Merge branch 'main' into main

This commit is contained in:
zggsong 2025-02-05 12:00:39 +08:00 committed by GitHub
commit f33ffc1f18
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
20 changed files with 632 additions and 50 deletions

View file

@ -0,0 +1,17 @@
# [Geneplore AI](https://geneplore.com/bot)
## Geneplore AI is building the world's easiest way to use AI - Use 50+ models, all on Discord
Chat with the all-new Deepseek v3, GPT-4o, Claude 3 Opus, LLaMA 3, Gemini Pro, FLUX.1, and ChatGPT with **one bot**. Generate videos with Stable Diffusion Video, and images with the newest and most popular models available.
Don't like how the bot responds? Simply change the model in *seconds* and continue chatting like normal, without adding another bot to your server. No more fiddling with API keys and webhooks - every model is completely integrated into the bot.
**NEW:** Try the most powerful open AI model, Deepseek v3, for free with our bot. Simply type /chat and select Deepseek in the model list.
![image](https://github.com/user-attachments/assets/14db7e3c-c2c7-46d7-9fe1-5a5d1e3fc856)
Use the bot trusted by over 60,000 servers and hundreds of paying subscribers, without the hassle of multiple $20/month subscriptions and complicated programming.
https://geneplore.com
© 2025 Geneplore AI, All Rights Reserved.

12
docs/Ncurator/README.md Normal file
View file

@ -0,0 +1,12 @@
<img src="./assets/logo.png" width="64" height="auto" />
# [Ncurator](https://www.ncurator.com)
Knowledge Base AI Q&A Assistant -
Let AI help you organize and analyze knowledge
## UI
<img src="./assets/screenshot3.png" width="360" height="auto" />
## Integrate with Deepseek API
<img src="./assets/screenshot2.png" width="360" height="auto" />

View file

@ -0,0 +1,11 @@
<img src="./assets/logo.png" width="64" height="auto" />
# [Ncurator](https://www.ncurator.com)
知识库AI问答助手-让AI帮助你整理与分析知识
## UI
<img src="./assets/screenshot1.png" width="360" height="auto" />
## 配置 Deepseek API
<img src="./assets/screenshot2.png" width="360" height="auto" />

Binary file not shown.

After

Width:  |  Height:  |  Size: 99 KiB

Binary file not shown.

After

Width:  |  Height:  |  Size: 178 KiB

Binary file not shown.

After

Width:  |  Height:  |  Size: 96 KiB

Binary file not shown.

After

Width:  |  Height:  |  Size: 180 KiB

View file

@ -25,16 +25,14 @@ return {
lazy = false,
version = false, -- set this if you want to always pull the latest change
opts = {
provider = "openai",
auto_suggestions_provider = "openai", -- Since auto-suggestions are a high-frequency operation and therefore expensive, it is recommended to specify an inexpensive provider or even a free provider: copilot
openai = {
endpoint = "https://api.deepseek.com/v1",
model = "deepseek-chat",
timeout = 30000, -- Timeout in milliseconds
temperature = 0,
max_tokens = 4096,
-- optional
api_key_name = "OPENAI_API_KEY", -- default OPENAI_API_KEY if not set
provider = "deepseek",
vendors = {
deepseek = {
__inherited_from = "openai",
api_key_name = "DEEPSEEK_API_KEY",
endpoint = "https://api.deepseek.com",
model = "deepseek-coder",
},
},
},
-- if you want to build from source then do `make BUILD_FROM_SOURCE=true`

