tmimmanuel 13d0df1562 feat: add Perplexity contextualized embeddings API as a new model provider (#13709) ...

### What problem does this PR solve?

Adds Perplexity contextualized embeddings API as a new model provider,
as requested in #13610.

- `PerplexityEmbed` provider in `rag/llm/embedding_model.py` supporting
both standard (`/v1/embeddings`) and contextualized
(`/v1/contextualizedembeddings`) endpoints
- All 4 Perplexity embedding models registered in
`conf/llm_factories.json`: `pplx-embed-v1-0.6b`, `pplx-embed-v1-4b`,
`pplx-embed-context-v1-0.6b`, `pplx-embed-context-v1-4b`
- Frontend entries (enum, icon mapping, API key URL) in
`web/src/constants/llm.ts`
- Updated `docs/guides/models/supported_models.mdx`
- 22 unit tests in `test/unit_test/rag/llm/test_perplexity_embed.py`

Perplexity's API returns `base64_int8` encoded embeddings (not
OpenAI-compatible), so this uses a custom `requests`-based
implementation. Contextualized vs standard model is auto-detected from
the model name.

Closes #13610

### Type of change

- [x] New Feature (non-breaking change which adds functionality)
- [x] Documentation Update

2026-03-20 10:47:48 +08:00

..

api

fix(jira): prevent missed incremental updates after issue edits (#13674)

2026-03-18 23:31:05 +08:00

common

Refa: convert download_img to async (#13477)

2026-03-09 19:00:17 +08:00

deepdoc/parser

Feat: support epub parsing (#13650)

2026-03-17 20:14:06 +08:00

memory/utils

feat(memory): implement get_highlight for OceanBase memory (#13449)

2026-03-06 20:17:11 +08:00

rag

feat: add Perplexity contextualized embeddings API as a new model provider (#13709)

2026-03-20 10:47:48 +08:00