2 Commits

Author	SHA1	Message	Date
Wang Qi	1a6df01b53	Bug fix: Enhance embeding model to give better error message (#15346) ... To resolve https://github.com/infiniflow/ragflow/issues/15343 enhance the model embedding message to give extact failure message to customer. # QWen ## Retrieval <img width="3321" height="1033" alt="image" src="https://github.com/user-attachments/assets/6b82921a-a3a7-4a33-a383-1cf316398ee2" /> ## Chat <img width="2241" height="311" alt="image" src="https://github.com/user-attachments/assets/ec311365-62d5-407a-8915-5c8d72be9716" /> # SiliconFlow ## Retrieval <img width="3321" height="1033" alt="image" src="https://github.com/user-attachments/assets/ee2cd191-a27d-4729-b53d-2fbdb4e352cd" /> ## Chat <img width="1562" height="210" alt="image" src="https://github.com/user-attachments/assets/10376a8e-a3f4-422f-bc2e-96f2a8a96448" /> # Baichuan ## Retrieval <img width="3321" height="1107" alt="image" src="https://github.com/user-attachments/assets/dcb5409d-f7fc-4804-b186-5e1ee11e09c4" /> ## Chat <img width="2241" height="311" alt="image" src="https://github.com/user-attachments/assets/ec311365-62d5-407a-8915-5c8d72be9716" /> # Zhipu zhipu is good.	2026-06-01 19:18:16 +08:00
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