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54
.github/pull_request_template.md
vendored
54
.github/pull_request_template.md
vendored
|
@ -1,34 +1,32 @@
|
|||
# Checklist:
|
||||
# Summary
|
||||
|
||||
Please include a summary of the change and which issue is fixed. Please also include relevant motivation and context. List any dependencies that are required for this change.
|
||||
|
||||
> [!Tip]
|
||||
> Close issue syntax: `Fixes #<issue number>` or `Resolves #<issue number>`, see [documentation](https://docs.github.com/en/issues/tracking-your-work-with-issues/linking-a-pull-request-to-an-issue#linking-a-pull-request-to-an-issue-using-a-keyword) for more details.
|
||||
|
||||
|
||||
# Screenshots
|
||||
|
||||
<table>
|
||||
<tr>
|
||||
<td>Before: </td>
|
||||
<td>After: </td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>...</td>
|
||||
<td>...</td>
|
||||
</tr>
|
||||
</table>
|
||||
|
||||
# Checklist
|
||||
|
||||
> [!IMPORTANT]
|
||||
> Please review the checklist below before submitting your pull request.
|
||||
|
||||
- [ ] Please open an issue before creating a PR or link to an existing issue
|
||||
- [ ] I have performed a self-review of my own code
|
||||
- [ ] I have commented my code, particularly in hard-to-understand areas
|
||||
- [ ] I ran `dev/reformat`(backend) and `cd web && npx lint-staged`(frontend) to appease the lint gods
|
||||
|
||||
# Description
|
||||
|
||||
Describe the big picture of your changes here to communicate to the maintainers why we should accept this pull request. If it fixes a bug or resolves a feature request, be sure to link to that issue. Close issue syntax: `Fixes #<issue number>`, see [documentation](https://docs.github.com/en/issues/tracking-your-work-with-issues/linking-a-pull-request-to-an-issue#linking-a-pull-request-to-an-issue-using-a-keyword) for more details.
|
||||
|
||||
Fixes
|
||||
|
||||
## Type of Change
|
||||
|
||||
- [ ] Bug fix (non-breaking change which fixes an issue)
|
||||
- [ ] New feature (non-breaking change which adds functionality)
|
||||
- [ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
|
||||
- [ ] This change requires a documentation update, included: [Dify Document](https://github.com/langgenius/dify-docs)
|
||||
- [ ] Improvement, including but not limited to code refactoring, performance optimization, and UI/UX improvement
|
||||
- [ ] Dependency upgrade
|
||||
|
||||
# Testing Instructions
|
||||
|
||||
Please describe the tests that you ran to verify your changes. Provide instructions so we can reproduce. Please also list any relevant details for your test configuration
|
||||
|
||||
- [ ] Test A
|
||||
- [ ] Test B
|
||||
|
||||
|
||||
- [x] I understand that this PR may be closed in case there was no previous discussion or issues. (This doesn't apply to typos!)
|
||||
- [x] I've added a test for each change that was introduced, and I tried as much as possible to make a single atomic change.
|
||||
- [x] I've updated the documentation accordingly.
|
||||
- [x] I ran `dev/reformat`(backend) and `cd web && npx lint-staged`(frontend) to appease the lint gods
|
||||
|
||||
|
|
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@ -19,6 +19,9 @@
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<a href="https://discord.gg/FngNHpbcY7" target="_blank">
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<img src="https://img.shields.io/discord/1082486657678311454?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb"
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alt="chat on Discord"></a>
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<a href="https://reddit.com/r/difyai" target="_blank">
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<img src="https://img.shields.io/reddit/subreddit-subscribers/difyai?style=plastic&logo=reddit&label=r%2Fdifyai&labelColor=white"
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alt="join Reddit"></a>
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alt="follow on X(Twitter)"></a>
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<a href="https://discord.gg/FngNHpbcY7" target="_blank">
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<img src="https://img.shields.io/discord/1082486657678311454?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb"
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alt="chat on Discord"></a>
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<a href="https://reddit.com/r/difyai" target="_blank">
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<img src="https://img.shields.io/reddit/subreddit-subscribers/difyai?style=plastic&logo=reddit&label=r%2Fdifyai&labelColor=white"
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alt="join Reddit"></a>
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alt="follow on X(Twitter)"></a>
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@ -15,6 +15,9 @@
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<a href="https://discord.gg/FngNHpbcY7" target="_blank">
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<img src="https://img.shields.io/discord/1082486657678311454?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb"
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alt="chat on Discord"></a>
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<a href="https://reddit.com/r/difyai" target="_blank">
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<img src="https://img.shields.io/reddit/subreddit-subscribers/difyai?style=plastic&logo=reddit&label=r%2Fdifyai&labelColor=white"
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alt="join Reddit"></a>
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<a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
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alt="follow on X(Twitter)"></a>
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<a href="https://discord.gg/FngNHpbcY7" target="_blank">
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<img src="https://img.shields.io/discord/1082486657678311454?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb"
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alt="chat en Discord"></a>
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<a href="https://reddit.com/r/difyai" target="_blank">
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<img src="https://img.shields.io/reddit/subreddit-subscribers/difyai?style=plastic&logo=reddit&label=r%2Fdifyai&labelColor=white"
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alt="join Reddit"></a>
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alt="seguir en X(Twitter)"></a>
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<a href="https://discord.gg/FngNHpbcY7" target="_blank">
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<img src="https://img.shields.io/discord/1082486657678311454?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb"
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alt="chat sur Discord"></a>
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<img src="https://img.shields.io/reddit/subreddit-subscribers/difyai?style=plastic&logo=reddit&label=r%2Fdifyai&labelColor=white"
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alt="join Reddit"></a>
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alt="suivre sur X(Twitter)"></a>
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<a href="https://discord.gg/FngNHpbcY7" target="_blank">
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<img src="https://img.shields.io/discord/1082486657678311454?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb"
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alt="Discordでチャット"></a>
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<img src="https://img.shields.io/reddit/subreddit-subscribers/difyai?style=plastic&logo=reddit&label=r%2Fdifyai&labelColor=white"
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alt="Reddit"></a>
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<a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
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alt="X(Twitter)でフォロー"></a>
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<a href="https://discord.gg/FngNHpbcY7" target="_blank">
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<img src="https://img.shields.io/discord/1082486657678311454?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb"
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alt="chat on Discord"></a>
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<img src="https://img.shields.io/reddit/subreddit-subscribers/difyai?style=plastic&logo=reddit&label=r%2Fdifyai&labelColor=white"
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alt="Follow Reddit"></a>
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alt="follow on X(Twitter)"></a>
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<a href="https://discord.gg/FngNHpbcY7" target="_blank">
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<img src="https://img.shields.io/discord/1082486657678311454?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb"
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alt="chat on Discord"></a>
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<img src="https://img.shields.io/reddit/subreddit-subscribers/difyai?style=plastic&logo=reddit&label=r%2Fdifyai&labelColor=white"
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alt="Follow Reddit"></a>
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<a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
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<img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
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alt="follow on X(Twitter)"></a>
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@ -19,6 +19,9 @@
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<a href="https://discord.gg/FngNHpbcY7" target="_blank">
|
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<img src="https://img.shields.io/discord/1082486657678311454?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb"
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alt="chat on Discord"></a>
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<a href="https://reddit.com/r/difyai" target="_blank">
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<img src="https://img.shields.io/reddit/subreddit-subscribers/difyai?style=plastic&logo=reddit&label=r%2Fdifyai&labelColor=white"
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alt="Follow Reddit"></a>
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<a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
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<img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
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alt="follow on X(Twitter)"></a>
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||||
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|
180
README_SI.md
Normal file
180
README_SI.md
Normal file
|
@ -0,0 +1,180 @@
|
|||
![cover-v5-optimized](https://github.com/langgenius/dify/assets/13230914/f9e19af5-61ba-4119-b926-d10c4c06ebab)
|
||||
|
||||
<p align="center">
|
||||
📌 <a href="https://dify.ai/blog/introducing-dify-workflow-file-upload-a-demo-on-ai-podcast">Predstavljamo nalaganje datotek Dify Workflow: znova ustvarite Google NotebookLM Podcast</a>
|
||||
</p>
|
||||
|
||||
<p align="center">
|
||||
<a href="https://cloud.dify.ai">Dify Cloud</a> ·
|
||||
<a href="https://docs.dify.ai/getting-started/install-self-hosted">Samostojno gostovanje</a> ·
|
||||
<a href="https://docs.dify.ai">Dokumentacija</a> ·
|
||||
<a href="https://udify.app/chat/22L1zSxg6yW1cWQg">Povpraševanje za podjetja</a>
|
||||
</p>
|
||||
|
||||
<p align="center">
|
||||
<a href="https://dify.ai" target="_blank">
|
||||
<img alt="Static Badge" src="https://img.shields.io/badge/Product-F04438"></a>
|
||||
<a href="https://dify.ai/pricing" target="_blank">
|
||||
<img alt="Static Badge" src="https://img.shields.io/badge/free-pricing?logo=free&color=%20%23155EEF&label=pricing&labelColor=%20%23528bff"></a>
|
||||
<a href="https://discord.gg/FngNHpbcY7" target="_blank">
|
||||
<img src="https://img.shields.io/discord/1082486657678311454?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb"
|
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alt="chat on Discord"></a>
|
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<a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
|
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<img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
|
||||
alt="follow on X(Twitter)"></a>
|
||||
<a href="https://hub.docker.com/u/langgenius" target="_blank">
|
||||
<img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
|
||||
<a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
|
||||
<img alt="Commits last month" src="https://img.shields.io/github/commit-activity/m/langgenius/dify?labelColor=%20%2332b583&color=%20%2312b76a"></a>
|
||||
<a href="https://github.com/langgenius/dify/" target="_blank">
|
||||
<img alt="Issues closed" src="https://img.shields.io/github/issues-search?query=repo%3Alanggenius%2Fdify%20is%3Aclosed&label=issues%20closed&labelColor=%20%237d89b0&color=%20%235d6b98"></a>
|
||||
<a href="https://github.com/langgenius/dify/discussions/" target="_blank">
|
||||
<img alt="Discussion posts" src="https://img.shields.io/github/discussions/langgenius/dify?labelColor=%20%239b8afb&color=%20%237a5af8"></a>
|
||||
</p>
|
||||
|
||||
<p align="center">
|
||||
<a href="./README.md"><img alt="README in English" src="https://img.shields.io/badge/English-d9d9d9"></a>
|
||||
<a href="./README_CN.md"><img alt="简体中文版自述文件" src="https://img.shields.io/badge/简体中文-d9d9d9"></a>
|
||||
<a href="./README_JA.md"><img alt="日本語のREADME" src="https://img.shields.io/badge/日本語-d9d9d9"></a>
|
||||
<a href="./README_ES.md"><img alt="README en Español" src="https://img.shields.io/badge/Español-d9d9d9"></a>
|
||||
<a href="./README_FR.md"><img alt="README en Français" src="https://img.shields.io/badge/Français-d9d9d9"></a>
|
||||
<a href="./README_KL.md"><img alt="README tlhIngan Hol" src="https://img.shields.io/badge/Klingon-d9d9d9"></a>
|
||||
<a href="./README_KR.md"><img alt="README in Korean" src="https://img.shields.io/badge/한국어-d9d9d9"></a>
|
||||
<a href="./README_AR.md"><img alt="README بالعربية" src="https://img.shields.io/badge/العربية-d9d9d9"></a>
|
||||
<a href="./README_TR.md"><img alt="Türkçe README" src="https://img.shields.io/badge/Türkçe-d9d9d9"></a>
|
||||
<a href="./README_VI.md"><img alt="README Tiếng Việt" src="https://img.shields.io/badge/Ti%E1%BA%BFng%20Vi%E1%BB%87t-d9d9d9"></a>
|
||||
<a href="./README_SI.md"><img alt="README Slovenščina" src="https://img.shields.io/badge/Sloven%C5%A1%C4%8Dina-d9d9d9"></a>
|
||||
</p>
|
||||
|
||||
|
||||
Dify je odprtokodna platforma za razvoj aplikacij LLM. Njegov intuitivni vmesnik združuje agentski potek dela z umetno inteligenco, cevovod RAG, zmogljivosti agentov, upravljanje modelov, funkcije opazovanja in več, kar vam omogoča hiter prehod od prototipa do proizvodnje.
|
||||
|
||||
## Hitri začetek
|
||||
> Preden namestite Dify, se prepričajte, da vaša naprava izpolnjuje naslednje minimalne sistemske zahteve:
|
||||
>
|
||||
>- CPU >= 2 Core
|
||||
>- RAM >= 4 GiB
|
||||
|
||||
</br>
|
||||
|
||||
Najlažji način za zagon strežnika Dify je prek docker compose . Preden zaženete Dify z naslednjimi ukazi, se prepričajte, da sta Docker in Docker Compose nameščena na vašem računalniku:
|
||||
|
||||
```bash
|
||||
cd dify
|
||||
cd docker
|
||||
cp .env.example .env
|
||||
docker compose up -d
|
||||
```
|
||||
|
||||
Po zagonu lahko dostopate do nadzorne plošče Dify v brskalniku na [http://localhost/install](http://localhost/install) in začnete postopek inicializacije.
