Fixes #211 with_structured_output for json_schema method

[WIll-Xu35]

Fixes #211

Add "name" key for response_format. It can optional input with key "schema_name". Otherwise default to "json_schema"

Change schema value type from tuple to dict.

[jennsun]

Thanks for the contribution! It looks like this only fixes the first of several cascading errors users hit with method="json_schema" (as reported in #211 (comment))

When strict: true is set, the OpenAI-compatible API also requires:

1. additionalProperties: false at every object-level node in the schema
2. required to match all keys in properties (which can break with nested models / $ref)

raw model_json_schema() doesn't satisfy either of these, so users will still hit 400 errors after this fix. Could you take a look at my comment here, and include test coverage (unit tests + manual testing info in PR description) after you have made updates?

also make sure you rebase newest changes as there is a current conflict

[jennsun]

the name should be derived and not hardcoded - here you should use convert_to_openai_function() ,(add an additional import from the langchain core function calling class for from langchain_core.utils.function_calling import convert_to_openai_function . we should also do this to address the other cascading errors (see my overall review comment)

can refer to how the partner library is doing this as a reference which calls convert_to_openai_function:
https://github.com/langchain-ai/langchain/blob/202d7f6c4a2ca8c7e5949d935bcf0ba9b0c23fb0/libs/partners/openai/langchain_openai/chat_models/base.py#L1449

suggested fix may look something like this, but please be sure to test!

from langchain_core.utils.function_calling import (
      convert_to_openai_function,  # add this import
      convert_to_openai_tool,
  )

  # ... in with_structured_output, json_schema branch:

  elif method == "json_schema":
      if schema is None:
          raise ValueError(
              "schema must be specified when method is 'json_schema'. Received None."
          )
      function = convert_to_openai_function(
          pydantic_schema if pydantic_schema else schema, strict=True
      )
      function["schema"] = function.pop("parameters")
      response_format = {"type": "json_schema", "json_schema": function}
      llm = self.bind(response_format=response_format)

[jennsun]

the pr is also missing unit test coverage - we have an existing test at tests/unit_tests/test_chat_models.py (test_chat_model_with_structured_output)

in which this line
assert bind["response_format"]["json_schema"]["schema"] == JSON_SCHEMA would likely fail.

can you update this test and include asserts for the name/strict/schema fields? may look something like:

elif method == "json_schema":
      js = bind["response_format"]["json_schema"]
      assert js["name"] == "AnswerWithJustification"
      assert js["strict"] is True
      assert js["schema"]["additionalProperties"] is False

can you also add the follow unit tests:

• pydantic schema produces a valid response_format
• raw dict schema produces a valid response_format
• nested Pydantic model to validate $ref dereferencing?

[jennsun]

see #351