perf: build debug log messages lazily so disabled debug logs cost nothing (#27834)

GLOBAL_LOG_LEVEL defaults to INFO, so every log.debug(...) in the backend is discarded, but the message is built first: 187 call sites interpolate their payload into an f-string before the logging call runs, so the work happens on every request and the result is thrown away. The worst one sits in process_chat_payload and stringifies the whole request body, full conversation history included, once per chat completion.

That one line with DEBUG disabled, CPython 3.12:

| conversation | payload | before   | after   |
| ------------ | ------- | -------- | ------- |
| 4 messages   | 1.2 kB  | 3.4 us   | 0.07 us |
| 20 messages  | 17 kB   | 24.8 us  | 0.07 us |
| 60 messages  | 123 kB  | 216.6 us | 0.07 us |

The lazy form log.debug('form_data: %s', form_data) hands the payload to record.getMessage(), which the InterceptHandler only reaches once a record has passed the level check. With DEBUG enabled the emitted lines are byte-identical, f'{x=}' sites included: those map to %r. MistralLoader._debug_log callers get the same treatment, since that wrapper already forwards *args.

backend/open_webui/retrieval/vector/dbs/pinecone.py

@@ -274,7 +274,7 @@ class PineconeClient(VectorDBBase):
                 log.error(f'Error inserting batch: {e}')
                 raise
         elapsed = time.time() - start_time
-        log.debug(f'Insert of {len(points)} vectors took {elapsed:.2f} seconds')
+        log.debug('Insert of %s vectors took %.2f seconds', len(points), elapsed)
         log.info(
             f"Successfully inserted {len(points)} vectors in parallel batches into '{collection_name_with_prefix}'"
         )
@@ -303,7 +303,7 @@ class PineconeClient(VectorDBBase):
                 log.error(f'Error upserting batch: {e}')
                 raise
         elapsed = time.time() - start_time
-        log.debug(f'Upsert of {len(points)} vectors took {elapsed:.2f} seconds')
+        log.debug('Upsert of %s vectors took %.2f seconds', len(points), elapsed)
         log.info(
             f"Successfully upserted {len(points)} vectors in parallel batches into '{collection_name_with_prefix}'"
         )
@@ -474,7 +474,9 @@ class PineconeClient(VectorDBBase):
                     # Note: When deleting by ID, we can't filter by collection_name
                     # This is a limitation of Pinecone - be careful with ID uniqueness
                     self.index.delete(ids=batch_ids)
-                    log.debug(f"Deleted batch of {len(batch_ids)} vectors by ID from '{collection_name_with_prefix}'")
+                    log.debug(
+                        "Deleted batch of %s vectors by ID from '%s'", len(batch_ids), collection_name_with_prefix
+                    )
                 log.info(f"Successfully deleted {len(ids)} vectors by ID from '{collection_name_with_prefix}'")
 
             elif filter: