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update readme
Browse files- README.md +22 -12
- README_zh.md +22 -12
README.md
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@@ -219,11 +219,7 @@ Alternatively, you can set environment variables directly in your terminal:
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> **Note**: Environment variables set directly in the terminal will only persist for the current session.
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### Additional Models
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For information on configuring other AI models beyond OpenAI, please refer to our [CAMEL models documentation](https://docs.camel-ai.org/key_modules/models.html#supported-model-platforms-in-camel).
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> **Note**: For optimal performance, we strongly recommend using OpenAI models. Our experiments show that other models may result in significantly lower performance on complex tasks and benchmarks.
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## **Running with Docker**
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## Running with Different Models
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###
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For information on configuring
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```bash
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# Run with Qwen model
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# 🧰 Configuring Toolkits
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OWL supports various toolkits that can be customized by modifying the `tools` list in your script:
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```python
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## Available Toolkits
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Key toolkits include:
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- **ImageAnalysisToolkit**: Image analysis
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- **SearchToolkit**: Web searches (Google, DuckDuckGo, Wikipedia)
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- **DocumentProcessingToolkit**: Document parsing (PDF, DOCX, etc.)
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> **Note**: Environment variables set directly in the terminal will only persist for the current session.
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## **Running with Docker**
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## Running with Different Models
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### Model Requirements
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- **Tool Calling**: OWL requires models with robust tool calling capabilities to interact with various toolkits. Models must be able to understand tool descriptions, generate appropriate tool calls, and process tool outputs.
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- **Multimodal Understanding**: For tasks involving web interaction, image analysis, or video processing, models with multimodal capabilities are required to interpret visual content and context.
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#### Supported Models
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For information on configuring AI models, please refer to our [CAMEL models documentation](https://docs.camel-ai.org/key_modules/models.html#supported-model-platforms-in-camel).
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> **Note**: For optimal performance, we strongly recommend using OpenAI models (GPT-4 or later versions). Our experiments show that other models may result in significantly lower performance on complex tasks and benchmarks, especially those requiring advanced multi-modal understanding and tool use.
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OWL supports various LLM backends, though capabilities may vary depending on the model's tool calling and multimodal abilities. You can use the following scripts to run with different models:
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```bash
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# Run with Qwen model
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# 🧰 Configuring Toolkits
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> **Important**: Effective use of toolkits requires models with strong tool calling capabilities. For multimodal toolkits (Web, Image, Video), models must also have multimodal understanding abilities.
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OWL supports various toolkits that can be customized by modifying the `tools` list in your script:
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```python
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## Available Toolkits
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Key toolkits include:
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### Multimodal Toolkits (Require multimodal model capabilities)
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- **WebToolkit**: Browser automation for web interaction and navigation
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- **VideoAnalysisToolkit**: Video processing and content analysis
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- **ImageAnalysisToolkit**: Image analysis and interpretation
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### Text-Based Toolkits
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- **AudioAnalysisToolkit**: Audio processing (requires OpenAI API)
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- **CodeExecutionToolkit**: Python code execution and evaluation
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- **SearchToolkit**: Web searches (Google, DuckDuckGo, Wikipedia)
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- **DocumentProcessingToolkit**: Document parsing (PDF, DOCX, etc.)
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README_zh.md
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@@ -218,10 +218,6 @@ OWL 需要各种 API 密钥来与不同的服务进行交互。`owl/.env_templat
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> **注意**:直接在终端中设置的环境变量仅在当前会话中有效。
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### 其他模型
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有关配置 OpenAI 以外的其他 AI 模型的信息,请参阅我们的 [CAMEL 模型文档](https://docs.camel-ai.org/key_modules/models.html#supported-model-platforms-in-camel)。
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## **使用Docker运行**
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如果您希望使用Docker运行OWL项目,我们提供了完整的Docker支持:
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## 使用不同的模型
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###
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```bash
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# 使用 Qwen 模型运行
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# 🧰 配置工具包
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OWL支持多种工具包,可通过修改脚本中的`tools`列表进行自定义:
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```python
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## 主要工具包
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关键工具包包括:
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- **ImageAnalysisToolkit
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- **SearchToolkit**:网络搜索(Google、DuckDuckGo、维基百科)
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- **DocumentProcessingToolkit**:文档解析(PDF、DOCX等)
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> **注意**:直接在终端中设置的环境变量仅在当前会话中有效。
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## **使用Docker运行**
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如果您希望使用Docker运行OWL项目,我们提供了完整的Docker支持:
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## 使用不同的模型
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### 模型要求
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- **工具调用能力**:OWL 需要具有强大工具调用能力的模型来与各种工具包交互。模型必须能够理解工具描述、生成适当的工具调用,并处理工具输出。
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- **多模态理解能力**:对于涉及网页交互、图像分析或视频处理的任务,需要具备多模态能力的模型来解释视觉内容和上下文。
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#### 支持的模型
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有关配置模型的信息,请参阅我们的 [CAMEL 模型文档](https://docs.camel-ai.org/key_modules/models.html#supported-model-platforms-in-camel)。
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> **注意**:为获得最佳性能,我们强烈推荐使用 OpenAI 模型(GPT-4 或更高版本)。我们的实验表明,其他模型在复杂任务和基准测试上可能表现明显较差,尤其是那些需要多模态理解和工具使用的任务。
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OWL 支持多种 LLM 后端,但功能可能因模型的工具调用和多模态能力而异。您可以使用以下脚本来运行不同的模型:
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```bash
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# 使用 Qwen 模型运行
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# 🧰 配置工具包
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> **重要提示**:有效使用工具包需要具备强大工具调用能力的模型。对于多模态工具包(Web、图像、视频),模型还必须具备多模态理解能力。
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OWL支持多种工具包,可通过修改脚本中的`tools`列表进行自定义:
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```python
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## 主要工具包
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关键工具包包括:
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### 多模态工具包(需要模型具备多模态能力)
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- **WebToolkit**:浏览器自动化,用于网页交互和导航
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- **VideoAnalysisToolkit**:视频处理和内容分析
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- **ImageAnalysisToolkit**:图像分析和解释
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### 基于文本的工具包
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- **AudioAnalysisToolkit**:音频处理(需要 OpenAI API)
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- **CodeExecutionToolkit**:Python 代码执行和评估
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- **SearchToolkit**:网络搜索(Google、DuckDuckGo、维基百科)
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- **DocumentProcessingToolkit**:文档解析(PDF、DOCX等)
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