|
||||
|
||||
#### Iskanje pomoči
|
||||
Prosimo, glejte naša pogosta vprašanja [FAQ](https://docs.dify.ai/getting-started/install-self-hosted/faqs) če naletite na težave pri nastavitvi Dify. Če imate še vedno težave, se obrnite na [skupnost ali nas](#community--contact).
|
||||
|
||||
> Če želite prispevati k Difyju ali narediti dodaten razvoj, glejte naš vodnik za [uvajanje iz izvorne kode](https://docs.dify.ai/getting-started/install-self-hosted/local-source-code)
|
||||
|
||||
## Ključne značilnosti
|
||||
**1. Potek dela**:
|
||||
Zgradite in preizkusite zmogljive poteke dela AI na vizualnem platnu, pri čemer izkoristite vse naslednje funkcije in več.
|
||||
|
||||
|
||||
https://github.com/langgenius/dify/assets/13230914/356df23e-1604-483d-80a6-9517ece318aa
|
||||
|
||||
|
||||
|
||||
**2. Celovita podpora za modele**:
|
||||
Brezhibna integracija s stotinami lastniških/odprtokodnih LLM-jev ducatov ponudnikov sklepanja in samostojnih rešitev, ki pokrivajo GPT, Mistral, Llama3 in vse modele, združljive z API-jem OpenAI. Celoten seznam podprtih ponudnikov modelov najdete [tukaj](https://docs.dify.ai/getting-started/readme/model-providers).
|
||||
|
||||
![providers-v5](https://github.com/langgenius/dify/assets/13230914/5a17bdbe-097a-4100-8363-40255b70f6e3)
|
||||
|
||||
|
||||
**3. Prompt IDE**:
|
||||
intuitivni vmesnik za ustvarjanje pozivov, primerjavo zmogljivosti modela in dodajanje dodatnih funkcij, kot je pretvorba besedila v govor, aplikaciji, ki temelji na klepetu.
|
||||
|
||||
**4. RAG Pipeline**:
|
||||
E Obsežne zmogljivosti RAG, ki pokrivajo vse od vnosa dokumenta do priklica, s podporo za ekstrakcijo besedila iz datotek PDF, PPT in drugih običajnih formatov dokumentov.
|
||||
|
||||
**5. Agent capabilities**:
|
||||
definirate lahko agente, ki temeljijo na klicanju funkcij LLM ali ReAct, in dodate vnaprej izdelana orodja ali orodja po meri za agenta. Dify ponuja več kot 50 vgrajenih orodij za agente AI, kot so Google Search, DALL·E, Stable Diffusion in WolframAlpha.
|
||||
|
||||
**6. LLMOps**:
|
||||
Spremljajte in analizirajte dnevnike aplikacij in učinkovitost skozi čas. Pozive, nabore podatkov in modele lahko nenehno izboljšujete na podlagi proizvodnih podatkov in opomb.
|
||||
|
||||
**7. Backend-as-a-Service**:
|
||||
AVse ponudbe Difyja so opremljene z ustreznimi API-ji, tako da lahko Dify brez težav integrirate v svojo poslovno logiko.
|
||||
|
||||
|
||||
## Uporaba Dify
|
||||
|
||||
- **Cloud </br>**
|
||||
Gostimo storitev Dify Cloud za vsakogar, ki jo lahko preizkusite brez nastavitev. Zagotavlja vse zmožnosti različice za samostojno namestitev in vključuje 200 brezplačnih klicev GPT-4 v načrtu peskovnika.
|
||||
|
||||
- **Self-hosting Dify Community Edition</br>**
|
||||
Hitro zaženite Dify v svojem okolju s tem [začetnim vodnikom](#quick-start) . Za dodatne reference in podrobnejša navodila uporabite našo [dokumentacijo](https://docs.dify.ai) .
|
||||
|
||||
|
||||
- **Dify za podjetja/organizacije</br>**
|
||||
Ponujamo dodatne funkcije, osredotočene na podjetja. Zabeležite svoja vprašanja prek tega klepetalnega robota ali nam pošljite e-pošto, da se pogovorimo o potrebah podjetja. </br>
|
||||
> Za novoustanovljena podjetja in mala podjetja, ki uporabljajo AWS, si oglejte Dify Premium na AWS Marketplace in ga z enim klikom uvedite v svoj AWS VPC. To je cenovno ugodna ponudba AMI z možnostjo ustvarjanja aplikacij z logotipom in blagovno znamko po meri.
|
||||
|
||||
|
||||
## Staying ahead
|
||||
|
||||
Star Dify on GitHub and be instantly notified of new releases.
|
||||
|
||||
![star-us](https://github.com/langgenius/dify/assets/13230914/b823edc1-6388-4e25-ad45-2f6b187adbb4)
|
||||
|
||||
|
||||
## Napredne nastavitve
|
||||
|
||||
Če morate prilagoditi konfiguracijo, si oglejte komentarje v naši datoteki .env.example in posodobite ustrezne vrednosti v svoji .env datoteki. Poleg tega boste morda morali prilagoditi docker-compose.yamlsamo datoteko, na primer spremeniti različice slike, preslikave vrat ali namestitve nosilca, glede na vaše specifično okolje in zahteve za uvajanje. Po kakršnih koli spremembah ponovno zaženite docker-compose up -d. Celoten seznam razpoložljivih spremenljivk okolja najdete tukaj .
|
||||
|
||||
Če želite konfigurirati visoko razpoložljivo nastavitev, so na voljo Helm Charts in datoteke YAML, ki jih prispeva skupnost, ki omogočajo uvedbo Difyja v Kubernetes.
|
||||
|
||||
- [Helm Chart by @LeoQuote](https://github.com/douban/charts/tree/master/charts/dify)
|
||||
- [Helm Chart by @BorisPolonsky](https://github.com/BorisPolonsky/dify-helm)
|
||||
- [YAML file by @Winson-030](https://github.com/Winson-030/dify-kubernetes)
|
||||
|
||||
#### Uporaba Terraform za uvajanje
|
||||
|
||||
namestite Dify v Cloud Platform z enim klikom z uporabo [terraform](https://www.terraform.io/)
|
||||
|
||||
##### Azure Global
|
||||
- [Azure Terraform by @nikawang](https://github.com/nikawang/dify-azure-terraform)
|
||||
|
||||
##### Google Cloud
|
||||
- [Google Cloud Terraform by @sotazum](https://github.com/DeNA/dify-google-cloud-terraform)
|
||||
|
||||
## Prispevam
|
||||
|
||||
Za tiste, ki bi radi prispevali kodo, si oglejte naš vodnik za prispevke . Hkrati vas prosimo, da podprete Dify tako, da ga delite na družbenih medijih ter na dogodkih in konferencah.
|
||||
|
||||
|
||||
|
||||
> Iščemo sodelavce za pomoč pri prevajanju Difyja v jezike, ki niso mandarinščina ali angleščina. Če želite pomagati, si oglejte i18n README za več informacij in nam pustite komentar v global-userskanalu našega strežnika skupnosti Discord .
|
||||
|
||||
## Skupnost in stik
|
||||
|
||||
* [Github Discussion](https://github.com/langgenius/dify/discussions). Najboljše za: izmenjavo povratnih informacij in postavljanje vprašanj.
|
||||
* [GitHub Issues](https://github.com/langgenius/dify/issues). Najboljše za: hrošče, na katere naletite pri uporabi Dify.AI, in predloge funkcij. Oglejte si naš [vodnik za prispevke](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md).
|
||||
* [Discord](https://discord.gg/FngNHpbcY7). Najboljše za: deljenje vaših aplikacij in druženje s skupnostjo.
|
||||
* [X(Twitter)](https://twitter.com/dify_ai). Najboljše za: deljenje vaših aplikacij in druženje s skupnostjo.
|
||||
|
||||
**Contributors**
|
||||
|
||||
<a href="https://github.com/langgenius/dify/graphs/contributors">
|
||||
<img src="https://contrib.rocks/image?repo=langgenius/dify" />
|
||||
</a>
|
||||
|
||||
## Star history
|
||||
|
||||
[![Star History Chart](https://api.star-history.com/svg?repos=langgenius/dify&type=Date)](https://star-history.com/#langgenius/dify&Date)
|
||||
|
||||
|
||||
## Varnostno razkritje
|
||||
|
||||
Zaradi zaščite vaše zasebnosti se izogibajte objavljanju varnostnih vprašanj na GitHub. Namesto tega pošljite vprašanja na security@dify.ai in zagotovili vam bomo podrobnejši odgovor.
|
||||
|
||||
## Licenca
|
||||
|
||||
To skladišče je na voljo pod [odprtokodno licenco Dify](LICENSE) , ki je v bistvu Apache 2.0 z nekaj dodatnimi omejitvami.
|
|
@ -15,6 +15,9 @@
|
|||
<a href="https://discord.gg/FngNHpbcY7" target="_blank">
|
||||
<img src="https://img.shields.io/discord/1082486657678311454?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb"
|
||||
alt="Discord'da sohbet et"></a>
|
||||
<a href="https://reddit.com/r/difyai" target="_blank">
|
||||
<img src="https://img.shields.io/reddit/subreddit-subscribers/difyai?style=plastic&logo=reddit&label=r%2Fdifyai&labelColor=white"
|
||||
alt="Follow Reddit"></a>
|
||||
<a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
|
||||
<img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
|
||||
alt="X(Twitter)'da takip et"></a>
|
||||
|
|
|
@ -15,6 +15,9 @@
|
|||
<a href="https://discord.gg/FngNHpbcY7" target="_blank">
|
||||
<img src="https://img.shields.io/discord/1082486657678311454?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb"
|
||||
alt="chat trên Discord"></a>
|
||||
<a href="https://reddit.com/r/difyai" target="_blank">
|
||||
<img src="https://img.shields.io/reddit/subreddit-subscribers/difyai?style=plastic&logo=reddit&label=r%2Fdifyai&labelColor=white"
|
||||
alt="Follow Reddit"></a>
|
||||
<a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
|
||||
<img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
|
||||
alt="theo dõi trên X(Twitter)"></a>
|
||||
|
|
|
@ -55,7 +55,7 @@ RUN apt-get update \
|
|||
&& echo "deb http://deb.debian.org/debian testing main" > /etc/apt/sources.list \
|
||||
&& apt-get update \
|
||||
# For Security
|
||||
&& apt-get install -y --no-install-recommends expat=2.6.3-2 libldap-2.5-0=2.5.18+dfsg-3+b1 perl=5.40.0-6 libsqlite3-0=3.46.1-1 zlib1g=1:1.3.dfsg+really1.3.1-1+b1 \
|
||||
&& apt-get install -y --no-install-recommends expat=2.6.4-1 libldap-2.5-0=2.5.18+dfsg-3+b1 perl=5.40.0-7 libsqlite3-0=3.46.1-1 zlib1g=1:1.3.dfsg+really1.3.1-1+b1 \
|
||||
# install a chinese font to support the use of tools like matplotlib
|
||||
&& apt-get install -y fonts-noto-cjk \
|
||||
&& apt-get autoremove -y \
|
||||
|
|
|
@ -1,4 +1,5 @@
|
|||
import os
|
||||
import sys
|
||||
|
||||
from configs import dify_config
|
||||
|
||||
|
@ -29,6 +30,9 @@ from models import account, dataset, model, source, task, tool, tools, web # no
|
|||
|
||||
# DO NOT REMOVE ABOVE
|
||||
|
||||
if sys.version_info[:2] == (3, 10):
|
||||
print("Warning: Python 3.10 will not be supported in the next version.")
|
||||
|
||||
|
||||
warnings.simplefilter("ignore", ResourceWarning)
|
||||
|
||||
|
@ -49,7 +53,6 @@ if dify_config.TESTING:
|
|||
@app.after_request
|
||||
def after_request(response):
|
||||
"""Add Version headers to the response."""
