Add SemanticTextSplitter with dual local/global similarity scoring

### Submission checklist - [x] This is a feature request, not a bug report or usage question. - [x] I added a clear and descriptive title that summarizes the feature request. - [x] I used the GitHub search to find a similar feature request and didn't find it. - [x] I checked the LangChain documentation and API reference to see if this feature already exists. - [x] This is not related to the langchain-community package. ### Package (Required) - [ ] langchain - [ ] langchain-openai - [ ] langchain-anthropic - [ ] langchain-classic - [ ] langchain-core - [ ] langchain-model-profiles - [ ] langchain-tests - [x] langchain-text-splitters - [ ] langchain-chroma - [ ] langchain-deepseek - [ ] langchain-exa - [ ] langchain-fireworks - [ ] langchain-groq - [ ] langchain-huggingface - [ ] langchain-mistralai - [ ] langchain-nomic - [ ] langchain-ollama - [ ] langchain-openrouter - [ ] langchain-perplexity - [ ] langchain-qdrant - [ ] langchain-xai - [ ] Other / not sure / general ### Feature Description I would like to propose a new semantic text splitter for `langchain-text-splitters` that combines local sentence similarity with global current-chunk similarity when deciding whether a sentence should be merged into the current chunk. The core scoring function is: ```text score = α × sim(new_sentence, previous_sentence) + (1 − α) × sim(new_sentence, current_chunk) ### Use Case ### Use Case ```markdown This is primarily intended for RAG ingestion pipelines where semantic coherence within each retrieved chunk is important. Character-based splitters are fast and predictable, but they do not directly consider semantic relationships between sentences. Purely adjacent semantic similarity can identify strong local boundaries, but it can also be affected by short-term similarity fluctuations or gradual topic drift. For example, a sequence of sentences may temporarily have lower similarity while still discussing the same broader topic. Conversely, a sentence may be highly similar …