View file

@ -25,16 +25,14 @@ return {
lazy = false,
version = false, -- set this if you want to always pull the latest change
opts = {
provider = "openai",
auto_suggestions_provider = "openai", -- Since auto-suggestions are a high-frequency operation and therefore expensive, it is recommended to specify an inexpensive provider or even a free provider: copilot
openai = {
endpoint = "https://api.deepseek.com/v1",
model = "deepseek-chat",
timeout = 30000, -- Timeout in milliseconds
temperature = 0,
max_tokens = 4096,
-- optional
api_key_name = "OPENAI_API_KEY", -- default OPENAI_API_KEY if not set
provider = "deepseek",
vendors = {
deepseek = {
__inherited_from = "openai",
api_key_name = "DEEPSEEK_API_KEY",
endpoint = "https://api.deepseek.com",
model = "deepseek-coder",
},
},
},
-- if you want to build from source then do `make BUILD_FROM_SOURCE=true`

View file

@ -34,9 +34,8 @@ return {
require("codecompanion").setup({
adapters = {
deepseek = function()
return require("codecompanion.adapters").extend("openai_compatible", {
return require("codecompanion.adapters").extend("deepseek", {
env = {
url = "https://api.deepseek.com",
api_key = "YOUR_API_KEY",
},
})
@ -71,9 +70,8 @@ later(function()
require("codecompanion").setup({
adapters = {
deepseek = function()
return require("codecompanion.adapters").extend("openai_compatible", {
return require("codecompanion.adapters").extend("deepseek", {
env = {
url = "https://api.deepseek.com",
api_key = "YOUR_API_KEY",
},
})

View file

@ -34,9 +34,8 @@ return {
require("codecompanion").setup({
adapters = {
deepseek = function()
return require("codecompanion.adapters").extend("openai_compatible", {
return require("codecompanion.adapters").extend("deepseek", {
env = {
url = "https://api.deepseek.com",
api_key = "YOUR_API_KEY",
},
})
@ -71,9 +70,8 @@ later(function()
require("codecompanion").setup({
adapters = {
deepseek = function()
return require("codecompanion.adapters").extend("openai_compatible", {
return require("codecompanion.adapters").extend("deepseek", {
env = {
url = "https://api.deepseek.com",
api_key = "YOUR_API_KEY",
},
})

View file

@ -1,4 +1,4 @@
<img src="https://github.com/deepseek-ai/awesome-deepseek-integration/assets/59196087/e4d082de-6f64-44b9-beaa-0de55d70cfab" width="64" height="auto" />
<img src="https://github.com/continuedev/continue/blob/main/docs/static/img/logo.png?raw=true" width="64" height="auto" />
# [Continue](https://continue.dev/)

View file

@ -1,4 +1,4 @@
<img src="https://github.com/deepseek-ai/awesome-deepseek-integration/assets/59196087/e4d082de-6f64-44b9-beaa-0de55d70cfab" width="64" height="auto" />
<img src="https://github.com/continuedev/continue/blob/main/docs/static/img/logo.png?raw=true" width="64" height="auto" />
# [Continue](https://continue.dev/)

30
docs/curator/README.md Normal file
View file

@ -0,0 +1,30 @@
![image](https://raw.githubusercontent.com/bespokelabsai/curator/main/docs/Bespoke-Labs-Logomark-Red-crop.png)
# [Curator](https://github.com/bespokelabsai/curator)
Curator is an open-source tool to curate large scale datasets for post-training LLMs.
Curator was used to curate [Bespoke-Stratos-17k](https://huggingface.co/datasets/bespokelabs/Bespoke-Stratos-17k), a reasoning dataset to train a fully open reasoning model [Bespoke-Stratos](https://www.bespokelabs.ai/blog/bespoke-stratos-the-unreasonable-effectiveness-of-reasoning-distillation).
### Curator supports:
- Calling Deepseek API for scalable synthetic data curation
- Easy structured data extraction
- Caching and automatic recovery
- Dataset visualization
- Saving $$$ using batch mode
### Call Deepseek API with Curator easily:
![image](https://pbs.twimg.com/media/GiLHb-xasAAbs4m?format=jpg&name=4096x4096)
# Get Started here
- [Colab Example](https://colab.research.google.com/drive/1Z78ciwHIl_ytACzcrslNrZP2iwK05eIF?usp=sharing)
- [Github Repo](https://github.com/bespokelabsai/curator)
- [Documentation](https://docs.bespokelabs.ai/)
- [Discord](https://discord.com/invite/KqpXvpzVBS)

