mirror of https://github.com/langgenius/dify.git
make logging not use f-str, change others to f-str (#22882)
This commit is contained in:
parent
570aee5fe6
commit
a189d293f8
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@ -49,8 +49,8 @@ jobs:
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if: steps.changed-files.outputs.any_changed == 'true'
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run: |
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uv run --directory api ruff --version
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uv run --directory api ruff check --diff ./
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uv run --directory api ruff format --check --diff ./
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uv run --directory api ruff check ./
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uv run --directory api ruff format --check ./
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- name: Dotenv check
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if: steps.changed-files.outputs.any_changed == 'true'
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@ -42,6 +42,8 @@ select = [
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"S301", # suspicious-pickle-usage, disallow use of `pickle` and its wrappers.
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"S302", # suspicious-marshal-usage, disallow use of `marshal` module
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"S311", # suspicious-non-cryptographic-random-usage
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"G001", # don't use str format to logging messages
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"G004", # don't use f-strings to format logging messages
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]
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ignore = [
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@ -32,7 +32,7 @@ def create_app() -> DifyApp:
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initialize_extensions(app)
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end_time = time.perf_counter()
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if dify_config.DEBUG:
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logging.info(f"Finished create_app ({round((end_time - start_time) * 1000, 2)} ms)")
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logging.info("Finished create_app (%s ms)", round((end_time - start_time) * 1000, 2))
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return app
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@ -91,14 +91,14 @@ def initialize_extensions(app: DifyApp):
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is_enabled = ext.is_enabled() if hasattr(ext, "is_enabled") else True
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if not is_enabled:
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if dify_config.DEBUG:
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logging.info(f"Skipped {short_name}")
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logging.info("Skipped %s", short_name)
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continue
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start_time = time.perf_counter()
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ext.init_app(app)
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end_time = time.perf_counter()
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if dify_config.DEBUG:
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logging.info(f"Loaded {short_name} ({round((end_time - start_time) * 1000, 2)} ms)")
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logging.info("Loaded %s (%s ms)", short_name, round((end_time - start_time) * 1000, 2))
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def create_migrations_app():
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@ -53,13 +53,13 @@ def reset_password(email, new_password, password_confirm):
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account = db.session.query(Account).where(Account.email == email).one_or_none()
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if not account:
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click.echo(click.style("Account not found for email: {}".format(email), fg="red"))
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click.echo(click.style(f"Account not found for email: {email}", fg="red"))
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return
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try:
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valid_password(new_password)
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except:
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click.echo(click.style("Invalid password. Must match {}".format(password_pattern), fg="red"))
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click.echo(click.style(f"Invalid password. Must match {password_pattern}", fg="red"))
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return
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# generate password salt
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@ -92,13 +92,13 @@ def reset_email(email, new_email, email_confirm):
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account = db.session.query(Account).where(Account.email == email).one_or_none()
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if not account:
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click.echo(click.style("Account not found for email: {}".format(email), fg="red"))
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click.echo(click.style(f"Account not found for email: {email}", fg="red"))
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return
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try:
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email_validate(new_email)
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except:
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click.echo(click.style("Invalid email: {}".format(new_email), fg="red"))
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click.echo(click.style(f"Invalid email: {new_email}", fg="red"))
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return
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account.email = new_email
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@ -142,7 +142,7 @@ def reset_encrypt_key_pair():
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click.echo(
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click.style(
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"Congratulations! The asymmetric key pair of workspace {} has been reset.".format(tenant.id),
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f"Congratulations! The asymmetric key pair of workspace {tenant.id} has been reset.",
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fg="green",
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)
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)
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@ -190,14 +190,14 @@ def migrate_annotation_vector_database():
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f"Processing the {total_count} app {app.id}. " + f"{create_count} created, {skipped_count} skipped."
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)
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try:
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click.echo("Creating app annotation index: {}".format(app.id))
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click.echo(f"Creating app annotation index: {app.id}")
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app_annotation_setting = (
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db.session.query(AppAnnotationSetting).where(AppAnnotationSetting.app_id == app.id).first()
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)
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if not app_annotation_setting:
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skipped_count = skipped_count + 1
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click.echo("App annotation setting disabled: {}".format(app.id))
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click.echo(f"App annotation setting disabled: {app.id}")
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continue
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# get dataset_collection_binding info
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dataset_collection_binding = (
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@ -206,7 +206,7 @@ def migrate_annotation_vector_database():
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.first()
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)
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if not dataset_collection_binding:
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click.echo("App annotation collection binding not found: {}".format(app.id))
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click.echo(f"App annotation collection binding not found: {app.id}")
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continue
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annotations = db.session.query(MessageAnnotation).where(MessageAnnotation.app_id == app.id).all()
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dataset = Dataset(
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@ -252,9 +252,7 @@ def migrate_annotation_vector_database():
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create_count += 1
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except Exception as e:
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click.echo(
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click.style(
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"Error creating app annotation index: {} {}".format(e.__class__.__name__, str(e)), fg="red"
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)
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click.style(f"Error creating app annotation index: {e.__class__.__name__} {str(e)}", fg="red")
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)
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continue
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@ -319,7 +317,7 @@ def migrate_knowledge_vector_database():
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f"Processing the {total_count} dataset {dataset.id}. {create_count} created, {skipped_count} skipped."
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)
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try:
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click.echo("Creating dataset vector database index: {}".format(dataset.id))
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click.echo(f"Creating dataset vector database index: {dataset.id}")
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if dataset.index_struct_dict:
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if dataset.index_struct_dict["type"] == vector_type:
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skipped_count = skipped_count + 1
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@ -423,9 +421,7 @@ def migrate_knowledge_vector_database():
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create_count += 1
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except Exception as e:
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db.session.rollback()
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click.echo(
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click.style("Error creating dataset index: {} {}".format(e.__class__.__name__, str(e)), fg="red")
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)
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click.echo(click.style(f"Error creating dataset index: {e.__class__.__name__} {str(e)}", fg="red"))
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continue
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click.echo(
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@ -476,7 +472,7 @@ def convert_to_agent_apps():
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break
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for app in apps:
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click.echo("Converting app: {}".format(app.id))
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click.echo(f"Converting app: {app.id}")
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try:
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app.mode = AppMode.AGENT_CHAT.value
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@ -488,11 +484,11 @@ def convert_to_agent_apps():
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)
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db.session.commit()
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click.echo(click.style("Converted app: {}".format(app.id), fg="green"))
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click.echo(click.style(f"Converted app: {app.id}", fg="green"))
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except Exception as e:
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click.echo(click.style("Convert app error: {} {}".format(e.__class__.__name__, str(e)), fg="red"))
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click.echo(click.style(f"Convert app error: {e.__class__.__name__} {str(e)}", fg="red"))
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click.echo(click.style("Conversion complete. Converted {} agent apps.".format(len(proceeded_app_ids)), fg="green"))
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click.echo(click.style(f"Conversion complete. Converted {len(proceeded_app_ids)} agent apps.", fg="green"))
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@click.command("add-qdrant-index", help="Add Qdrant index.")
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@ -665,7 +661,7 @@ def create_tenant(email: str, language: Optional[str] = None, name: Optional[str
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click.echo(
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click.style(
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"Account and tenant created.\nAccount: {}\nPassword: {}".format(email, new_password),
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f"Account and tenant created.\nAccount: {email}\nPassword: {new_password}",
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fg="green",
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)
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)
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@ -726,16 +722,16 @@ where sites.id is null limit 1000"""
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if tenant:
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accounts = tenant.get_accounts()
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if not accounts:
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print("Fix failed for app {}".format(app.id))
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print(f"Fix failed for app {app.id}")
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continue
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account = accounts[0]
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print("Fixing missing site for app {}".format(app.id))
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print(f"Fixing missing site for app {app.id}")
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app_was_created.send(app, account=account)
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except Exception:
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failed_app_ids.append(app_id)
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click.echo(click.style("Failed to fix missing site for app {}".format(app_id), fg="red"))
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logging.exception(f"Failed to fix app related site missing issue, app_id: {app_id}")
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click.echo(click.style(f"Failed to fix missing site for app {app_id}", fg="red"))
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logging.exception("Failed to fix app related site missing issue, app_id: %s", app_id)
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continue
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if not processed_count:
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@ -41,7 +41,7 @@ class RemoteSettingsSourceFactory(PydanticBaseSettingsSource):
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case RemoteSettingsSourceName.NACOS:
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remote_source = NacosSettingsSource(current_state)
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case _:
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logger.warning(f"Unsupported remote source: {remote_source_name}")
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logger.warning("Unsupported remote source: %s", remote_source_name)
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return {}
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d: dict[str, Any] = {}
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@ -245,11 +245,7 @@ class CeleryConfig(DatabaseConfig):
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@computed_field
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def CELERY_RESULT_BACKEND(self) -> str | None:
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return (
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"db+{}".format(self.SQLALCHEMY_DATABASE_URI)
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if self.CELERY_BACKEND == "database"
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else self.CELERY_BROKER_URL
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)
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return f"db+{self.SQLALCHEMY_DATABASE_URI}" if self.CELERY_BACKEND == "database" else self.CELERY_BROKER_URL
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@property
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def BROKER_USE_SSL(self) -> bool:
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@ -76,7 +76,7 @@ class ApolloClient:
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code, body = http_request(url, timeout=3, headers=self._sign_headers(url))
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if code == 200:
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if not body:
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logger.error(f"get_json_from_net load configs failed, body is {body}")
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logger.error("get_json_from_net load configs failed, body is %s", body)
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return None
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data = json.loads(body)
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data = data["configurations"]
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@ -207,7 +207,7 @@ class ApolloClient:
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# if the length is 0 it is returned directly
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if len(notifications) == 0:
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return
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url = "{}/notifications/v2".format(self.config_url)
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url = f"{self.config_url}/notifications/v2"
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params = {
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"appId": self.app_id,
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"cluster": self.cluster,
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@ -222,7 +222,7 @@ class ApolloClient:
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return
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if http_code == 200:
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if not body:
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logger.error(f"_long_poll load configs failed,body is {body}")
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logger.error("_long_poll load configs failed,body is %s", body)
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return
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data = json.loads(body)
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for entry in data:
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@ -273,12 +273,12 @@ class ApolloClient:
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time.sleep(60 * 10) # 10 minutes
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def _do_heart_beat(self, namespace):
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url = "{}/configs/{}/{}/{}?ip={}".format(self.config_url, self.app_id, self.cluster, namespace, self.ip)
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url = f"{self.config_url}/configs/{self.app_id}/{self.cluster}/{namespace}?ip={self.ip}"
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try:
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code, body = http_request(url, timeout=3, headers=self._sign_headers(url))
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if code == 200:
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if not body:
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logger.error(f"_do_heart_beat load configs failed,body is {body}")
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logger.error("_do_heart_beat load configs failed,body is %s", body)
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return None
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data = json.loads(body)
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if self.last_release_key == data["releaseKey"]:
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@ -24,7 +24,7 @@ def url_encode_wrapper(params):
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def no_key_cache_key(namespace, key):
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return "{}{}{}".format(namespace, len(namespace), key)
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return f"{namespace}{len(namespace)}{key}"
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# Returns whether the obtained value is obtained, and None if it does not
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@ -28,5 +28,5 @@ def supported_language(lang):
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if lang in languages:
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return lang
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error = "{lang} is not a valid language.".format(lang=lang)
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error = f"{lang} is not a valid language."
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raise ValueError(error)
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@ -86,7 +86,7 @@ class AnnotationReplyActionStatusApi(Resource):
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raise Forbidden()
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job_id = str(job_id)
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app_annotation_job_key = "{}_app_annotation_job_{}".format(action, str(job_id))
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app_annotation_job_key = f"{action}_app_annotation_job_{str(job_id)}"
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cache_result = redis_client.get(app_annotation_job_key)
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if cache_result is None:
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raise ValueError("The job does not exist.")
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@ -94,7 +94,7 @@ class AnnotationReplyActionStatusApi(Resource):
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job_status = cache_result.decode()
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error_msg = ""
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if job_status == "error":
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app_annotation_error_key = "{}_app_annotation_error_{}".format(action, str(job_id))
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app_annotation_error_key = f"{action}_app_annotation_error_{str(job_id)}"
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error_msg = redis_client.get(app_annotation_error_key).decode()
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return {"job_id": job_id, "job_status": job_status, "error_msg": error_msg}, 200
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@ -223,14 +223,14 @@ class AnnotationBatchImportStatusApi(Resource):
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raise Forbidden()
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job_id = str(job_id)
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indexing_cache_key = "app_annotation_batch_import_{}".format(str(job_id))
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indexing_cache_key = f"app_annotation_batch_import_{str(job_id)}"
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cache_result = redis_client.get(indexing_cache_key)
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if cache_result is None:
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raise ValueError("The job does not exist.")
