Docs/issue 1661 add tip to source docs and update weaviate docs (#1662)

docs/website/docs/dlt-ecosystem/destinations/lancedb.md

@@ -144,7 +144,22 @@ lancedb_adapter(
 )
 ```
 
-Bear in mind that you can't use an adapter on a [dlt source](../../general-usage/source.md), only a [dlt resource](../../general-usage/resource.md).
+When using the `lancedb_adapter`, it's important to apply it directly to resources, not to the whole source. Here's an example:
+
+```py
+products_tables = sql_database().with_resources("products", "customers")
+
+pipeline = dlt.pipeline(
+        pipeline_name="postgres_to_lancedb_pipeline",
+        destination="lancedb",
+    )
+
+# apply adapter to the needed resources
+lancedb_adapter(products_tables.products, embed="description")
+lancedb_adapter(products_tables.customers, embed="bio")
+
+info = pipeline.run(products_tables)
+```
 
 ## Write disposition
 

docs/website/docs/dlt-ecosystem/destinations/qdrant.md

@@ -106,10 +106,25 @@ qdrant_adapter(
 )
 ```
 
-:::tip
+When using the `qdrant_adapter`, it's important to apply it directly to resources, not to the whole source. Here's an example:
 
-A more comprehensive pipeline would load data from some API or use one of dlt's [verified sources](../verified-sources/).
+```py
+products_tables = sql_database().with_resources("products", "customers")
+
+pipeline = dlt.pipeline(
+        pipeline_name="postgres_to_qdrant_pipeline",
+        destination="qdrant",
+    )
 
+# apply adapter to the needed resources
+qdrant_adapter(products_tables.products, embed="description")
+qdrant_adapter(products_tables.customers, embed="bio")
+
+info = pipeline.run(products_tables)
+```
+
+:::tip
+A more comprehensive pipeline would load data from some API or use one of dlt's [verified sources](../verified-sources/).
 :::
 
 ## Write disposition

docs/website/docs/dlt-ecosystem/destinations/weaviate.md

@@ -116,6 +116,22 @@ weaviate_adapter(
     tokenization={"title": "word", "description": "whitespace"},
 )
 ```
+When using the `weaviate_adapter`, it's important to apply it directly to resources, not to the whole source. Here's an example:  
+
+```py
+products_tables = sql_database().with_resources("products", "customers")
+
+pipeline = dlt.pipeline(
+        pipeline_name="postgres_to_weaviate_pipeline",
+        destination="weaviate",
+    )
+
+# apply adapter to the needed resources
+weaviate_adapter(products_tables.products, vectorize="description")
+weaviate_adapter(products_tables.customers, vectorize="bio")
+
+info = pipeline.run(products_tables)
+```    
 
 :::tip
 

docs/website/docs/general-usage/source.md

@@ -187,6 +187,26 @@ Several data sources are prone to contain semi-structured documents with very de
 MongoDB databases. Our practical experience is that setting the `max_nesting_level` to 2 or 3
 produces the clearest and human-readable schemas.
 
+:::tip
+The `max_table_nesting` parameter at the source level doesn't automatically apply to individual 
+resources when accessed directly (e.g., using `source.resources["resource_1"])`. To make sure it 
+works, either use `source.with_resources("resource_1")` or set the parameter directly on the resource.
+:::
+
+
+You can directly configure the `max_table_nesting` parameter on the resource level as:
+
+```py
+@dlt.resource(max_table_nesting=0)
+def my_resource():
+    ...
+```
+or
+```py
+my_source = source()
+my_source.my_resource.max_table_nesting = 0
+```
+
 ### Modify schema
 
 The schema is available via `schema` property of the source.