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new 8a0d0bea feat: persist schema generator examples (#362)
8a0d0bea is described below
commit 8a0d0bea5e095d785ebb87b1d8c1dd309e15c48b
Author: Nannan Wang <[email protected]>
AuthorDate: Mon Jun 15 13:59:07 2026 +0800
feat: persist schema generator examples (#362)
## Purpose
Closes #346.
This PR persists edited schema-generator query examples and few-shot
schema examples in the demo.
## Changes
* Added prompt config fields for schema-generator query examples and
few-shot schema examples.
* Load persisted schema-generator examples into the demo UI before
falling back to bundled resource examples.
* Persist edited examples through the existing prompt config save path.
* Validate edited examples as JSON before saving.
* Reject invalid JSON with a clear UI error and avoid persisting invalid
content.
* Keep bundled examples under `resources/prompt_examples` read-only as
defaults.
* Added tests for save/load behavior, invalid JSON handling, bundled
fallback behavior, invalid persisted fallback behavior, UI persistence
wiring, and old prompt config compatibility.
nt`
---------
Co-authored-by: nannan-2026 <[email protected]>
---
.../config/models/base_prompt_config.py | 4 +
.../demo/rag_demo/vector_graph_block.py | 197 +++++++++++-
.../test_schema_generator_examples_persistence.py | 347 +++++++++++++++++++++
3 files changed, 534 insertions(+), 14 deletions(-)
diff --git
a/hugegraph-llm/src/hugegraph_llm/config/models/base_prompt_config.py
b/hugegraph-llm/src/hugegraph_llm/config/models/base_prompt_config.py
index e8eb663f..7a7cfa7f 100644
--- a/hugegraph-llm/src/hugegraph_llm/config/models/base_prompt_config.py
+++ b/hugegraph-llm/src/hugegraph_llm/config/models/base_prompt_config.py
@@ -79,6 +79,8 @@ class BasePromptConfig:
gremlin_generate_prompt: str = ""
doc_input_text: str = ""
graph_extract_split_type: str = "document"
+ schema_generator_query_examples: str = ""
+ schema_generator_few_shot_examples: str = ""
_language_generated: str = ""
generate_extract_prompt_template: str = ""
@@ -138,6 +140,8 @@ class BasePromptConfig:
"gremlin_generate_prompt":
to_literal(self.gremlin_generate_prompt),
"doc_input_text": to_literal(self.doc_input_text),
"graph_extract_split_type":
to_literal(self.graph_extract_split_type),
+ "schema_generator_query_examples":
to_literal(self.schema_generator_query_examples),
+ "schema_generator_few_shot_examples":
to_literal(self.schema_generator_few_shot_examples),
"_language_generated":
str(self.llm_settings.language).lower().strip(),
"generate_extract_prompt_template":
to_literal(self.generate_extract_prompt_template),
}
diff --git
a/hugegraph-llm/src/hugegraph_llm/demo/rag_demo/vector_graph_block.py
b/hugegraph-llm/src/hugegraph_llm/demo/rag_demo/vector_graph_block.py
index 81de3480..9e5cf0b5 100644
--- a/hugegraph-llm/src/hugegraph_llm/demo/rag_demo/vector_graph_block.py
+++ b/hugegraph-llm/src/hugegraph_llm/demo/rag_demo/vector_graph_block.py
@@ -44,7 +44,116 @@ from hugegraph_llm.utils.vector_index_utils import (
)
-def store_prompt(doc, schema, example_prompt,
graph_extract_split_type="document"):
+def _dump_json_examples(value):
+ return json.dumps(value, indent=2, ensure_ascii=False)
+
+
+def _normalize_schema_generator_query_examples(examples):
+ examples = (examples or "").strip()
+ if not examples:
+ return ""
+
+ try:
+ parsed_examples = json.loads(examples)
+ except json.JSONDecodeError as exc:
+ raise gr.Error(
+ f"Query examples must be valid JSON: {exc.msg} at line
{exc.lineno}, column {exc.colno}"
+ ) from exc
+
+ if not isinstance(parsed_examples, list):
+ raise gr.Error("Query examples must be a JSON list.")