|
||||
response.set_cookie("remember_token", "", expires=0)
|
||||
response.headers.add("X-Version", dify_config.CURRENT_VERSION)
|
||||
response.headers.add("X-Env", dify_config.DEPLOY_ENV)
|
||||
return response
|
||||
|
|
|
@ -589,7 +589,7 @@ def upgrade_db():
|
|||
click.echo(click.style("Database migration successful!", fg="green"))
|
||||
|
||||
except Exception as e:
|
||||
logging.exception(f"Database migration failed: {e}")
|
||||
logging.exception("Failed to execute database migration")
|
||||
finally:
|
||||
lock.release()
|
||||
else:
|
||||
|
@ -633,7 +633,7 @@ where sites.id is null limit 1000"""
|
|||
except Exception as e:
|
||||
failed_app_ids.append(app_id)
|
||||
click.echo(click.style("Failed to fix missing site for app {}".format(app_id), fg="red"))
|
||||
logging.exception(f"Fix app related site missing issue failed, error: {e}")
|
||||
logging.exception(f"Failed to fix app related site missing issue, app_id: {app_id}")
|
||||
continue
|
||||
|
||||
if not processed_count:
|
||||
|
|
|
@ -9,7 +9,7 @@ class PackagingInfo(BaseSettings):
|
|||
|
||||
CURRENT_VERSION: str = Field(
|
||||
description="Dify version",
|
||||
default="0.11.0",
|
||||
default="0.11.1",
|
||||
)
|
||||
|
||||
COMMIT_SHA: str = Field(
|
||||
|
|
|
@ -17,6 +17,7 @@ language_timezone_mapping = {
|
|||
"hi-IN": "Asia/Kolkata",
|
||||
"tr-TR": "Europe/Istanbul",
|
||||
"fa-IR": "Asia/Tehran",
|
||||
"sl-SI": "Europe/Ljubljana",
|
||||
}
|
||||
|
||||
languages = list(language_timezone_mapping.keys())
|
||||
|
|
|
@ -70,7 +70,7 @@ class ChatMessageAudioApi(Resource):
|
|||
except ValueError as e:
|
||||
raise e
|
||||
except Exception as e:
|
||||
logging.exception(f"internal server error, {str(e)}.")
|
||||
logging.exception("Failed to handle post request to ChatMessageAudioApi")
|
||||
raise InternalServerError()
|
||||
|
||||
|
||||
|
@ -128,7 +128,7 @@ class ChatMessageTextApi(Resource):
|
|||
except ValueError as e:
|
||||
raise e
|
||||
except Exception as e:
|
||||
logging.exception(f"internal server error, {str(e)}.")
|
||||
logging.exception("Failed to handle post request to ChatMessageTextApi")
|
||||
raise InternalServerError()
|
||||
|
||||
|
||||
|
@ -170,7 +170,7 @@ class TextModesApi(Resource):
|
|||
except ValueError as e:
|
||||
raise e
|
||||
except Exception as e:
|
||||
logging.exception(f"internal server error, {str(e)}.")
|
||||
logging.exception("Failed to handle get request to TextModesApi")
|
||||
raise InternalServerError()
|
||||
|
||||
|
||||
|
|
|
@ -948,7 +948,7 @@ class DocumentRetryApi(DocumentResource):
|
|||
raise DocumentAlreadyFinishedError()
|
||||
retry_documents.append(document)
|
||||
except Exception as e:
|
||||
logging.exception(f"Document {document_id} retry failed: {str(e)}")
|
||||
logging.exception(f"Failed to retry document, document id: {document_id}")
|
||||
continue
|
||||
# retry document
|
||||
DocumentService.retry_document(dataset_id, retry_documents)
|
||||
|
|
|
@ -72,7 +72,10 @@ class DefaultModelApi(Resource):
|
|||
model=model_setting["model"],
|
||||
)
|
||||
except Exception as ex:
|
||||
logging.exception(f"{model_setting['model_type']} save error: {ex}")
|
||||
logging.exception(
|
||||
f"Failed to update default model, model type: {model_setting['model_type']},"
|
||||
f" model:{model_setting.get('model')}"
|
||||
)
|
||||
raise ex
|
||||
|
||||
return {"result": "success"}
|
||||
|
@ -156,7 +159,10 @@ class ModelProviderModelApi(Resource):
|
|||
credentials=args["credentials"],
|
||||
)
|
||||
except CredentialsValidateFailedError as ex:
|
||||
logging.exception(f"save model credentials error: {ex}")
|
||||
logging.exception(
|
||||
f"Failed to save model credentials, tenant_id: {tenant_id},"
|
||||
f" model: {args.get('model')}, model_type: {args.get('model_type')}"
|
||||
)
|
||||
raise ValueError(str(ex))
|
||||
|
||||
return {"result": "success"}, 200
|
||||
|
|
|
@ -59,7 +59,7 @@ class AudioApi(WebApiResource):
|
|||
except ValueError as e:
|
||||
raise e
|
||||
except Exception as e:
|
||||
logging.exception(f"internal server error: {str(e)}")
|
||||
logging.exception("Failed to handle post request to AudioApi")
|
||||
raise InternalServerError()
|
||||
|
||||
|
||||
|
@ -117,7 +117,7 @@ class TextApi(WebApiResource):
|
|||
except ValueError as e:
|
||||
raise e
|
||||
except Exception as e:
|
||||
logging.exception(f"internal server error: {str(e)}")
|
||||
logging.exception("Failed to handle post request to TextApi")
|
||||
raise InternalServerError()
|
||||
|
||||
|
||||
|
|
|
@ -360,5 +360,5 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
|
|||
if e.args[0] == "I/O operation on closed file.": # ignore this error
|
||||
raise GenerateTaskStoppedError()
|
||||
else:
|
||||
logger.exception(e)
|
||||
logger.exception(f"Failed to process generate task pipeline, conversation_id: {conversation.id}")
|
||||
raise e
|
||||
|
|
|
@ -242,7 +242,7 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
|
|||
start_listener_time = time.time()
|
||||
yield MessageAudioStreamResponse(audio=audio_trunk.audio, task_id=task_id)
|
||||
except Exception as e:
|
||||
logger.exception(e)
|
||||
logger.exception(f"Failed to listen audio message, task_id: {task_id}")
|
||||
break
|
||||
if tts_publisher:
|
||||
yield MessageAudioEndStreamResponse(audio="", task_id=task_id)
|
||||
|
|
|
@ -80,7 +80,7 @@ class MessageBasedAppGenerator(BaseAppGenerator):
|
|||
if e.args[0] == "I/O operation on closed file.": # ignore this error
|
||||
raise GenerateTaskStoppedError()
|
||||
else:
|
||||
logger.exception(e)
|
||||
logger.exception(f"Failed to handle response, conversation_id: {conversation.id}")
|
||||
raise e
|
||||
|
||||
def _get_conversation_by_user(
|
||||
|
|
|
@ -298,5 +298,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
|
|||
if e.args[0] == "I/O operation on closed file.": # ignore this error
|
||||
raise GenerateTaskStoppedError()
|
||||
else:
|
||||
logger.exception(e)
|
||||
logger.exception(
|
||||
f"Fails to process generate task pipeline, task_id: {application_generate_entity.task_id}"
|
||||
)
|
||||
raise e
|
||||
|
|
|
@ -216,7 +216,7 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
|
|||
else:
|
||||
yield MessageAudioStreamResponse(audio=audio_trunk.audio, task_id=task_id)
|
||||
except Exception as e:
|
||||
logger.exception(e)
|
||||
logger.exception(f"Fails to get audio trunk, task_id: {task_id}")
|
||||
break
|
||||
if tts_publisher:
|
||||
yield MessageAudioEndStreamResponse(audio="", task_id=task_id)
|
||||
|
|
|
@ -361,6 +361,7 @@ class WorkflowBasedAppRunner(AppRunner):
|
|||
node_run_index=workflow_entry.graph_engine.graph_runtime_state.node_run_steps,
|
||||
output=event.pre_iteration_output,
|
||||
parallel_mode_run_id=event.parallel_mode_run_id,
|
||||
duration=event.duration,
|
||||
)
|
||||
)
|
||||
elif isinstance(event, (IterationRunSucceededEvent | IterationRunFailedEvent)):
|
||||
|
|
|
@ -111,6 +111,7 @@ class QueueIterationNextEvent(AppQueueEvent):
|
|||
"""iteratoin run in parallel mode run id"""
|
||||
node_run_index: int
|
||||
output: Optional[Any] = None # output for the current iteration
|
||||
duration: Optional[float] = None
|
||||
|
||||
@field_validator("output", mode="before")
|
||||
@classmethod
|
||||
|
@ -307,6 +308,8 @@ class QueueNodeSucceededEvent(AppQueueEvent):
|
|||
execution_metadata: Optional[dict[NodeRunMetadataKey, Any]] = None
|
||||
|
||||
error: Optional[str] = None
|
||||
"""single iteration duration map"""
|
||||
iteration_duration_map: Optional[dict[str, float]] = None
|
||||
|
||||
|
||||
class QueueNodeInIterationFailedEvent(AppQueueEvent):
|
||||
|
|
|
@ -434,6 +434,7 @@ class IterationNodeNextStreamResponse(StreamResponse):
|
|||
parallel_id: Optional[str] = None
|
||||
parallel_start_node_id: Optional[str] = None
|
||||
parallel_mode_run_id: Optional[str] = None
|
||||
duration: Optional[float] = None
|
||||
|
||||
event: StreamEvent = StreamEvent.ITERATION_NEXT
|
||||
workflow_run_id: str
|
||||
|
|
|
@ -86,7 +86,7 @@ class MessageCycleManage:
|
|||
conversation.name = name
|
||||
except Exception as e:
|
||||
if dify_config.DEBUG:
|
||||
logging.exception(f"generate conversation name failed: {e}")
|
||||
logging.exception(f"generate conversation name failed, conversation_id: {conversation_id}")
|
||||
pass
|
||||
|
||||
db.session.merge(conversation)
|
||||
|
|
|
@ -624,6 +624,7 @@ class WorkflowCycleManage:
|
|||
parallel_id=event.parallel_id,
|
||||
parallel_start_node_id=event.parallel_start_node_id,
|
||||
parallel_mode_run_id=event.parallel_mode_run_id,
|
||||
duration=event.duration,
|
||||
),
|
||||
)
|
||||
|
||||
|
|
|
@ -0,0 +1,3 @@
|
|||
from .code_executor import CodeExecutor, CodeLanguage
|
||||
|
||||
__all__ = ["CodeExecutor", "CodeLanguage"]
|
|
@ -1,7 +1,8 @@
|
|||
import logging
|
||||
from collections.abc import Mapping
|
||||
from enum import Enum
|
||||
from threading import Lock
|
||||
from typing import Optional
|
||||
from typing import Any, Optional
|
||||
|
||||
from httpx import Timeout, post
|
||||
from pydantic import BaseModel
|
||||
|
@ -117,7 +118,7 @@ class CodeExecutor:
|
|||
return response.data.stdout or ""
|
||||
|
||||
@classmethod
|
||||
def execute_workflow_code_template(cls, language: CodeLanguage, code: str, inputs: dict) -> dict:
|
||||
def execute_workflow_code_template(cls, language: CodeLanguage, code: str, inputs: Mapping[str, Any]) -> dict:
|
||||
"""
|
||||
Execute code
|
||||
:param language: code language
|
||||
|
|
|
@ -2,6 +2,8 @@ import json
|
|||
import re
|
||||
from abc import ABC, abstractmethod
|
||||
from base64 import b64encode
|
||||
from collections.abc import Mapping
|
||||
from typing import Any
|
||||
|
||||
|
||||
class TemplateTransformer(ABC):
|
||||
|
@ -10,7 +12,7 @@ class TemplateTransformer(ABC):
|
|||
_result_tag: str = "<<RESULT>>"
|
||||
|
||||
@classmethod
|
||||
def transform_caller(cls, code: str, inputs: dict) -> tuple[str, str]:
|
||||
def transform_caller(cls, code: str, inputs: Mapping[str, Any]) -> tuple[str, str]:
|
||||
"""
|
||||
Transform code to python runner
|
||||
:param code: code
|
||||
|
@ -48,13 +50,13 @@ class TemplateTransformer(ABC):
|
|||
pass
|
||||
|
||||
@classmethod
|
||||
def serialize_inputs(cls, inputs: dict) -> str:
|
||||
def serialize_inputs(cls, inputs: Mapping[str, Any]) -> str:
|
||||
inputs_json_str = json.dumps(inputs, ensure_ascii=False).encode()
|
||||
input_base64_encoded = b64encode(inputs_json_str).decode("utf-8")
|
||||
return input_base64_encoded
|
||||
|
||||
@classmethod
|
||||
def assemble_runner_script(cls, code: str, inputs: dict) -> str:
|
||||
def assemble_runner_script(cls, code: str, inputs: Mapping[str, Any]) -> str:
|
||||
# assemble runner script
|
||||
script = cls.get_runner_script()
|
||||
script = script.replace(cls._code_placeholder, code)
|
||||
|
|
|
@ -41,7 +41,7 @@ def check_moderation(model_config: ModelConfigWithCredentialsEntity, text: str)
|
|||
if moderation_result is True:
|
||||
return True
|
||||
except Exception as ex:
|
||||
logger.exception(ex)
|
||||
logger.exception(f"Fails to check moderation, provider_name: {provider_name}")
|
||||
raise InvokeBadRequestError("Rate limit exceeded, please try again later.")
