cleanup

README.md

@@ -28,11 +28,11 @@ The main MCP function is `retrieve_mcp` which provides a top_k retrieval and rer
 - `answer_metadata`: Document metadata
 - `score`: Relevance score [disabled when reranker used]
 
-
+**Example useage**:
 ```python
 from gradio_client import Client
 
-client = Client("https://mtyrrell-chatfed-retriever.hf.space/")
+client = Client("ENTER CONTAINER URL / SPACE ID")
 result = client.predict(
 		query="...",
 		reports_filter="",
@@ -44,7 +44,7 @@ result = client.predict(
 print(result)
 ```
 
-## ⚙️ Configuration
+## Configuration
 
 ### Vector Store Configuration
 1. Set your data source according to the provider
@@ -58,27 +58,4 @@ docker build -t chatfed-retriever .
 docker run -p 7860:7860 chatfed-retriever
 ```
 
-6. Test connection
-
-```python
-from gradio_client import Client
-
-def test_retrieve_mcp():
-    client = Client("ENTER CONTAINER URL")
-    
-    # Make a simple query
-    result = client.predict(
-        query="Return all audit reports relating to climate change?",
-        reports_filter="",
-        sources_filter="",
-        subtype_filter="",
-        year_filter="",
-        api_name="/retrieve_mcp"
-    )
-    
-    print(result)
-
-if __name__ == "__main__":
-    test_retrieve_mcp()
-```