+
+ normalized_examples = []
+ for index, item in enumerate(parsed_examples):
+ if isinstance(item, str):
+ description = item.strip()
+ if not description:
+ raise gr.Error(f"Query examples[{index}] must be a non-empty
string.")
+ normalized_examples.append(
+ {
+ "description": description,
+ "gremlin": "",
+ }
+ )
+ continue
+
+ if isinstance(item, dict):
+ description = item.get("description")
+ gremlin = item.get("gremlin")
+ if not isinstance(description, str) or not description.strip():
+ raise gr.Error("Each query example object must contain a
non-empty `description` string.")
+ if not isinstance(gremlin, str):
+ raise gr.Error("Each query example object must contain a
`gremlin` string.")
+ normalized_examples.append(
+ {
+ "description": description.strip(),
+ "gremlin": gremlin.strip(),
+ }
+ )
+ continue
+
+ raise gr.Error("Query examples must contain strings or objects with
`description` and `gremlin` fields.")
+
+ return _dump_json_examples(normalized_examples)
+
+
+def _validate_schema_generator_few_shot_examples(examples):
+ examples = (examples or "").strip()
+ if not examples:
+ return ""
+
+ try:
+ parsed_examples = json.loads(examples)
+ except json.JSONDecodeError as exc:
+ raise gr.Error(
+ f"Few-shot schema examples must be valid JSON: {exc.msg} at line
{exc.lineno}, column {exc.colno}"
+ ) from exc
+
+ if not isinstance(parsed_examples, dict):
+ raise gr.Error("Few-shot schema examples must be a JSON object.")
+
+ return _dump_json_examples(parsed_examples)
+
+
+def _load_persisted_json_examples(examples, label):
+ examples = (examples or "").strip()
+ if not examples:
+ return ""
+ try:
+ json.loads(examples)
+ except json.JSONDecodeError as exc:
+ log.warning("Ignoring invalid persisted %s: %s", label, exc)
+ return ""
+ return examples
+
+
+def _persist_schema_generator_examples(query_examples, few_shot_examples):
+ validated_query_examples =
_normalize_schema_generator_query_examples(query_examples)
+ validated_few_shot_examples =
_validate_schema_generator_few_shot_examples(few_shot_examples)
+
+ changed = False
+ if getattr(prompt, "schema_generator_query_examples", "") !=
validated_query_examples:
+ prompt.schema_generator_query_examples = validated_query_examples
+ changed = True
+
+ if getattr(prompt, "schema_generator_few_shot_examples", "") !=
validated_few_shot_examples:
+ prompt.schema_generator_few_shot_examples = validated_few_shot_examples
+ changed = True
+
+ if changed:
+ prompt.update_yaml_file()
+
+ effective_query_examples = validated_query_examples or
load_query_examples()
+ effective_few_shot_examples = validated_few_shot_examples or
load_schema_fewshot_examples()
+ return effective_query_examples, effective_few_shot_examples
+
+
+def store_prompt(
+ doc,
+ schema,
+ example_prompt,
+ graph_extract_split_type="document",
+):
if (
prompt.doc_input_text != doc
or prompt.graph_schema != schema
@@ -89,6 +198,13 @@ def load_example_names():
def load_query_examples():
"""Load query examples from JSON file based on the prompt language
setting"""
+ persisted_examples = _load_persisted_json_examples(
+ getattr(prompt, "schema_generator_query_examples", ""),
+ "schema generator query examples",
+ )
+ if persisted_examples:
+ return _normalize_schema_generator_query_examples(persisted_examples)
+
try:
language = getattr(
prompt,
@@ -102,24 +218,31 @@ def load_query_examples():
with open(examples_path, "r", encoding="utf-8") as f:
examples = json.load(f)
- return json.dumps(examples, indent=2, ensure_ascii=False)
+ return _normalize_schema_generator_query_examples(json.dumps(examples,
ensure_ascii=False))
except (FileNotFoundError, json.JSONDecodeError):
try:
examples_path = os.path.join(resource_path, "prompt_examples",
"query_examples.json")
with open(examples_path, "r", encoding="utf-8") as f:
examples = json.load(f)
- return json.dumps(examples, indent=2, ensure_ascii=False)
+ return
_normalize_schema_generator_query_examples(json.dumps(examples,
ensure_ascii=False))
except (FileNotFoundError, json.JSONDecodeError):
return "[]"
def load_schema_fewshot_examples():
"""Load few-shot examples from a JSON file"""
+ persisted_examples = _load_persisted_json_examples(
+ getattr(prompt, "schema_generator_few_shot_examples", ""),
+ "schema generator few-shot examples",
+ )
+ if persisted_examples:
+ return _validate_schema_generator_few_shot_examples(persisted_examples)
+
try:
examples_path = os.path.join(resource_path, "prompt_examples",
"schema_examples.json")
with open(examples_path, "r", encoding="utf-8") as f:
examples = json.load(f)
- return json.dumps(examples, indent=2, ensure_ascii=False)
+ return
_validate_schema_generator_few_shot_examples(json.dumps(examples,
ensure_ascii=False))
except (FileNotFoundError, json.JSONDecodeError):
return "[]"
@@ -205,6 +328,7 @@ def _create_prompt_helper_block(demo, input_text,
info_extract_template):
def _build_schema_and_provide_feedback(input_text, query_example, few_shot):
+ query_example, few_shot =
_persist_schema_generator_examples(query_example, few_shot)
gr.Info("Generating schema, please wait...")