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job_status = cache_result.decode()
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error_msg = ""
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if job_status == "error":
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indexing_error_msg_key = "app_annotation_batch_import_error_msg_{}".format(str(job_id))
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indexing_error_msg_key = f"app_annotation_batch_import_error_msg_{str(job_id)}"
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error_msg = redis_client.get(indexing_error_msg_key).decode()
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return {"job_id": job_id, "job_status": job_status, "error_msg": error_msg}, 200
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@ -51,8 +51,8 @@ class CompletionConversationApi(Resource):
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if args["keyword"]:
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query = query.join(Message, Message.conversation_id == Conversation.id).where(
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or_(
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Message.query.ilike("%{}%".format(args["keyword"])),
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Message.answer.ilike("%{}%".format(args["keyword"])),
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Message.query.ilike(f"%{args['keyword']}%"),
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Message.answer.ilike(f"%{args['keyword']}%"),
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)
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)
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@ -174,7 +174,7 @@ class ChatConversationApi(Resource):
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query = db.select(Conversation).where(Conversation.app_id == app_model.id)
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if args["keyword"]:
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keyword_filter = "%{}%".format(args["keyword"])
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keyword_filter = f"%{args['keyword']}%"
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query = (
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query.join(
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Message,
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@ -81,7 +81,7 @@ class OAuthDataSourceBinding(Resource):
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oauth_provider.get_access_token(code)
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except requests.exceptions.HTTPError as e:
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logging.exception(
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f"An error occurred during the OAuthCallback process with {provider}: {e.response.text}"
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"An error occurred during the OAuthCallback process with %s: %s", provider, e.response.text
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)
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return {"error": "OAuth data source process failed"}, 400
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@ -103,7 +103,9 @@ class OAuthDataSourceSync(Resource):
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try:
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oauth_provider.sync_data_source(binding_id)
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except requests.exceptions.HTTPError as e:
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logging.exception(f"An error occurred during the OAuthCallback process with {provider}: {e.response.text}")
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logging.exception(
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"An error occurred during the OAuthCallback process with %s: %s", provider, e.response.text
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)
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return {"error": "OAuth data source process failed"}, 400
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return {"result": "success"}, 200
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|
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@ -80,7 +80,7 @@ class OAuthCallback(Resource):
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user_info = oauth_provider.get_user_info(token)
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except requests.exceptions.RequestException as e:
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error_text = e.response.text if e.response else str(e)
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logging.exception(f"An error occurred during the OAuth process with {provider}: {error_text}")
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logging.exception("An error occurred during the OAuth process with %s: %s", provider, error_text)
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return {"error": "OAuth process failed"}, 400
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if invite_token and RegisterService.is_valid_invite_token(invite_token):
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|
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@ -970,7 +970,7 @@ class DocumentRetryApi(DocumentResource):
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raise DocumentAlreadyFinishedError()
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retry_documents.append(document)
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except Exception:
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logging.exception(f"Failed to retry document, document id: {document_id}")
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logging.exception("Failed to retry document, document id: %s", document_id)
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continue
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# retry document
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DocumentService.retry_document(dataset_id, retry_documents)
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|
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@ -184,7 +184,7 @@ class DatasetDocumentSegmentApi(Resource):
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raise ProviderNotInitializeError(ex.description)
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segment_ids = request.args.getlist("segment_id")
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document_indexing_cache_key = "document_{}_indexing".format(document.id)
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document_indexing_cache_key = f"document_{document.id}_indexing"
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cache_result = redis_client.get(document_indexing_cache_key)
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if cache_result is not None:
|
||||
raise InvalidActionError("Document is being indexed, please try again later")
|
||||
|
|
@ -391,7 +391,7 @@ class DatasetDocumentSegmentBatchImportApi(Resource):
|
|||
raise ValueError("The CSV file is empty.")
|
||||
# async job
|
||||
job_id = str(uuid.uuid4())
|
||||
indexing_cache_key = "segment_batch_import_{}".format(str(job_id))
|
||||
indexing_cache_key = f"segment_batch_import_{str(job_id)}"
|
||||
# send batch add segments task
|
||||
redis_client.setnx(indexing_cache_key, "waiting")
|
||||
batch_create_segment_to_index_task.delay(
|
||||
|
|
@ -406,7 +406,7 @@ class DatasetDocumentSegmentBatchImportApi(Resource):
|
|||
@account_initialization_required
|
||||
def get(self, job_id):
|
||||
job_id = str(job_id)
|
||||
indexing_cache_key = "segment_batch_import_{}".format(job_id)
|
||||
indexing_cache_key = f"segment_batch_import_{job_id}"
|
||||
cache_result = redis_client.get(indexing_cache_key)
|
||||
if cache_result is None:
|
||||
raise ValueError("The job does not exist.")
|
||||
|
|
|
|||
|
|
@ -74,7 +74,7 @@ class InstalledAppsListApi(Resource):
|
|||
):
|
||||
res.append(installed_app)
|
||||
installed_app_list = res
|
||||
logger.debug(f"installed_app_list: {installed_app_list}, user_id: {user_id}")
|
||||
logger.debug("installed_app_list: %s, user_id: %s", installed_app_list, user_id)
|
||||
|
||||
installed_app_list.sort(
|
||||
key=lambda app: (
|
||||
|
|
|
|||
|
|
@ -34,7 +34,7 @@ class VersionApi(Resource):
|
|||
try:
|
||||
response = requests.get(check_update_url, {"current_version": args.get("current_version")})
|
||||
except Exception as error:
|
||||
logging.warning("Check update version error: {}.".format(str(error)))
|
||||
logging.warning("Check update version error: %s.", str(error))
|
||||
result["version"] = args.get("current_version")
|
||||
return result
|
||||
|
||||
|
|
@ -55,7 +55,7 @@ def _has_new_version(*, latest_version: str, current_version: str) -> bool:
|
|||
# Compare versions
|
||||
return latest > current
|
||||
except version.InvalidVersion:
|
||||
logging.warning(f"Invalid version format: latest={latest_version}, current={current_version}")
|
||||
logging.warning("Invalid version format: latest=%s, current=%s", latest_version, current_version)
|
||||
return False
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -73,8 +73,9 @@ class DefaultModelApi(Resource):
|
|||
)
|
||||
except Exception as ex:
|
||||
logging.exception(
|
||||
f"Failed to update default model, model type: {model_setting['model_type']},"
|
||||
f" model:{model_setting.get('model')}"
|
||||
"Failed to update default model, model type: %s, model: %s",
|
||||
model_setting["model_type"],
|
||||
model_setting.get("model"),
|
||||
)
|
||||
raise ex
|
||||
|
||||
|
|
@ -160,8 +161,10 @@ class ModelProviderModelApi(Resource):
|
|||
)
|
||||
except CredentialsValidateFailedError as ex:
|
||||
logging.exception(
|
||||
f"Failed to save model credentials, tenant_id: {tenant_id},"
|
||||
f" model: {args.get('model')}, model_type: {args.get('model_type')}"
|
||||
"Failed to save model credentials, tenant_id: %s, model: %s, model_type: %s",
|
||||
tenant_id,
|
||||
args.get("model"),
|
||||
args.get("model_type"),
|
||||
)
|
||||
raise ValueError(str(ex))
|
||||
|
||||
|
|
|
|||
|
|
@ -34,7 +34,7 @@ class AnnotationReplyActionStatusApi(Resource):
|
|||
@validate_app_token
|
||||
def get(self, app_model: App, job_id, action):
|
||||
job_id = str(job_id)
|
||||
app_annotation_job_key = "{}_app_annotation_job_{}".format(action, str(job_id))
|
||||
app_annotation_job_key = f"{action}_app_annotation_job_{str(job_id)}"
|
||||
cache_result = redis_client.get(app_annotation_job_key)
|
||||
if cache_result is None:
|
||||
raise ValueError("The job does not exist.")
|
||||
|
|
@ -42,7 +42,7 @@ class AnnotationReplyActionStatusApi(Resource):
|
|||
job_status = cache_result.decode()
|
||||
error_msg = ""
|
||||
if job_status == "error":
|
||||
app_annotation_error_key = "{}_app_annotation_error_{}".format(action, str(job_id))
|
||||
app_annotation_error_key = f"{action}_app_annotation_error_{str(job_id)}"
|
||||
error_msg = redis_client.get(app_annotation_error_key).decode()
|
||||
|
||||
return {"job_id": job_id, "job_status": job_status, "error_msg": error_msg}, 200
|
||||
|
|
|
|||
|
|
@ -600,5 +600,5 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
|
|||
if len(e.args) > 0 and e.args[0] == "I/O operation on closed file.": # ignore this error
|
||||
raise GenerateTaskStoppedError()
|
||||
else:
|
||||
logger.exception(f"Failed to process generate task pipeline, conversation_id: {conversation.id}")
|
||||
logger.exception("Failed to process generate task pipeline, conversation_id: %s", conversation.id)
|
||||
raise e
|
||||
|
|
|
|||
|
|
@ -271,7 +271,7 @@ class AdvancedChatAppGenerateTaskPipeline:
|
|||
start_listener_time = time.time()
|
||||
yield MessageAudioStreamResponse(audio=audio_trunk.audio, task_id=task_id)
|
||||
except Exception:
|
||||
logger.exception(f"Failed to listen audio message, task_id: {task_id}")
|
||||
logger.exception("Failed to listen audio message, task_id: %s", task_id)
|
||||
break
|
||||
if tts_publisher:
|
||||
yield MessageAudioEndStreamResponse(audio="", task_id=task_id)
|
||||
|
|
|
|||
|
|
@ -78,7 +78,7 @@ class MessageBasedAppGenerator(BaseAppGenerator):
|
|||
if len(e.args) > 0 and e.args[0] == "I/O operation on closed file.": # ignore this error
|
||||
raise GenerateTaskStoppedError()
|
||||
else:
|
||||
logger.exception(f"Failed to handle response, conversation_id: {conversation.id}")
|
||||
logger.exception("Failed to handle response, conversation_id: %s", conversation.id)
|
||||
raise e
|
||||
|
||||
def _get_app_model_config(self, app_model: App, conversation: Optional[Conversation] = None) -> AppModelConfig:
|
||||
|
|
|
|||
|
|
@ -483,7 +483,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
|
|||
try:
|
||||
runner.run()
|
||||
except GenerateTaskStoppedError as e:
|
||||
logger.warning(f"Task stopped: {str(e)}")
|
||||
logger.warning("Task stopped: %s", str(e))
|
||||
pass
|
||||
except InvokeAuthorizationError:
|
||||
queue_manager.publish_error(
|
||||
|
|
@ -540,6 +540,6 @@ class WorkflowAppGenerator(BaseAppGenerator):
|
|||
raise GenerateTaskStoppedError()
|
||||
else:
|
||||
logger.exception(
|
||||
f"Fails to process generate task pipeline, task_id: {application_generate_entity.task_id}"
|
||||
"Fails to process generate task pipeline, task_id: %s", application_generate_entity.task_id
|
||||
)
|
||||
raise e
|
||||
|
|
|
|||
|
|
@ -246,7 +246,7 @@ class WorkflowAppGenerateTaskPipeline:
|
|||
else:
|
||||
yield MessageAudioStreamResponse(audio=audio_trunk.audio, task_id=task_id)
|
||||
except Exception:
|
||||
logger.exception(f"Fails to get audio trunk, task_id: {task_id}")
|
||||
logger.exception("Fails to get audio trunk, task_id: %s", task_id)
|
||||
break
|
||||
if tts_publisher:
|
||||
yield MessageAudioEndStreamResponse(audio="", task_id=task_id)
|
||||
|
|
|
|||
|
|
@ -83,7 +83,7 @@ class AnnotationReplyFeature:
|
|||
|
||||
return annotation
|
||||
except Exception as e:
|
||||
logger.warning(f"Query annotation failed, exception: {str(e)}.")
|
||||
logger.warning("Query annotation failed, exception: %s.", str(e))
|
||||
return None
|
||||
|
||||
return None
|
||||
|
|
|
|||
|
|
@ -97,7 +97,7 @@ class MessageCycleManager:
|
|||
conversation.name = name
|
||||
except Exception as e:
|
||||
if dify_config.DEBUG:
|
||||
logging.exception(f"generate conversation name failed, conversation_id: {conversation_id}")
|
||||
logging.exception("generate conversation name failed, conversation_id: %s", conversation_id)
|
||||
pass
|
||||
|
||||
db.session.merge(conversation)
|
||||
|
|
|
|||
|
|
@ -900,7 +900,7 @@ class ProviderConfiguration(BaseModel):
|
|||
credentials=copy_credentials,
|
||||
)
|
||||
except Exception as ex:
|
||||
logger.warning(f"get custom model schema failed, {ex}")
|
||||
logger.warning("get custom model schema failed, %s", ex)
|
||||
continue
|
||||
|
||||
if not custom_model_schema:
|
||||
|
|
@ -1009,7 +1009,7 @@ class ProviderConfiguration(BaseModel):
|
|||
credentials=model_configuration.credentials,
|
||||
)
|
||||
except Exception as ex:
|
||||
logger.warning(f"get custom model schema failed, {ex}")
|
||||
logger.warning("get custom model schema failed, %s", ex)
|
||||
continue
|
||||
|
||||
if not custom_model_schema:
|
||||
|
|
|
|||
|
|
@ -22,7 +22,7 @@ class APIBasedExtensionRequestor:
|
|||
:param params: the request params
|
||||
:return: the response json
|
||||
"""
|
||||
headers = {"Content-Type": "application/json", "Authorization": "Bearer {}".format(self.api_key)}
|
||||
headers = {"Content-Type": "application/json", "Authorization": f"Bearer {self.api_key}"}
|
||||
|
||||
url = self.api_endpoint
|
||||
|
||||
|
|
@ -49,8 +49,6 @@ class APIBasedExtensionRequestor:
|
|||
raise ValueError("request connection error")
|
||||
|
||||
if response.status_code != 200:
|
||||
raise ValueError(
|
||||
"request error, status_code: {}, content: {}".format(response.status_code, response.text[:100])
|
||||
)
|
||||
raise ValueError(f"request error, status_code: {response.status_code}, content: {response.text[:100]}")
|
||||
|
||||
return cast(dict, response.json())
|
||||
|
|
|
|||
|
|
@ -66,7 +66,7 @@ class Extensible:
|
|||
|
||||
# Check for extension module file
|
||||
if (extension_name + ".py") not in file_names:
|
||||
logging.warning(f"Missing {extension_name}.py file in {subdir_path}, Skip.")
|
||||
logging.warning("Missing %s.py file in %s, Skip.", extension_name, subdir_path)
|
||||
continue
|
||||
|
||||
# Check for builtin flag and position
|
||||
|
|
@ -95,7 +95,7 @@ class Extensible:
|
|||
break
|
||||
|
||||
if not extension_class:
|
||||
logging.warning(f"Missing subclass of {cls.__name__} in {module_name}, Skip.")
|
||||
logging.warning("Missing subclass of %s in %s, Skip.", cls.__name__, module_name)
|
||||
continue
|
||||
|
||||
# Load schema if not builtin
|
||||
|
|
@ -103,7 +103,7 @@ class Extensible:
|
|||
if not builtin:
|
||||
json_path = os.path.join(subdir_path, "schema.json")
|
||||
if not os.path.exists(json_path):
|
||||
logging.warning(f"Missing schema.json file in {subdir_path}, Skip.")
