Enhance Docker configuration and Hugging Face integration

Enhance embedding and chat model integration by adding support for community Hugging Face models. Update error handling for missing dependencies and ensure API keys are securely managed using SecretStr. Refactor embedding function and chat model creation to accommodate new imports and improve robustness.

Refactor embedding and chat model integration to use langchain-huggingface. Update HuggingFace embedding function to require API key and adjust error handling. Modify retriever to import from langchain-huggingface and enhance chat model creation with temperature setting.

Refactor embedding function creation and document loading. Update ingest and query routes to remove unnecessary settings parameters, streamline chunking logic, and enhance load_documents function to handle both string and list inputs. Adjust model name in embedder for consistency with OpenAI API.

Enhance configuration and ingestion functionality for Milestone 4. Update .env.example with new environment variables, expand milestones documentation with integration details, and add necessary dependencies to pyproject.toml and requirements.txt. Refactor ingest and query routes to support file uploads and retrieval, implementing validation and error handling. Update settings to include new model configurations and parameters for chunking and embedding.