# Call the original build_schema function
generated_schema = build_schema(input_text, query_example, few_shot)
@@ -311,31 +435,66 @@ def create_vector_graph_block():
vector_index_btn0.click(get_vector_index_info, outputs=out).then(
store_prompt,
- inputs=[input_text, input_schema, info_extract_template,
graph_split_type],
+ inputs=[
+ input_text,
+ input_schema,
+ info_extract_template,
+ graph_split_type,
+ ],
)
vector_index_btn1.click(clean_vector_index).then(
store_prompt,
- inputs=[input_text, input_schema, info_extract_template,
graph_split_type],
+ inputs=[
+ input_text,
+ input_schema,
+ info_extract_template,
+ graph_split_type,
+ ],
)
vector_import_bt.click(build_vector_index, inputs=[input_file,
input_text], outputs=out).then(
store_prompt,
- inputs=[input_text, input_schema, info_extract_template,
graph_split_type],
+ inputs=[
+ input_text,
+ input_schema,
+ info_extract_template,
+ graph_split_type,
+ ],
)
graph_index_btn0.click(get_graph_index_info, outputs=out).then(
store_prompt,
- inputs=[input_text, input_schema, info_extract_template,
graph_split_type],
+ inputs=[
+ input_text,
+ input_schema,
+ info_extract_template,
+ graph_split_type,
+ ],
)
graph_index_btn1.click(clean_all_graph_index).then(
store_prompt,
- inputs=[input_text, input_schema, info_extract_template,
graph_split_type],
+ inputs=[
+ input_text,
+ input_schema,
+ info_extract_template,
+ graph_split_type,
+ ],
)
graph_data_btn0.click(clean_all_graph_data).then(
store_prompt,
- inputs=[input_text, input_schema, info_extract_template,
graph_split_type],
+ inputs=[
+ input_text,
+ input_schema,
+ info_extract_template,
+ graph_split_type,
+ ],
)
graph_index_rebuild_bt.click(update_vid_embedding, outputs=out).then(
store_prompt,
- inputs=[input_text, input_schema, info_extract_template,
graph_split_type],
+ inputs=[
+ input_text,
+ input_schema,
+ info_extract_template,
+ graph_split_type,
+ ],
)
# origin_out = gr.Textbox(visible=False)
@@ -351,14 +510,24 @@ def create_vector_graph_block():
outputs=[out],
).then(
store_prompt,
- inputs=[input_text, input_schema, info_extract_template,
graph_split_type],
+ inputs=[
+ input_text,
+ input_schema,
+ info_extract_template,
+ graph_split_type,
+ ],
)
graph_loading_bt.click(import_graph_data, inputs=[out, input_schema],
outputs=[out]).then(
update_vid_embedding
).then(
store_prompt,
- inputs=[input_text, input_schema, info_extract_template,
graph_split_type],
+ inputs=[
+ input_text,
+ input_schema,
+ info_extract_template,
+ graph_split_type,
+ ],
)