|
||||
logging.warning("Missing schema.json file in %s, Skip.", subdir_path)
|
||||
continue
|
||||
|
||||
with open(json_path, encoding="utf-8") as f:
|
||||
|
|
|
|||
|
|
@ -49,7 +49,7 @@ class ApiExternalDataTool(ExternalDataTool):
|
|||
"""
|
||||
# get params from config
|
||||
if not self.config:
|
||||
raise ValueError("config is required, config: {}".format(self.config))
|
||||
raise ValueError(f"config is required, config: {self.config}")
|
||||
api_based_extension_id = self.config.get("api_based_extension_id")
|
||||
assert api_based_extension_id is not None, "api_based_extension_id is required"
|
||||
|
||||
|
|
@ -74,7 +74,7 @@ class ApiExternalDataTool(ExternalDataTool):
|
|||
# request api
|
||||
requestor = APIBasedExtensionRequestor(api_endpoint=api_based_extension.api_endpoint, api_key=api_key)
|
||||
except Exception as e:
|
||||
raise ValueError("[External data tool] API query failed, variable: {}, error: {}".format(self.variable, e))
|
||||
raise ValueError(f"[External data tool] API query failed, variable: {self.variable}, error: {e}")
|
||||
|
||||
response_json = requestor.request(
|
||||
point=APIBasedExtensionPoint.APP_EXTERNAL_DATA_TOOL_QUERY,
|
||||
|
|
@ -90,7 +90,7 @@ class ApiExternalDataTool(ExternalDataTool):
|
|||
|
||||
if not isinstance(response_json["result"], str):
|
||||
raise ValueError(
|
||||
"[External data tool] API query failed, variable: {}, error: result is not string".format(self.variable)
|
||||
f"[External data tool] API query failed, variable: {self.variable}, error: result is not string"
|
||||
)
|
||||
|
||||
return response_json["result"]
|
||||
|
|
|
|||
|
|
@ -55,7 +55,7 @@ def check_moderation(tenant_id: str, model_config: ModelConfigWithCredentialsEnt
|
|||
if moderation_result is True:
|
||||
return True
|
||||
except Exception:
|
||||
logger.exception(f"Fails to check moderation, provider_name: {provider_name}")
|
||||
logger.exception("Fails to check moderation, provider_name: %s", provider_name)
|
||||
raise InvokeBadRequestError("Rate limit exceeded, please try again later.")
|
||||
|
||||
return False
|
||||
|
|
|
|||
|
|
@ -30,7 +30,7 @@ def import_module_from_source(*, module_name: str, py_file_path: AnyStr, use_laz
|
|||
spec.loader.exec_module(module)
|
||||
return module
|
||||
except Exception as e:
|
||||
logging.exception(f"Failed to load module {module_name} from script file '{py_file_path!r}'")
|
||||
logging.exception("Failed to load module %s from script file '%s'", module_name, repr(py_file_path))
|
||||
raise e
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -73,10 +73,12 @@ def make_request(method, url, max_retries=SSRF_DEFAULT_MAX_RETRIES, **kwargs):
|
|||
if response.status_code not in STATUS_FORCELIST:
|
||||
return response
|
||||
else:
|
||||
logging.warning(f"Received status code {response.status_code} for URL {url} which is in the force list")
|
||||
logging.warning(
|
||||
"Received status code %s for URL %s which is in the force list", response.status_code, url
|
||||
)
|
||||
|
||||
except httpx.RequestError as e:
|
||||
logging.warning(f"Request to URL {url} failed on attempt {retries + 1}: {e}")
|
||||
logging.warning("Request to URL %s failed on attempt %s: %s", url, retries + 1, e)
|
||||
if max_retries == 0:
|
||||
raise
|
||||
|
||||
|
|
|
|||
|
|
@ -84,14 +84,14 @@ class IndexingRunner:
|
|||
documents=documents,
|
||||
)
|
||||
except DocumentIsPausedError:
|
||||
raise DocumentIsPausedError("Document paused, document id: {}".format(dataset_document.id))
|
||||
raise DocumentIsPausedError(f"Document paused, document id: {dataset_document.id}")
|
||||
except ProviderTokenNotInitError as e:
|
||||
dataset_document.indexing_status = "error"
|
||||
dataset_document.error = str(e.description)
|
||||
dataset_document.stopped_at = datetime.datetime.now(datetime.UTC).replace(tzinfo=None)
|
||||
db.session.commit()
|
||||
except ObjectDeletedError:
|
||||
logging.warning("Document deleted, document id: {}".format(dataset_document.id))
|
||||
logging.warning("Document deleted, document id: %s", dataset_document.id)
|
||||
except Exception as e:
|
||||
logging.exception("consume document failed")
|
||||
dataset_document.indexing_status = "error"
|
||||
|
|
@ -147,7 +147,7 @@ class IndexingRunner:
|
|||
index_processor=index_processor, dataset=dataset, dataset_document=dataset_document, documents=documents
|
||||
)
|
||||
except DocumentIsPausedError:
|
||||
raise DocumentIsPausedError("Document paused, document id: {}".format(dataset_document.id))
|
||||
raise DocumentIsPausedError(f"Document paused, document id: {dataset_document.id}")
|
||||
except ProviderTokenNotInitError as e:
|
||||
dataset_document.indexing_status = "error"
|
||||
dataset_document.error = str(e.description)
|
||||
|
|
@ -222,7 +222,7 @@ class IndexingRunner:
|
|||
index_processor=index_processor, dataset=dataset, dataset_document=dataset_document, documents=documents
|
||||
)
|
||||
except DocumentIsPausedError:
|
||||
raise DocumentIsPausedError("Document paused, document id: {}".format(dataset_document.id))
|
||||
raise DocumentIsPausedError(f"Document paused, document id: {dataset_document.id}")
|
||||
except ProviderTokenNotInitError as e:
|
||||
dataset_document.indexing_status = "error"
|
||||
dataset_document.error = str(e.description)
|
||||
|
|
@ -324,7 +324,8 @@ class IndexingRunner:
|
|||
except Exception:
|
||||
logging.exception(
|
||||
"Delete image_files failed while indexing_estimate, \
|
||||
image_upload_file_is: {}".format(upload_file_id)
|
||||
image_upload_file_is: %s",
|
||||
upload_file_id,
|
||||
)
|
||||
db.session.delete(image_file)
|
||||
|
||||
|
|
@ -649,7 +650,7 @@ class IndexingRunner:
|
|||
|
||||
@staticmethod
|
||||
def _check_document_paused_status(document_id: str):
|
||||
indexing_cache_key = "document_{}_is_paused".format(document_id)
|
||||
indexing_cache_key = f"document_{document_id}_is_paused"
|
||||
result = redis_client.get(indexing_cache_key)
|
||||
if result:
|
||||
raise DocumentIsPausedError()
|
||||
|
|
|
|||
|
|
@ -167,7 +167,7 @@ class LLMGenerator:
|
|||
error = str(e)
|
||||
error_step = "generate rule config"
|
||||
except Exception as e:
|
||||
logging.exception(f"Failed to generate rule config, model: {model_config.get('name')}")
|
||||
logging.exception("Failed to generate rule config, model: %s", model_config.get("name"))
|
||||
rule_config["error"] = str(e)
|
||||
|
||||
rule_config["error"] = f"Failed to {error_step}. Error: {error}" if error else ""
|
||||
|
|
@ -264,7 +264,7 @@ class LLMGenerator:
|
|||
error_step = "generate conversation opener"
|
||||
|
||||
except Exception as e:
|
||||
logging.exception(f"Failed to generate rule config, model: {model_config.get('name')}")
|
||||
logging.exception("Failed to generate rule config, model: %s", model_config.get("name"))
|
||||
rule_config["error"] = str(e)
|
||||
|
||||
rule_config["error"] = f"Failed to {error_step}. Error: {error}" if error else ""
|
||||
|
|
@ -314,7 +314,7 @@ class LLMGenerator:
|
|||
return {"code": "", "language": code_language, "error": f"Failed to generate code. Error: {error}"}
|
||||
except Exception as e:
|
||||
logging.exception(
|
||||
f"Failed to invoke LLM model, model: {model_config.get('name')}, language: {code_language}"
|
||||
"Failed to invoke LLM model, model: %s, language: %s", model_config.get("name"), code_language
|
||||
)
|
||||
return {"code": "", "language": code_language, "error": f"An unexpected error occurred: {str(e)}"}
|
||||
|
||||
|
|
@ -386,5 +386,5 @@ class LLMGenerator:
|
|||
error = str(e)
|
||||
return {"output": "", "error": f"Failed to generate JSON Schema. Error: {error}"}
|
||||
except Exception as e:
|
||||
logging.exception(f"Failed to invoke LLM model, model: {model_config.get('name')}")
|
||||
logging.exception("Failed to invoke LLM model, model: %s", model_config.get("name"))
|
||||
return {"output": "", "error": f"An unexpected error occurred: {str(e)}"}
|
||||
|
|
|
|||
|
|
@ -88,7 +88,7 @@ class SSETransport:
|
|||
status_queue: Queue to put status updates.
|
||||
"""
|
||||
endpoint_url = urljoin(self.url, sse_data)
|
||||
logger.info(f"Received endpoint URL: {endpoint_url}")
|
||||
logger.info("Received endpoint URL: %s", endpoint_url)
|
||||
|
||||
if not self._validate_endpoint_url(endpoint_url):
|
||||
error_msg = f"Endpoint origin does not match connection origin: {endpoint_url}"
|
||||
|
|
@ -107,7 +107,7 @@ class SSETransport:
|
|||
"""
|
||||
try:
|
||||
message = types.JSONRPCMessage.model_validate_json(sse_data)
|
||||
logger.debug(f"Received server message: {message}")
|
||||
logger.debug("Received server message: %s", message)
|
||||
session_message = SessionMessage(message)
|
||||
read_queue.put(session_message)
|
||||
except Exception as exc:
|
||||
|
|
@ -128,7 +128,7 @@ class SSETransport:
|
|||
case "message":
|
||||
self._handle_message_event(sse.data, read_queue)
|
||||
case _:
|
||||
logger.warning(f"Unknown SSE event: {sse.event}")
|
||||
logger.warning("Unknown SSE event: %s", sse.event)
|
||||
|
||||
def sse_reader(self, event_source, read_queue: ReadQueue, status_queue: StatusQueue) -> None:
|
||||
"""Read and process SSE events.
|
||||
|
|
@ -142,7 +142,7 @@ class SSETransport:
|
|||
for sse in event_source.iter_sse():
|
||||
self._handle_sse_event(sse, read_queue, status_queue)
|
||||
except httpx.ReadError as exc:
|
||||
logger.debug(f"SSE reader shutting down normally: {exc}")
|
||||
logger.debug("SSE reader shutting down normally: %s", exc)
|
||||
except Exception as exc:
|
||||
read_queue.put(exc)
|
||||
finally:
|
||||
|
|
@ -165,7 +165,7 @@ class SSETransport:
|
|||
),
|
||||
)
|
||||
response.raise_for_status()
|
||||
logger.debug(f"Client message sent successfully: {response.status_code}")
|
||||
logger.debug("Client message sent successfully: %s", response.status_code)
|
||||
|
||||
def post_writer(self, client: httpx.Client, endpoint_url: str, write_queue: WriteQueue) -> None:
|
||||
"""Handle writing messages to the server.
|
||||
|
|
@ -190,7 +190,7 @@ class SSETransport:
|
|||
except queue.Empty:
|
||||
continue
|
||||
except httpx.ReadError as exc:
|
||||
logger.debug(f"Post writer shutting down normally: {exc}")
|
||||
logger.debug("Post writer shutting down normally: %s", exc)
|
||||
except Exception as exc:
|
||||
logger.exception("Error writing messages")
|
||||
write_queue.put(exc)
|
||||
|
|
@ -326,7 +326,7 @@ def send_message(http_client: httpx.Client, endpoint_url: str, session_message:
|
|||
),
|
||||
)
|
||||
response.raise_for_status()
|
||||
logger.debug(f"Client message sent successfully: {response.status_code}")
|
||||
logger.debug("Client message sent successfully: %s", response.status_code)
|
||||
except Exception as exc:
|
||||
logger.exception("Error sending message")
|
||||
raise
|
||||
|
|
@ -349,13 +349,13 @@ def read_messages(
|
|||
if sse.event == "message":
|
||||
try:
|
||||
message = types.JSONRPCMessage.model_validate_json(sse.data)
|
||||
logger.debug(f"Received server message: {message}")
|
||||
logger.debug("Received server message: %s", message)
|
||||
yield SessionMessage(message)
|
||||
except Exception as exc:
|
||||
logger.exception("Error parsing server message")
|
||||
yield exc
|
||||
else:
|
||||
logger.warning(f"Unknown SSE event: {sse.event}")
|
||||
logger.warning("Unknown SSE event: %s", sse.event)
|
||||
except Exception as exc:
|
||||
logger.exception("Error reading SSE messages")
|
||||
yield exc
|
||||
|
|
|
|||
|
|
@ -129,7 +129,7 @@ class StreamableHTTPTransport:
|
|||
new_session_id = response.headers.get(MCP_SESSION_ID)
|
||||
if new_session_id:
|
||||
self.session_id = new_session_id
|
||||
logger.info(f"Received session ID: {self.session_id}")
|
||||
logger.info("Received session ID: %s", self.session_id)
|
||||
|
||||
def _handle_sse_event(
|
||||
self,
|
||||
|
|
@ -142,7 +142,7 @@ class StreamableHTTPTransport:
|
|||
if sse.event == "message":
|
||||
try:
|
||||
message = JSONRPCMessage.model_validate_json(sse.data)
|
||||
logger.debug(f"SSE message: {message}")
|
||||
logger.debug("SSE message: %s", message)
|
||||
|
||||
# If this is a response and we have original_request_id, replace it
|
||||
if original_request_id is not None and isinstance(message.root, JSONRPCResponse | JSONRPCError):
|
||||
|
|
@ -168,7 +168,7 @@ class StreamableHTTPTransport:
|
|||
logger.debug("Received ping event")
|
||||
return False
|
||||
else:
|
||||
logger.warning(f"Unknown SSE event: {sse.event}")
|
||||
logger.warning("Unknown SSE event: %s", sse.event)
|
||||
return False
|
||||
|
||||
def handle_get_stream(
|
||||
|
|
@ -197,7 +197,7 @@ class StreamableHTTPTransport:
|
|||
self._handle_sse_event(sse, server_to_client_queue)
|
||||
|
||||
except Exception as exc:
|
||||
logger.debug(f"GET stream error (non-fatal): {exc}")
|
||||
logger.debug("GET stream error (non-fatal): %s", exc)
|
||||
|
||||
def _handle_resumption_request(self, ctx: RequestContext) -> None:
|
||||
"""Handle a resumption request using GET with SSE."""
