fix: replace deprecated Pydantic .schema() calls with v1/v2 compatible pattern (#32162)

This PR addresses deprecation warnings users encounter when using
LangChain tools with Pydantic v2:

```
PydanticDeprecatedSince20: The `schema` method is deprecated; use `model_json_schema` instead. 
Deprecated in Pydantic V2.0 to be removed in V3.0.
```

## Root Cause

Several LangChain components were still using the deprecated `.schema()`
method directly instead of the Pydantic v1/v2 compatible approach. While
users calling `.schema()` on returned models will still see warnings
(which is correct), LangChain's internal code should not generate these
warnings.

## Changes Made

Updated 3 files to use the standard compatibility pattern:

```python
# Before (deprecated)
schema = model.schema()

# After (compatible with both v1 and v2) 
if hasattr(model, "model_json_schema"):
    schema = model.model_json_schema()  # Pydantic v2
else:
    schema = model.schema()  # Pydantic v1
```

### Files Updated:
- **`evaluation/parsing/json_schema.py`**: Fixed `_parse_json()` method
to handle Pydantic models correctly
- **`output_parsers/yaml.py`**: Fixed `get_format_instructions()` to use
compatible schema access
- **`chains/openai_functions/citation_fuzzy_match.py`**: Fixed direct
`.schema()` call on QuestionAnswer model

## Verification

✅ **Zero breaking changes** - all existing functionality preserved  
✅ **No deprecation warnings** from LangChain internal code  
✅ **Backward compatible** with Pydantic v1  
✅ **Forward compatible** with Pydantic v2  
✅ **Edge cases handled** (strings, plain objects, etc.)

## User Impact

LangChain users will no longer see deprecation warnings from internal
LangChain code. Users who directly call `.schema()` on schemas returned
by LangChain should adopt the same compatibility pattern:

```python
# User code should use this pattern
input_schema = tool.get_input_schema()
if hasattr(input_schema, "model_json_schema"):
    schema_result = input_schema.model_json_schema()
else:
    schema_result = input_schema.schema()
```

Fixes #31458.

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Author: Copilot

libs/langchain/langchain/chains/openai_functions/citation_fuzzy_match.py

@@ -123,7 +123,10 @@ def create_citation_fuzzy_match_chain(llm: BaseLanguageModel) -> LLMChain:
         Chain (LLMChain) that can be used to answer questions with citations.
     """
     output_parser = PydanticOutputFunctionsParser(pydantic_schema=QuestionAnswer)
-    schema = QuestionAnswer.schema()
+    if hasattr(QuestionAnswer, "model_json_schema"):
+        schema = QuestionAnswer.model_json_schema()
+    else:
+        schema = QuestionAnswer.schema()
     function = {
         "name": schema["title"],
         "description": schema["description"],

libs/langchain/langchain/evaluation/parsing/json_schema.py

@@ -70,8 +70,11 @@ def evaluation_name(self) -> str:
     def _parse_json(self, node: Any) -> Union[dict, list, None, float, bool, int, str]:
         if isinstance(node, str):
             return parse_json_markdown(node)
+        if hasattr(node, "model_json_schema") and callable(node.model_json_schema):
+            # Pydantic v2 model
+            return node.model_json_schema()
         if hasattr(node, "schema") and callable(node.schema):
-            # Pydantic model
+            # Pydantic v1 model
             return node.schema()
         return node
 

libs/langchain/langchain/output_parsers/yaml.py

@@ -43,7 +43,15 @@ def parse(self, text: str) -> T:
 
     def get_format_instructions(self) -> str:
         # Copy schema to avoid altering original Pydantic schema.
-        schema = dict(self.pydantic_object.schema().items())
+        if hasattr(self.pydantic_object, "model_json_schema"):
+            # Pydantic v2
+            schema = dict(self.pydantic_object.model_json_schema().items())
+        elif hasattr(self.pydantic_object, "schema"):
+            # Pydantic v1
+            schema = dict(self.pydantic_object.schema().items())
+        else:
+            msg = "Pydantic object must have either model_json_schema or schema method"
+            raise ValueError(msg)
 
         # Remove extraneous fields.
         reduced_schema = schema