# TODO: we should store the examples after the user changed them.
@@ -373,7 +542,7 @@ def create_vector_graph_block():
input_schema,
info_extract_template,
graph_split_type,
- ], # TODO: Store the updated examples
+ ], # Persist the updated schema-generator examples
)
def on_tab_select(input_f, input_t, evt: gr.SelectData):
diff --git
a/hugegraph-llm/src/tests/document/test_schema_generator_examples_persistence.py
b/hugegraph-llm/src/tests/document/test_schema_generator_examples_persistence.py
new file mode 100644
index 00000000..fb22cee7
--- /dev/null
+++
b/hugegraph-llm/src/tests/document/test_schema_generator_examples_persistence.py
@@ -0,0 +1,347 @@
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import inspect
+import json
+from types import SimpleNamespace
+
+import gradio as gr
+import pytest
+
+from hugegraph_llm.config.models import base_prompt_config
+from hugegraph_llm.config.models.base_prompt_config import BasePromptConfig
+from hugegraph_llm.demo.rag_demo import vector_graph_block
+
+
+class DummyPrompt:
+ def __init__(self):
+ self.doc_input_text = ""
+ self.graph_schema = ""
+ self.extract_graph_prompt = ""
+ self.graph_extract_split_type = "document"
+ self.schema_generator_query_examples = ""
+ self.schema_generator_few_shot_examples = ""
+ self.llm_settings = SimpleNamespace(language="EN")
+ self.update_count = 0
+
+ def update_yaml_file(self):
+ self.update_count += 1
+
+
+def _write_bundled_examples(tmp_path):
+ prompt_examples_dir = tmp_path / "prompt_examples"
+ prompt_examples_dir.mkdir()
+ (prompt_examples_dir / "query_examples.json").write_text(
+ '["Find all persons", "Find all webpages"]',
+ encoding="utf-8",
+ )
+ (prompt_examples_dir / "schema_examples.json").write_text(
+ '{"vertexlabels": [], "edgelabels": []}',
+ encoding="utf-8",
+ )
+
+
+def test_query_examples_normalize_bundled_string_list_to_downstream_shape():
+ normalized =
vector_graph_block._normalize_schema_generator_query_examples('["Find all
persons"]')
+
+ assert json.loads(normalized) == [
+ {
+ "description": "Find all persons",
+ "gremlin": "",
+ }
+ ]
+
+
+def test_query_examples_accept_description_gremlin_object_shape():
+ normalized = vector_graph_block._normalize_schema_generator_query_examples(
+ json.dumps(
+ [
+ {
+ "description": "Find persons",
+ "gremlin": 'g.V().hasLabel("person")',
+ }
+ ]
+ )
+ )
+
+ assert json.loads(normalized) == [
+ {
+ "description": "Find persons",
+ "gremlin": 'g.V().hasLabel("person")',
+ }
+ ]
+
+
+def test_query_examples_reject_invalid_shape():
+ with pytest.raises(gr.Error, match="description"):
+
vector_graph_block._normalize_schema_generator_query_examples('[{"query": "Find
persons"}]')
+
+
+def test_few_shot_examples_must_be_json_object():
+ with pytest.raises(gr.Error, match="JSON object"):
+
vector_graph_block._validate_schema_generator_few_shot_examples('[{"schema":
{"vertices": []}}]')
+
+
+def test_schema_generator_persist_helper_saves_valid_examples(monkeypatch,
tmp_path):
+ _write_bundled_examples(tmp_path)
+ dummy_prompt = DummyPrompt()
+ monkeypatch.setattr(vector_graph_block, "prompt", dummy_prompt)
+ monkeypatch.setattr(vector_graph_block, "resource_path", str(tmp_path))
+
+ query_examples = '["who knows marko?"]'
