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17
docs/Geneplore AI/README.md
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docs/Geneplore AI/README.md
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# [Geneplore AI](https://geneplore.com/bot)
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## Geneplore AI is building the world's easiest way to use AI - Use 50+ models, all on Discord
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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.
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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.
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**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.
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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.
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https://geneplore.com
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© 2025 Geneplore AI, All Rights Reserved.
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12
docs/Ncurator/README.md
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docs/Ncurator/README.md
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<img src="./assets/logo.png" width="64" height="auto" />
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# [Ncurator](https://www.ncurator.com)
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Knowledge Base AI Q&A Assistant -
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Let AI help you organize and analyze knowledge
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## UI
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<img src="./assets/screenshot3.png" width="360" height="auto" />
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## Integrate with Deepseek API
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<img src="./assets/screenshot2.png" width="360" height="auto" />
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docs/Ncurator/README_cn.md
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docs/Ncurator/README_cn.md
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<img src="./assets/logo.png" width="64" height="auto" />
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# [Ncurator](https://www.ncurator.com)
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知识库AI问答助手-让AI帮助你整理与分析知识
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## UI
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<img src="./assets/screenshot1.png" width="360" height="auto" />
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## 配置 Deepseek API
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<img src="./assets/screenshot2.png" width="360" height="auto" />
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docs/Ncurator/assets/logo.png
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docs/Ncurator/assets/screenshot1.png
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docs/Ncurator/assets/screenshot2.png
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docs/Ncurator/assets/screenshot3.png
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@ -25,16 +25,14 @@ return {
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lazy = false,
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version = false, -- set this if you want to always pull the latest change
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opts = {
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provider = "openai",
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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
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openai = {
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endpoint = "https://api.deepseek.com/v1",
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model = "deepseek-chat",
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timeout = 30000, -- Timeout in milliseconds
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temperature = 0,
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max_tokens = 4096,
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-- optional
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api_key_name = "OPENAI_API_KEY", -- default OPENAI_API_KEY if not set
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provider = "deepseek",
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vendors = {
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deepseek = {
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__inherited_from = "openai",
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api_key_name = "DEEPSEEK_API_KEY",
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endpoint = "https://api.deepseek.com",
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model = "deepseek-coder",
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},
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},
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},
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-- if you want to build from source then do `make BUILD_FROM_SOURCE=true`
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lazy = false,
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version = false, -- set this if you want to always pull the latest change
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opts = {
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provider = "openai",
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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
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openai = {
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endpoint = "https://api.deepseek.com/v1",
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model = "deepseek-chat",
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timeout = 30000, -- Timeout in milliseconds
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temperature = 0,
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max_tokens = 4096,
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-- optional
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api_key_name = "OPENAI_API_KEY", -- default OPENAI_API_KEY if not set
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provider = "deepseek",
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vendors = {
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deepseek = {
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__inherited_from = "openai",
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api_key_name = "DEEPSEEK_API_KEY",
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endpoint = "https://api.deepseek.com",
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model = "deepseek-coder",
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},
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},
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},
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-- if you want to build from source then do `make BUILD_FROM_SOURCE=true`
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@ -34,9 +34,8 @@ return {
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require("codecompanion").setup({
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adapters = {
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deepseek = function()
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return require("codecompanion.adapters").extend("openai_compatible", {
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return require("codecompanion.adapters").extend("deepseek", {
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env = {
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url = "https://api.deepseek.com",
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api_key = "YOUR_API_KEY",
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},
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})
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@ -71,9 +70,8 @@ later(function()
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require("codecompanion").setup({
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adapters = {
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deepseek = function()
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return require("codecompanion.adapters").extend("openai_compatible", {
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return require("codecompanion.adapters").extend("deepseek", {
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env = {
