range(max_retries):
             try:
                 return await client.query(query=query, store_id=store_id)