|
||||
|
|
@ -352,7 +352,7 @@ class StreamableHTTPTransport:
|
|||
# Check if this is a resumption request
|
||||
is_resumption = bool(metadata and metadata.resumption_token)
|
||||
|
||||
logger.debug(f"Sending client message: {message}")
|
||||
logger.debug("Sending client message: %s", message)
|
||||
|
||||
# Handle initialized notification
|
||||
if self._is_initialized_notification(message):
|
||||
|
|
@ -389,9 +389,9 @@ class StreamableHTTPTransport:
|
|||
if response.status_code == 405:
|
||||
logger.debug("Server does not allow session termination")
|
||||
elif response.status_code != 200:
|
||||
logger.warning(f"Session termination failed: {response.status_code}")
|
||||
logger.warning("Session termination failed: %s", response.status_code)
|
||||
except Exception as exc:
|
||||
logger.warning(f"Session termination failed: {exc}")
|
||||
logger.warning("Session termination failed: %s", exc)
|
||||
|
||||
def get_session_id(self) -> str | None:
|
||||
"""Get the current session ID."""
|
||||
|
|
|
|||
|
|
@ -75,7 +75,7 @@ class MCPClient:
|
|||
self.connect_server(client_factory, method_name)
|
||||
else:
|
||||
try:
|
||||
logger.debug(f"Not supported method {method_name} found in URL path, trying default 'mcp' method.")
|
||||
logger.debug("Not supported method %s found in URL path, trying default 'mcp' method.", method_name)
|
||||
self.connect_server(sse_client, "sse")
|
||||
except MCPConnectionError:
|
||||
logger.debug("MCP connection failed with 'sse', falling back to 'mcp' method.")
|
||||
|
|
|
|||
|
|
@ -368,7 +368,7 @@ class BaseSession(
|
|||
self._handle_incoming(notification)
|
||||
except Exception as e:
|
||||
# For other validation errors, log and continue
|
||||
logging.warning(f"Failed to validate notification: {e}. Message was: {message.message.root}")
|
||||
logging.warning("Failed to validate notification: %s. Message was: %s", e, message.message.root)
|
||||
else: # Response or error
|
||||
response_queue = self._response_streams.get(message.message.root.id)
|
||||
if response_queue is not None:
|
||||
|
|
|
|||
|
|
@ -535,9 +535,19 @@ class LBModelManager:
|
|||
|
||||
if dify_config.DEBUG:
|
||||
logger.info(
|
||||
f"Model LB\nid: {config.id}\nname:{config.name}\n"
|
||||
f"tenant_id: {self._tenant_id}\nprovider: {self._provider}\n"
|
||||
f"model_type: {self._model_type.value}\nmodel: {self._model}"
|
||||
"""Model LB
|
||||
id: %s
|
||||
name:%s
|
||||
tenant_id: %s
|
||||
provider: %s
|
||||
model_type: %s
|
||||
model: %s""",
|
||||
config.id,
|
||||
config.name,
|
||||
self._tenant_id,
|
||||
self._provider,
|
||||
self._model_type.value,
|
||||
self._model,
|
||||
)
|
||||
|
||||
return config
|
||||
|
|
|
|||
|
|
@ -440,7 +440,9 @@ class LargeLanguageModel(AIModel):
|
|||
if callback.raise_error:
|
||||
raise e
|
||||
else:
|
||||
logger.warning(f"Callback {callback.__class__.__name__} on_before_invoke failed with error {e}")
|
||||
logger.warning(
|
||||
"Callback %s on_before_invoke failed with error %s", callback.__class__.__name__, e
|
||||
)
|
||||
|
||||
def _trigger_new_chunk_callbacks(
|
||||
self,
|
||||
|
|
@ -487,7 +489,7 @@ class LargeLanguageModel(AIModel):
|
|||
if callback.raise_error:
|
||||
raise e
|
||||
else:
|
||||
logger.warning(f"Callback {callback.__class__.__name__} on_new_chunk failed with error {e}")
|
||||
logger.warning("Callback %s on_new_chunk failed with error %s", callback.__class__.__name__, e)
|
||||
|
||||
def _trigger_after_invoke_callbacks(
|
||||
self,
|
||||
|
|
@ -535,7 +537,9 @@ class LargeLanguageModel(AIModel):
|
|||
if callback.raise_error:
|
||||
raise e
|
||||
else:
|
||||
logger.warning(f"Callback {callback.__class__.__name__} on_after_invoke failed with error {e}")
|
||||
logger.warning(
|
||||
"Callback %s on_after_invoke failed with error %s", callback.__class__.__name__, e
|
||||
)
|
||||
|
||||
def _trigger_invoke_error_callbacks(
|
||||
self,
|
||||
|
|
@ -583,4 +587,6 @@ class LargeLanguageModel(AIModel):
|
|||
if callback.raise_error:
|
||||
raise e
|
||||
else:
|
||||
logger.warning(f"Callback {callback.__class__.__name__} on_invoke_error failed with error {e}")
|
||||
logger.warning(
|
||||
"Callback %s on_invoke_error failed with error %s", callback.__class__.__name__, e
|
||||
)
|
||||
|
|
|
|||
|
|
@ -136,6 +136,6 @@ class OutputModeration(BaseModel):
|
|||
result: ModerationOutputsResult = moderation_factory.moderation_for_outputs(moderation_buffer)
|
||||
return result
|
||||
except Exception as e:
|
||||
logger.exception(f"Moderation Output error, app_id: {app_id}")
|
||||
logger.exception("Moderation Output error, app_id: %s", app_id)
|
||||
|
||||
return None
|
||||
|
|
|
|||
|
|
@ -97,7 +97,7 @@ class AliyunDataTrace(BaseTraceInstance):
|
|||
try:
|
||||
return self.trace_client.get_project_url()
|
||||
except Exception as e:
|
||||
logger.info(f"Aliyun get run url failed: {str(e)}", exc_info=True)
|
||||
logger.info("Aliyun get run url failed: %s", str(e), exc_info=True)
|
||||
raise ValueError(f"Aliyun get run url failed: {str(e)}")
|
||||
|
||||
def workflow_trace(self, trace_info: WorkflowTraceInfo):
|
||||
|
|
@ -286,7 +286,7 @@ class AliyunDataTrace(BaseTraceInstance):
|
|||
node_span = self.build_workflow_task_span(trace_id, workflow_span_id, trace_info, node_execution)
|
||||
return node_span
|
||||
except Exception as e:
|
||||
logging.debug(f"Error occurred in build_workflow_node_span: {e}", exc_info=True)
|
||||
logging.debug("Error occurred in build_workflow_node_span: %s", e, exc_info=True)
|
||||
return None
|
||||
|
||||
def get_workflow_node_status(self, node_execution: WorkflowNodeExecution) -> Status:
|
||||
|
|
|
|||
|
|
@ -69,10 +69,10 @@ class TraceClient:
|
|||
if response.status_code == 405:
|
||||
return True
|
||||
else:
|
||||
logger.debug(f"AliyunTrace API check failed: Unexpected status code: {response.status_code}")
|
||||
logger.debug("AliyunTrace API check failed: Unexpected status code: %s", response.status_code)
|
||||
return False
|
||||
except requests.exceptions.RequestException as e:
|
||||
logger.debug(f"AliyunTrace API check failed: {str(e)}")
|
||||
logger.debug("AliyunTrace API check failed: %s", str(e))
|
||||
raise ValueError(f"AliyunTrace API check failed: {str(e)}")
|
||||
|
||||
def get_project_url(self):
|
||||
|
|
@ -109,7 +109,7 @@ class TraceClient:
|
|||
try:
|
||||
self.exporter.export(spans_to_export)
|
||||
except Exception as e:
|
||||
logger.debug(f"Error exporting spans: {e}")
|
||||
logger.debug("Error exporting spans: %s", e)
|
||||
|
||||
def shutdown(self):
|
||||
with self.condition:
|
||||
|
|
|
|||
|
|
@ -77,10 +77,10 @@ def setup_tracer(arize_phoenix_config: ArizeConfig | PhoenixConfig) -> tuple[tra
|
|||
|
||||
# Create a named tracer instead of setting the global provider
|
||||
tracer_name = f"arize_phoenix_tracer_{arize_phoenix_config.project}"
|
||||
logger.info(f"[Arize/Phoenix] Created tracer with name: {tracer_name}")
|
||||
logger.info("[Arize/Phoenix] Created tracer with name: %s", tracer_name)
|
||||
return cast(trace_sdk.Tracer, provider.get_tracer(tracer_name)), processor
|
||||
except Exception as e:
|
||||
logger.error(f"[Arize/Phoenix] Failed to setup the tracer: {str(e)}", exc_info=True)
|
||||
logger.error("[Arize/Phoenix] Failed to setup the tracer: %s", str(e), exc_info=True)
|
||||
raise
|
||||
|
||||
|
||||
|
|
@ -120,7 +120,7 @@ class ArizePhoenixDataTrace(BaseTraceInstance):
|
|||
self.file_base_url = os.getenv("FILES_URL", "http://127.0.0.1:5001")
|
||||
|
||||
def trace(self, trace_info: BaseTraceInfo):
|
||||
logger.info(f"[Arize/Phoenix] Trace: {trace_info}")
|
||||
logger.info("[Arize/Phoenix] Trace: %s", trace_info)
|
||||
try:
|
||||
if isinstance(trace_info, WorkflowTraceInfo):
|
||||
self.workflow_trace(trace_info)
|
||||
|
|
@ -138,7 +138,7 @@ class ArizePhoenixDataTrace(BaseTraceInstance):
|
|||
self.generate_name_trace(trace_info)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"[Arize/Phoenix] Error in the trace: {str(e)}", exc_info=True)
|
||||
logger.error("[Arize/Phoenix] Error in the trace: %s", str(e), exc_info=True)
|
||||
raise
|
||||
|
||||
def workflow_trace(self, trace_info: WorkflowTraceInfo):
|
||||
|
|
@ -570,7 +570,7 @@ class ArizePhoenixDataTrace(BaseTraceInstance):
|
|||
|
||||
trace_id = uuid_to_trace_id(trace_info.message_id)
|
||||
tool_span_id = RandomIdGenerator().generate_span_id()
|
||||
logger.info(f"[Arize/Phoenix] Creating tool trace with trace_id: {trace_id}, span_id: {tool_span_id}")
|
||||
logger.info("[Arize/Phoenix] Creating tool trace with trace_id: %s, span_id: %s", trace_id, tool_span_id)
|
||||
|
||||
# Create span context with the same trace_id as the parent
|
||||
# todo: Create with the appropriate parent span context, so that the tool span is
|
||||
|
|
@ -673,7 +673,7 @@ class ArizePhoenixDataTrace(BaseTraceInstance):
|
|||
span.set_attribute("test", "true")
|
||||
return True
|
||||
except Exception as e:
|
||||
logger.info(f"[Arize/Phoenix] API check failed: {str(e)}", exc_info=True)
|
||||
logger.info("[Arize/Phoenix] API check failed: %s", str(e), exc_info=True)
|
||||
raise ValueError(f"[Arize/Phoenix] API check failed: {str(e)}")
|
||||
|
||||
def get_project_url(self):
|
||||
|
|
@ -683,7 +683,7 @@ class ArizePhoenixDataTrace(BaseTraceInstance):
|
|||
else:
|
||||
return f"{self.arize_phoenix_config.endpoint}/projects/"
|
||||
except Exception as e:
|
||||
logger.info(f"[Arize/Phoenix] Get run url failed: {str(e)}", exc_info=True)
|
||||
logger.info("[Arize/Phoenix] Get run url failed: %s", str(e), exc_info=True)
|
||||
raise ValueError(f"[Arize/Phoenix] Get run url failed: {str(e)}")
|
||||
|
||||
def _get_workflow_nodes(self, workflow_run_id: str):
|
||||
|
|
|
|||
|
|
@ -440,7 +440,7 @@ class LangFuseDataTrace(BaseTraceInstance):
|
|||
try:
|
||||
return self.langfuse_client.auth_check()
|
||||
except Exception as e:
|
||||
logger.debug(f"LangFuse API check failed: {str(e)}")
|
||||
logger.debug("LangFuse API check failed: %s", str(e))
|
||||
raise ValueError(f"LangFuse API check failed: {str(e)}")
|
||||
|
||||
def get_project_key(self):
|
||||
|
|
@ -448,5 +448,5 @@ class LangFuseDataTrace(BaseTraceInstance):
|
|||
projects = self.langfuse_client.client.projects.get()
|
||||
return projects.data[0].id
|
||||
except Exception as e:
|
||||
logger.debug(f"LangFuse get project key failed: {str(e)}")
|
||||
logger.debug("LangFuse get project key failed: %s", str(e))
|
||||
raise ValueError(f"LangFuse get project key failed: {str(e)}")
|
||||
|
|
|
|||
|
|
@ -504,7 +504,7 @@ class LangSmithDataTrace(BaseTraceInstance):
|
|||
self.langsmith_client.delete_project(project_name=random_project_name)
|
||||
return True
|
||||
except Exception as e:
|
||||
logger.debug(f"LangSmith API check failed: {str(e)}")
|
||||
logger.debug("LangSmith API check failed: %s", str(e))
|
||||
raise ValueError(f"LangSmith API check failed: {str(e)}")
|
||||
|
||||
def get_project_url(self):
|
||||
|
|
@ -523,5 +523,5 @@ class LangSmithDataTrace(BaseTraceInstance):
|
|||
)
|
||||
return project_url.split("/r/")[0]
|
||||
except Exception as e:
|
||||
logger.debug(f"LangSmith get run url failed: {str(e)}")
|
||||
logger.debug("LangSmith get run url failed: %s", str(e))
|
||||
raise ValueError(f"LangSmith get run url failed: {str(e)}")
|
||||
|
|
|
|||
|
|
@ -453,12 +453,12 @@ class OpikDataTrace(BaseTraceInstance):
|
|||
self.opik_client.auth_check()
|
||||
return True
|
||||
except Exception as e:
|
||||
logger.info(f"Opik API check failed: {str(e)}", exc_info=True)
|
||||
logger.info("Opik API check failed: %s", str(e), exc_info=True)
|
||||
raise ValueError(f"Opik API check failed: {str(e)}")
|
||||
|
||||
def get_project_url(self):
|
||||
try:
|
||||
return self.opik_client.get_project_url(project_name=self.project)
|
||||
except Exception as e:
|
||||
logger.info(f"Opik get run url failed: {str(e)}", exc_info=True)
|
||||
logger.info("Opik get run url failed: %s", str(e), exc_info=True)
|
