ChatGroq._combine_llm_outputs mutates per-generation token_usage in place and mishandles None values (silent clobber / TypeError)

### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [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). - [x] This is not related to the langchain-community package. - [x] I posted a self-contained, minimal, reproducible example. A maintainer can copy it and run it AS IS. ### Package (Required) - [ ] langchain - [ ] langchain-openai - [ ] langchain-anthropic - [ ] langchain-classic - [ ] langchain-core - [ ] langchain-model-profiles - [ ] langchain-tests - [ ] langchain-text-splitters - [ ] langchain-chroma - [ ] langchain-deepseek - [ ] langchain-exa - [ ] langchain-fireworks - [x] langchain-groq - [ ] langchain-huggingface - [ ] langchain-mistralai - [ ] langchain-nomic - [ ] langchain-ollama - [ ] langchain-openrouter - [ ] langchain-perplexity - [ ] langchain-qdrant - [ ] langchain-xai - [ ] Other / not sure / general ### Related Issues / PRs * #38482 — `langchain-mistralai` has the naive `+=` version of this merge (no nested-dict handling at all) * #38648 / #38646 — the `langchain-fireworks` sibling (same naive `+=`) and its fix * `langchain-groq` is the interesting case: it already *attempts* nested-dict handling and None-guarding, but both are implemented incorrectly (details below) ### Reproduction Steps / Example Code (Python) ```python import os os.environ.setdefault("GROQ_API_KEY", "fake-key") # offline repro, no network needed from langchain_groq import ChatGroq llm = ChatGroq(model="llama-3.3-70b-versatile") # --- 1. Nested-dict merge mutates the caller's llm_outputs in place --- o1 = { "token_usage": {"prompt_tokens": 10, "input_tokens_details": {"cached_tokens": 5}}, "model_name": "m", } o2 = { "token_usage": {"prompt_tokens": 20, "input_…