+ few_shot_examples = '{"vertexlabels": [], "edgelabels": []}'
+
+ effective_query, effective_few_shot =
vector_graph_block._persist_schema_generator_examples(
+ query_examples,
+ few_shot_examples,
+ )
+
+ assert json.loads(effective_query) == [
+ {
+ "description": "who knows marko?",
+ "gremlin": "",
+ }
+ ]
+ assert json.loads(effective_few_shot) == {
+ "vertexlabels": [],
+ "edgelabels": [],
+ }
+ assert dummy_prompt.schema_generator_query_examples == effective_query
+ assert dummy_prompt.schema_generator_few_shot_examples ==
effective_few_shot
+ assert dummy_prompt.update_count == 1
+
+
+def test_schema_generator_persist_helper_rejects_invalid_query_examples(
+ monkeypatch,
+ tmp_path,
+):
+ _write_bundled_examples(tmp_path)
+ dummy_prompt = DummyPrompt()
+ monkeypatch.setattr(vector_graph_block, "prompt", dummy_prompt)
+ monkeypatch.setattr(vector_graph_block, "resource_path", str(tmp_path))
+
+ with pytest.raises(gr.Error, match="Query examples must be valid JSON"):
+ vector_graph_block._persist_schema_generator_examples(
+ "{invalid json",
+ "{}",
+ )
+
+ assert dummy_prompt.schema_generator_query_examples == ""
+ assert dummy_prompt.schema_generator_few_shot_examples == ""
+ assert dummy_prompt.update_count == 0
+
+
+def test_blank_schema_generator_examples_clear_persisted_overrides_to_bundled(
+ monkeypatch,
+ tmp_path,
+):
+ _write_bundled_examples(tmp_path)
+ dummy_prompt = DummyPrompt()
+ dummy_prompt.schema_generator_query_examples = '[{"description": "saved
query", "gremlin": ""}]'
+ dummy_prompt.schema_generator_few_shot_examples = '{"vertexlabels":
[{"name": "saved"}], "edgelabels": []}'
+ monkeypatch.setattr(vector_graph_block, "prompt", dummy_prompt)
+ monkeypatch.setattr(vector_graph_block, "resource_path", str(tmp_path))
+
+ effective_query, effective_few_shot =
vector_graph_block._persist_schema_generator_examples(
+ " ",
+ "",
+ )
+
+ assert dummy_prompt.schema_generator_query_examples == ""
+ assert dummy_prompt.schema_generator_few_shot_examples == ""
+ assert json.loads(effective_query) == [
+ {
+ "description": "Find all persons",
+ "gremlin": "",
+ },
+ {
+ "description": "Find all webpages",
+ "gremlin": "",
+ },
+ ]
+ assert json.loads(effective_few_shot) == {
+ "vertexlabels": [],
+ "edgelabels": [],
+ }
+ assert dummy_prompt.update_count == 1
+
+
+def test_build_schema_feedback_persists_examples_before_running_flow(
+ monkeypatch,
+ tmp_path,
+):
+ _write_bundled_examples(tmp_path)
+ dummy_prompt = DummyPrompt()
+ monkeypatch.setattr(vector_graph_block, "prompt", dummy_prompt)
+ monkeypatch.setattr(vector_graph_block, "resource_path", str(tmp_path))
+
+ calls = []
+
+ def fake_build_schema(input_text, query_examples, few_shot_schema):
+ calls.append((input_text, query_examples, few_shot_schema))
+ return "{}"
+
+ monkeypatch.setattr(vector_graph_block, "build_schema", fake_build_schema)
+
+ result = vector_graph_block._build_schema_and_provide_feedback(
+ "source text",
+ '["who knows lop?"]',
+ '{"vertexlabels": [], "edgelabels": []}',
+ )
+
+ assert result == "{}"
+ assert calls
+ _, query_payload, few_shot_payload = calls[0]
+ assert json.loads(query_payload) == [
+ {
+ "description": "who knows lop?",
+ "gremlin": "",
+ }
+ ]
+ assert json.loads(few_shot_payload) == {
+ "vertexlabels": [],
+ "edgelabels": [],
+ }
+
+
+def test_build_schema_feedback_rejects_invalid_few_shot_before_flow(
+ monkeypatch,
+ tmp_path,
+):
+ _write_bundled_examples(tmp_path)
+ dummy_prompt = DummyPrompt()
+ monkeypatch.setattr(vector_graph_block, "prompt", dummy_prompt)
