Support separate embedding base URL configuration

[dpersek]

Description

Adds a dedicated embedding endpoint configuration for self-hosted deployments that run embedding models separately from chat/completion models.

Motivation and Context

FIX #1354

SurfSense already lets operators configure EMBEDDING_MODEL, but there was no separate environment variable for the embedding provider endpoint. This made split deployments harder, such as running chat models on one Ollama instance and embeddings on another machine or port.

Chonkie's custom endpoint support for this path is exposed through LiteLLM embeddings, so this change maps EMBEDDING_BASE_URL to Chonkie's api_base kwarg for litellm:// embedding models. OLLAMA_EMBEDDING_BASE_URL is also accepted as an Ollama-specific fallback when the generic variable is unset.

Screenshots

N/A - backend configuration and documentation change.

API Changes

• This PR includes API changes

Change Type

• Bug fix
• New feature
• Performance improvement
• Refactoring
• Documentation
• Dependency/Build system
• Breaking change
• Other (specify):

Testing Performed

• Tested locally
• Manual/QA verification

Commands:

• EMBEDDING_MODEL=sentence-transformers/all-MiniLM-L6-v2 uv run pytest tests/unit/config/test_embedding_settings.py
  • 6 passed
• uv run ruff check app/config/__init__.py app/config/embedding_settings.py tests/unit/config/test_embedding_settings.py
  • passed
• EMBEDDING_MODEL=sentence-transformers/all-MiniLM-L6-v2 uv run pytest -m unit
  • 2384 passed, 1 skipped, 636 deselected
• git diff --check
  • passed

Notes:

• Scope is backend config, env examples, and docs only.
• No model-connection UI, database/API schema, dependency, or native Chonkie provider changes.
• No live external embedding server smoke test was run.

Checklist

• Follows project coding standards and conventions
• Documentation updated as needed
• Dependencies updated as needed
• No lint/build errors or new warnings
• All relevant tests are passing

High-level PR Summary

This PR adds support for configuring a separate embedding endpoint to enable split deployments where embedding models run on different servers than chat/completion models. It introduces EMBEDDING_BASE_URL and OLLAMA_EMBEDDING_BASE_URL environment variables that map to Chonkie's api_base parameter for litellm:// embedding models, while preserving existing Azure OpenAI configuration support. The changes include new configuration logic, comprehensive unit tests, updated environment variable examples, and documentation for self-hosted deployments.

⏱️ Estimated Review Time: 15-30 minutes

💡 Review Order Suggestion

Order	File Path
1	surfsense_backend/app/config/embedding_settings.py
2	surfsense_backend/tests/unit/config/test_embedding_settings.py
3	surfsense_backend/app/config/__init__.py
4	surfsense_backend/.env.example
5	docker/.env.example
6	surfsense_web/content/docs/docker-installation/docker-compose.mdx
7	surfsense_web/content/docs/local-models/ollama.mdx
8	surfsense_web/content/docs/manual-installation.mdx

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