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02-use-cases/data_analysis_with_datalake/README.md

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### 1. 配置文件设置
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编辑 `data_analysis_with_code/agentkit_deploy/settings.txt` 文件,配置以下两个项
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编辑 `data_analysis_with_code/agentkit_deploy/settings.txt` 文件,可选配置以下
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```
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MODEL_AGENT_API_KEY=your_api_key_here
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TOOL_LAS_API_KEY=your_api_key_here
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VOLCENGINE_ACCESS_KEY=your_ak
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VOLCENGINE_SECRET_KEY=your_sk
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```
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### 2. 项目部署
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```bash
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cd agentkit_deploy
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uv python install 3.12
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uv venv -p 3.12 .venv
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source .venv/bin/activate
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uv pip install -r requirements.txt
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# veadk运行
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veadk web
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# 在agentkit上运行
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agentkit config --tos_bucket <your bucket name>
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agentkit launch
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```
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### 方式一:使用 Python 客户端
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当使用 agentkit 运行时可以通过 client 进行连接
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```bash
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python client.py
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```
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3. **Q3: Ang Lee 评分超过 7 分的有哪些电影?**
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4. **Q4: Ang Lee 评分超过 7 分的电影中,有哪个电影海报中含有动物?**
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5. **Q5: Life of Pi 的电影海报,变成视频**
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6. **Q6: 帮我找一张海报里有红色机车的电影,并把它做成视频**
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## 运行流程
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```
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data_analysis_with_code/
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├── agentkit_deploy/
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│ ├── .agentkit/
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│ ├── .dockerignore
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│ ├── agent.py
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│ ├── prompts.py
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│ ├── requirements.txt
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│ ├── settings.txt
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│ └── tools/
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│ ├── catalog_discovery.py
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│ ├── duckdb_sql_execution.py
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│ ├── lancedb_hybrid_execution.py
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│ └── video_generation.py
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├── agent.py
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├── prompts.py
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├── requirements.txt
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├── settings.txt
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└── tools/
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├── catalog_discovery.py
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├── duckdb_sql_execution.py
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├── lancedb_hybrid_execution.py
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└── video_generation.py
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├── client.py
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└── web/
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└── app.py

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