# TNSA API Python Client
A powerful, OpenAI-compatible Python SDK for TNSA NGen3 Pro and Lite Models.
## Features
- 🚀 **OpenAI-Compatible API** - Familiar interface for easy migration
- ⚡ **Async & Sync Support** - Both synchronous and asynchronous clients
- 🌊 **Streaming Responses** - Real-time token streaming for interactive applications
- 🔧 **Comprehensive Error Handling** - Robust error handling with retry logic
- 📊 **Usage Tracking** - Built-in token counting and cost estimation
- 💬 **Conversation Management** - Automatic chat history and context management
- 🔒 **Secure Authentication** - API key management with environment variable support
- 📝 **Type Safety** - Full type hints for better IDE support
- 🎯 **Framework Integration** - Works seamlessly with FastAPI, Django, and more
## Installation
```bash
pip install tnsa-api
```
## Quick Start
```python
from tnsa_api_v2 import TNSA
# Initialize the client
client = TNSA(api_key="your-api-key")
# List available models
models = client.models.list()
print("Available models:", [model.id for model in models])
# Create a chat completion
response = client.chat.completions.create(
model="NGen3.9-Pro",
messages=[
{"role": "user", "content": "Hello, how are you?"}
]
)
print(response.choices[0].message.content)
```
## Streaming Example
```python
# Streaming responses
stream = client.chat.completions.create(
model="NGen3.9-Lite",
messages=[{"role": "user", "content": "Tell me a story"}],
stream=True
)
for chunk in stream:
if chunk.choices[0].delta.content:
print(chunk.choices[0].delta.content, end="")
```
## Async Usage
```python
import asyncio
from tnsa_api_v2 import AsyncTNSA
async def main():
client = AsyncTNSA(api_key="your-api-key")
response = await client.chat.completions.acreate(
model="NGen3.9-Pro",
messages=[{"role": "user", "content": "Hello!"}]
)
print(response.choices[0].message.content)
asyncio.run(main())
```
## Configuration
The client can be configured using environment variables, configuration files, or direct parameters:
### Environment Variables
```bash
export TNSA_API_KEY="your-api-key"
export TNSA_BASE_URL="https://api.tnsaai.com"
export TNSA_TIMEOUT=30.0
```
### Configuration File (config.yaml)
```yaml
api_key: "your-api-key"
base_url: "https://api.tnsaai.com"
timeout: 30.0
max_retries: 3
default_model: "NGen3.9-Pro"
```
### Direct Parameters
```python
client = TNSA(
api_key="your-api-key",
base_url="https://api.tnsaai.com",
timeout=30.0,
max_retries=3
)
```
## Available Models
- **NGen3.9-Pro** - High-performance model for complex tasks
- **NGen3.9-Lite** - Fast, efficient model for general use
- **NGen3-7B-0625** - Specialized model variant
- **Farmvaidya-Bot** - Agricultural domain-specific model
## Error Handling
```python
from tnsa_api_v2 import TNSAError, RateLimitError, AuthenticationError
try:
response = client.chat.completions.create(
model="NGen3.9-Pro",
messages=[{"role": "user", "content": "Hello!"}]
)
except AuthenticationError:
print("Invalid API key")
except RateLimitError:
print("Rate limit exceeded")
except TNSAError as e:
print(f"API error: {e}")
```
## Documentation
For detailed documentation, examples, and API reference, visit: [https://docs.tnsaai.com](https://docs.tnsaai.com)
## Support
- 📧 Email: info@tnsaai.com
- 🐛 Issues: [GitHub Issues](https://github.com/tnsaai/tnsa-api-python/issues)
- 📖 Documentation: [https://docs.tnsaai.com](https://docs.tnsaai.com)
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
