feat(community): add support for tool_calls response (#23765)

When `model_kwargs={"tools": tools}` are passed to `ChatLiteLLM`, they
are executed, but the response is not recognized correctly

Let's add `tool_calls` to the `additional_kwargs`

Thank you for contributing to LangChain!

## ChatAnthropic

I used the following example to verify the output of llm with tools:

```python
from langchain_core.pydantic_v1 import BaseModel, Field
from langchain_anthropic import ChatAnthropic

class GetWeather(BaseModel):
    '''Get the current weather in a given location'''

    location: str = Field(..., description="The city and state, e.g. San Francisco, CA")

class GetPopulation(BaseModel):
    '''Get the current population in a given location'''

    location: str = Field(..., description="The city and state, e.g. San Francisco, CA")

llm = ChatAnthropic(model="claude-3-sonnet-20240229")
llm_with_tools = llm.bind_tools([GetWeather, GetPopulation])
ai_msg = llm_with_tools.invoke("Which city is hotter today and which is bigger: LA or NY?")
print(ai_msg.tool_calls)
```

I get the following response:

```json
[{'name': 'GetWeather', 'args': {'location': 'Los Angeles, CA'}, 'id': 'toolu_01UfDA89knrhw3vFV9X47neT'}, {'name': 'GetWeather', 'args': {'location': 'New York, NY'}, 'id': 'toolu_01NrYVRYae7m7z7tBgyPb3Gd'}, {'name': 'GetPopulation', 'args': {'location': 'Los Angeles, CA'}, 'id': 'toolu_01EPFEpDgzL6vV2dTpD9SVP5'}, {'name': 'GetPopulation', 'args': {'location': 'New York, NY'}, 'id': 'toolu_01B5J6tPJXgwwfhQX9BHP2dt'}]
```

## LiteLLM

Based on https://litellm.vercel.app/docs/completion/function_call

```python
from langchain_core.pydantic_v1 import BaseModel, Field
from langchain_core.utils.function_calling import convert_to_openai_tool
import litellm

class GetWeather(BaseModel):
    '''Get the current weather in a given location'''

    location: str = Field(..., description="The city and state, e.g. San Francisco, CA")

class GetPopulation(BaseModel):
    '''Get the current population in a given location'''

    location: str = Field(..., description="The city and state, e.g. San Francisco, CA")

prompt = "Which city is hotter today and which is bigger: LA or NY?"
tools = [convert_to_openai_tool(GetWeather), convert_to_openai_tool(GetPopulation)]

response = litellm.completion(model="claude-3-sonnet-20240229", messages=[{'role': 'user', 'content': prompt}], tools=tools)
print(response.choices[0].message.tool_calls)
```

```python
[ChatCompletionMessageToolCall(function=Function(arguments='{"location": "Los Angeles, CA"}', name='GetWeather'), id='toolu_01HeDWV5vP7BDFfytH5FJsja', type='function'), ChatCompletionMessageToolCall(function=Function(arguments='{"location": "New York, NY"}', name='GetWeather'), id='toolu_01EiLesUSEr3YK1DaE2jxsQv', type='function'), ChatCompletionMessageToolCall(function=Function(arguments='{"location": "Los Angeles, CA"}', name='GetPopulation'), id='toolu_01Xz26zvkBDRxEUEWm9pX6xa', type='function'), ChatCompletionMessageToolCall(function=Function(arguments='{"location": "New York, NY"}', name='GetPopulation'), id='toolu_01SDqKnsLjvUXuBsgAZdEEpp', type='function')]
```

## ChatLiteLLM

When I try the following

```python
from langchain_core.pydantic_v1 import BaseModel, Field
from langchain_core.utils.function_calling import convert_to_openai_tool
from langchain_community.chat_models import ChatLiteLLM

class GetWeather(BaseModel):
    '''Get the current weather in a given location'''

    location: str = Field(..., description="The city and state, e.g. San Francisco, CA")

class GetPopulation(BaseModel):
    '''Get the current population in a given location'''

    location: str = Field(..., description="The city and state, e.g. San Francisco, CA")

prompt = "Which city is hotter today and which is bigger: LA or NY?"
tools = [convert_to_openai_tool(GetWeather), convert_to_openai_tool(GetPopulation)]

llm = ChatLiteLLM(model="claude-3-sonnet-20240229", model_kwargs={"tools": tools})
ai_msg = llm.invoke(prompt)
print(ai_msg)
print(ai_msg.tool_calls)
```

```python
content="Okay, let's find out the current weather and populations for Los Angeles and New York City:" response_metadata={'token_usage': Usage(prompt_tokens=329, completion_tokens=193, total_tokens=522), 'model': 'claude-3-sonnet-20240229', 'finish_reason': 'tool_calls'} id='run-748b7a84-84f4-497e-bba1-320bd4823937-0'
[]
```

---

When I apply the changes of this PR, the output is

```json
[{'name': 'GetWeather', 'args': {'location': 'Los Angeles, CA'}, 'id': 'toolu_017D2tGjiaiakB1HadsEFZ4e'}, {'name': 'GetWeather', 'args': {'location': 'New York, NY'}, 'id': 'toolu_01WrDpJfVqLkPejWzonPCbLW'}, {'name': 'GetPopulation', 'args': {'location': 'Los Angeles, CA'}, 'id': 'toolu_016UKyYrVAV9Pz99iZGgGU7V'}, {'name': 'GetPopulation', 'args': {'location': 'New York, NY'}, 'id': 'toolu_01Sgv1imExFX1oiR1Cw88zKy'}]
```

If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.

Co-authored-by: Igor Drozdov <idrozdov@gitlab.com>

libs/community/langchain_community/chat_models/litellm.py

@@ -83,10 +83,14 @@ def _convert_dict_to_message(_dict: Mapping[str, Any]) -> BaseMessage:
         # Fix for azure
         # Also OpenAI returns None for tool invocations
         content = _dict.get("content", "") or ""
+
+        additional_kwargs = {}
         if _dict.get("function_call"):
-            additional_kwargs = {"function_call": dict(_dict["function_call"])}
-        else:
-            additional_kwargs = {}
+            additional_kwargs["function_call"] = dict(_dict["function_call"])
+
+        if _dict.get("tool_calls"):
+            additional_kwargs["tool_calls"] = _dict["tool_calls"]
+
         return AIMessage(content=content, additional_kwargs=additional_kwargs)
     elif role == "system":
         return SystemMessage(content=_dict["content"])