||||
raise ValueError(f"Opik get run url failed: {str(e)}")
|
||||
|
|
|
|||
|
|
@ -287,7 +287,7 @@ class OpsTraceManager:
|
|||
# create new tracing_instance and update the cache if it absent
|
||||
tracing_instance = trace_instance(config_class(**decrypt_trace_config))
|
||||
cls.ops_trace_instances_cache[decrypt_trace_config_key] = tracing_instance
|
||||
logging.info(f"new tracing_instance for app_id: {app_id}")
|
||||
logging.info("new tracing_instance for app_id: %s", app_id)
|
||||
return tracing_instance
|
||||
|
||||
@classmethod
|
||||
|
|
@ -843,7 +843,7 @@ class TraceQueueManager:
|
|||
trace_task.app_id = self.app_id
|
||||
trace_manager_queue.put(trace_task)
|
||||
except Exception as e:
|
||||
logging.exception(f"Error adding trace task, trace_type {trace_task.trace_type}")
|
||||
logging.exception("Error adding trace task, trace_type %s", trace_task.trace_type)
|
||||
finally:
|
||||
self.start_timer()
|
||||
|
||||
|
|
|
|||
|
|
@ -66,11 +66,11 @@ class WeaveDataTrace(BaseTraceInstance):
|
|||
project_url = f"https://wandb.ai/{self.weave_client._project_id()}"
|
||||
return project_url
|
||||
except Exception as e:
|
||||
logger.debug(f"Weave get run url failed: {str(e)}")
|
||||
logger.debug("Weave get run url failed: %s", str(e))
|
||||
raise ValueError(f"Weave get run url failed: {str(e)}")
|
||||
|
||||
def trace(self, trace_info: BaseTraceInfo):
|
||||
logger.debug(f"Trace info: {trace_info}")
|
||||
logger.debug("Trace info: %s", trace_info)
|
||||
if isinstance(trace_info, WorkflowTraceInfo):
|
||||
self.workflow_trace(trace_info)
|
||||
if isinstance(trace_info, MessageTraceInfo):
|
||||
|
|
@ -403,7 +403,7 @@ class WeaveDataTrace(BaseTraceInstance):
|
|||
print("Weave login successful")
|
||||
return True
|
||||
except Exception as e:
|
||||
logger.debug(f"Weave API check failed: {str(e)}")
|
||||
logger.debug("Weave API check failed: %s", str(e))
|
||||
raise ValueError(f"Weave API check failed: {str(e)}")
|
||||
|
||||
def start_call(self, run_data: WeaveTraceModel, parent_run_id: Optional[str] = None):
|
||||
|
|
|
|||
|
|
@ -24,7 +24,7 @@ class Jieba(BaseKeyword):
|
|||
self._config = KeywordTableConfig()
|
||||
|
||||
def create(self, texts: list[Document], **kwargs) -> BaseKeyword:
|
||||
lock_name = "keyword_indexing_lock_{}".format(self.dataset.id)
|
||||
lock_name = f"keyword_indexing_lock_{self.dataset.id}"
|
||||
with redis_client.lock(lock_name, timeout=600):
|
||||
keyword_table_handler = JiebaKeywordTableHandler()
|
||||
keyword_table = self._get_dataset_keyword_table()
|
||||
|
|
@ -43,7 +43,7 @@ class Jieba(BaseKeyword):
|
|||
return self
|
||||
|
||||
def add_texts(self, texts: list[Document], **kwargs):
|
||||
lock_name = "keyword_indexing_lock_{}".format(self.dataset.id)
|
||||
lock_name = f"keyword_indexing_lock_{self.dataset.id}"
|
||||
with redis_client.lock(lock_name, timeout=600):
|
||||
keyword_table_handler = JiebaKeywordTableHandler()
|
||||
|
||||
|
|
@ -76,7 +76,7 @@ class Jieba(BaseKeyword):
|
|||
return id in set.union(*keyword_table.values())
|
||||
|
||||
def delete_by_ids(self, ids: list[str]) -> None:
|
||||
lock_name = "keyword_indexing_lock_{}".format(self.dataset.id)
|
||||
lock_name = f"keyword_indexing_lock_{self.dataset.id}"
|
||||
with redis_client.lock(lock_name, timeout=600):
|
||||
keyword_table = self._get_dataset_keyword_table()
|
||||
if keyword_table is not None:
|
||||
|
|
@ -116,7 +116,7 @@ class Jieba(BaseKeyword):
|
|||
return documents
|
||||
|
||||
def delete(self) -> None:
|
||||
lock_name = "keyword_indexing_lock_{}".format(self.dataset.id)
|
||||
lock_name = f"keyword_indexing_lock_{self.dataset.id}"
|
||||
with redis_client.lock(lock_name, timeout=600):
|
||||
dataset_keyword_table = self.dataset.dataset_keyword_table
|
||||
if dataset_keyword_table:
|
||||
|
|
|
|||
|
|
@ -203,9 +203,9 @@ class BaiduVector(BaseVector):
|
|||
|
||||
def _create_table(self, dimension: int) -> None:
|
||||
# Try to grab distributed lock and create table
|
||||
lock_name = "vector_indexing_lock_{}".format(self._collection_name)
|
||||
lock_name = f"vector_indexing_lock_{self._collection_name}"
|
||||
with redis_client.lock(lock_name, timeout=60):
|
||||
table_exist_cache_key = "vector_indexing_{}".format(self._collection_name)
|
||||
table_exist_cache_key = f"vector_indexing_{self._collection_name}"
|
||||
if redis_client.get(table_exist_cache_key):
|
||||
return
|
||||
|
||||
|
|
|
|||
|
|
@ -57,9 +57,9 @@ class ChromaVector(BaseVector):
|
|||
self.add_texts(texts, embeddings, **kwargs)
|
||||
|
||||
def create_collection(self, collection_name: str):
|
||||
lock_name = "vector_indexing_lock_{}".format(collection_name)
|
||||
lock_name = f"vector_indexing_lock_{collection_name}"
|
||||
with redis_client.lock(lock_name, timeout=20):
|
||||
collection_exist_cache_key = "vector_indexing_{}".format(self._collection_name)
|
||||
collection_exist_cache_key = f"vector_indexing_{self._collection_name}"
|
||||
if redis_client.get(collection_exist_cache_key):
|
||||
return
|
||||
self._client.get_or_create_collection(collection_name)
|
||||
|
|
|
|||
|
|
@ -74,9 +74,9 @@ class CouchbaseVector(BaseVector):
|
|||
self.add_texts(texts, embeddings)
|
||||
|
||||
def _create_collection(self, vector_length: int, uuid: str):
|
||||
lock_name = "vector_indexing_lock_{}".format(self._collection_name)
|
||||
lock_name = f"vector_indexing_lock_{self._collection_name}"
|
||||
with redis_client.lock(lock_name, timeout=20):
|
||||
collection_exist_cache_key = "vector_indexing_{}".format(self._collection_name)
|
||||
collection_exist_cache_key = f"vector_indexing_{self._collection_name}"
|
||||
if redis_client.get(collection_exist_cache_key):
|
||||
return
|
||||
if self._collection_exists(self._collection_name):
|
||||
|
|
@ -242,7 +242,7 @@ class CouchbaseVector(BaseVector):
|
|||
try:
|
||||
self._cluster.query(query, named_parameters={"doc_ids": ids}).execute()
|
||||
except Exception as e:
|
||||
logger.exception(f"Failed to delete documents, ids: {ids}")
|
||||
logger.exception("Failed to delete documents, ids: %s", ids)
|
||||
|
||||
def delete_by_document_id(self, document_id: str):
|
||||
query = f"""
|
||||
|
|
|
|||
|
|
@ -29,7 +29,7 @@ class ElasticSearchJaVector(ElasticSearchVector):
|
|||
with redis_client.lock(lock_name, timeout=20):
|
||||
collection_exist_cache_key = f"vector_indexing_{self._collection_name}"
|
||||
if redis_client.get(collection_exist_cache_key):
|
||||
logger.info(f"Collection {self._collection_name} already exists.")
|
||||
logger.info("Collection %s already exists.", self._collection_name)
|
||||
return
|
||||
|
||||
if not self._client.indices.exists(index=self._collection_name):
|
||||
|
|
|
|||
|
|
@ -186,7 +186,7 @@ class ElasticSearchVector(BaseVector):
|
|||
with redis_client.lock(lock_name, timeout=20):
|
||||
collection_exist_cache_key = f"vector_indexing_{self._collection_name}"
|
||||
if redis_client.get(collection_exist_cache_key):
|
||||
logger.info(f"Collection {self._collection_name} already exists.")
|
||||
logger.info("Collection %s already exists.", self._collection_name)
|
||||
return
|
||||
|
||||
if not self._client.indices.exists(index=self._collection_name):
|
||||
|
|
|
|||
|
|
@ -164,7 +164,7 @@ class HuaweiCloudVector(BaseVector):
|
|||
with redis_client.lock(lock_name, timeout=20):
|
||||
collection_exist_cache_key = f"vector_indexing_{self._collection_name}"
|
||||
if redis_client.get(collection_exist_cache_key):
|
||||
logger.info(f"Collection {self._collection_name} already exists.")
|
||||
logger.info("Collection %s already exists.", self._collection_name)
|
||||
return
|
||||
|
||||
if not self._client.indices.exists(index=self._collection_name):
|
||||
|
|
|
|||
|
|
@ -89,7 +89,7 @@ class LindormVectorStore(BaseVector):
|
|||
timeout: int = 60,
|
||||
**kwargs,
|
||||
):
|
||||
logger.info(f"Total documents to add: {len(documents)}")
|
||||
logger.info("Total documents to add: %s", len(documents))
|
||||
uuids = self._get_uuids(documents)
|
||||
|
||||
total_docs = len(documents)
|
||||
|
|
@ -147,7 +147,7 @@ class LindormVectorStore(BaseVector):
|
|||
time.sleep(0.5)
|
||||
|
||||
except Exception:
|
||||
logger.exception(f"Failed to process batch {batch_num + 1}")
|
||||
logger.exception("Failed to process batch %s", batch_num + 1)
|
||||
raise
|
||||
|
||||
def get_ids_by_metadata_field(self, key: str, value: str):
|
||||
|
|
@ -180,7 +180,7 @@ class LindormVectorStore(BaseVector):
|
|||
|
||||
# 1. First check if collection exists
|
||||
if not self._client.indices.exists(index=self._collection_name):
|
||||
logger.warning(f"Collection {self._collection_name} does not exist")
|
||||
logger.warning("Collection %s does not exist", self._collection_name)
|
||||
return
|
||||
|
||||
# 2. Batch process deletions
|
||||
|
|
@ -196,7 +196,7 @@ class LindormVectorStore(BaseVector):
|
|||
}
|
||||
)
|
||||
else:
|
||||
logger.warning(f"DELETE BY ID: ID {id} does not exist in the index.")
|
||||
logger.warning("DELETE BY ID: ID %s does not exist in the index.", id)
|
||||
|
||||
# 3. Perform bulk deletion if there are valid documents to delete
|
||||
if actions:
|
||||
|
|
@ -209,9 +209,9 @@ class LindormVectorStore(BaseVector):
|
|||
doc_id = delete_error.get("_id")
|
||||
|
||||
if status == 404:
|
||||
logger.warning(f"Document not found for deletion: {doc_id}")
|
||||
logger.warning("Document not found for deletion: %s", doc_id)
|
||||
else:
|
||||
logger.exception(f"Error deleting document: {error}")
|
||||
logger.exception("Error deleting document: %s", error)
|
||||
|
||||
def delete(self) -> None:
|
||||
if self._using_ugc:
|
||||
|
|
@ -225,7 +225,7 @@ class LindormVectorStore(BaseVector):
|
|||
self._client.indices.delete(index=self._collection_name, params={"timeout": 60})
|
||||
logger.info("Delete index success")
|
||||
else:
|
||||
logger.warning(f"Index '{self._collection_name}' does not exist. No deletion performed.")
|
||||
logger.warning("Index '%s' does not exist. No deletion performed.", self._collection_name)
|
||||
|
||||
def text_exists(self, id: str) -> bool:
|
||||
try:
|
||||
|
|
@ -257,7 +257,7 @@ class LindormVectorStore(BaseVector):
|
|||
params["routing"] = self._routing # type: ignore
|
||||
response = self._client.search(index=self._collection_name, body=query, params=params)
|
||||
except Exception:
|
||||
logger.exception(f"Error executing vector search, query: {query}")
|
||||
logger.exception("Error executing vector search, query: %s", query)
|
||||
raise
|
||||
|
||||
docs_and_scores = []
|
||||
|
|
@ -324,10 +324,10 @@ class LindormVectorStore(BaseVector):
|
|||
with redis_client.lock(lock_name, timeout=20):
|
||||
collection_exist_cache_key = f"vector_indexing_{self._collection_name}"
|
||||
if redis_client.get(collection_exist_cache_key):
|
||||
logger.info(f"Collection {self._collection_name} already exists.")
|
||||
logger.info("Collection %s already exists.", self._collection_name)
|
||||
return
|
||||
if self._client.indices.exists(index=self._collection_name):
|
||||
logger.info(f"{self._collection_name.lower()} already exists.")
|
||||
logger.info("%s already exists.", self._collection_name.lower())
|
||||
redis_client.set(collection_exist_cache_key, 1, ex=3600)
|
||||
return
|
||||
if len(self.kwargs) == 0 and len(kwargs) != 0:
|
||||
|
|
|
|||
|
|
@ -103,7 +103,7 @@ class MilvusVector(BaseVector):
|
|||
# For standard Milvus installations, check version number
|
||||
return version.parse(milvus_version).base_version >= version.parse("2.5.0").base_version
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to check Milvus version: {str(e)}. Disabling hybrid search.")
|
||||
logger.warning("Failed to check Milvus version: %s. Disabling hybrid search.", str(e))
|
||||
return False
|
||||
|
||||
def get_type(self) -> str:
|
||||
|
|
@ -289,9 +289,9 @@ class MilvusVector(BaseVector):
|
|||
"""
|
||||
Create a new collection in Milvus with the specified schema and index parameters.
