# TNSAAI Python Client
A powerful, OpenAI-compatible Python SDK for TNSA NGen3 Pro and Lite Models.
## Installation
```bash
pip install tnsaai-client
```
## Quick Start
```python
from tnsaai import TNSA
# Initialize the client
client = TNSA(api_key="your-api-key", base_url="https://api.tnsaai.com")
# Create a chat completion
response = client.chat.create(
model="NGen3.9-Pro",
messages=[{"role": "user", "content": "Hello!"}]
)
print(response.choices[0].message.content)
```
## Streaming
```python
stream = client.chat.create(
model="NGen3.9-Lite",
messages=[{"role": "user", "content": "Tell me a story"}],
stream=True
)
for chunk in stream:
if chunk.content:
print(chunk.content, end="")
```
## Async Usage
```python
import asyncio
from tnsaai import AsyncTNSA
async def main():
async with AsyncTNSA(api_key="your-api-key") as client:
response = await client.chat.create(
model="NGen3.9-Pro",
messages=[{"role": "user", "content": "Hello!"}]
)
print(response.choices[0].message.content)
asyncio.run(main())
```
## Available Models
- **NGen3.9-Pro** - High-performance model for complex tasks
- **NGen3.9-Lite** - Fast, efficient model for general use
- **Farmvaidya-Bot** - Agricultural domain-specific model
## Configuration
Set your API key as an environment variable:
```bash
export TNSA_API_KEY="your-api-key"
export TNSA_BASE_URL="https://api.tnsaai.com"
```
Or pass it directly:
```python
client = TNSA(
api_key="your-api-key",
base_url="https://api.tnsaai.com"
)
```
## Features
- ✅ OpenAI-compatible API
- ✅ Synchronous and asynchronous clients
- ✅ Streaming responses
- ✅ Comprehensive error handling
- ✅ Automatic retries with exponential backoff
- ✅ Usage tracking and cost estimation
- ✅ Conversation management
- ✅ Type hints and IDE support
## Support
- Email: info@tnsaai.com
- Documentation: https://docs.tnsaai.com
- Issues: https://github.com/tnsaai/tnsaai-python/issues
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