|
||||
|
||||
return False
|
||||
|
|
|
@ -29,7 +29,7 @@ def import_module_from_source(*, module_name: str, py_file_path: AnyStr, use_laz
|
|||
spec.loader.exec_module(module)
|
||||
return module
|
||||
except Exception as e:
|
||||
logging.exception(f"Failed to load module {module_name} from {py_file_path}: {str(e)}")
|
||||
logging.exception(f"Failed to load module {module_name} from script file '{py_file_path}'")
|
||||
raise e
|
||||
|
||||
|
||||
|
|
|
@ -554,7 +554,7 @@ class IndexingRunner:
|
|||
qa_documents.append(qa_document)
|
||||
format_documents.extend(qa_documents)
|
||||
except Exception as e:
|
||||
logging.exception(e)
|
||||
logging.exception("Failed to format qa document")
|
||||
|
||||
all_qa_documents.extend(format_documents)
|
||||
|
||||
|
|
|
@ -102,7 +102,7 @@ class LLMGenerator:
|
|||
except InvokeError:
|
||||
questions = []
|
||||
except Exception as e:
|
||||
logging.exception(e)
|
||||
logging.exception("Failed to generate suggested questions after answer")
|
||||
questions = []
|
||||
|
||||
return questions
|
||||
|
@ -148,7 +148,7 @@ class LLMGenerator:
|
|||
error = str(e)
|
||||
error_step = "generate rule config"
|
||||
except Exception as e:
|
||||
logging.exception(e)
|
||||
logging.exception(f"Failed to generate rule config, model: {model_config.get('name')}")
|
||||
rule_config["error"] = str(e)
|
||||
|
||||
rule_config["error"] = f"Failed to {error_step}. Error: {error}" if error else ""
|
||||
|
@ -234,7 +234,7 @@ class LLMGenerator:
|
|||
error_step = "generate conversation opener"
|
||||
|
||||
except Exception as e:
|
||||
logging.exception(e)
|
||||
logging.exception(f"Failed to generate rule config, model: {model_config.get('name')}")
|
||||
rule_config["error"] = str(e)
|
||||
|
||||
rule_config["error"] = f"Failed to {error_step}. Error: {error}" if error else ""
|
||||
|
@ -286,7 +286,9 @@ class LLMGenerator:
|
|||
error = str(e)
|
||||
return {"code": "", "language": code_language, "error": f"Failed to generate code. Error: {error}"}
|
||||
except Exception as e:
|
||||
logging.exception(e)
|
||||
logging.exception(
|
||||
f"Failed to invoke LLM model, model: {model_config.get('name')}, language: {code_language}"
|
||||
)
|
||||
return {"code": "", "language": code_language, "error": f"An unexpected error occurred: {str(e)}"}
|
||||
|
||||
@classmethod
|
||||
|
|
|
@ -103,7 +103,7 @@ class AzureRerankModel(RerankModel):
|
|||
return RerankResult(model=model, docs=rerank_documents)
|
||||
|
||||
except Exception as e:
|
||||
logger.exception(f"Exception in Azure rerank: {e}")
|
||||
logger.exception(f"Failed to invoke rerank model, model: {model}")
|
||||
raise
|
||||
|
||||
def validate_credentials(self, model: str, credentials: dict) -> None:
|
||||
|
|
|
@ -113,7 +113,7 @@ class AzureOpenAILargeLanguageModel(_CommonAzureOpenAI, LargeLanguageModel):
|
|||
try:
|
||||
client = AzureOpenAI(**self._to_credential_kwargs(credentials))
|
||||
|
||||
if model.startswith("o1"):
|
||||
if "o1" in model:
|
||||
client.chat.completions.create(
|
||||
messages=[{"role": "user", "content": "ping"}],
|
||||
model=model,
|
||||
|
@ -311,7 +311,7 @@ class AzureOpenAILargeLanguageModel(_CommonAzureOpenAI, LargeLanguageModel):
|
|||
prompt_messages = self._clear_illegal_prompt_messages(model, prompt_messages)
|
||||
|
||||
block_as_stream = False
|
||||
if model.startswith("o1"):
|
||||
if "o1" in model:
|
||||
if stream:
|
||||
block_as_stream = True
|
||||
stream = False
|
||||
|
@ -404,7 +404,7 @@ class AzureOpenAILargeLanguageModel(_CommonAzureOpenAI, LargeLanguageModel):
|
|||
]
|
||||
)
|
||||
|
||||
if model.startswith("o1"):
|
||||
if "o1" in model:
|
||||
system_message_count = len([m for m in prompt_messages if isinstance(m, SystemPromptMessage)])
|
||||
if system_message_count > 0:
|
||||
new_prompt_messages = []
|
||||
|
@ -653,7 +653,7 @@ class AzureOpenAILargeLanguageModel(_CommonAzureOpenAI, LargeLanguageModel):
|
|||
tokens_per_message = 4
|
||||
# if there's a name, the role is omitted
|
||||
tokens_per_name = -1
|
||||
elif model.startswith("gpt-35-turbo") or model.startswith("gpt-4") or model.startswith("o1"):
|
||||
elif model.startswith("gpt-35-turbo") or model.startswith("gpt-4") or "o1" in model:
|
||||
tokens_per_message = 3
|
||||
tokens_per_name = 1
|
||||
else:
|
||||
|
|
|
@ -0,0 +1,95 @@
|
|||
model: Qwen2.5-72B-Instruct
|
||||
label:
|
||||
zh_Hans: Qwen2.5-72B-Instruct
|
||||
en_US: Qwen2.5-72B-Instruct
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 32768
|
||||
parameter_rules:
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
label:
|
||||
en_US: "Max Tokens"
|
||||
zh_Hans: "最大Token数"
|
||||
type: int
|
||||
default: 512
|
||||
min: 1
|
||||
required: true
|
||||
help:
|
||||
en_US: "The maximum number of tokens that can be generated by the model varies depending on the model."
|
||||
zh_Hans: "模型可生成的最大 token 个数,不同模型上限不同。"
|
||||
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
label:
|
||||
en_US: "Temperature"
|
||||
zh_Hans: "采样温度"
|
||||
type: float
|
||||
default: 0.7
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
precision: 1
|
||||
required: true
|
||||
help:
|
||||
en_US: "The randomness of the sampling temperature control output. The temperature value is within the range of [0.0, 1.0]. The higher the value, the more random and creative the output; the lower the value, the more stable it is. It is recommended to adjust either top_p or temperature parameters according to your needs to avoid adjusting both at the same time."
|
||||
zh_Hans: "采样温度控制输出的随机性。温度值在 [0.0, 1.0] 范围内,值越高,输出越随机和创造性;值越低,输出越稳定。建议根据需求调整 top_p 或 temperature 参数,避免同时调整两者。"
|
||||
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
label:
|
||||
en_US: "Top P"
|
||||
zh_Hans: "Top P"
|
||||
type: float
|
||||
default: 0.7
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
precision: 1
|
||||
required: true
|
||||
help:
|
||||
en_US: "The value range of the sampling method is [0.0, 1.0]. The top_p value determines that the model selects tokens from the top p% of candidate words with the highest probability; when top_p is 0, this parameter is invalid. It is recommended to adjust either top_p or temperature parameters according to your needs to avoid adjusting both at the same time."
|
||||
zh_Hans: "采样方法的取值范围为 [0.0,1.0]。top_p 值确定模型从概率最高的前p%的候选词中选取 tokens;当 top_p 为 0 时,此参数无效。建议根据需求调整 top_p 或 temperature 参数,避免同时调整两者。"
|
||||
|
||||
- name: top_k
|
||||
use_template: top_k
|
||||
label:
|
||||
en_US: "Top K"
|
||||
zh_Hans: "Top K"
|
||||
type: int
|
||||
default: 50
|
||||
min: 0
|
||||
max: 100
|
||||
required: true
|
||||
help:
|
||||
en_US: "The value range is [0,100], which limits the model to only select from the top k words with the highest probability when choosing the next word at each step. The larger the value, the more diverse text generation will be."
|
||||
zh_Hans: "取值范围为 [0,100],限制模型在每一步选择下一个词时,只从概率最高的前 k 个词中选取。数值越大,文本生成越多样。"
|
||||
|
||||
- name: frequency_penalty
|
||||
use_template: frequency_penalty
|
||||
label:
|
||||
en_US: "Frequency Penalty"
|
||||
zh_Hans: "频率惩罚"
|
||||
type: float
|
||||
default: 0
|
||||
min: -1.0
|
||||
max: 1.0
|
||||
precision: 1
|
||||
required: false
|
||||
help:
|
||||
en_US: "Used to adjust the frequency of repeated content in automatically generated text. Positive numbers reduce repetition, while negative numbers increase repetition. After setting this parameter, if a word has already appeared in the text, the model will decrease the probability of choosing that word for subsequent generation."
|
||||
zh_Hans: "用于调整自动生成文本中重复内容的频率。正数减少重复,负数增加重复。设置此参数后,如果一个词在文本中已经出现过,模型在后续生成中选择该词的概率会降低。"
|
||||
|
||||
- name: user
|
||||
use_template: text
|
||||
label:
|
||||
en_US: "User"
|
||||
zh_Hans: "用户"
|
||||
type: string
|
||||
required: false
|
||||
help:
|
||||
en_US: "Used to track and differentiate conversation requests from different users."
|
||||
zh_Hans: "用于追踪和区分不同用户的对话请求。"
|
|
@ -1,3 +1,4 @@
|
|||
- Qwen2.5-72B-Instruct
|
||||
- Qwen2-7B-Instruct
|
||||
- Qwen2-72B-Instruct
|
||||
- Yi-1.5-34B-Chat
|
||||
|
|
|
@ -6,6 +6,7 @@ from core.model_runtime.entities.message_entities import (
|
|||
PromptMessage,
|
||||
PromptMessageTool,
|
||||
)
|
||||
from core.model_runtime.entities.model_entities import ModelFeature
|
||||
from core.model_runtime.model_providers.openai_api_compatible.llm.llm import OAIAPICompatLargeLanguageModel
|
||||
|
||||
|
||||
|
@ -28,14 +29,13 @@ class GiteeAILargeLanguageModel(OAIAPICompatLargeLanguageModel):
|
|||
user: Optional[str] = None,
|
||||
) -> Union[LLMResult, Generator]:
|
||||
self._add_custom_parameters(credentials, model, model_parameters)
|
||||
return super()._invoke(model, credentials, prompt_messages, model_parameters, tools, stop, stream)
|
||||
return super()._invoke(model, credentials, prompt_messages, model_parameters, tools, stop, stream, user)
|
||||
|
||||
def validate_credentials(self, model: str, credentials: dict) -> None:
|
||||
self._add_custom_parameters(credentials, model, None)
|
||||
super().validate_credentials(model, credentials)
|
||||
|
||||
@staticmethod
|
||||
def _add_custom_parameters(credentials: dict, model: str, model_parameters: dict) -> None:
|
||||
def _add_custom_parameters(self, credentials: dict, model: str, model_parameters: dict) -> None:
|
||||
if model is None:
|
||||
model = "bge-large-zh-v1.5"
|
||||
|
||||
|
@ -45,3 +45,7 @@ class GiteeAILargeLanguageModel(OAIAPICompatLargeLanguageModel):
|
|||
credentials["mode"] = LLMMode.COMPLETION.value
|
||||
else:
|
||||
credentials["mode"] = LLMMode.CHAT.value
|
||||
|
||||
schema = self.get_model_schema(model, credentials)
|
||||
if ModelFeature.TOOL_CALL in schema.features or ModelFeature.MULTI_TOOL_CALL in schema.features:
|
||||
credentials["function_calling_type"] = "tool_call"
|
||||
|
|
|
@ -55,6 +55,7 @@ class JinaRerankModel(RerankModel):
|
|||
base_url + "/rerank",
|
||||
json={"model": model, "query": query, "documents": docs, "top_n": top_n},
|
||||
headers={"Authorization": f"Bearer {credentials.get('api_key')}"},
|
||||
timeout=20,
|
||||
)
|
||||
response.raise_for_status()
|
||||
results = response.json()
|
||||
|
|
|
@ -0,0 +1,46 @@
|
|||
model: abab7-chat-preview
|
||||
label:
|
||||
en_US: Abab7-chat-preview
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 245760
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
min: 0.01
|
||||
max: 1
|
||||
default: 0.1
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
min: 0.01
|
||||
max: 1
|
||||
default: 0.95
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 2048
|
||||
min: 1
|
||||
max: 245760
|
||||
- name: mask_sensitive_info
|
||||
type: boolean
|
||||
default: true
|
||||
label:
|
||||
zh_Hans: 隐私保护
|
||||
en_US: Moderate
|
||||
help:
|
||||
zh_Hans: 对输出中易涉及隐私问题的文本信息进行打码,目前包括但不限于邮箱、域名、链接、证件号、家庭住址等,默认true,即开启打码
|
||||
en_US: Mask the sensitive info of the generated content, such as email/domain/link/address/phone/id..