|
||||
"""
|
||||
lock_name = "vector_indexing_lock_{}".format(self._collection_name)
|
||||
lock_name = f"vector_indexing_lock_{self._collection_name}"
|
||||
with redis_client.lock(lock_name, timeout=20):
|
||||
collection_exist_cache_key = "vector_indexing_{}".format(self._collection_name)
|
||||
collection_exist_cache_key = f"vector_indexing_{self._collection_name}"
|
||||
if redis_client.get(collection_exist_cache_key):
|
||||
return
|
||||
# Grab the existing collection if it exists
|
||||
|
|
|
|||
|
|
@ -53,7 +53,7 @@ class MyScaleVector(BaseVector):
|
|||
return self.add_texts(documents=texts, embeddings=embeddings, **kwargs)
|
||||
|
||||
def _create_collection(self, dimension: int):
|
||||
logging.info(f"create MyScale collection {self._collection_name} with dimension {dimension}")
|
||||
logging.info("create MyScale collection %s with dimension %s", self._collection_name, dimension)
|
||||
self._client.command(f"CREATE DATABASE IF NOT EXISTS {self._config.database}")
|
||||
fts_params = f"('{self._config.fts_params}')" if self._config.fts_params else ""
|
||||
sql = f"""
|
||||
|
|
@ -151,7 +151,7 @@ class MyScaleVector(BaseVector):
|
|||
for r in self._client.query(sql).named_results()
|
||||
]
|
||||
except Exception as e:
|
||||
logging.exception(f"\033[91m\033[1m{type(e)}\033[0m \033[95m{str(e)}\033[0m") # noqa:TRY401
|
||||
logging.exception("\033[91m\033[1m%s\033[0m \033[95m%s\033[0m", type(e), str(e)) # noqa:TRY401
|
||||
return []
|
||||
|
||||
def delete(self) -> None:
|
||||
|
|
|
|||
|
|
@ -147,7 +147,7 @@ class OceanBaseVector(BaseVector):
|
|||
logger.debug("Current OceanBase version is %s", ob_version)
|
||||
return version.parse(ob_version).base_version >= version.parse("4.3.5.1").base_version
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to check OceanBase version: {str(e)}. Disabling hybrid search.")
|
||||
logger.warning("Failed to check OceanBase version: %s. Disabling hybrid search.", str(e))
|
||||
return False
|
||||
|
||||
def add_texts(self, documents: list[Document], embeddings: list[list[float]], **kwargs):
|
||||
|
|
@ -229,7 +229,7 @@ class OceanBaseVector(BaseVector):
|
|||
|
||||
return docs
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to fulltext search: {str(e)}.")
|
||||
logger.warning("Failed to fulltext search: %s.", str(e))
|
||||
return []
|
||||
|
||||
def search_by_vector(self, query_vector: list[float], **kwargs: Any) -> list[Document]:
|
||||
|
|
|
|||
|
|
@ -131,7 +131,7 @@ class OpenSearchVector(BaseVector):
|
|||
def delete_by_ids(self, ids: list[str]) -> None:
|
||||
index_name = self._collection_name.lower()
|
||||
if not self._client.indices.exists(index=index_name):
|
||||
logger.warning(f"Index {index_name} does not exist")
|
||||
logger.warning("Index %s does not exist", index_name)
|
||||
return
|
||||
|
||||
# Obtaining All Actual Documents_ID
|
||||
|
|
@ -142,7 +142,7 @@ class OpenSearchVector(BaseVector):
|
|||
if es_ids:
|
||||
actual_ids.extend(es_ids)
|
||||
else:
|
||||
logger.warning(f"Document with metadata doc_id {doc_id} not found for deletion")
|
||||
logger.warning("Document with metadata doc_id %s not found for deletion", doc_id)
|
||||
|
||||
if actual_ids:
|
||||
actions = [{"_op_type": "delete", "_index": index_name, "_id": es_id} for es_id in actual_ids]
|
||||
|
|
@ -155,9 +155,9 @@ class OpenSearchVector(BaseVector):
|
|||
doc_id = delete_error.get("_id")
|
||||
|
||||
if status == 404:
|
||||
logger.warning(f"Document not found for deletion: {doc_id}")
|
||||
logger.warning("Document not found for deletion: %s", doc_id)
|
||||
else:
|
||||
logger.exception(f"Error deleting document: {error}")
|
||||
logger.exception("Error deleting document: %s", error)
|
||||
|
||||
def delete(self) -> None:
|
||||
self._client.indices.delete(index=self._collection_name.lower())
|
||||
|
|
@ -198,7 +198,7 @@ class OpenSearchVector(BaseVector):
|
|||
try:
|
||||
response = self._client.search(index=self._collection_name.lower(), body=query)
|
||||
except Exception as e:
|
||||
logger.exception(f"Error executing vector search, query: {query}")
|
||||
logger.exception("Error executing vector search, query: %s", query)
|
||||
raise
|
||||
|
||||
docs = []
|
||||
|
|
@ -242,7 +242,7 @@ class OpenSearchVector(BaseVector):
|
|||
with redis_client.lock(lock_name, timeout=20):
|
||||
collection_exist_cache_key = f"vector_indexing_{self._collection_name.lower()}"
|
||||
if redis_client.get(collection_exist_cache_key):
|
||||
logger.info(f"Collection {self._collection_name.lower()} already exists.")
|
||||
logger.info("Collection %s already exists.", self._collection_name.lower())
|
||||
return
|
||||
|
||||
if not self._client.indices.exists(index=self._collection_name.lower()):
|
||||
|
|
@ -272,7 +272,7 @@ class OpenSearchVector(BaseVector):
|
|||
},
|
||||
}
|
||||
|
||||
logger.info(f"Creating OpenSearch index {self._collection_name.lower()}")
|
||||
logger.info("Creating OpenSearch index %s", self._collection_name.lower())
|
||||
self._client.indices.create(index=self._collection_name.lower(), body=index_body)
|
||||
|
||||
redis_client.set(collection_exist_cache_key, 1, ex=3600)
|
||||
|
|
|
|||
|
|
@ -82,9 +82,9 @@ class PGVectoRS(BaseVector):
|
|||
self.add_texts(texts, embeddings)
|
||||
|
||||
def create_collection(self, dimension: int):
|
||||
lock_name = "vector_indexing_lock_{}".format(self._collection_name)
|
||||
lock_name = f"vector_indexing_lock_{self._collection_name}"
|
||||
with redis_client.lock(lock_name, timeout=20):
|
||||
collection_exist_cache_key = "vector_indexing_{}".format(self._collection_name)
|
||||
collection_exist_cache_key = f"vector_indexing_{self._collection_name}"
|
||||
if redis_client.get(collection_exist_cache_key):
|
||||
return
|
||||
index_name = f"{self._collection_name}_embedding_index"
|
||||
|
|
|
|||
|
|
@ -155,7 +155,7 @@ class PGVector(BaseVector):
|
|||
cur.execute(f"DELETE FROM {self.table_name} WHERE id IN %s", (tuple(ids),))
|
||||
except psycopg2.errors.UndefinedTable:
|
||||
# table not exists
|
||||
logging.warning(f"Table {self.table_name} not found, skipping delete operation.")
|
||||
logging.warning("Table %s not found, skipping delete operation.", self.table_name)
|
||||
return
|
||||
except Exception as e:
|
||||
raise e
|
||||
|
|
|
|||
|
|
@ -95,9 +95,9 @@ class QdrantVector(BaseVector):
|
|||
self.add_texts(texts, embeddings, **kwargs)
|
||||
|
||||
def create_collection(self, collection_name: str, vector_size: int):
|
||||
lock_name = "vector_indexing_lock_{}".format(collection_name)
|
||||
lock_name = f"vector_indexing_lock_{collection_name}"
|
||||
with redis_client.lock(lock_name, timeout=20):
|
||||
collection_exist_cache_key = "vector_indexing_{}".format(self._collection_name)
|
||||
collection_exist_cache_key = f"vector_indexing_{self._collection_name}"
|
||||
if redis_client.get(collection_exist_cache_key):
|
||||
return
|
||||
collection_name = collection_name or uuid.uuid4().hex
|
||||
|
|
|
|||
|
|
@ -70,9 +70,9 @@ class RelytVector(BaseVector):
|
|||
self.add_texts(texts, embeddings)
|
||||
|
||||
def create_collection(self, dimension: int):
|
||||
lock_name = "vector_indexing_lock_{}".format(self._collection_name)
|
||||
lock_name = f"vector_indexing_lock_{self._collection_name}"
|
||||
with redis_client.lock(lock_name, timeout=20):
|
||||
collection_exist_cache_key = "vector_indexing_{}".format(self._collection_name)
|
||||
collection_exist_cache_key = f"vector_indexing_{self._collection_name}"
|
||||
if redis_client.get(collection_exist_cache_key):
|
||||
return
|
||||
index_name = f"{self._collection_name}_embedding_index"
|
||||
|
|
|
|||
|
|
@ -142,7 +142,7 @@ class TableStoreVector(BaseVector):
|
|||
with redis_client.lock(lock_name, timeout=20):
|
||||
collection_exist_cache_key = f"vector_indexing_{self._collection_name}"
|
||||
if redis_client.get(collection_exist_cache_key):
|
||||
logging.info(f"Collection {self._collection_name} already exists.")
|
||||
logging.info("Collection %s already exists.", self._collection_name)
|
||||
return
|
||||
|
||||
self._create_table_if_not_exist()
|
||||
|
|
|
|||
|
|
@ -92,9 +92,9 @@ class TencentVector(BaseVector):
|
|||
|
||||
def _create_collection(self, dimension: int) -> None:
|
||||
self._dimension = dimension
|
||||
lock_name = "vector_indexing_lock_{}".format(self._collection_name)
|
||||
lock_name = f"vector_indexing_lock_{self._collection_name}"
|
||||
with redis_client.lock(lock_name, timeout=20):
|
||||
collection_exist_cache_key = "vector_indexing_{}".format(self._collection_name)
|
||||
collection_exist_cache_key = f"vector_indexing_{self._collection_name}"
|
||||
if redis_client.get(collection_exist_cache_key):
|
||||
return
|
||||
|
||||
|
|
|
|||
|
|
@ -104,9 +104,9 @@ class TidbOnQdrantVector(BaseVector):
|
|||
self.add_texts(texts, embeddings, **kwargs)
|
||||
|
||||
def create_collection(self, collection_name: str, vector_size: int):
|
||||
lock_name = "vector_indexing_lock_{}".format(collection_name)
|
||||
lock_name = f"vector_indexing_lock_{collection_name}"
|
||||
with redis_client.lock(lock_name, timeout=20):
|
||||
collection_exist_cache_key = "vector_indexing_{}".format(self._collection_name)
|
||||
collection_exist_cache_key = f"vector_indexing_{self._collection_name}"
|
||||
if redis_client.get(collection_exist_cache_key):
|
||||
return
|
||||
collection_name = collection_name or uuid.uuid4().hex
|
||||
|
|
|
|||
|
|
@ -91,9 +91,9 @@ class TiDBVector(BaseVector):
|
|||
|
||||
def _create_collection(self, dimension: int):
|
||||
logger.info("_create_collection, collection_name " + self._collection_name)
|
||||
lock_name = "vector_indexing_lock_{}".format(self._collection_name)
|
||||
lock_name = f"vector_indexing_lock_{self._collection_name}"
|
||||
with redis_client.lock(lock_name, timeout=20):
|
||||
collection_exist_cache_key = "vector_indexing_{}".format(self._collection_name)
|
||||
collection_exist_cache_key = f"vector_indexing_{self._collection_name}"
|
||||
if redis_client.get(collection_exist_cache_key):
|
||||
return
|
||||
tidb_dist_func = self._get_distance_func()
|
||||
|
|
@ -192,7 +192,7 @@ class TiDBVector(BaseVector):
|
|||
query_vector_str = ", ".join(format(x) for x in query_vector)
|
||||
query_vector_str = "[" + query_vector_str + "]"
|
||||
logger.debug(
|
||||
f"_collection_name: {self._collection_name}, score_threshold: {score_threshold}, distance: {distance}"
|
||||
"_collection_name: %s, score_threshold: %s, distance: %s", self._collection_name, score_threshold, distance
|
||||
)
|
||||
|
||||
docs = []
|
||||
|
|
|
|||
|
|
@ -178,19 +178,19 @@ class Vector:
|
|||
def create(self, texts: Optional[list] = None, **kwargs):
|
||||
if texts:
|
||||
start = time.time()
|
||||
logger.info(f"start embedding {len(texts)} texts {start}")
|
||||
logger.info("start embedding %s texts %s", len(texts), start)
|
||||
batch_size = 1000
|
||||
total_batches = len(texts) + batch_size - 1
|
||||
for i in range(0, len(texts), batch_size):
|
||||
batch = texts[i : i + batch_size]
|
||||
batch_start = time.time()
|
||||
logger.info(f"Processing batch {i // batch_size + 1}/{total_batches} ({len(batch)} texts)")
|
||||
logger.info("Processing batch %s/%s (%s texts)", i // batch_size + 1, total_batches, len(batch))
|
||||
batch_embeddings = self._embeddings.embed_documents([document.page_content for document in batch])
|
||||
logger.info(
|
||||
f"Embedding batch {i // batch_size + 1}/{total_batches} took {time.time() - batch_start:.3f}s"
|
||||
"Embedding batch %s/%s took %s s", i // batch_size + 1, total_batches, time.time() - batch_start
|
||||
)
|
||||
self._vector_processor.create(texts=batch, embeddings=batch_embeddings, **kwargs)
|
||||
logger.info(f"Embedding {len(texts)} texts took {time.time() - start:.3f}s")
|
||||
logger.info("Embedding %s texts took %s s", len(texts), time.time() - start)
|
||||
|
||||
def add_texts(self, documents: list[Document], **kwargs):
|
||||
if kwargs.get("duplicate_check", False):
|
||||
|
|
@ -219,7 +219,7 @@ class Vector:
|
|||
self._vector_processor.delete()
|
||||
# delete collection redis cache
|
||||
if self._vector_processor.collection_name:
|
