cr

gpt_index/__init__.py

@@ -141,5 +141,6 @@
 import logging
 from logging import NullHandler
 
-# best practices for library logging: https://docs.python.org/3/howto/logging.html#configuring-logging-for-a-library
+# best practices for library logging:
+# https://docs.python.org/3/howto/logging.html#configuring-logging-for-a-library
 logging.getLogger(__name__).addHandler(NullHandler())

gpt_index/indices/query/keyword_table/query.py

@@ -97,7 +97,8 @@ def _get_nodes_for_response(
         if logging.getLogger(__name__).getEffectiveLevel() == logging.DEBUG:
             for chunk_idx, node in zip(sorted_chunk_indices, sorted_nodes):
                 logging.debug(
-                    f"> Querying with idx: {chunk_idx}: {truncate_text(node.get_text(), 50)}"
+                    f"> Querying with idx: {chunk_idx}: "
+                    f"{truncate_text(node.get_text(), 50)}"
                 )
 
         return sorted_nodes

gpt_index/indices/query/tree/leaf_query.py

@@ -177,9 +177,11 @@ def _query_level(
                 f">[Level {level}] Selected node: "
                 f"[{number}]/[{','.join([str(int(n)) for n in numbers])}]"
             )
+            debug_str = " ".join(selected_node.get_text().splitlines())
             logging.debug(
                 f">[Level {level}] Node "
-                f"[{number}] Summary text: { truncate_text(' '.join(selected_node.get_text().splitlines()), 100) }"
+                f"[{number}] Summary text: "
+                f"{ truncate_text(debug_str, 100) }"
             )
             result_response = self._query_with_selected_node(
                 selected_node,

gpt_index/indices/query/vector_store/pinecone.py

@@ -84,7 +84,7 @@ def _get_nodes_for_response(
             if similarity_tracker is not None:
                 similarity_tracker.add(node, match.score)
 
-        if logging.logger.getEffectiveLevel() == logging.DEBUG:
+        if logging.getLogger(__name__).getEffectiveLevel() == logging.DEBUG:
             fmt_txts = []
             for node_idx, node_similarity, node in zip(
                 top_k_ids, top_k_scores, top_k_nodes

gpt_index/indices/query/vector_store/weaviate.py

@@ -52,7 +52,7 @@ def _get_nodes_for_response(
         nodes = nodes[: self.similarity_top_k]
         node_idxs = [str(i) for i in range(len(nodes))]
 
-        if logging.logger.getEffectiveLevel() == logging.DEBUG:
+        if logging.getLogger(__name__).getEffectiveLevel() == logging.DEBUG:
             fmt_txts = []
             for node_idx, node in zip(node_idxs, nodes):
                 fmt_txt = f"> [Node {node_idx}] {truncate_text(node.get_text(), 100)}"

gpt_index/readers/slack.py

@@ -63,14 +63,14 @@ def _read_message(self, channel_id: str, message_ts: str) -> str:
                 next_cursor = result["response_metadata"]["next_cursor"]
             except SlackApiError as e:
                 if e.response["error"] == "ratelimited":
-                    logger.error(
+                    logging.error(
                         "Rate limit error reached, sleeping for: {} seconds".format(
                             e.response.headers["retry-after"]
                         )
                     )
                     time.sleep(int(e.response.headers["retry-after"]))
                 else:
-                    logger.error("Error parsing conversation replies: {}".format(e))
+                    logging.error("Error parsing conversation replies: {}".format(e))
 
         return "\n\n".join(messages_text)
 

setup.py

@@ -17,7 +17,7 @@
     "transformers",
     "nltk",
     "numpy",
-    "tenacity",
+    "tenacity<8.2.0",
     "pandas",
 ]