Activate Bugbear rules

pyproject.toml

@@ -97,7 +97,7 @@ fixable = ["ALL"]
 
 # Select or ignore from https://beta.ruff.rs/docs/rules/
 select = [
-    # "B",  # bugbear
+    "B",  # bugbear
     # "D",  # pydocstyle
     # "E",  # pycodestyle errors
     "F",  # Pyflakes

src/curate_gpt/cli.py

@@ -1243,7 +1243,7 @@ def ask(query, path, collection, model, show_references, _continue, conversation
             conversation = load_conversation(conversation_id)
             print(f"CONTINUING CONVERSATION {conversation}")
         except UnknownModelError as ex:
-            raise click.ClickException(str(ex))
+            raise click.ClickException(str(ex)) from ex
     chatbot = ChatAgent(path)
     chatbot.extractor = extractor
     chatbot.knowledge_source = db

src/curate_gpt/utils/vectordb_operations.py

@@ -36,6 +36,6 @@ def match_collections(
     tm_ix, tm_vals = top_matches(sim_matrix)
     logger.info(f"Yielding {len(tm_ix)} matches")
     i = 0
-    for ix, val in zip(tm_ix, tm_vals):
+    for ix, val in zip(tm_ix, tm_vals, strict=True):
         yield left_objs[i][0], right_objs[ix][0], val
         i += 1

src/llm_gpt4all.py

@@ -163,14 +163,16 @@ def fetch_cached_json(url, path, cache_timeout):
             json.dump(response.json(), file)
 
         return response.json()
-    except (httpx.HTTPError, urllib3.exceptions.NameResolutionError):
+    except (httpx.HTTPError, urllib3.exceptions.NameResolutionError) as ex:
         # If there's an existing file, load it
         if path.is_file():
             with open(path, "r") as file:
                 return json.load(file)
         else:
             # If not, raise an error
-            raise DownloadError(f"Failed to download data and no cache is available at {path}")
+            raise DownloadError(
+                f"Failed to download data and no cache is available at {path}. Error: {ex}"
+            ) from ex
 
 
 def human_readable_size(size_bytes):