|
||||
- name: presence_penalty
|
||||
use_template: presence_penalty
|
||||
- name: frequency_penalty
|
||||
use_template: frequency_penalty
|
||||
pricing:
|
||||
input: '0.1'
|
||||
output: '0.1'
|
||||
unit: '0.001'
|
||||
currency: RMB
|
|
@ -34,6 +34,7 @@ from core.model_runtime.model_providers.minimax.llm.types import MinimaxMessage
|
|||
|
||||
class MinimaxLargeLanguageModel(LargeLanguageModel):
|
||||
model_apis = {
|
||||
"abab7-chat-preview": MinimaxChatCompletionPro,
|
||||
"abab6.5s-chat": MinimaxChatCompletionPro,
|
||||
"abab6.5-chat": MinimaxChatCompletionPro,
|
||||
"abab6-chat": MinimaxChatCompletionPro,
|
||||
|
|
|
@ -617,6 +617,10 @@ class OpenAILargeLanguageModel(_CommonOpenAI, LargeLanguageModel):
|
|||
# o1 compatibility
|
||||
block_as_stream = False
|
||||
if model.startswith("o1"):
|
||||
if "max_tokens" in model_parameters:
|
||||
model_parameters["max_completion_tokens"] = model_parameters["max_tokens"]
|
||||
del model_parameters["max_tokens"]
|
||||
|
||||
if stream:
|
||||
block_as_stream = True
|
||||
stream = False
|
||||
|
|
|
@ -113,7 +113,7 @@ class SageMakerRerankModel(RerankModel):
|
|||
return RerankResult(model=model, docs=rerank_documents)
|
||||
|
||||
except Exception as e:
|
||||
logger.exception(f"Exception {e}, line : {line}")
|
||||
logger.exception(f"Failed to invoke rerank model, model: {model}")
|
||||
|
||||
def validate_credentials(self, model: str, credentials: dict) -> None:
|
||||
"""
|
||||
|
|
|
@ -78,7 +78,7 @@ class SageMakerSpeech2TextModel(Speech2TextModel):
|
|||
json_obj = json.loads(json_str)
|
||||
asr_text = json_obj["text"]
|
||||
except Exception as e:
|
||||
logger.exception(f"failed to invoke speech2text model, {e}")
|
||||
logger.exception(f"failed to invoke speech2text model, model: {model}")
|
||||
raise CredentialsValidateFailedError(str(e))
|
||||
|
||||
return asr_text
|
||||
|
|
|
@ -117,7 +117,7 @@ class SageMakerEmbeddingModel(TextEmbeddingModel):
|
|||
return TextEmbeddingResult(embeddings=all_embeddings, usage=usage, model=model)
|
||||
|
||||
except Exception as e:
|
||||
logger.exception(f"Exception {e}, line : {line}")
|
||||
logger.exception(f"Failed to invoke text embedding model, model: {model}, line: {line}")
|
||||
|
||||
def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int:
|
||||
"""
|
||||
|
|
|
@ -0,0 +1,84 @@
|
|||
model: OpenGVLab/InternVL2-26B
|
||||
label:
|
||||
en_US: OpenGVLab/InternVL2-26B
|
||||
model_type: llm
|
||||
features:
|
||||
- vision
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 32768
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
type: float
|
||||
default: 0.3
|
||||
min: 0.0
|
||||
max: 2.0
|
||||
help:
|
||||
zh_Hans: 用于控制随机性和多样性的程度。具体来说,temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值,使得更多的低概率词被选择,生成结果更加多样化;而较低的temperature值则会增强概率分布的峰值,使得高概率词更容易被选择,生成结果更加确定。
|
||||
en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain.
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
type: int
|
||||
default: 2000
|
||||
min: 1
|
||||
max: 2000
|
||||
help:
|
||||
zh_Hans: 用于指定模型在生成内容时token的最大数量,它定义了生成的上限,但不保证每次都会生成到这个数量。
|
||||
en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time.
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
type: float
|
||||
default: 0.8
|
||||
min: 0.1
|
||||
max: 0.9
|
||||
help:
|
||||
zh_Hans: 生成过程中核采样方法概率阈值,例如,取值为0.8时,仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为(0,1.0),取值越大,生成的随机性越高;取值越低,生成的确定性越高。
|
||||
en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated.
|
||||
- name: top_k
|
||||
type: int
|
||||
min: 0
|
||||
max: 99
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
help:
|
||||
zh_Hans: 生成时,采样候选集的大小。例如,取值为50时,仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大,生成的随机性越高;取值越小,生成的确定性越高。
|
||||
en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated.
|
||||
- name: seed
|
||||
required: false
|
||||
type: int
|
||||
default: 1234
|
||||
label:
|
||||
zh_Hans: 随机种子
|
||||
en_US: Random seed
|
||||
help:
|
||||
zh_Hans: 生成时使用的随机数种子,用户控制模型生成内容的随机性。支持无符号64位整数,默认值为 1234。在使用seed时,模型将尽可能生成相同或相似的结果,但目前不保证每次生成的结果完全相同。
|
||||
en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time.
|
||||
- name: repetition_penalty
|
||||
required: false
|
||||
type: float
|
||||
default: 1.1
|
||||
label:
|
||||
zh_Hans: 重复惩罚
|
||||
en_US: Repetition penalty
|
||||
help:
|
||||
zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
|
||||
en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
|
||||
- name: response_format
|
||||
label:
|
||||
zh_Hans: 回复格式
|
||||
en_US: Response Format
|
||||
type: string
|
||||
help:
|
||||
zh_Hans: 指定模型必须输出的格式
|
||||
en_US: specifying the format that the model must output
|
||||
required: false
|
||||
options:
|
||||
- text
|
||||
- json_object
|
||||
pricing:
|
||||
input: '21'
|
||||
output: '21'
|
||||
unit: '0.000001'
|
||||
currency: RMB
|
|
@ -0,0 +1,84 @@
|
|||
model: Pro/OpenGVLab/InternVL2-8B
|
||||
label:
|
||||
en_US: Pro/OpenGVLab/InternVL2-8B
|
||||
model_type: llm
|
||||
features:
|
||||
- vision
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 32768
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
type: float
|
||||
default: 0.3
|
||||
min: 0.0
|
||||
max: 2.0
|
||||
help:
|
||||
zh_Hans: 用于控制随机性和多样性的程度。具体来说,temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值,使得更多的低概率词被选择,生成结果更加多样化;而较低的temperature值则会增强概率分布的峰值,使得高概率词更容易被选择,生成结果更加确定。
|
||||
en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain.
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
type: int
|
||||
default: 2000
|
||||
min: 1
|
||||
max: 2000
|
||||
help:
|
||||
zh_Hans: 用于指定模型在生成内容时token的最大数量,它定义了生成的上限,但不保证每次都会生成到这个数量。
|
||||
en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time.
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
type: float
|
||||
default: 0.8
|
||||
min: 0.1
|
||||
max: 0.9
|
||||
help:
|
||||
zh_Hans: 生成过程中核采样方法概率阈值,例如,取值为0.8时,仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为(0,1.0),取值越大,生成的随机性越高;取值越低,生成的确定性越高。
|
||||
en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated.
|
||||
- name: top_k
|
||||
type: int
|
||||
min: 0
|
||||
max: 99
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
help:
|
||||
zh_Hans: 生成时,采样候选集的大小。例如,取值为50时,仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大,生成的随机性越高;取值越小,生成的确定性越高。
|
||||
en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated.
|
||||
- name: seed
|
||||
required: false
|
||||
type: int
|
||||
default: 1234
|
||||
label:
|
||||
zh_Hans: 随机种子
|
||||
en_US: Random seed
|
||||
help:
|
||||
zh_Hans: 生成时使用的随机数种子,用户控制模型生成内容的随机性。支持无符号64位整数,默认值为 1234。在使用seed时,模型将尽可能生成相同或相似的结果,但目前不保证每次生成的结果完全相同。
|
||||
en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time.
|
||||
- name: repetition_penalty
|
||||
required: false
|
||||
type: float
|
||||
default: 1.1
|
||||
label:
|
||||
zh_Hans: 重复惩罚
|
||||
en_US: Repetition penalty
|
||||
help:
|
||||
zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
|
||||
en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
|
||||
- name: response_format
|
||||
label:
|
||||
zh_Hans: 回复格式
|
||||
en_US: Response Format
|
||||
type: string
|
||||
help:
|
||||
zh_Hans: 指定模型必须输出的格式
|
||||
en_US: specifying the format that the model must output
|
||||
required: false
|
||||
options:
|
||||
- text
|
||||
- json_object
|
||||
pricing:
|
||||
input: '21'
|
||||
output: '21'
|
||||
unit: '0.000001'
|
||||
currency: RMB
|
|
@ -1,16 +1,18 @@
|
|||
- Tencent/Hunyuan-A52B-Instruct
|
||||
- Qwen/Qwen2.5-72B-Instruct
|
||||
- Qwen/Qwen2.5-32B-Instruct
|
||||
- Qwen/Qwen2.5-14B-Instruct
|
||||
- Qwen/Qwen2.5-7B-Instruct
|
||||
- Qwen/Qwen2.5-Coder-32B-Instruct
|
||||
- Qwen/Qwen2.5-Coder-7B-Instruct
|
||||
- Qwen/Qwen2.5-Math-72B-Instruct
|
||||
- Qwen/Qwen2-72B-Instruct
|
||||
- Qwen/Qwen2-57B-A14B-Instruct
|
||||
- Qwen/Qwen2-7B-Instruct
|
||||
- Qwen/Qwen2-VL-72B-Instruct
|
||||
- Qwen/Qwen2-1.5B-Instruct
|
||||
- Pro/Qwen/Qwen2-VL-7B-Instruct
|
||||
- OpenGVLab/InternVL2-Llama3-76B
|
||||
- OpenGVLab/InternVL2-26B
|
||||
- Pro/OpenGVLab/InternVL2-8B
|
||||
- deepseek-ai/DeepSeek-V2.5
|
||||
- deepseek-ai/DeepSeek-V2-Chat
|
||||
- deepseek-ai/DeepSeek-Coder-V2-Instruct
|
||||
- THUDM/glm-4-9b-chat
|
||||
- 01-ai/Yi-1.5-34B-Chat-16K
|
||||
- 01-ai/Yi-1.5-9B-Chat-16K
|
||||
|
@ -20,9 +22,6 @@
|
|||
- meta-llama/Meta-Llama-3.1-405B-Instruct
|
||||
- meta-llama/Meta-Llama-3.1-70B-Instruct
|
||||
- meta-llama/Meta-Llama-3.1-8B-Instruct
|
||||
- meta-llama/Meta-Llama-3-70B-Instruct
|
||||
- meta-llama/Meta-Llama-3-8B-Instruct
|
||||
- google/gemma-2-27b-it
|
||||
- google/gemma-2-9b-it
|
||||
- mistralai/Mistral-7B-Instruct-v0.2
|
||||
- mistralai/Mixtral-8x7B-Instruct-v0.1
|
||||
- deepseek-ai/DeepSeek-V2-Chat
|
||||
|
|
|
@ -37,3 +37,4 @@ pricing:
|
|||
output: '1.33'
|
||||
unit: '0.000001'
|
||||
currency: RMB
|
||||
deprecated: true
|
||||
|
|
|
@ -37,3 +37,4 @@ pricing:
|
|||
output: '1.33'
|
||||
unit: '0.000001'
|
||||
currency: RMB
|
||||
deprecated: true
|
||||
|
|
|
@ -4,6 +4,8 @@ label:
|
|||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 32768
|
||||
|
@ -32,6 +34,18 @@ parameter_rules:
|
|||
required: false
|
||||
- name: frequency_penalty
|
||||
use_template: frequency_penalty
|
||||
- name: response_format
|
||||
label:
|
||||
zh_Hans: 回复格式
|
||||
en_US: Response Format
|
||||
type: string
|
||||
help:
|
||||
zh_Hans: 指定模型必须输出的格式
|
||||
en_US: specifying the format that the model must output
|
||||
required: false
|
||||
options:
|
||||
- text
|
||||
- json_object
|
||||
pricing:
|
||||
input: '1.33'
|
||||
output: '1.33'
|
||||
|
|
|
@ -32,6 +32,18 @@ parameter_rules:
|
|||
required: false
|
||||
- name: frequency_penalty
|
||||
use_template: frequency_penalty
|
||||
- name: response_format
|
||||
label:
|
||||
zh_Hans: 回复格式
|
||||
en_US: Response Format
|
||||
type: string
|
||||
help:
|
||||
zh_Hans: 指定模型必须输出的格式
|
||||
en_US: specifying the format that the model must output
|
||||
required: false
|
||||
options:
|
||||
- text
|
||||
- json_object
|
||||
pricing:
|
||||
input: '1.26'
|
||||
output: '1.26'
|
||||
|
|
|
@ -32,6 +32,18 @@ parameter_rules:
|
|||
required: false
|
||||
- name: frequency_penalty
|
||||
use_template: frequency_penalty
|
||||
- name: response_format
|
||||
label:
|
||||
zh_Hans: 回复格式
|
||||
en_US: Response Format
|
||||
type: string
|
||||
help:
|
||||
zh_Hans: 指定模型必须输出的格式
|
||||
en_US: specifying the format that the model must output
|
||||
required: false
|
||||
options:
|
||||
- text
|
||||
- json_object
|
||||
pricing:
|
||||
input: '0'
|
||||
output: '0'
|
||||
|
|
|
@ -32,6 +32,18 @@ parameter_rules:
|
|||
required: false
|
||||
- name: frequency_penalty
|
||||
use_template: frequency_penalty
|
||||
- name: response_format
|
||||
label:
|
||||
zh_Hans: 回复格式
|
||||
en_US: Response Format
|
||||
type: string
|
||||
help:
|
||||
zh_Hans: 指定模型必须输出的格式
|
||||
en_US: specifying the format that the model must output
|
||||
required: false
|
||||
options:
|
||||
- text
|
||||
- json_object
|
||||
pricing:
|
||||
input: '0'
|
||||
output: '0'
|
||||
|
|
|
@ -0,0 +1,84 @@
|
|||
model: Tencent/Hunyuan-A52B-Instruct
|
||||
label:
|
||||
en_US: Tencent/Hunyuan-A52B-Instruct
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 32768
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
type: float
|
||||
default: 0.3
|
||||
min: 0.0
|
||||
max: 2.0
|
||||
help:
|
||||
zh_Hans: 用于控制随机性和多样性的程度。具体来说,temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值,使得更多的低概率词被选择,生成结果更加多样化;而较低的temperature值则会增强概率分布的峰值,使得高概率词更容易被选择,生成结果更加确定。
|
||||
en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain.
