diff --git a/test_websearch_chat_completion.py b/test_websearch_chat_completion.py
new file mode 100644
index 0000000000..e572e4d860
--- /dev/null
+++ b/test_websearch_chat_completion.py
@@ -0,0 +1,136 @@
+"""
+Test script for WebSearch interception with chat completions API.
+
+This script demonstrates how to use the websearch_interception callback
+with litellm.acompletion() for transparent server-side web search execution.
+"""
+import asyncio
+import litellm
+
+# Enable verbose logging to see what's happening
+litellm.set_verbose = True
+
+
+async def test_websearch_chat_completion():
+    """Test websearch interception with chat completions API."""
+    
+    # Configure WebSearch interception
+    litellm.callbacks = ["websearch_interception"]
+    
+    print("\n" + "="*80)
+    print("Testing WebSearch Interception with Chat Completions API")
+    print("="*80 + "\n")
+    
+    # User makes a simple completion call with tools
+    print("Making request to GPT-4o with litellm_web_search tool...")
+    print("Question: What's the weather in San Francisco today?")
+    print("\nExpected behavior:")
+    print("1. Model calls litellm_web_search tool")
+    print("2. Server executes web search automatically")
+    print("3. Server makes follow-up request with search results")
+    print("4. User gets final answer\n")
+    
+    response = await litellm.acompletion(
+        model="gpt-4o",
+        messages=[
+            {"role": "user", "content": "What's the weather in San Francisco today?"}
+        ],
+        tools=[
+            {
+                "type": "function",
+                "function": {
+                    "name": "litellm_web_search",
+                    "description": "Search the web for information",
+                    "parameters": {
+                        "type": "object",
+                        "properties": {
+                            "query": {"type": "string", "description": "Search query"}
+                        },
+                        "required": ["query"]
+                    }
+                }
+            }
+        ]
+    )
+    
+    print("\n" + "-"*80)
+    print("FINAL RESPONSE:")
+    print("-"*80)
+    print(f"\nContent: {response.choices[0].message.content}")
+    print(f"\nFinish reason: {response.choices[0].finish_reason}")
+    
+    # Check if we got tool_calls (should NOT if agentic loop worked)
+    if hasattr(response.choices[0].message, 'tool_calls') and response.choices[0].message.tool_calls:
+        print("\n⚠️  WARNING: Got tool_calls in response!")
+        print("This means the agentic loop did NOT execute automatically.")
+        print(f"Tool calls: {response.choices[0].message.tool_calls}")
+    else:
+        print("\n✅ SUCCESS: No tool_calls in response!")
+        print("The agentic loop executed automatically and returned the final answer.")
+    
+    print("\n" + "="*80 + "\n")
+
+
+async def test_streaming_websearch():
+    """Test websearch interception with streaming."""
+    
+    # Configure WebSearch interception
+    litellm.callbacks = ["websearch_interception"]
+    
+    print("\n" + "="*80)
+    print("Testing WebSearch Interception with STREAMING")
+    print("="*80 + "\n")
+    
+    print("Making STREAMING request to GPT-4o with litellm_web_search tool...")
+    print("Question: What are the latest AI news?")
+    
+    response = await litellm.acompletion(
+        model="gpt-4o",
+        messages=[
+            {"role": "user", "content": "What are the latest AI news from today?"}
+        ],
+        tools=[
+            {
+                "type": "function",
+                "function": {
+                    "name": "litellm_web_search",
+                    "description": "Search the web for information",
+                    "parameters": {
+                        "type": "object",
+                        "properties": {
+                            "query": {"type": "string"}
+                        }
+                    }
+                }
+            }
+        ],
+        stream=True
+    )
+    
+    print("\n" + "-"*80)
+    print("STREAMING RESPONSE:")
+    print("-"*80 + "\n")
+    
+    full_content = ""
+    async for chunk in response:
+        if hasattr(chunk.choices[0].delta, 'content') and chunk.choices[0].delta.content:
+            content = chunk.choices[0].delta.content
+            print(content, end="", flush=True)
+            full_content += content
+    
+    print("\n\n✅ Streaming completed successfully!")
+    print(f"Total content length: {len(full_content)} chars")
+    print("\n" + "="*80 + "\n")
+
+
+if __name__ == "__main__":
+    print("\nWebSearch Interception Test Suite")
+    print("==================================\n")
+    print("This test demonstrates transparent server-side web search execution.")
+    print("The agentic loop happens automatically - user just gets the final answer.\n")
+    
+    # Run tests
+    asyncio.run(test_websearch_chat_completion())
+    
+    # Uncomment to test streaming
+    # asyncio.run(test_streaming_websearch())