Commit Graph

2 Commits

Author SHA1 Message Date
jiashi19
0d7ad0ed0c Feat/agent thinking switch (#15446)
### What problem does this PR solve?

This PR adds an Agent LLM setting to control thinking mode for official
providers that expose a thinking switch.

Related to #12842.  
Closes #15445.

Some providers expose thinking controls through provider-specific
request fields, but Agent LLM settings did not have a unified option for
users to enable or disable thinking mode.

This PR adds a `Thinking` selector with:

- System default
- Enabled
- Disabled
<img width="452" height="278" alt="8566b0b4-0546-4c8a-913d-f9bbd38319f6"
src="https://github.com/user-attachments/assets/25b497f7-1ba0-4bfe-940d-6fe79287d6ab"
/>
<img width="471" height="971" alt="8a0a6bee-f45f-48d5-bd83-17af260de3db"
src="https://github.com/user-attachments/assets/41ad43c1-5087-48f1-bf37-f2ca14c2be2f"
/>
Initial support is limited to the verified official providers:

- Qwen / DashScope: `enable_thinking`
- Kimi / Moonshot: `thinking.type`
- GLM / ZHIPU-AI: `thinking.type`

For LiteLLM-based providers, provider-specific fields are forwarded
through `extra_body` before `drop_params` filtering so the request
parameters are preserved.



### Type of change

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

---------

Co-authored-by: jiashi <jiashi19@outlook.com>
Co-authored-by: Zhichang Yu <yuzhichang@gmail.com>
2026-06-29 09:45:16 +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