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
type: int
|
||||
default: 2000
|
||||
min: 1
|
||||
max: 2000
|
||||
help:
|
||||
zh_Hans: 用于指定模型在生成内容时token的最大数量,它定义了生成的上限,但不保证每次都会生成到这个数量。
|
||||
en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time.
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
type: float
|
||||
default: 0.8
|
||||
min: 0.1
|
||||
max: 0.9
|
||||
help:
|
||||
zh_Hans: 生成过程中核采样方法概率阈值,例如,取值为0.8时,仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为(0,1.0),取值越大,生成的随机性越高;取值越低,生成的确定性越高。
|
||||
en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated.
|
||||
- name: top_k
|
||||
type: int
|
||||
min: 0
|
||||
max: 99
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
help:
|
||||
zh_Hans: 生成时,采样候选集的大小。例如,取值为50时,仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大,生成的随机性越高;取值越小,生成的确定性越高。
|
||||
en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated.
|
||||
- name: seed
|
||||
required: false
|
||||
type: int
|
||||
default: 1234
|
||||
label:
|
||||
zh_Hans: 随机种子
|
||||
en_US: Random seed
|
||||
help:
|
||||
zh_Hans: 生成时使用的随机数种子,用户控制模型生成内容的随机性。支持无符号64位整数,默认值为 1234。在使用seed时,模型将尽可能生成相同或相似的结果,但目前不保证每次生成的结果完全相同。
|
||||
en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time.
|
||||
- name: repetition_penalty
|
||||
required: false
|
||||
type: float
|
||||
default: 1.1
|
||||
label:
|
||||
zh_Hans: 重复惩罚
|
||||
en_US: Repetition penalty
|
||||
help:
|
||||
zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
|
||||
en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
|
||||
- name: response_format
|
||||
label:
|
||||
zh_Hans: 回复格式
|
||||
en_US: Response Format
|
||||
type: string
|
||||
help:
|
||||
zh_Hans: 指定模型必须输出的格式
|
||||
en_US: specifying the format that the model must output
|
||||
required: false
|
||||
options:
|
||||
- text
|
||||
- json_object
|
||||
pricing:
|
||||
input: '21'
|
||||
output: '21'
|
||||
unit: '0.000001'
|
||||
currency: RMB
|
|
@ -32,6 +32,18 @@ parameter_rules:
|
|||
required: false
|
||||
- name: frequency_penalty
|
||||
use_template: frequency_penalty
|
||||
- name: response_format
|
||||
label:
|
||||
zh_Hans: 回复格式
|
||||
en_US: Response Format
|
||||
type: string
|
||||
help:
|
||||
zh_Hans: 指定模型必须输出的格式
|
||||
en_US: specifying the format that the model must output
|
||||
required: false
|
||||
options:
|
||||
- text
|
||||
- json_object
|
||||
pricing:
|
||||
input: '1'
|
||||
output: '1'
|
||||
|
|
|
@ -32,6 +32,18 @@ parameter_rules:
|
|||
required: false
|
||||
- name: frequency_penalty
|
||||
use_template: frequency_penalty
|
||||
- name: response_format
|
||||
label:
|
||||
zh_Hans: 回复格式
|
||||
en_US: Response Format
|
||||
type: string
|
||||
help:
|
||||
zh_Hans: 指定模型必须输出的格式
|
||||
en_US: specifying the format that the model must output
|
||||
required: false
|
||||
options:
|
||||
- text
|
||||
- json_object
|
||||
pricing:
|
||||
input: '0'
|
||||
output: '0'
|
||||
|
|
|
@ -0,0 +1,84 @@
|
|||
model: OpenGVLab/InternVL2-Llama3-76B
|
||||
label:
|
||||
en_US: OpenGVLab/InternVL2-Llama3-76B
|
||||
model_type: llm
|
||||
features:
|
||||
- vision
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 8192
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
type: float
|
||||
default: 0.3
|
||||
min: 0.0
|
||||
max: 2.0
|
||||
help:
|
||||
zh_Hans: 用于控制随机性和多样性的程度。具体来说,temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值,使得更多的低概率词被选择,生成结果更加多样化;而较低的temperature值则会增强概率分布的峰值,使得高概率词更容易被选择,生成结果更加确定。
|
||||
en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain.
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
type: int
|
||||
default: 2000
|
||||
min: 1
|
||||
max: 2000
|
||||
help:
|
||||
zh_Hans: 用于指定模型在生成内容时token的最大数量,它定义了生成的上限,但不保证每次都会生成到这个数量。
|
||||
en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time.
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
type: float
|
||||
default: 0.8
|
||||
min: 0.1
|
||||
max: 0.9
|
||||
help:
|
||||
zh_Hans: 生成过程中核采样方法概率阈值,例如,取值为0.8时,仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为(0,1.0),取值越大,生成的随机性越高;取值越低,生成的确定性越高。
|
||||
en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated.
|
||||
- name: top_k
|
||||
type: int
|
||||
min: 0
|
||||
max: 99
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
help:
|
||||
zh_Hans: 生成时,采样候选集的大小。例如,取值为50时,仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大,生成的随机性越高;取值越小,生成的确定性越高。
|
||||
en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated.
|
||||
- name: seed
|
||||
required: false
|
||||
type: int
|
||||
default: 1234
|
||||
label:
|
||||
zh_Hans: 随机种子
|
||||
en_US: Random seed
|
||||
help:
|
||||
zh_Hans: 生成时使用的随机数种子,用户控制模型生成内容的随机性。支持无符号64位整数,默认值为 1234。在使用seed时,模型将尽可能生成相同或相似的结果,但目前不保证每次生成的结果完全相同。
|
||||
en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time.
|
||||
- name: repetition_penalty
|
||||
required: false
|
||||
type: float
|
||||
default: 1.1
|
||||
label:
|
||||
zh_Hans: 重复惩罚
|
||||
en_US: Repetition penalty
|
||||
help:
|
||||
zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
|
||||
en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
|
||||
- name: response_format
|
||||
label:
|
||||
zh_Hans: 回复格式
|
||||
en_US: Response Format
|
||||
type: string
|
||||
help:
|
||||
zh_Hans: 指定模型必须输出的格式
|
||||
en_US: specifying the format that the model must output
|
||||
required: false
|
||||
options:
|
||||
- text
|
||||
- json_object
|
||||
pricing:
|
||||
input: '21'
|
||||
output: '21'
|
||||
unit: '0.000001'
|
||||
currency: RMB
|
|
@ -29,6 +29,9 @@ class SiliconflowLargeLanguageModel(OAIAPICompatLargeLanguageModel):
|
|||
user: Optional[str] = None,
|
||||
) -> Union[LLMResult, Generator]:
|
||||
self._add_custom_parameters(credentials)
|
||||
# {"response_format": "json_object"} need convert to {"response_format": {"type": "json_object"}}
|
||||
if "response_format" in model_parameters:
|
||||
model_parameters["response_format"] = {"type": model_parameters.get("response_format")}
|
||||
return super()._invoke(model, credentials, prompt_messages, model_parameters, tools, stop, stream)
|
||||
|
||||
def validate_credentials(self, model: str, credentials: dict) -> None:
|
||||
|
|
|
@ -37,3 +37,4 @@ pricing:
|
|||
output: '4.13'
|
||||
unit: '0.000001'
|
||||
currency: RMB
|
||||
deprecated: true
|
||||
|
|
|
@ -37,3 +37,4 @@ pricing:
|
|||
output: '0'
|
||||
unit: '0.000001'
|
||||
currency: RMB
|
||||
deprecated: true
|
||||
|
|
|
@ -32,6 +32,18 @@ parameter_rules:
|
|||
required: false
|
||||
- name: frequency_penalty
|
||||
use_template: frequency_penalty
|
||||
- name: response_format
|
||||
label:
|
||||
zh_Hans: 回复格式
|
||||
en_US: Response Format
|
||||
type: string
|
||||
help:
|
||||
zh_Hans: 指定模型必须输出的格式
|
||||
en_US: specifying the format that the model must output
|
||||
required: false
|
||||
options:
|
||||
- text
|
||||
- json_object
|
||||
pricing:
|
||||
input: '21'
|
||||
output: '21'
|
||||
|
|
|
@ -6,7 +6,7 @@ features:
|
|||
- agent-thought
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 32768
|
||||
context_size: 8192
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
|
@ -32,6 +32,18 @@ parameter_rules:
|
|||
required: false
|
||||
- name: frequency_penalty
|
||||
use_template: frequency_penalty
|
||||
- name: response_format
|
||||
label:
|
||||
zh_Hans: 回复格式
|
||||
en_US: Response Format
|
||||
type: string
|
||||
help:
|
||||
zh_Hans: 指定模型必须输出的格式
|
||||
en_US: specifying the format that the model must output
|
||||
required: false
|
||||
options:
|
||||
- text
|
||||
- json_object
|
||||
pricing:
|
||||
input: '4.13'
|
||||
output: '4.13'
|
||||
|
|
|
@ -32,6 +32,18 @@ parameter_rules:
|
|||
required: false
|
||||
- name: frequency_penalty
|
||||
use_template: frequency_penalty
|
||||
- name: response_format
|
||||
label:
|
||||
zh_Hans: 回复格式
|
||||
en_US: Response Format
|
||||
type: string
|
||||
help:
|
||||
zh_Hans: 指定模型必须输出的格式
|
||||
en_US: specifying the format that the model must output
|
||||
required: false
|
||||
options:
|
||||
- text
|
||||
- json_object
|
||||
pricing:
|
||||
input: '0'
|
||||
output: '0'
|
||||
|
|
|
@ -37,3 +37,4 @@ pricing:
|
|||
output: '1.26'
|
||||
unit: '0.000001'
|
||||
currency: RMB
|
||||
deprecated: true
|
||||
|
|
|
@ -37,3 +37,4 @@ pricing:
|
|||
output: '4.13'
|
||||
unit: '0.000001'
|
||||
currency: RMB
|
||||
deprecated: true
|
||||
|
|
|
@ -37,3 +37,4 @@ pricing:
|
|||
output: '0'
|
||||
unit: '0.000001'
|
||||
currency: RMB
|
||||
deprecated: true
|
||||
|
|
|
@ -0,0 +1,84 @@
|
|||
model: Qwen/Qwen2-VL-72B-Instruct
|
||||
label:
|
||||
en_US: Qwen/Qwen2-VL-72B-Instruct
|
||||
model_type: llm
|
||||
features:
|
||||
- vision
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 32768
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
type: float
|
||||
default: 0.3
|
||||
min: 0.0
|
||||
max: 2.0
|
||||
help:
|
||||
zh_Hans: 用于控制随机性和多样性的程度。具体来说,temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值,使得更多的低概率词被选择,生成结果更加多样化;而较低的temperature值则会增强概率分布的峰值,使得高概率词更容易被选择,生成结果更加确定。
|
||||
en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain.
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
type: int
|
||||
default: 2000
|
||||
min: 1
|
||||
max: 2000
|
||||
help:
|
||||
zh_Hans: 用于指定模型在生成内容时token的最大数量,它定义了生成的上限,但不保证每次都会生成到这个数量。
|
||||
en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time.
