Error using Langchain neo4j-Cypher template

[cugcoder]

Checked other resources

• [X] I added a very descriptive title to this issue.
• [X] I searched the LangChain documentation with the integrated search.
• [X] I used the GitHub search to find a similar question and didn't find it.
• [X] I am sure that this is a bug in LangChain rather than my code.
• [X] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package).

Example Code

def handler_func(schema_or_field: CoreSchemaOrField) -> JsonSchemaValue:
            """Generate a JSON schema based on the input schema.

            Args:
                schema_or_field: The core schema to generate a JSON schema from.

            Returns:
                The generated JSON schema.

            Raises:
                TypeError: If an unexpected schema type is encountered.
            """
            # Generate the core-schema-type-specific bits of the schema generation:
            json_schema: JsonSchemaValue | None = None
            if self.mode == 'serialization' and 'serialization' in schema_or_field:
                # In this case, we skip the JSON Schema generation of the schema
                # and use the `'serialization'` schema instead (canonical example:
                # `Annotated[int, PlainSerializer(str)]`).
                ser_schema = schema_or_field['serialization']  # type: ignore
                json_schema = self.ser_schema(ser_schema)

                # It might be that the 'serialization'` is skipped depending on `when_used`.
                # This is only relevant for `nullable` schemas though, so we special case here.
                if (
                    json_schema is not None
                    and ser_schema.get('when_used') in ('unless-none', 'json-unless-none')
                    and schema_or_field['type'] == 'nullable'
                ):
                    json_schema = self.get_flattened_anyof([{'type': 'null'}, json_schema])
            if json_schema is None:
                if _core_utils.is_core_schema(schema_or_field) or _core_utils.is_core_schema_field(schema_or_field):
                    generate_for_schema_type = self._schema_type_to_method[schema_or_field['type']]
                    json_schema = generate_for_schema_type(schema_or_field)
                else:
                    raise TypeError(f'Unexpected schema type: schema={schema_or_field}')
            if _core_utils.is_core_schema(schema_or_field):
                json_schema = populate_defs(schema_or_field, json_schema)
            return json_schema

        current_handler = _schema_generation_shared.GenerateJsonSchemaHandler(self, handler_func)

        for js_modify_function in metadata_handler.metadata.get('pydantic_js_functions', ()):

            def new_handler_func(
                schema_or_field: CoreSchemaOrField,
                current_handler: GetJsonSchemaHandler = current_handler,
                js_modify_function: GetJsonSchemaFunction = js_modify_function,
            ) -> JsonSchemaValue:
                json_schema = js_modify_function(schema_or_field, current_handler)
                if _core_utils.is_core_schema(schema_or_field):
                    json_schema = populate_defs(schema_or_field, json_schema)
                original_schema = current_handler.resolve_ref_schema(json_schema)
                ref = json_schema.pop('$ref', None)
                if ref and json_schema:
                    original_schema.update(json_schema)
                return original_schema

            current_handler = _schema_generation_shared.GenerateJsonSchemaHandler(self, new_handler_func)

        for js_modify_function in metadata_handler.metadata.get('pydantic_js_annotation_functions', ()):

            def new_handler_func(
                schema_or_field: CoreSchemaOrField,
                current_handler: GetJsonSchemaHandler = current_handler,
                js_modify_function: GetJsonSchemaFunction = js_modify_function,
            ) -> JsonSchemaValue:
                json_schema = js_modify_function(schema_or_field, current_handler)
                if _core_utils.is_core_schema(schema_or_field):
                    json_schema = populate_defs(schema_or_field, json_schema)
                return json_schema

            current_handler = _schema_generation_shared.GenerateJsonSchemaHandler(self, new_handler_func)

        json_schema = current_handler(schema)
        if _core_utils.is_core_schema(schema):
            json_schema = populate_defs(schema, json_schema)
        return json_schema

Error Message and Stack Trace (if applicable)

  File "E:\Software\Anaconda\envs\Langchain311\Lib\site-packages\pydantic\json_schema.py", line 511, in handler_func
    return self.handler(core_schema)
           ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "E:\Software\Anaconda\envs\Langchain311\Lib\site-packages\pydantic\json_schema.py", line 511, in handler_func
    json_schema = generate_for_schema_type(schema_or_field)
  File "E:\Software\Anaconda\envs\Langchain311\Lib\site-packages\pydantic\json_schema.py", line 511, in handler_func
    json_schema = generate_for_schema_type(schema_or_field)
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    json_schema = generate_for_schema_type(schema_or_field)
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "E:\Software\Anaconda\envs\Langchain311\Lib\site-packages\pydantic\json_schema.py", line 1014, in function_plain_schema
    return self.handle_invalid_for_json_schema(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "E:\Software\Anaconda\envs\Langchain311\Lib\site-packages\pydantic\json_schema.py", line 2185, in handle_invalid_for_json_schema
    raise PydanticInvalidForJsonSchema(f'Cannot generate a JsonSchema for {error_info}')
pydantic.errors.PydanticInvalidForJsonSchema: Cannot generate a JsonSchema for core_schema.PlainValidatorFunctionSchema ({'type': 'with-info', 'function': <bound method BaseModel.validate of <class 'neo4j_cypher.chain.Question'>>})

Description

When using Langchain's neo4j-cypher template, pydanticv2 always reports errors and is not compatible. Switching pydantic version to v1 is not compatible either.

System Info

Python 3.11 pydantic 2.9.2 pydantic-core 2.23.4 langchain-cli 0.0.31 langchain-community 0.0.33

[shamssab]

Hello! We're a group of students from the University of Toronto Scarborough, and we're excited to contribute to LangChain. We'd love the opportunity to investigate this bug further.