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"description": "# TNSA API Python Client\r\n\r\nA powerful, OpenAI-compatible Python SDK for TNSA NGen3 Pro and Lite Models.\r\n\r\n## Features\r\n\r\n- \ud83d\ude80 **OpenAI-Compatible API** - Familiar interface for easy migration\r\n- \u26a1 **Async & Sync Support** - Both synchronous and asynchronous clients\r\n- \ud83c\udf0a **Streaming Responses** - Real-time token streaming for interactive applications\r\n- \ud83d\udd27 **Comprehensive Error Handling** - Robust error handling with retry logic\r\n- \ud83d\udcca **Usage Tracking** - Built-in token counting and cost estimation\r\n- \ud83d\udcac **Conversation Management** - Automatic chat history and context management\r\n- \ud83d\udd12 **Secure Authentication** - API key management with environment variable support\r\n- \ud83d\udcdd **Type Safety** - Full type hints for better IDE support\r\n- \ud83c\udfaf **Framework Integration** - Works seamlessly with FastAPI, Django, and more\r\n\r\n## Installation\r\n\r\n```bash\r\npip install tnsa-api\r\n```\r\n\r\n## Quick Start\r\n\r\n```python\r\nfrom tnsa_api_v2 import TNSA\r\n\r\n# Initialize the client\r\nclient = TNSA(api_key=\"your-api-key\")\r\n\r\n# List available models\r\nmodels = client.models.list()\r\nprint(\"Available models:\", [model.id for model in models])\r\n\r\n# Create a chat completion\r\nresponse = client.chat.completions.create(\r\n model=\"NGen3.9-Pro\",\r\n messages=[\r\n {\"role\": \"user\", \"content\": \"Hello, how are you?\"}\r\n ]\r\n)\r\n\r\nprint(response.choices[0].message.content)\r\n```\r\n\r\n## Streaming Example\r\n\r\n```python\r\n# Streaming responses\r\nstream = client.chat.completions.create(\r\n model=\"NGen3.9-Lite\",\r\n messages=[{\"role\": \"user\", \"content\": \"Tell me a story\"}],\r\n stream=True\r\n)\r\n\r\nfor chunk in stream:\r\n if chunk.choices[0].delta.content:\r\n print(chunk.choices[0].delta.content, end=\"\")\r\n```\r\n\r\n## Async Usage\r\n\r\n```python\r\nimport asyncio\r\nfrom tnsa_api_v2 import AsyncTNSA\r\n\r\nasync def main():\r\n client = AsyncTNSA(api_key=\"your-api-key\")\r\n \r\n response = await client.chat.completions.acreate(\r\n model=\"NGen3.9-Pro\",\r\n messages=[{\"role\": \"user\", \"content\": \"Hello!\"}]\r\n )\r\n \r\n print(response.choices[0].message.content)\r\n\r\nasyncio.run(main())\r\n```\r\n\r\n## Configuration\r\n\r\nThe client can be configured using environment variables, configuration files, or direct parameters:\r\n\r\n### Environment Variables\r\n\r\n```bash\r\nexport TNSA_API_KEY=\"your-api-key\"\r\nexport TNSA_BASE_URL=\"https://api.tnsaai.com\"\r\nexport TNSA_TIMEOUT=30.0\r\n```\r\n\r\n### Configuration File (config.yaml)\r\n\r\n```yaml\r\napi_key: \"your-api-key\"\r\nbase_url: \"https://api.tnsaai.com\"\r\ntimeout: 30.0\r\nmax_retries: 3\r\ndefault_model: \"NGen3.9-Pro\"\r\n```\r\n\r\n### Direct Parameters\r\n\r\n```python\r\nclient = TNSA(\r\n api_key=\"your-api-key\",\r\n base_url=\"https://api.tnsaai.com\",\r\n timeout=30.0,\r\n max_retries=3\r\n)\r\n```\r\n\r\n## Available Models\r\n\r\n- **NGen3.9-Pro** - High-performance model for complex tasks\r\n- **NGen3.9-Lite** - Fast, efficient model for general use\r\n- **NGen3-7B-0625** - Specialized model variant\r\n- **Farmvaidya-Bot** - Agricultural domain-specific model\r\n\r\n## Error Handling\r\n\r\n```python\r\nfrom tnsa_api_v2 import TNSAError, RateLimitError, AuthenticationError\r\n\r\ntry:\r\n response = client.chat.completions.create(\r\n model=\"NGen3.9-Pro\",\r\n messages=[{\"role\": \"user\", \"content\": \"Hello!\"}]\r\n )\r\nexcept AuthenticationError:\r\n print(\"Invalid API key\")\r\nexcept RateLimitError:\r\n print(\"Rate limit exceeded\")\r\nexcept TNSAError as e:\r\n print(f\"API error: {e}\")\r\n```\r\n\r\n## Documentation\r\n\r\nFor detailed documentation, examples, and API reference, visit: [https://docs.tnsaai.com](https://docs.tnsaai.com)\r\n\r\n## Support\r\n\r\n- \ud83d\udce7 Email: info@tnsaai.com\r\n- \ud83d\udc1b Issues: [GitHub Issues](https://github.com/tnsaai/tnsa-api-python/issues)\r\n- \ud83d\udcd6 Documentation: [https://docs.tnsaai.com](https://docs.tnsaai.com)\r\n\r\n## License\r\n\r\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\r\n",
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