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url = "https://api.deepseek.com",
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api_key = "YOUR_API_KEY",
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},
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})
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@ -34,9 +34,8 @@ return {
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require("codecompanion").setup({
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adapters = {
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deepseek = function()
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return require("codecompanion.adapters").extend("openai_compatible", {
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return require("codecompanion.adapters").extend("deepseek", {
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env = {
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url = "https://api.deepseek.com",
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api_key = "YOUR_API_KEY",
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},
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})
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require("codecompanion").setup({
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adapters = {
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deepseek = function()
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return require("codecompanion.adapters").extend("openai_compatible", {
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return require("codecompanion.adapters").extend("deepseek", {
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env = {
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url = "https://api.deepseek.com",
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api_key = "YOUR_API_KEY",
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},
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})
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<img src="https://github.com/deepseek-ai/awesome-deepseek-integration/assets/59196087/e4d082de-6f64-44b9-beaa-0de55d70cfab" width="64" height="auto" />
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<img src="https://github.com/continuedev/continue/blob/main/docs/static/img/logo.png?raw=true" width="64" height="auto" />
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# [Continue](https://continue.dev/)
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<img src="https://github.com/deepseek-ai/awesome-deepseek-integration/assets/59196087/e4d082de-6f64-44b9-beaa-0de55d70cfab" width="64" height="auto" />
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<img src="https://github.com/continuedev/continue/blob/main/docs/static/img/logo.png?raw=true" width="64" height="auto" />
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# [Continue](https://continue.dev/)
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docs/curator/README.md
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docs/curator/README.md
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# [Curator](https://github.com/bespokelabsai/curator)
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Curator is an open-source tool to curate large scale datasets for post-training LLMs.
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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).
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### Curator supports:
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- Calling Deepseek API for scalable synthetic data curation
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- Easy structured data extraction
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- Caching and automatic recovery
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- Dataset visualization
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- Saving $$$ using batch mode
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### Call Deepseek API with Curator easily:
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# Get Started here
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- [Colab Example](https://colab.research.google.com/drive/1Z78ciwHIl_ytACzcrslNrZP2iwK05eIF?usp=sharing)
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- [Github Repo](https://github.com/bespokelabsai/curator)
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- [Documentation](https://docs.bespokelabs.ai/)
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- [Discord](https://discord.com/invite/KqpXvpzVBS)
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29
docs/curator/README_cn.md
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# [Curator](https://github.com/bespokelabsai/curator)
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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。
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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。
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### Curator 支持:
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- 调用 Deepseek API 进行可扩展的合成数据管理
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- 简便的结构化数据提取
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- 缓存和自动恢复
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- 数据集可视化
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- 使用批处理模式节省费用
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### 轻松使用 Curator 调用 Deepseek API:
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# 从这里开始
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- [Colab 示例](https://colab.research.google.com/drive/1Z78ciwHIl_ytACzcrslNrZP2iwK05eIF?usp=sharing)
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- [Github 仓库](https://github.com/bespokelabsai/curator)
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- [文档](https://docs.bespokelabs.ai/)
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- [Discord](https://discord.com/invite/KqpXvpzVBS)
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33
docs/superagentx/README.md
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docs/superagentx/README.md
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# `SuperAgentX`
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> 🤖 SuperAgentX: A lightweight autonomous true multi-agent framework with AGI capabilities.
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**SuperAgentX Source Code**: [https://github.com/superagentxai/superagentx](https://github.com/superagentxai/superagentx)
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**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)
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**Documentation** : [https://docs.superagentx.ai/](https://docs.superagentx.ai/)
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The SuperAgentX framework integrates DeepSeek as its LLM service provider, enhancing the multi-agent's reasoning and decision-making capabilities.
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## 🤖 Introduction
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`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.
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### ✨ Key Features
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🚀 Open-Source Framework: A lightweight, open-source AI framework built for multi-agent applications with Artificial General Intelligence (AGI) capabilities.
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🎯 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.
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🏖️ Easy Deployment: Offers WebSocket, RESTful API, and IO console interfaces for rapid setup of agent-based AI solutions.
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♨️ Streamlined Architecture: Enterprise-ready scalable and pluggable architecture. No major dependencies; built independently!
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📚 Contextual Memory: Uses SQL + Vector databases to store and retrieve user-specific context effectively.
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🧠 Flexible LLM Configuration: Supports simple configuration options of various Gen AI models.
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🤝🏻 Extendable Handlers: Allows integration with diverse APIs, databases, data warehouses, data lakes, IoT streams, and more, making them accessible for function-calling features.
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