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
type: float
|
||||
default: 0.8
|
||||
min: 0.1
|
||||
max: 0.9
|
||||
help:
|
||||
zh_Hans: 生成过程中核采样方法概率阈值,例如,取值为0.8时,仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为(0,1.0),取值越大,生成的随机性越高;取值越低,生成的确定性越高。
|
||||
en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated.
|
||||
- name: top_k
|
||||
type: int
|
||||
min: 0
|
||||
max: 99
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
help:
|
||||
zh_Hans: 生成时,采样候选集的大小。例如,取值为50时,仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大,生成的随机性越高;取值越小,生成的确定性越高。
|
||||
en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated.
|
||||
- name: seed
|
||||
required: false
|
||||
type: int
|
||||
default: 1234
|
||||
label:
|
||||
zh_Hans: 随机种子
|
||||
en_US: Random seed
|
||||
help:
|
||||
zh_Hans: 生成时使用的随机数种子,用户控制模型生成内容的随机性。支持无符号64位整数,默认值为 1234。在使用seed时,模型将尽可能生成相同或相似的结果,但目前不保证每次生成的结果完全相同。
|
||||
en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time.
|
||||
- name: repetition_penalty
|
||||
required: false
|
||||
type: float
|
||||
default: 1.1
|
||||
label:
|
||||
zh_Hans: 重复惩罚
|
||||
en_US: Repetition penalty
|
||||
help:
|
||||
zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
|
||||
en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
|
||||
- name: response_format
|
||||
label:
|
||||
zh_Hans: 回复格式
|
||||
en_US: Response Format
|
||||
type: string
|
||||
help:
|
||||
zh_Hans: 指定模型必须输出的格式
|
||||
en_US: specifying the format that the model must output
|
||||
required: false
|
||||
options:
|
||||
- text
|
||||
- json_object
|
||||
pricing:
|
||||
input: '21'
|
||||
output: '21'
|
||||
unit: '0.000001'
|
||||
currency: RMB
|
|
@ -0,0 +1,84 @@
|
|||
model: Pro/Qwen/Qwen2-VL-7B-Instruct
|
||||
label:
|
||||
en_US: Pro/Qwen/Qwen2-VL-7B-Instruct
|
||||
model_type: llm
|
||||
features:
|
||||
- vision
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 32768
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
type: float
|
||||
default: 0.3
|
||||
min: 0.0
|
||||
max: 2.0
|
||||
help:
|
||||
zh_Hans: 用于控制随机性和多样性的程度。具体来说,temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值,使得更多的低概率词被选择,生成结果更加多样化;而较低的temperature值则会增强概率分布的峰值,使得高概率词更容易被选择,生成结果更加确定。
|
||||
en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain.
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
type: int
|
||||
default: 2000
|
||||
min: 1
|
||||
max: 2000
|
||||
help:
|
||||
zh_Hans: 用于指定模型在生成内容时token的最大数量,它定义了生成的上限,但不保证每次都会生成到这个数量。
|
||||
en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time.
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
type: float
|
||||
default: 0.8
|
||||
min: 0.1
|
||||
max: 0.9
|
||||
help:
|
||||
zh_Hans: 生成过程中核采样方法概率阈值,例如,取值为0.8时,仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为(0,1.0),取值越大,生成的随机性越高;取值越低,生成的确定性越高。
|
||||
en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated.
|
||||
- name: top_k
|
||||
type: int
|
||||
min: 0
|
||||
max: 99
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
help:
|
||||
zh_Hans: 生成时,采样候选集的大小。例如,取值为50时,仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大,生成的随机性越高;取值越小,生成的确定性越高。
|
||||
en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated.
|
||||
- name: seed
|
||||
required: false
|
||||
type: int
|
||||
default: 1234
|
||||
label:
|
||||
zh_Hans: 随机种子
|
||||
en_US: Random seed
|
||||
help:
|
||||
zh_Hans: 生成时使用的随机数种子,用户控制模型生成内容的随机性。支持无符号64位整数,默认值为 1234。在使用seed时,模型将尽可能生成相同或相似的结果,但目前不保证每次生成的结果完全相同。
|
||||
en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time.
|
||||
- name: repetition_penalty
|
||||
required: false
|
||||
type: float
|
||||
default: 1.1
|
||||
label:
|
||||
zh_Hans: 重复惩罚
|
||||
en_US: Repetition penalty
|
||||
help:
|
||||
zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
|
||||
en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
|
||||
- name: response_format
|
||||
label:
|
||||
zh_Hans: 回复格式
|
||||
en_US: Response Format
|
||||
type: string
|
||||
help:
|
||||
zh_Hans: 指定模型必须输出的格式
|
||||
en_US: specifying the format that the model must output
|
||||
required: false
|
||||
options:
|
||||
- text
|
||||
- json_object
|
||||
pricing:
|
||||
input: '21'
|
||||
output: '21'
|
||||
unit: '0.000001'
|
||||
currency: RMB
|
|
@ -32,6 +32,18 @@ parameter_rules:
|
|||
required: false
|
||||
- name: frequency_penalty
|
||||
use_template: frequency_penalty
|
||||
- name: response_format
|
||||
label:
|
||||
zh_Hans: 回复格式
|
||||
en_US: Response Format
|
||||
type: string
|
||||
help:
|
||||
zh_Hans: 指定模型必须输出的格式
|
||||
en_US: specifying the format that the model must output
|
||||
required: false
|
||||
options:
|
||||
- text
|
||||
- json_object
|
||||
pricing:
|
||||
input: '0.7'
|
||||
output: '0.7'
|
||||
|
|
|
@ -32,6 +32,18 @@ parameter_rules:
|
|||
required: false
|
||||
- name: frequency_penalty
|
||||
use_template: frequency_penalty
|
||||
- name: response_format
|
||||
label:
|
||||
zh_Hans: 回复格式
|
||||
en_US: Response Format
|
||||
type: string
|
||||
help:
|
||||
zh_Hans: 指定模型必须输出的格式
|
||||
en_US: specifying the format that the model must output
|
||||
required: false
|
||||
options:
|
||||
- text
|
||||
- json_object
|
||||
pricing:
|
||||
input: '1.26'
|
||||
output: '1.26'
|
||||
|
|
|
@ -32,6 +32,18 @@ parameter_rules:
|
|||
required: false
|
||||
- name: frequency_penalty
|
||||
use_template: frequency_penalty
|
||||
- name: response_format
|
||||
label:
|
||||
zh_Hans: 回复格式
|
||||
en_US: Response Format
|
||||
type: string
|
||||
help:
|
||||
zh_Hans: 指定模型必须输出的格式
|
||||
en_US: specifying the format that the model must output
|
||||
required: false
|
||||
options:
|
||||
- text
|
||||
- json_object
|
||||
pricing:
|
||||
input: '4.13'
|
||||
output: '4.13'
|
||||
|
|
|
@ -32,6 +32,18 @@ parameter_rules:
|
|||
required: false
|
||||
- name: frequency_penalty
|
||||
use_template: frequency_penalty
|
||||
- name: response_format
|
||||
label:
|
||||
zh_Hans: 回复格式
|
||||
en_US: Response Format
|
||||
type: string
|
||||
help:
|
||||
zh_Hans: 指定模型必须输出的格式
|
||||
en_US: specifying the format that the model must output
|
||||
required: false
|
||||
options:
|
||||
- text
|
||||
- json_object
|
||||
pricing:
|
||||
input: '0'
|
||||
output: '0'
|
||||
|
|
|
@ -0,0 +1,84 @@
|
|||
model: Qwen/Qwen2.5-Coder-32B-Instruct
|
||||
label:
|
||||
en_US: Qwen/Qwen2.5-Coder-32B-Instruct
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 32768
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
type: float
|
||||
default: 0.3
|
||||
min: 0.0
|
||||
max: 2.0
|
||||
help:
|
||||
zh_Hans: 用于控制随机性和多样性的程度。具体来说,temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值,使得更多的低概率词被选择,生成结果更加多样化;而较低的temperature值则会增强概率分布的峰值,使得高概率词更容易被选择,生成结果更加确定。
|
||||
en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain.
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
type: int
|
||||
default: 8192
|
||||
min: 1
|
||||
max: 8192
|
||||
help:
|
||||
zh_Hans: 用于指定模型在生成内容时token的最大数量,它定义了生成的上限,但不保证每次都会生成到这个数量。
|
||||
en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time.
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
type: float
|
||||
default: 0.8
|
||||
min: 0.1
|
||||
max: 0.9
|
||||
help:
|
||||
zh_Hans: 生成过程中核采样方法概率阈值,例如,取值为0.8时,仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为(0,1.0),取值越大,生成的随机性越高;取值越低,生成的确定性越高。
|
||||
en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated.
|
||||
- name: top_k
|
||||
type: int
|
||||
min: 0
|
||||
max: 99
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
help:
|
||||
zh_Hans: 生成时,采样候选集的大小。例如,取值为50时,仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大,生成的随机性越高;取值越小,生成的确定性越高。
|
||||
en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated.
|
||||
- name: seed
|
||||
required: false
|
||||
type: int
|
||||
default: 1234
|
||||
label:
|
||||
zh_Hans: 随机种子
|
||||
en_US: Random seed
|
||||
help:
|
||||
zh_Hans: 生成时使用的随机数种子,用户控制模型生成内容的随机性。支持无符号64位整数,默认值为 1234。在使用seed时,模型将尽可能生成相同或相似的结果,但目前不保证每次生成的结果完全相同。
|
||||
en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time.
|
||||
- name: repetition_penalty
|
||||
required: false
|
||||
type: float
|
||||
default: 1.1
|
||||
label:
|
||||
zh_Hans: 重复惩罚
|
||||
en_US: Repetition penalty
|
||||
help:
|
||||
zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
|
||||
en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
|
||||
- name: response_format
|
||||
label:
|
||||
zh_Hans: 回复格式
|
||||
en_US: Response Format
|
||||
type: string
|
||||
help:
|
||||
zh_Hans: 指定模型必须输出的格式
|
||||
en_US: specifying the format that the model must output
|
||||
required: false
|
||||
options:
|
||||
- text
|
||||
- json_object
|
||||
pricing:
|
||||
input: '1.26'
|
||||
output: '1.26'
|
||||
unit: '0.000001'
|
||||
currency: RMB
|
|
@ -66,7 +66,17 @@ parameter_rules:
|
|||
zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
|
||||
en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
|
||||
- name: response_format
|
||||
use_template: response_format
|
||||
label:
|
||||
zh_Hans: 回复格式
|
||||
en_US: Response Format
|
||||
type: string
|
||||
help:
|
||||
zh_Hans: 指定模型必须输出的格式
|
||||
en_US: specifying the format that the model must output
|
||||
required: false
|
||||
options:
|
||||
- text
|
||||
- json_object
|
||||
pricing:
|
||||
input: '0'
|
||||
output: '0'
|
||||
|
|
|
@ -66,7 +66,17 @@ parameter_rules:
|
|||
zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
|
||||
en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
|
||||
- name: response_format
|
||||
use_template: response_format
|
||||
label:
|
||||
zh_Hans: 回复格式
|
||||
en_US: Response Format
|
||||
type: string
|
||||
help:
|
||||
zh_Hans: 指定模型必须输出的格式
|
||||
en_US: specifying the format that the model must output
|
||||
required: false
|
||||
options:
|
||||
- text
|
||||
- json_object
|
||||
pricing:
|
||||
input: '4.13'
|
||||
output: '4.13'
|
||||
|
|
|
@ -0,0 +1,5 @@
|
|||
model: FunAudioLLM/SenseVoiceSmall
|
||||
model_type: speech2text
|
||||
model_properties:
|
||||
file_upload_limit: 1
|
||||
supported_file_extensions: mp3,wav
|
|
@ -3,3 +3,4 @@ model_type: speech2text
|
|||
model_properties:
|
||||
file_upload_limit: 1
|
||||
supported_file_extensions: mp3,wav
|
||||
deprecated: true
|
||||
|
|
|
@ -1,5 +1,6 @@
|
|||
import json
|
||||
import random
|
||||
from collections import UserDict
|
||||
from datetime import datetime
|
||||
|
||||
|
||||
|
@ -10,9 +11,9 @@ class ChatRole:
|
|||
FUNCTION = "function"
|
||||
|
||||
|
||||
class _Dict(dict):
|
||||
__setattr__ = dict.__setitem__
|
||||
__getattr__ = dict.__getitem__
|
||||
class _Dict(UserDict):
|
||||
__setattr__ = UserDict.__setitem__
|
||||
__getattr__ = UserDict.__getitem__
|
||||
|
||||
def __missing__(self, key):
|
||||
return None
|
||||
|
|
|
@ -126,6 +126,6 @@ class OutputModeration(BaseModel):
|
|||
result: ModerationOutputsResult = moderation_factory.moderation_for_outputs(moderation_buffer)
|
||||
return result
|
||||
except Exception as e:
|
||||
logger.exception("Moderation Output error: %s", e)
|
||||
logger.exception(f"Moderation Output error, app_id: {app_id}")
|
||||
|
||||
return None
|
||||
|
|
|
@ -711,7 +711,7 @@ class TraceQueueManager:
|
|||
trace_task.app_id = self.app_id
|
||||
trace_manager_queue.put(trace_task)
|
||||
except Exception as e:
|
||||
logging.exception(f"Error adding trace task: {e}")
|
||||
logging.exception(f"Error adding trace task, trace_type {trace_task.trace_type}")
|
||||
finally:
|
||||
self.start_timer()
|
||||
|
||||
|
@ -730,7 +730,7 @@ class TraceQueueManager:
|
|||
if tasks:
|
||||
self.send_to_celery(tasks)
|
||||
except Exception as e:
|
||||
logging.exception(f"Error processing trace tasks: {e}")
|
||||
logging.exception("Error processing trace tasks")
|
||||
|
||||
def start_timer(self):
|
||||
global trace_manager_timer
|
||||
|
|
|
@ -242,7 +242,7 @@ class CouchbaseVector(BaseVector):
|
|||
try:
|
||||
self._cluster.query(query, named_parameters={"doc_ids": ids}).execute()
|
||||
except Exception as e:
|
||||
logger.exception(e)
|
||||
logger.exception(f"Failed to delete documents, ids: {ids}")
|
||||
|
||||
def delete_by_document_id(self, document_id: str):
|
||||
query = f"""
|
||||
|
|
|
@ -178,6 +178,7 @@ class ElasticSearchVector(BaseVector):
|
|||
Field.VECTOR.value: { # Make sure the dimension is correct here
|
||||
"type": "dense_vector",
|
||||
"dims": dim,
|
||||
"index": True,
|
||||
"similarity": "cosine",
|
||||
},
|
||||
Field.METADATA_KEY.value: {
|
||||
|
|
|
@ -79,7 +79,7 @@ class LindormVectorStore(BaseVector):
|
|||
existing_docs = self._client.mget(index=self._collection_name, body={"ids": batch_ids}, _source=False)
|
||||
return {doc["_id"] for doc in existing_docs["docs"] if doc["found"]}
|
||||
except Exception as e:
|
||||
logger.exception(f"Error fetching batch {batch_ids}: {e}")
|
||||
logger.exception(f"Error fetching batch {batch_ids}")
|
||||
return set()
|
||||
|
||||
@retry(stop=stop_after_attempt(3), wait=wait_fixed(60))
|
||||
|
@ -96,7 +96,7 @@ class LindormVectorStore(BaseVector):
|
|||
)
|
||||
return {doc["_id"] for doc in existing_docs["docs"] if doc["found"]}
|
||||
except Exception as e:
|
||||
logger.exception(f"Error fetching batch {batch_ids}: {e}")
|
||||
logger.exception(f"Error fetching batch ids: {batch_ids}")
|
||||
return set()
|
||||
|
||||
if ids is None:
|
||||
|
@ -177,7 +177,7 @@ class LindormVectorStore(BaseVector):
|
|||
else:
|
||||
logger.warning(f"Index '{self._collection_name}' does not exist. No deletion performed.")