29
docs/curator/README_cn.md Normal file
View file

@ -0,0 +1,29 @@
![image](https://raw.githubusercontent.com/bespokelabsai/curator/main/docs/Bespoke-Labs-Logomark-Red-crop.png)
# [Curator](https://github.com/bespokelabsai/curator)
Curator 是一个用于后训练大型语言模型 (LLMs) 和结构化数据提取的制作与管理可扩展的数据集的开源工具。
Curator 被用来制作 [Bespoke-Stratos-17k](https://huggingface.co/datasets/bespokelabs/Bespoke-Stratos-17k),这是一个用于训练完全开源的推理模型 [Bespoke-Stratos](https://www.bespokelabs.ai/blog/bespoke-stratos-the-unreasonable-effectiveness-of-reasoning-distillation) 的推理数据集。
### Curator 支持:
- 调用 Deepseek API 进行可扩展的合成数据管理
- 简便的结构化数据提取
- 缓存和自动恢复
- 数据集可视化
- 使用批处理模式节省费用
### 轻松使用 Curator 调用 Deepseek API
![image](https://pbs.twimg.com/media/GiLHb-xasAAbs4m?format=jpg&name=4096x4096)
# 从这里开始
- [Colab 示例](https://colab.research.google.com/drive/1Z78ciwHIl_ytACzcrslNrZP2iwK05eIF?usp=sharing)
- [Github 仓库](https://github.com/bespokelabsai/curator)
- [文档](https://docs.bespokelabs.ai/)
- [Discord](https://discord.com/invite/KqpXvpzVBS)

View file

@ -0,0 +1,33 @@
# `SuperAgentX`
> 🤖 SuperAgentX: A lightweight autonomous true multi-agent framework with AGI capabilities.
**SuperAgentX Source Code**: [https://github.com/superagentxai/superagentx](https://github.com/superagentxai/superagentx)
**DeepSeek AI Agent Example**: [https://github.com/superagentxai/superagentx/blob/master/tests/llm/test_deepseek_client.py](https://github.com/superagentxai/superagentx/blob/master/tests/llm/test_deepseek_client.py)
**Documentation** : [https://docs.superagentx.ai/](https://docs.superagentx.ai/)
The SuperAgentX framework integrates DeepSeek as its LLM service provider, enhancing the multi-agent's reasoning and decision-making capabilities.
## 🤖 Introduction
`SuperAgentX` SuperAgentX is an advanced agentic AI framework designed to accelerate the development of Artificial General Intelligence (AGI). It provides a powerful, modular, and flexible platform for building autonomous AI agents capable of executing complex tasks with minimal human intervention.
![SuperAgentX Diagram](https://raw.githubusercontent.com/superagentxai/superagentX/refs/heads/master/docs/images/architecture.png)
### ✨ Key Features
🚀 Open-Source Framework: A lightweight, open-source AI framework built for multi-agent applications with Artificial General Intelligence (AGI) capabilities.
🎯 Goal-Oriented Multi-Agents: This technology enables the creation of agents with retry mechanisms to achieve set goals. Communication between agents is Parallel, Sequential, or hybrid.
🏖️ Easy Deployment: Offers WebSocket, RESTful API, and IO console interfaces for rapid setup of agent-based AI solutions.
♨️ Streamlined Architecture: Enterprise-ready scalable and pluggable architecture. No major dependencies; built independently!
📚 Contextual Memory: Uses SQL + Vector databases to store and retrieve user-specific context effectively.
🧠 Flexible LLM Configuration: Supports simple configuration options of various Gen AI models.
🤝🏻 Extendable Handlers: Allows integration with diverse APIs, databases, data warehouses, data lakes, IoT streams, and more, making them accessible for function-calling features.

Binary file not shown.

After

Width:  |  Height:  |  Size: 99 KiB