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| # 详细文档见https://modelscope.cn/docs/%E5%88%9B%E7%A9%BA%E9%97%B4%E5%8D%A1%E7%89%87 | |
| domain: #领域：cv/nlp/audio/multi-modal/AutoML | |
| - multi-modal | |
| tags: #自定义标签 | |
| - agent | |
| - AgentFabric | |
| ## 启动文件(若SDK为Gradio/Streamlit，默认为app.py, 若为Static HTML, 默认为index.html) | |
| deployspec: | |
| entry_file: app.py | |
| license: Apache License 2.0 | |
| <h1> Modelscope AgentFabric: Customizable AI-Agents For All</h1> | |
| <p align="center"> | |
| <br> | |
| <img src="https://modelscope.oss-cn-beijing.aliyuncs.com/modelscope.gif" width="400"/> | |
| <br> | |
| <p> | |
| ## Introduction | |
| **ModelScope AgentFabric** is an interactive framework to facilitate creation of agents tailored to various real-world applications. AgentFabric is built around pluggable and customizable LLMs, and enhance capabilities of instrcution following, extra knowledge retrieval and leveraging external tools. The AgentFabric is woven with interfaces including: | |
| - ⚡ **Agent Builder**: an automatic instructions and tools provider for customizing user's agents through natural conversational interactions. | |
| - ⚡ **User Agent**: a customized agent for building real-world applications, with instructions, extra-knowledge and tools provided by builder agent and/or user inputs. | |
| - ⚡ **Configuration Tooling**: the interface to customize user agent configurations. Allows real-time preview of agent behavior as new confiugrations are updated. | |
| 🔗 We currently leverage AgentFabric to build various agents around [Qwen2.0 LLM API](https://help.aliyun.com/zh/dashscope/developer-reference/api-details) available via DashScope. We are also actively exploring | |
| other options to incorporate (and compare) more LLMs via API, as well as via native ModelScope models. | |
| ## Installation | |
| Simply clone the repo and install dependency. | |
| ```bash | |
| git clone https://github.com/modelscope/modelscope-agent.git | |
| cd modelscope-agent && pip install -r requirements.txt && pip install -r demo/agentfabric/requirements.txt | |
| ``` | |
| ## Prerequisites | |
| - Python 3.10 | |
| - Accessibility to LLM API service such as [DashScope](https://help.aliyun.com/zh/dashscope/developer-reference/activate-dashscope-and-create-an-api-key) (free to start). | |
| ## Usage | |
| ```bash | |
| export PYTHONPATH=$PYTHONPATH:/path/to/your/modelscope-agent | |
| export DASHSCOPE_API_KEY=your_api_key | |
| cd modelscope-agent/demo/agentfabric | |
| python app.py | |
| ``` | |
| ## 🚀 Roadmap | |
| - [x] Allow customizable agent-building via configurations. | |
| - [x] Agent-building through interactive conversations with LLMs. | |
| - [x] Support multi-user preview on ModelScope space. [link](https://modelscope.cn/studios/wenmengzhou/AgentFabric/summary) [PR #98](https://github.com/modelscope/modelscope-agent/pull/98) | |
| - [x] Optimize knowledge retrival. [PR #105](https://github.com/modelscope/modelscope-agent/pull/105) [PR #107](https://github.com/modelscope/modelscope-agent/pull/107) [PR #109](https://github.com/modelscope/modelscope-agent/pull/109) | |
| - [x] Allow publication and sharing of agent. [PR #111](https://github.com/modelscope/modelscope-agent/pull/111) | |
| - [ ] Support more pluggable LLMs via API or ModelScope interface. | |
| - [ ] Improve long context via memory. | |
| - [ ] Improve logging and profiling. | |
| - [ ] Fine-tuning for specific agent. | |
| - [ ] Evaluation for agents in different scenarios. | |