DeepSeek API 的 Python 客户端

# DeepSeek Python Client A feature-rich Python client for interacting with DeepSeek's powerful language models, supporting both synchronous and asynchronous operations. ## Installation ```bash pip install deepseek-sdk ``` ## Quick Start ```python from deepseek import DeepSeekClient # Initialize client client = DeepSeekClient(api_key="your-api-key") # Basic chat completion response = client.chat_completion( messages=[{"role": "user", "content": "Hello, how are you?"}] ) print(response.choices[0].message.content) ``` ## Features ✅ Synchronous & Async Support 🚀 Streaming Responses 🔧 Customizable Parameters 🛠 Error Handling ⚡️ Context Manager Support 🔁 Retry Mechanisms ## Complete Usage Guide ### 1. Basic Chat Completion ```python response = client.chat_completion( messages=[ {"role": "system", "content": "You are a helpful assistant"}, {"role": "user", "content": "Explain quantum computing in simple terms"} ], model="deepseek-chat", # default model temperature=0.8, # control randomness (0-2) max_tokens=500 # limit response length ) ``` ### 2. Streaming Responses **Synchronous Streaming:** ```python for chunk in client.stream_response( messages=[{"role": "user", "content": "Tell me a story about AI"}] ): content = chunk.choices[0].delta.content or "" print(content, end="", flush=True) ``` **Async Streaming:** ```python async def stream_response(): async for chunk in client.async_stream_response( messages=[{"role": "user", "content": "Explain blockchain technology"}] ): content = chunk.choices[0].delta.content or "" print(content, end="", flush=True) # Run in event loop import asyncio asyncio.run(stream_response()) ``` ### 3. Advanced Configuration **Custom Client Initialization:** ```python client = DeepSeekClient( api_key="your-api-key", base_url="https://api.deepseek.com/v1", # Custom endpoint default_model="deepseek-chat-advanced" # Set default model ) ``` **Context Manager for Streams:** ```python with client.stream_response( messages=[{"role": "user", "content": "Generate Python code for quicksort"}] ) as stream: for chunk in stream: print(chunk.choices[0].delta.content or "", end="") ``` ### 4. Error Handling ```python try: response = client.chat_completion(messages=[{"role": "user", "content": "Hello"}]) except DeepSeekAPIError as e: print(f"API Error: {str(e)}") except DeepSeekError as e: print(f"Client Error: {str(e)}") ``` ### 5. Advanced Parameters **Using All Available Options:** ```python response = client.chat_completion( messages=[{"role": "user", "content": "Compare Python and JavaScript"}], model="deepseek-chat", temperature=1.2, top_p=0.9, max_tokens=1000, presence_penalty=0.5, frequency_penalty=0.5, stream=False ) ``` ### 6. Retry Mechanism ```python from tenacity import retry, stop_after_attempt, wait_exponential class RobustClient(DeepSeekClient): @retry(stop=stop_after_attempt(3), wait=wait_exponential(multiplier=1, min=4, max=10)) def chat_completion(self, *args, **kwargs): return super().chat_completion(*args, **kwargs) # Usage client = RobustClient(api_key="your-api-key") ``` ## Inspiration: What Can You Build? ### 🤖 Intelligent Chatbot ```python while True: user_input = input("You: ") if user_input.lower() == 'exit': break response = client.chat_completion( messages=[{"role": "user", "content": user_input}], temperature=0.9 ) print(f"AI: {response.choices[0].message.content}") ``` ### 📝 Content Generation System ```python def generate_blog_post(topic: str) -> str: prompt = f"Write a 500-word blog post about {topic} with markdown formatting:" response = client.chat_completion( messages=[{"role": "user", "content": prompt}], temperature=0.7, max_tokens=1500 ) return response.choices[0].message.content ``` ### 💻 CLI Interface (using Click) ```python import click @click.command() @click.option('--api-key', required=True, help='Your DeepSeek API key') @click.option('--prompt', required=True, help='Your query/prompt') @click.option('--stream', is_flag=True, help='Enable streaming') def deepseek_cli(api_key, prompt, stream): client = DeepSeekClient(api_key=api_key) if stream: for chunk in client.stream_response([{"role": "user", "content": prompt}]): click.echo(chunk.choices[0].delta.content or "", nl=False) else: response = client.chat_completion([{"role": "user", "content": prompt}]) click.echo(response.choices[0].message.content) if __name__ == '__main__': deepseek_cli() ``` ## Contributing 1. Fork the repository 2. Create your feature branch (`git checkout -b feature/awesome-feature`) 3. Commit your changes (`git commit -am 'Add awesome feature'`) 4. Push to the branch (`git push origin feature/awesome-feature`) 5. Open a Pull Request ## License MIT License - See [LICENSE](LICENSE) for details ## Support For issues and feature requests, please [open an issue](https://github.com/Pro-Sifat-Hasan/deepseek-python/issues) --- **🚀 Pro Tip:** Combine with other libraries like `rich` for beautiful console output, or `fastapi` to create AI-powered web services!