+ monkeypatch.setattr(vector_graph_block, "resource_path", str(tmp_path))
+
+ called = False
+
+ def fake_build_schema(*args):
+ nonlocal called
+ called = True
+ return "{}"
+
+ monkeypatch.setattr(vector_graph_block, "build_schema", fake_build_schema)
+
+ with pytest.raises(gr.Error, match="Few-shot schema examples must be valid
JSON"):
+ vector_graph_block._build_schema_and_provide_feedback(
+ "source text",
+ "[]",
+ "{invalid json",
+ )
+
+ assert called is False
+ assert dummy_prompt.update_count == 0
+
+
+def test_load_examples_prefers_persisted_prompt_values(monkeypatch):
+ dummy_prompt = DummyPrompt()
+ dummy_prompt.schema_generator_query_examples = '[{"description": "saved
query", "gremlin": ""}]'
+ dummy_prompt.schema_generator_few_shot_examples = '{"vertexlabels": [],
"edgelabels": []}'
+ monkeypatch.setattr(vector_graph_block, "prompt", dummy_prompt)
+
+ query_examples = json.loads(vector_graph_block.load_query_examples())
+ few_shot_examples =
json.loads(vector_graph_block.load_schema_fewshot_examples())
+
+ assert query_examples == [
+ {
+ "description": "saved query",
+ "gremlin": "",
+ }
+ ]
+ assert few_shot_examples == {
+ "vertexlabels": [],
+ "edgelabels": [],
+ }
+
+
+def test_load_examples_falls_back_to_bundled_resources(monkeypatch, tmp_path):
+ _write_bundled_examples(tmp_path)
+ dummy_prompt = DummyPrompt()
+ monkeypatch.setattr(vector_graph_block, "prompt", dummy_prompt)
+ monkeypatch.setattr(vector_graph_block, "resource_path", str(tmp_path))
+
+ query_examples = json.loads(vector_graph_block.load_query_examples())
+ few_shot_examples =
json.loads(vector_graph_block.load_schema_fewshot_examples())
+
+ assert query_examples == [
+ {
+ "description": "Find all persons",
+ "gremlin": "",
+ },
+ {
+ "description": "Find all webpages",
+ "gremlin": "",
+ },
+ ]
+ assert few_shot_examples == {
+ "vertexlabels": [],
+ "edgelabels": [],
+ }
+
+
+def test_invalid_persisted_examples_fall_back_to_bundled_resources(
+ monkeypatch,
+ tmp_path,
+):
+ _write_bundled_examples(tmp_path)
+ dummy_prompt = DummyPrompt()
+ dummy_prompt.schema_generator_query_examples = "{invalid json"
+ dummy_prompt.schema_generator_few_shot_examples = "{invalid json"
+ monkeypatch.setattr(vector_graph_block, "prompt", dummy_prompt)
+ monkeypatch.setattr(vector_graph_block, "resource_path", str(tmp_path))
+
+ query_examples = json.loads(vector_graph_block.load_query_examples())
+ few_shot_examples =
json.loads(vector_graph_block.load_schema_fewshot_examples())
+
+ assert query_examples == [
+ {
+ "description": "Find all persons",
+ "gremlin": "",
+ },
+ {
+ "description": "Find all webpages",
+ "gremlin": "",
+ },
+ ]
+ assert few_shot_examples == {
+ "vertexlabels": [],
+ "edgelabels": [],
+ }
+
+
+def test_generic_store_prompt_does_not_handle_schema_generator_examples():
+ parameters = inspect.signature(vector_graph_block.store_prompt).parameters
+
+ assert "query_examples" not in parameters
+ assert "few_shot_examples" not in parameters
+
+
+def test_old_prompt_config_without_schema_generator_examples_still_loads(
+ monkeypatch,
+ tmp_path,
+):
+ prompt_path = tmp_path / "config_prompt.yaml"
+ prompt_path.write_text(
+ "doc_input_text: old doc\ngraph_schema: '{}'\nextract_graph_prompt:
old prompt\n",
+ encoding="utf-8",
+ )
+ monkeypatch.setattr(base_prompt_config, "yaml_file_path", str(prompt_path))
+
+ config = BasePromptConfig()
+ config.llm_settings = SimpleNamespace(language="EN")
+ config.ensure_yaml_file_exists()
+
+ assert config.schema_generator_query_examples == ""
+ assert config.schema_generator_few_shot_examples == ""