|
||||
except Exception as e:
|
||||
logger.exception(f"Error occurred while deleting the index: {e}")
|
||||
logger.exception(f"Error occurred while deleting the index: {self._collection_name}")
|
||||
raise e
|
||||
|
||||
def text_exists(self, id: str) -> bool:
|
||||
|
@ -201,7 +201,7 @@ class LindormVectorStore(BaseVector):
|
|||
try:
|
||||
response = self._client.search(index=self._collection_name, body=query)
|
||||
except Exception as e:
|
||||
logger.exception(f"Error executing search: {e}")
|
||||
logger.exception(f"Error executing vector search, query: {query}")
|
||||
raise
|
||||
|
||||
docs_and_scores = []
|
||||
|
|
|
@ -142,7 +142,7 @@ class MyScaleVector(BaseVector):
|
|||
for r in self._client.query(sql).named_results()
|
||||
]
|
||||
except Exception as e:
|
||||
logging.exception(f"\033[91m\033[1m{type(e)}\033[0m \033[95m{str(e)}\033[0m")
|
||||
logging.exception(f"\033[91m\033[1m{type(e)}\033[0m \033[95m{str(e)}\033[0m") # noqa:TRY401
|
||||
return []
|
||||
|
||||
def delete(self) -> None:
|
||||
|
|
|
@ -158,7 +158,7 @@ class OpenSearchVector(BaseVector):
|
|||
try:
|
||||
response = self._client.search(index=self._collection_name.lower(), body=query)
|
||||
except Exception as e:
|
||||
logger.exception(f"Error executing search: {e}")
|
||||
logger.exception(f"Error executing vector search, query: {query}")
|
||||
raise
|
||||
|
||||
docs = []
|
||||
|
|
|
@ -69,7 +69,7 @@ class CacheEmbedding(Embeddings):
|
|||
except IntegrityError:
|
||||
db.session.rollback()
|
||||
except Exception as e:
|
||||
logging.exception("Failed transform embedding: %s", e)
|
||||
logging.exception("Failed transform embedding")
|
||||
cache_embeddings = []
|
||||
try:
|
||||
for i, embedding in zip(embedding_queue_indices, embedding_queue_embeddings):
|
||||
|
@ -89,7 +89,7 @@ class CacheEmbedding(Embeddings):
|
|||
db.session.rollback()
|
||||
except Exception as ex:
|
||||
db.session.rollback()
|
||||
logger.exception("Failed to embed documents: %s", ex)
|
||||
logger.exception("Failed to embed documents: %s")
|
||||
raise ex
|
||||
|
||||
return text_embeddings
|
||||
|
@ -112,7 +112,7 @@ class CacheEmbedding(Embeddings):
|
|||
embedding_results = (embedding_results / np.linalg.norm(embedding_results)).tolist()
|
||||
except Exception as ex:
|
||||
if dify_config.DEBUG:
|
||||
logging.exception(f"Failed to embed query text: {ex}")
|
||||
logging.exception(f"Failed to embed query text '{text[:10]}...({len(text)} chars)'")
|
||||
raise ex
|
||||
|
||||
try:
|
||||
|
@ -126,7 +126,7 @@ class CacheEmbedding(Embeddings):
|
|||
redis_client.setex(embedding_cache_key, 600, encoded_str)
|
||||
except Exception as ex:
|
||||
if dify_config.DEBUG:
|
||||
logging.exception("Failed to add embedding to redis %s", ex)
|
||||
logging.exception(f"Failed to add embedding to redis for the text '{text[:10]}...({len(text)} chars)'")
|
||||
raise ex
|
||||
|
||||
return embedding_results
|
||||
|
|
|
@ -50,7 +50,7 @@ class WordExtractor(BaseExtractor):
|
|||
|
||||
self.web_path = self.file_path
|
||||
# TODO: use a better way to handle the file
|
||||
with tempfile.NamedTemporaryFile(delete=False) as self.temp_file:
|
||||
self.temp_file = tempfile.NamedTemporaryFile() # noqa: SIM115
|
||||
self.temp_file.write(r.content)
|
||||
self.file_path = self.temp_file.name
|
||||
elif not os.path.isfile(self.file_path):
|
||||
|
@ -229,7 +229,7 @@ class WordExtractor(BaseExtractor):
|
|||
for i in url_pattern.findall(x.text):
|
||||
hyperlinks_url = str(i)
|
||||
except Exception as e:
|
||||
logger.exception(e)
|
||||
logger.exception("Failed to parse HYPERLINK xml")
|
||||
|
||||
def parse_paragraph(paragraph):
|
||||
paragraph_content = []
|
||||
|
|
|
@ -159,7 +159,7 @@ class QAIndexProcessor(BaseIndexProcessor):
|
|||
qa_documents.append(qa_document)
|
||||
format_documents.extend(qa_documents)
|
||||
except Exception as e:
|
||||
logging.exception(e)
|
||||
logging.exception("Failed to format qa document")
|
||||
|
||||
all_qa_documents.extend(format_documents)
|
||||
|
||||
|
|
|
@ -1,6 +1,6 @@
|
|||
from typing import Literal, Optional
|
||||
|
||||
from pydantic import BaseModel
|
||||
from pydantic import BaseModel, Field, field_validator
|
||||
|
||||
from core.model_runtime.utils.encoders import jsonable_encoder
|
||||
from core.tools.entities.common_entities import I18nObject
|
||||
|
@ -32,9 +32,14 @@ class UserToolProvider(BaseModel):
|
|||
original_credentials: Optional[dict] = None
|
||||
is_team_authorization: bool = False
|
||||
allow_delete: bool = True
|
||||
tools: list[UserTool] | None = None
|
||||
tools: list[UserTool] = Field(default_factory=list)
|
||||
labels: list[str] | None = None
|
||||
|
||||
@field_validator("tools", mode="before")
|
||||
@classmethod
|
||||
def convert_none_to_empty_list(cls, v):
|
||||
return v if v is not None else []
|
||||
|
||||
def to_dict(self) -> dict:
|
||||
# -------------
|
||||
# overwrite tool parameter types for temp fix
|
||||
|
|
|
@ -78,3 +78,4 @@
|
|||
- regex
|
||||
- trello
|
||||
- vanna
|
||||
- fal
|
||||
|
|
3
api/core/tools/provider/builtin/audio/_assets/icon.svg
Normal file
3
api/core/tools/provider/builtin/audio/_assets/icon.svg
Normal file
|
@ -0,0 +1,3 @@
|
|||
<svg xmlns="http://www.w3.org/2000/svg" width="200" height="200" viewBox="0 0 200 200" fill="none">
|
||||
<path d="M167.358 102.395C167.358 117.174 157.246 129.18 144.61 131.027H137.861C125.225 129.18 115.113 117.174 115.113 102.395H100.792C100.792 123.637 115.118 142.106 133.653 145.801V164.276H147.139V145.801C165.674 142.106 180 124.558 180 102.4H167.358V102.395ZM154.717 62.677C154.717 53.4397 147.979 46.9765 140.396 46.9765C138.523 46.9446 136.663 47.3273 134.924 48.1024C133.185 48.8775 131.603 50.0294 130.27 51.4909C128.936 52.9524 127.878 54.6943 127.157 56.6148C126.436 58.5354 126.066 60.5962 126.07 62.677V78.3775H154.717V70.4478V62.677ZM126.07 102.395C126.07 111.632 132.813 118.095 140.396 118.095C142.269 118.127 144.13 117.744 145.868 116.969C147.607 116.194 149.189 115.042 150.523 113.581C151.856 112.119 152.914 110.377 153.635 108.457C154.356 106.536 154.726 104.475 154.722 102.395V86.694H126.07V102.395ZM92.1297 45.8938L70.4796 21.7595L69.4235 20.5865L59.604 20L68.3674 20.5865L67.3113 21.7654L64.1429 25.2961L63.6149 25.8826L64.1429 27.0614L66.2552 29.4133L77.8723 42.3631H54.1099C35.1 43.5361 20.3146 61.1896 20.3146 81.7874V83.5527H28.2354V81.7932C28.2354 65.8992 39.8525 52.3628 54.1099 51.1899H77.8723L66.2552 64.1338L64.671 65.8992L64.1429 67.0722L63.6149 67.6645L64.1429 68.251L68.3674 72.9606L68.8954 73.5471L69.4235 72.9606L74.1759 67.6645L92.1297 47.6591L92.6578 47.0727L92.1297 45.8938ZM20 95.8496V118.213H30.033V107.034H50.099V168.821H40.066V180H70.165V168.821H60.132V107.034H80.198V118.213H90.231V95.8496H20Z" fill="#FF0099"/>
|
||||
</svg>
|
After Width: | Height: | Size: 1.5 KiB |
6
api/core/tools/provider/builtin/audio/audio.py
Normal file
6
api/core/tools/provider/builtin/audio/audio.py
Normal file
|
@ -0,0 +1,6 @@
|
|||
from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController
|
||||
|
||||
|
||||
class AudioToolProvider(BuiltinToolProviderController):
|
||||
def _validate_credentials(self, credentials: dict) -> None:
|
||||
pass
|
11
api/core/tools/provider/builtin/audio/audio.yaml
Normal file
11
api/core/tools/provider/builtin/audio/audio.yaml
Normal file
|
@ -0,0 +1,11 @@
|
|||
identity:
|
||||
author: hjlarry
|
||||
name: audio
|
||||
label:
|
||||
en_US: Audio
|
||||
description:
|
||||
en_US: A tool for tts and asr.
|
||||
zh_Hans: 一个用于文本转语音和语音转文本的工具。
|
||||
icon: icon.svg
|
||||
tags:
|
||||
- utilities
|
Some files were not shown because too many files have changed in this diff Show More
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Reference in New Issue
Block a user