||||
collection_exist_cache_key = "vector_indexing_{}".format(self._vector_processor.collection_name)
|
||||
collection_exist_cache_key = f"vector_indexing_{self._vector_processor.collection_name}"
|
||||
redis_client.delete(collection_exist_cache_key)
|
||||
|
||||
def _get_embeddings(self) -> Embeddings:
|
||||
|
|
|
|||
|
|
@ -92,9 +92,9 @@ class WeaviateVector(BaseVector):
|
|||
self.add_texts(texts, embeddings)
|
||||
|
||||
def _create_collection(self):
|
||||
lock_name = "vector_indexing_lock_{}".format(self._collection_name)
|
||||
lock_name = f"vector_indexing_lock_{self._collection_name}"
|
||||
with redis_client.lock(lock_name, timeout=20):
|
||||
collection_exist_cache_key = "vector_indexing_{}".format(self._collection_name)
|
||||
collection_exist_cache_key = f"vector_indexing_{self._collection_name}"
|
||||
if redis_client.get(collection_exist_cache_key):
|
||||
return
|
||||
schema = self._default_schema(self._collection_name)
|
||||
|
|
|
|||
|
|
@ -69,7 +69,7 @@ class CacheEmbedding(Embeddings):
|
|||
# stackoverflow best way: https://stackoverflow.com/questions/20319813/how-to-check-list-containing-nan
|
||||
if np.isnan(normalized_embedding).any():
|
||||
# for issue #11827 float values are not json compliant
|
||||
logger.warning(f"Normalized embedding is nan: {normalized_embedding}")
|
||||
logger.warning("Normalized embedding is nan: %s", normalized_embedding)
|
||||
continue
|
||||
embedding_queue_embeddings.append(normalized_embedding)
|
||||
except IntegrityError:
|
||||
|
|
@ -122,7 +122,7 @@ class CacheEmbedding(Embeddings):
|
|||
raise ValueError("Normalized embedding is nan please try again")
|
||||
except Exception as ex:
|
||||
if dify_config.DEBUG:
|
||||
logging.exception(f"Failed to embed query text '{text[:10]}...({len(text)} chars)'")
|
||||
logging.exception("Failed to embed query text '%s...(%s chars)'", text[:10], len(text))
|
||||
raise ex
|
||||
|
||||
try:
|
||||
|
|
@ -136,7 +136,9 @@ class CacheEmbedding(Embeddings):
|
|||
redis_client.setex(embedding_cache_key, 600, encoded_str)
|
||||
except Exception as ex:
|
||||
if dify_config.DEBUG:
|
||||
logging.exception(f"Failed to add embedding to redis for the text '{text[:10]}...({len(text)} chars)'")
|
||||
logging.exception(
|
||||
"Failed to add embedding to redis for the text '%s...(%s chars)'", text[:10], len(text)
|
||||
)
|
||||
raise ex
|
||||
|
||||
return embedding_results # type: ignore
|
||||
|
|
|
|||
|
|
@ -116,7 +116,7 @@ class TextSplitter(BaseDocumentTransformer, ABC):
|
|||
if total + _len + (separator_len if len(current_doc) > 0 else 0) > self._chunk_size:
|
||||
if total > self._chunk_size:
|
||||
logger.warning(
|
||||
f"Created a chunk of size {total}, which is longer than the specified {self._chunk_size}"
|
||||
"Created a chunk of size %s, which is longer than the specified %s", total, self._chunk_size
|
||||
)
|
||||
if len(current_doc) > 0:
|
||||
doc = self._join_docs(current_doc, separator)
|
||||
|
|
|
|||
|
|
@ -153,7 +153,7 @@ class DifyCoreRepositoryFactory:
|
|||
RepositoryImportError: If the configured repository cannot be created
|
||||
"""
|
||||
class_path = dify_config.CORE_WORKFLOW_EXECUTION_REPOSITORY
|
||||
logger.debug(f"Creating WorkflowExecutionRepository from: {class_path}")
|
||||
logger.debug("Creating WorkflowExecutionRepository from: %s", class_path)
|
||||
|
||||
try:
|
||||
repository_class = cls._import_class(class_path)
|
||||
|
|
@ -199,7 +199,7 @@ class DifyCoreRepositoryFactory:
|
|||
RepositoryImportError: If the configured repository cannot be created
|
||||
"""
|
||||
class_path = dify_config.CORE_WORKFLOW_NODE_EXECUTION_REPOSITORY
|
||||
logger.debug(f"Creating WorkflowNodeExecutionRepository from: {class_path}")
|
||||
logger.debug("Creating WorkflowNodeExecutionRepository from: %s", class_path)
|
||||
|
||||
try:
|
||||
repository_class = cls._import_class(class_path)
|
||||
|
|
|
|||
|
|
@ -203,5 +203,5 @@ class SQLAlchemyWorkflowExecutionRepository(WorkflowExecutionRepository):
|
|||
session.commit()
|
||||
|
||||
# Update the in-memory cache for faster subsequent lookups
|
||||
logger.debug(f"Updating cache for execution_id: {db_model.id}")
|
||||
logger.debug("Updating cache for execution_id: %s", db_model.id)
|
||||
self._execution_cache[db_model.id] = db_model
|
||||
|
|
|
|||
|
|
@ -215,7 +215,7 @@ class SQLAlchemyWorkflowNodeExecutionRepository(WorkflowNodeExecutionRepository)
|
|||
# Update the in-memory cache for faster subsequent lookups
|
||||
# Only cache if we have a node_execution_id to use as the cache key
|
||||
if db_model.node_execution_id:
|
||||
logger.debug(f"Updating cache for node_execution_id: {db_model.node_execution_id}")
|
||||
logger.debug("Updating cache for node_execution_id: %s", db_model.node_execution_id)
|
||||
self._node_execution_cache[db_model.node_execution_id] = db_model
|
||||
|
||||
def get_db_models_by_workflow_run(
|
||||
|
|
|
|||
|
|
@ -206,7 +206,7 @@ class ToolManager:
|
|||
)
|
||||
except Exception as e:
|
||||
builtin_provider = None
|
||||
logger.info(f"Error getting builtin provider {credential_id}:{e}", exc_info=True)
|
||||
logger.info("Error getting builtin provider %s:%s", credential_id, e, exc_info=True)
|
||||
# if the provider has been deleted, raise an error
|
||||
if builtin_provider is None:
|
||||
raise ToolProviderNotFoundError(f"provider has been deleted: {credential_id}")
|
||||
|
|
@ -569,7 +569,7 @@ class ToolManager:
|
|||
yield provider
|
||||
|
||||
except Exception:
|
||||
logger.exception(f"load builtin provider {provider_path}")
|
||||
logger.exception("load builtin provider %s", provider_path)
|
||||
continue
|
||||
# set builtin providers loaded
|
||||
cls._builtin_providers_loaded = True
|
||||
|
|
|
|||
|
|
@ -55,7 +55,7 @@ def get_url(url: str, user_agent: Optional[str] = None) -> str:
|
|||
main_content_type = mimetypes.guess_type(filename)[0]
|
||||
|
||||
if main_content_type not in supported_content_types:
|
||||
return "Unsupported content-type [{}] of URL.".format(main_content_type)
|
||||
return f"Unsupported content-type [{main_content_type}] of URL."
|
||||
|
||||
if main_content_type in extract_processor.SUPPORT_URL_CONTENT_TYPES:
|
||||
return cast(str, ExtractProcessor.load_from_url(url, return_text=True))
|
||||
|
|
@ -67,7 +67,7 @@ def get_url(url: str, user_agent: Optional[str] = None) -> str:
|
|||
response = scraper.get(url, headers=headers, follow_redirects=True, timeout=(120, 300)) # type: ignore
|
||||
|
||||
if response.status_code != 200:
|
||||
return "URL returned status code {}.".format(response.status_code)
|
||||
return f"URL returned status code {response.status_code}."
|
||||
|
||||
# Detect encoding using chardet
|
||||
detected_encoding = chardet.detect(response.content)
|
||||
|
|
|
|||
|
|
@ -194,7 +194,7 @@ class WorkflowTool(Tool):
|
|||
|
||||
files.append(file_dict)
|
||||
except Exception:
|
||||
logger.exception(f"Failed to transform file {file}")
|
||||
logger.exception("Failed to transform file %s", file)
|
||||
else:
|
||||
parameters_result[parameter.name] = tool_parameters.get(parameter.name)
|
||||
|
||||
|
|
|
|||
|
|
@ -238,13 +238,13 @@ class GraphEngine:
|
|||
while True:
|
||||
# max steps reached
|
||||
if self.graph_runtime_state.node_run_steps > self.max_execution_steps:
|
||||
raise GraphRunFailedError("Max steps {} reached.".format(self.max_execution_steps))
|
||||
raise GraphRunFailedError(f"Max steps {self.max_execution_steps} reached.")
|
||||
|
||||
# or max execution time reached
|
||||
if self._is_timed_out(
|
||||
start_at=self.graph_runtime_state.start_at, max_execution_time=self.max_execution_time
|
||||
):
|
||||
raise GraphRunFailedError("Max execution time {}s reached.".format(self.max_execution_time))
|
||||
raise GraphRunFailedError(f"Max execution time {self.max_execution_time}s reached.")
|
||||
|
||||
# init route node state
|
||||
route_node_state = self.graph_runtime_state.node_run_state.create_node_state(node_id=next_node_id)
|
||||
|
|
@ -377,7 +377,7 @@ class GraphEngine:
|
|||
|
||||
edge = cast(GraphEdge, sub_edge_mappings[0])
|
||||
if edge.run_condition is None:
|
||||
logger.warning(f"Edge {edge.target_node_id} run condition is None")
|
||||
logger.warning("Edge %s run condition is None", edge.target_node_id)
|
||||
continue
|
||||
|
||||
result = ConditionManager.get_condition_handler(
|
||||
|
|
@ -848,7 +848,7 @@ class GraphEngine:
|
|||
)
|
||||
return
|
||||
except Exception as e:
|
||||
logger.exception(f"Node {node.title} run failed")
|
||||
logger.exception("Node %s run failed", node.title)
|
||||
raise e
|
||||
|
||||
def _append_variables_recursively(self, node_id: str, variable_key_list: list[str], variable_value: VariableValue):
|
||||
|
|
|
|||
|
|
@ -36,7 +36,7 @@ class StreamProcessor(ABC):
|
|||
reachable_node_ids: list[str] = []
|
||||
unreachable_first_node_ids: list[str] = []
|
||||
if finished_node_id not in self.graph.edge_mapping:
|
||||
logger.warning(f"node {finished_node_id} has no edge mapping")
|
||||
logger.warning("node %s has no edge mapping", finished_node_id)
|
||||
return
|
||||
for edge in self.graph.edge_mapping[finished_node_id]:
|
||||
if (
|
||||
|
|
|
|||
|
|
@ -65,7 +65,7 @@ class BaseNode:
|
|||
try:
|
||||
result = self._run()
|
||||
except Exception as e:
|
||||
logger.exception(f"Node {self.node_id} failed to run")
|
||||
logger.exception("Node %s failed to run", self.node_id)
|
||||
result = NodeRunResult(
|
||||
status=WorkflowNodeExecutionStatus.FAILED,
|
||||
error=str(e),
|
||||
|
|
|
|||
|
|
@ -363,7 +363,7 @@ def _extract_text_from_docx(file_content: bytes) -> str:
|
|||
|
||||
text.append(markdown_table)
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to extract table from DOC: {e}")
|
||||
logger.warning("Failed to extract table from DOC: %s", e)
|
||||
continue
|
||||
|
||||
return "\n".join(text)
|
||||
|
|
|
|||
|
|
@ -129,7 +129,7 @@ class HttpRequestNode(BaseNode):
|
|||
},
|
||||
)
|
||||
except HttpRequestNodeError as e:
|
||||
logger.warning(f"http request node {self.node_id} failed to run: {e}")
|
||||
logger.warning("http request node %s failed to run: %s", self.node_id, e)
|
||||
return NodeRunResult(
|
||||
status=WorkflowNodeExecutionStatus.FAILED,
|
||||
error=str(e),
|
||||
|
|
|
|||
|
|
@ -129,7 +129,7 @@ class IfElseNode(BaseNode):
|
|||
var_mapping: dict[str, list[str]] = {}
|
||||
for case in typed_node_data.cases or []:
|
||||
for condition in case.conditions:
|
||||
key = "{}.#{}#".format(node_id, ".".join(condition.variable_selector))
|
||||
key = f"{node_id}.#{'.'.join(condition.variable_selector)}#"
|
||||
var_mapping[key] = condition.variable_selector
|
||||
|
||||
return var_mapping
|
||||
|
|
|
|||
|
|
@ -616,7 +616,7 @@ class IterationNode(BaseNode):
|
|||
)
|
||||
|
||||
except IterationNodeError as e:
|
||||
logger.warning(f"Iteration run failed:{str(e)}")
|
||||
logger.warning("Iteration run failed:%s", str(e))
|
||||
yield IterationRunFailedEvent(
|
||||
iteration_id=self.id,
|
||||
iteration_node_id=self.node_id,
|
||||
|
|
|
|||
|
|
@ -670,7 +670,7 @@ class ParameterExtractorNode(BaseNode):
|
|||
return cast(dict, json.loads(json_str))
|
||||
except Exception:
|
||||
pass
|
||||
logger.info(f"extra error: {result}")
|
||||
logger.info("extra error: %s", result)
|
||||
return None
|
||||
|
||||
def _extract_json_from_tool_call(self, tool_call: AssistantPromptMessage.ToolCall) -> Optional[dict]:
|
||||
|
|
@ -690,7 +690,7 @@ class ParameterExtractorNode(BaseNode):
|
|||
return cast(dict, json.loads(json_str))
|
||||
except Exception:
|
||||
pass
|
||||
logger.info(f"extra error: {result}")
|
||||
logger.info("extra error: %s", result)
|
||||
return None
|
||||
|
||||
def _generate_default_result(self, data: ParameterExtractorNodeData) -> dict:
|
||||
|
|
|
|||
|
|
@ -67,7 +67,7 @@ class WorkflowEntry:
|
|||
# check call depth
|
||||
workflow_call_max_depth = dify_config.WORKFLOW_CALL_MAX_DEPTH
|
||||
if call_depth > workflow_call_max_depth:
|
||||
raise ValueError("Max workflow call depth {} reached.".format(workflow_call_max_depth))
|
||||
raise ValueError(f"Max workflow call depth {workflow_call_max_depth} reached.")
