core[minor], ...: add tool calls message (#18947)

core[minor], langchain[patch], openai[minor], anthropic[minor], fireworks[minor], groq[minor], mistralai[minor]

```python
class ToolCall(TypedDict):
    name: str
    args: Dict[str, Any]
    id: Optional[str]

class InvalidToolCall(TypedDict):
    name: Optional[str]
    args: Optional[str]
    id: Optional[str]
    error: Optional[str]

class ToolCallChunk(TypedDict):
    name: Optional[str]
    args: Optional[str]
    id: Optional[str]
    index: Optional[int]


class AIMessage(BaseMessage):
    ...
    tool_calls: List[ToolCall] = []
    invalid_tool_calls: List[InvalidToolCall] = []
    ...


class AIMessageChunk(AIMessage, BaseMessageChunk):
    ...
    tool_call_chunks: Optional[List[ToolCallChunk]] = None
    ...
```
Important considerations:
- Parsing logic occurs within different providers;
- ~Changing output type is a breaking change for anyone doing explicit
type checking;~
- ~Langsmith rendering will need to be updated:
https://github.com/langchain-ai/langchainplus/pull/3561~
- ~Langserve will need to be updated~
- Adding chunks:
- ~AIMessage + ToolCallsMessage = ToolCallsMessage if either has
non-null .tool_calls.~
- Tool call chunks are appended, merging when having equal values of
`index`.
  - additional_kwargs accumulate the normal way.
- During streaming:
- ~Messages can change types (e.g., from AIMessageChunk to
AIToolCallsMessageChunk)~
- Output parsers parse additional_kwargs (during .invoke they read off
tool calls).

Packages outside of `partners/`:
- https://github.com/langchain-ai/langchain-cohere/pull/7
- https://github.com/langchain-ai/langchain-google/pull/123/files

---------

Co-authored-by: Chester Curme <chester.curme@gmail.com>

libs/partners/mistralai/langchain_mistralai/chat_models.py

@@ -49,6 +49,8 @@ from langchain_core.output_parsers.base import OutputParserLike
 from langchain_core.output_parsers.openai_tools import (
     JsonOutputKeyToolsParser,
     PydanticToolsParser,
+    make_invalid_tool_call,
+    parse_tool_call,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
 from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr, root_validator
@@ -82,9 +84,31 @@ def _convert_mistral_chat_message_to_message(
     content = cast(str, _message["content"])
 
     additional_kwargs: Dict = {}
-    if tool_calls := _message.get("tool_calls"):
-        additional_kwargs["tool_calls"] = tool_calls
-    return AIMessage(content=content, additional_kwargs=additional_kwargs)
+    tool_calls = []
+    invalid_tool_calls = []
+    if raw_tool_calls := _message.get("tool_calls"):
+        additional_kwargs["tool_calls"] = raw_tool_calls
+        for raw_tool_call in raw_tool_calls:
+            try:
+                parsed: dict = cast(
+                    dict, parse_tool_call(raw_tool_call, return_id=False)
+                )
+                tool_calls.append(
+                    {
+                        **parsed,
+                        **{"id": None},
+                    },
+                )
+            except Exception as e:
+                invalid_tool_calls.append(
+                    dict(make_invalid_tool_call(raw_tool_call, str(e)))
+                )
+    return AIMessage(
+        content=content,
+        additional_kwargs=additional_kwargs,
+        tool_calls=tool_calls,
+        invalid_tool_calls=invalid_tool_calls,
+    )
 
 
 async def _aiter_sse(
@@ -133,9 +157,27 @@ def _convert_delta_to_message_chunk(
         return HumanMessageChunk(content=content)
     elif role == "assistant" or default_class == AIMessageChunk:
         additional_kwargs: Dict = {}
-        if tool_calls := _delta.get("tool_calls"):
-            additional_kwargs["tool_calls"] = tool_calls
-        return AIMessageChunk(content=content, additional_kwargs=additional_kwargs)
+        if raw_tool_calls := _delta.get("tool_calls"):
+            additional_kwargs["tool_calls"] = raw_tool_calls
+            try:
+                tool_call_chunks = [
+                    {
+                        "name": rtc["function"].get("name"),
+                        "args": rtc["function"].get("arguments"),
+                        "id": rtc.get("id"),
+                        "index": rtc.get("index"),
+                    }
+                    for rtc in raw_tool_calls
+                ]
+            except KeyError:
+                pass
+        else:
+            tool_call_chunks = []
+        return AIMessageChunk(
+            content=content,
+            additional_kwargs=additional_kwargs,
+            tool_call_chunks=tool_call_chunks,
+        )
     elif role == "system" or default_class == SystemMessageChunk:
         return SystemMessageChunk(content=content)
     elif role or default_class == ChatMessageChunk:
@@ -163,7 +205,7 @@ def _convert_message_to_mistral_chat_message(
                 for tc in message.additional_kwargs["tool_calls"]
             ]
         else:
-            tool_calls = None
+            tool_calls = []
         return {
             "role": "assistant",
             "content": message.content,