swordenamine/deepseek-ai-agent

DeepSeek AI Agent Repository 🚀

Full-featured Bash CLI agent for DeepSeek API with complete repository integration capabilities

✨ Features

• ✅ Interactive Chat Mode - Continuous conversation (Ctrl+C to exit)
• ✅ Single-shot Queries - script.sh "your question"
• ✅ Multi-model Support - deepseek-chat, deepseek-coder
• ✅ Environment-driven - Secure .env configuration
• ✅ Advanced Parameters - Temperature, max tokens
• ✅ Production Ready - Error handling, JSON parsing
• ✅ Agentic Workflow Compatible - CrewAI, GitHub Actions ready

📦 Quick Start

# 1. Clone repository
git clone https://github.com/swordenkisk/deepseek-ai-agent.git
cd deepseek-ai-agent

# 2. Make executable
chmod +x deepseek-ai-agent.sh

# 3. Create .env (get key from https://platform.deepseek.com/)
echo "DEEPSEEK_API_KEY=sk-your-key-here" > .env

# 4. Run!
./deepseek-ai-agent.sh "Hello, write me a Python script"

🚀 Usage Examples

# Interactive mode
./deepseek-ai-agent.sh

# Single query
./deepseek-ai-agent.sh "Explain quantum computing simply"

# Coder model
./deepseek-ai-agent.sh -m deepseek-coder "Debug this Python code"

# Custom parameters
./deepseek-ai-agent.sh -m deepseek-chat -t 8000 -T 0.3 "Creative writing"

⚙️ Configuration

.env file:

DEEPSEEK_API_KEY=sk-your-actual-api-key
DEEPSEEK_MODEL=deepseek-chat
MAX_TOKENS=4096
TEMPERATURE=0.7

🛠️ CLI Options

Flag	Description	Example
-m, --model	Model selection	-m deepseek-coder
-t, --tokens	Max tokens	-t 8192
-T, --temperature	Creativity (0.0-2.0)	-T 0.1
-h, --help	Show help	-h

📁 Repository Structure

deepseek-ai-agent/
├── deepseek-ai-agent.sh     # Main executable
├── .env.example            # Template config
├── README.md              # This file
├── docker/                 # Docker deployment (optional)
└── examples/               # Usage examples

🔧 Dependencies

# Required
curl jq

# Verify installation
command -v curl >/dev/null 2>&1 || { echo "Install curl"; exit 1; }
command -v jq >/dev/null 2>&1 || { echo "Install jq"; exit 1; }

🐳 Docker

# Dockerfile
FROM alpine:latest
RUN apk add --no-cache curl jq bash
COPY deepseek-ai-agent.sh /usr/local/bin/
COPY .env /
RUN chmod +x /usr/local/bin/deepseek-ai-agent.sh
CMD ["/usr/local/bin/deepseek-ai-agent.sh"]

docker build -t deepseek-agent .
docker run -it --env-file .env deepseek-agent

🔗 Integration Examples

CrewAI Agent Repository

from crewai import Agent
agent = Agent(
    role='DeepSeek Researcher',
    goal='Research using DeepSeek API',
    backstory='Expert researcher with DeepSeek access',
    execute_function='./deepseek-ai-agent.sh "research query"'
)

GitHub Actions

- name: AI Code Review
  run: ./deepseek-ai-agent.sh -m deepseek-coder "Review this PR code"

📊 Architecture

graph TD
    User[User Input] --> CLI[deepseek-ai-agent.sh]
    CLI --> Env[.env Config]
    CLI --> API[DeepSeek API]
    API --> JSON[JSON Response]
    JSON --> JQ[jq Parser]
    JQ --> Output[Clean Response]

🔒 Security

• ✅ Zero-trust: API key never exposed in script
• ✅ Environment-only: .env gitignored by default
• ✅ No persistent storage: Stateless execution
• ✅ Input sanitized: Safe curl JSON escaping

🤝 Contributing

1. Fork the repository
2. Create feature branch (git checkout -b feature/amazing-feature)
3. Commit changes (git commit -m 'Add amazing feature')
4. Push to branch (git push origin feature/amazing-feature)
5. Open Pull Request

📄 License

MIT License - see LICENSE file.

🙏 Acknowledgments

• DeepSeek - Amazing open API platform
• CrewAI - Agent framework inspiration
• GitHub - Agentic workflow patterns

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🐛 Found a bug? Open an issue!