|
||||
|
||||
# init workflow run state
|
||||
graph_runtime_state = GraphRuntimeState(variable_pool=variable_pool, start_at=time.perf_counter())
|
||||
|
|
@ -193,7 +193,13 @@ class WorkflowEntry:
|
|||
# run node
|
||||
generator = node.run()
|
||||
except Exception as e:
|
||||
logger.exception(f"error while running node, {workflow.id=}, {node.id=}, {node.type_=}, {node.version()=}")
|
||||
logger.exception(
|
||||
"error while running node, workflow_id=%s, node_id=%s, node_type=%s, node_version=%s",
|
||||
workflow.id,
|
||||
node.id,
|
||||
node.type_,
|
||||
node.version(),
|
||||
)
|
||||
raise WorkflowNodeRunFailedError(node=node, err_msg=str(e))
|
||||
return node, generator
|
||||
|
||||
|
|
@ -297,7 +303,12 @@ class WorkflowEntry:
|
|||
|
||||
return node, generator
|
||||
except Exception as e:
|
||||
logger.exception(f"error while running node, {node.id=}, {node.type_=}, {node.version()=}")
|
||||
logger.exception(
|
||||
"error while running node, node_id=%s, node_type=%s, node_version=%s",
|
||||
node.id,
|
||||
node.type_,
|
||||
node.version(),
|
||||
)
|
||||
raise WorkflowNodeRunFailedError(node=node, err_msg=str(e))
|
||||
|
||||
@staticmethod
|
||||
|
|
|
|||
|
|
@ -18,7 +18,7 @@ def handle(sender, **kwargs):
|
|||
documents = []
|
||||
start_at = time.perf_counter()
|
||||
for document_id in document_ids:
|
||||
logging.info(click.style("Start process document: {}".format(document_id), fg="green"))
|
||||
logging.info(click.style(f"Start process document: {document_id}", fg="green"))
|
||||
|
||||
document = (
|
||||
db.session.query(Document)
|
||||
|
|
@ -42,7 +42,7 @@ def handle(sender, **kwargs):
|
|||
indexing_runner = IndexingRunner()
|
||||
indexing_runner.run(documents)
|
||||
end_at = time.perf_counter()
|
||||
logging.info(click.style("Processed dataset: {} latency: {}".format(dataset_id, end_at - start_at), fg="green"))
|
||||
logging.info(click.style(f"Processed dataset: {dataset_id} latency: {end_at - start_at}", fg="green"))
|
||||
except DocumentIsPausedError as ex:
|
||||
logging.info(click.style(str(ex), fg="yellow"))
|
||||
except Exception:
|
||||
|
|
|
|||
|
|
@ -131,9 +131,11 @@ def handle(sender: Message, **kwargs):
|
|||
duration = time_module.perf_counter() - start_time
|
||||
|
||||
logger.info(
|
||||
f"Provider updates completed successfully. "
|
||||
f"Updates: {len(updates_to_perform)}, Duration: {duration:.3f}s, "
|
||||
f"Tenant: {tenant_id}, Provider: {provider_name}"
|
||||
"Provider updates completed successfully. Updates: %s, Duration: %s s, Tenant: %s, Provider: %s",
|
||||
len(updates_to_perform),
|
||||
duration,
|
||||
tenant_id,
|
||||
provider_name,
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
|
|
@ -141,9 +143,11 @@ def handle(sender: Message, **kwargs):
|
|||
duration = time_module.perf_counter() - start_time
|
||||
|
||||
logger.exception(
|
||||
f"Provider updates failed after {duration:.3f}s. "
|
||||
f"Updates: {len(updates_to_perform)}, Tenant: {tenant_id}, "
|
||||
f"Provider: {provider_name}"
|
||||
"Provider updates failed after %s s. Updates: %s, Tenant: %s, Provider: %s",
|
||||
duration,
|
||||
len(updates_to_perform),
|
||||
tenant_id,
|
||||
provider_name,
|
||||
)
|
||||
raise
|
||||
|
||||
|
|
@ -219,16 +223,20 @@ def _execute_provider_updates(updates_to_perform: list[_ProviderUpdateOperation]
|
|||
rows_affected = result.rowcount
|
||||
|
||||
logger.debug(
|
||||
f"Provider update ({description}): {rows_affected} rows affected. "
|
||||
f"Filters: {filters.model_dump()}, Values: {update_values}"
|
||||
"Provider update (%s): %s rows affected. Filters: %s, Values: %s",
|
||||
description,
|
||||
rows_affected,
|
||||
filters.model_dump(),
|
||||
update_values,
|
||||
)
|
||||
|
||||
# If no rows were affected for quota updates, log a warning
|
||||
if rows_affected == 0 and description == "quota_deduction_update":
|
||||
logger.warning(
|
||||
f"No Provider rows updated for quota deduction. "
|
||||
f"This may indicate quota limit exceeded or provider not found. "
|
||||
f"Filters: {filters.model_dump()}"
|
||||
"No Provider rows updated for quota deduction. "
|
||||
"This may indicate quota limit exceeded or provider not found. "
|
||||
"Filters: %s",
|
||||
filters.model_dump(),
|
||||
)
|
||||
|
||||
logger.debug(f"Successfully processed {len(updates_to_perform)} Provider updates")
|
||||
logger.debug("Successfully processed %s Provider updates", len(updates_to_perform))
|
||||
|
|
|
|||
|
|
@ -64,7 +64,7 @@ class Mail:
|
|||
sendgrid_api_key=dify_config.SENDGRID_API_KEY, _from=dify_config.MAIL_DEFAULT_SEND_FROM or ""
|
||||
)
|
||||
case _:
|
||||
raise ValueError("Unsupported mail type {}".format(mail_type))
|
||||
raise ValueError(f"Unsupported mail type {mail_type}")
|
||||
|
||||
def send(self, to: str, subject: str, html: str, from_: Optional[str] = None):
|
||||
if not self._client:
|
||||
|
|
|
|||
|
|
@ -137,7 +137,7 @@ def redis_fallback(default_return: Any = None):
|
|||
try:
|
||||
return func(*args, **kwargs)
|
||||
except RedisError as e:
|
||||
logger.warning(f"Redis operation failed in {func.__name__}: {str(e)}", exc_info=True)
|
||||
logger.warning("Redis operation failed in %s: %s", func.__name__, str(e), exc_info=True)
|
||||
return default_return
|
||||
|
||||
return wrapper
|
||||
|
|
|
|||
|
|
@ -69,7 +69,7 @@ class AzureBlobStorage(BaseStorage):
|
|||
if self.account_key == "managedidentity":
|
||||
return BlobServiceClient(account_url=self.account_url, credential=self.credential) # type: ignore
|
||||
|
||||
cache_key = "azure_blob_sas_token_{}_{}".format(self.account_name, self.account_key)
|
||||
cache_key = f"azure_blob_sas_token_{self.account_name}_{self.account_key}"
|
||||
cache_result = redis_client.get(cache_key)
|
||||
if cache_result is not None:
|
||||
sas_token = cache_result.decode("utf-8")
|
||||
|
|
|
|||
|
|
@ -35,21 +35,21 @@ class OpenDALStorage(BaseStorage):
|
|||
Path(root).mkdir(parents=True, exist_ok=True)
|
||||
|
||||
self.op = opendal.Operator(scheme=scheme, **kwargs) # type: ignore
|
||||
logger.debug(f"opendal operator created with scheme {scheme}")
|
||||
logger.debug("opendal operator created with scheme %s", scheme)
|
||||
retry_layer = opendal.layers.RetryLayer(max_times=3, factor=2.0, jitter=True)
|
||||
self.op = self.op.layer(retry_layer)
|
||||
logger.debug("added retry layer to opendal operator")
|
||||
|
||||
def save(self, filename: str, data: bytes) -> None:
|
||||
self.op.write(path=filename, bs=data)
|
||||
logger.debug(f"file {filename} saved")
|
||||
logger.debug("file %s saved", filename)
|
||||
|
||||
def load_once(self, filename: str) -> bytes:
|
||||
if not self.exists(filename):
|
||||
raise FileNotFoundError("File not found")
|
||||
|
||||
content: bytes = self.op.read(path=filename)
|
||||
logger.debug(f"file {filename} loaded")
|
||||
logger.debug("file %s loaded", filename)
|
||||
return content
|
||||
|
||||
def load_stream(self, filename: str) -> Generator:
|
||||
|
|
@ -60,7 +60,7 @@ class OpenDALStorage(BaseStorage):
|
|||
file = self.op.open(path=filename, mode="rb")
|
||||
while chunk := file.read(batch_size):
|
||||
yield chunk
|
||||
logger.debug(f"file {filename} loaded as stream")
|
||||
logger.debug("file %s loaded as stream", filename)
|
||||
|
||||
def download(self, filename: str, target_filepath: str):
|
||||
if not self.exists(filename):
|
||||
|
|
@ -68,7 +68,7 @@ class OpenDALStorage(BaseStorage):
|
|||
|
||||
with Path(target_filepath).open("wb") as f:
|
||||
f.write(self.op.read(path=filename))
|
||||
logger.debug(f"file {filename} downloaded to {target_filepath}")
|
||||
logger.debug("file %s downloaded to %s", filename, target_filepath)
|
||||
|
||||
def exists(self, filename: str) -> bool:
|
||||
res: bool = self.op.exists(path=filename)
|
||||
|
|
@ -77,9 +77,9 @@ class OpenDALStorage(BaseStorage):
|
|||
def delete(self, filename: str):
|
||||
if self.exists(filename):
|
||||
self.op.delete(path=filename)
|
||||
logger.debug(f"file {filename} deleted")
|
||||
logger.debug("file %s deleted", filename)
|
||||
return
|
||||
logger.debug(f"file {filename} not found, skip delete")
|
||||
logger.debug("file %s not found, skip delete", filename)
|
||||
|
||||
def scan(self, path: str, files: bool = True, directories: bool = False) -> list[str]:
|
||||
if not self.exists(path):
|
||||
|
|
@ -87,13 +87,13 @@ class OpenDALStorage(BaseStorage):
|
|||
|
||||
all_files = self.op.scan(path=path)
|
||||
if files and directories:
|
||||
logger.debug(f"files and directories on {path} scanned")
|
||||
logger.debug("files and directories on %s scanned", path)
|
||||
return [f.path for f in all_files]
|
||||
if files:
|
||||
logger.debug(f"files on {path} scanned")
|
||||
logger.debug("files on %s scanned", path)
|
||||
return [f.path for f in all_files if not f.path.endswith("/")]
|
||||
elif directories:
|
||||
logger.debug(f"directories on {path} scanned")
|
||||
logger.debug("directories on %s scanned", path)
|
||||
return [f.path for f in all_files if f.path.endswith("/")]
|
||||
else:
|
||||
raise ValueError("At least one of files or directories must be True")
|
||||
|
|
|
|||
|
|
@ -25,7 +25,7 @@ class VolcengineTosStorage(BaseStorage):
|
|||
def load_once(self, filename: str) -> bytes:
|
||||
data = self.client.get_object(bucket=self.bucket_name, key=filename).read()
|
||||
if not isinstance(data, bytes):
|
||||
raise TypeError("Expected bytes, got {}".format(type(data).__name__))
|
||||
raise TypeError(f"Expected bytes, got {type(data).__name__}")
|
||||
return data
|
||||
|
||||
def load_stream(self, filename: str) -> Generator:
|
||||
|
|
|
|||
|
|
@ -95,7 +95,7 @@ def email(email):
|
|||
if re.match(pattern, email) is not None:
|
||||
return email
|
||||
|
||||
error = "{email} is not a valid email.".format(email=email)
|
||||
error = f"{email} is not a valid email."
|
||||
raise ValueError(error)
|
||||
|
||||
|
||||
|
|
@ -107,7 +107,7 @@ def uuid_value(value):
|
|||
uuid_obj = uuid.UUID(value)
|
||||
return str(uuid_obj)
|
||||
except ValueError:
|
||||
error = "{value} is not a valid uuid.".format(value=value)
|
||||
error = f"{value} is not a valid uuid."
|
||||
raise ValueError(error)
|
||||
|
||||
|
||||
|
|
@ -126,7 +126,7 @@ def timestamp_value(timestamp):
|
|||
raise ValueError
|
||||
return int_timestamp
|
||||
except ValueError:
|
||||
error = "{timestamp} is not a valid timestamp.".format(timestamp=timestamp)
|
||||
error = f"{timestamp} is not a valid timestamp."
|
||||
raise ValueError(error)
|
||||
|
||||
|
||||
|
|
@ -169,14 +169,14 @@ def _get_float(value):
|
|||
try:
|
||||
return float(value)
|
||||
except (TypeError, ValueError):
|
||||
raise ValueError("{} is not a valid float".format(value))
|
||||
raise ValueError(f"{value} is not a valid float")
|
||||
|
||||
|
||||
def timezone(timezone_string):
|
||||
if timezone_string and timezone_string in available_timezones():
|
||||
return timezone_string
|
||||
|
||||
error = "{timezone_string} is not a valid timezone.".format(timezone_string=timezone_string)
|
||||
error = f"{timezone_string} is not a valid timezone."
|
||||
raise ValueError(error)
|
||||
|
||||
|
||||
|
|
@ -321,7 +321,7 @@ class TokenManager:
|
|||
key = cls._get_token_key(token, token_type)
|
||||
token_data_json = redis_client.get(key)
|
||||
if token_data_json is None:
|
||||
logging.warning(f"{token_type} token {token} not found with key {key}")
|
||||
logging.warning("%s token %s not found with key %s", token_type, token, key)
|
||||
return None
|
||||
token_data: Optional[dict[str, Any]] = json.loads(token_data_json)
|
||||
return token_data
|
||||
|
|
|
|||
|
|
@ -50,13 +50,13 @@ def encrypt(text: str, public_key: Union[str, bytes]) -> bytes:
|
|||
def get_decrypt_decoding(tenant_id: str) -> tuple[RSA.RsaKey, object]:
|
||||
filepath = os.path.join("privkeys", tenant_id, "private.pem")
|
||||
|
||||
cache_key = "tenant_privkey:{hash}".format(hash=hashlib.sha3_256(filepath.encode()).hexdigest())
|
||||
cache_key = f"tenant_privkey:{hashlib.sha3_256(filepath.encode()).hexdigest()}"
|
||||
private_key = redis_client.get(cache_key)
|
||||
if not private_key:
|
||||
try:
|
||||
private_key = storage.load(filepath)
|
||||
except FileNotFoundError:
|
||||
raise PrivkeyNotFoundError("Private key not found, tenant_id: {tenant_id}".format(tenant_id=tenant_id))
|
||||
raise PrivkeyNotFoundError(f"Private key not found, tenant_id: {tenant_id}")
|
||||
|
||||
redis_client.setex(cache_key, 120, private_key)
|
||||
|
||||
|
|
|
|||
|
|
@ -41,5 +41,5 @@ class SendGridClient:
|
|||
)
|
||||
raise
|
||||
except Exception as e:
|
||||
logging.exception(f"SendGridClient Unexpected error occurred while sending email to {_to}")
|
||||
logging.exception("SendGridClient Unexpected error occurred while sending email to %s", _to)
|
||||
raise
|
||||
|
|
|
|||
|
|
@ -50,7 +50,7 @@ class SMTPClient:
|
|||
logging.exception("Timeout occurred while sending email")
|
||||
raise
|
||||
except Exception as e:
|
||||
logging.exception(f"Unexpected error occurred while sending email to {mail['to']}")
|
||||
logging.exception("Unexpected error occurred while sending email to %s", mail["to"])
|
||||
raise
|
||||
finally:
|
||||
if smtp:
|
||||
|
|
|
|||
Some files were not shown because too many files have changed in this diff Show More
Loading…
Reference in New Issue