botintel-sdk 0.0.3

Official Python SDK for BotIntel API

BotIntel Python SDK

The official Python client for BotIntel's enterprise-grade AI API, featuring multi-model support, real-time web integration, and advanced analytics.

# Basic Example
from botintel import Client

client = Client(api_key="your_api_key")
response = client.chat.completions.create(
    model="botintel-v3",
    messages=[{"role": "user", "content": "Latest AI breakthroughs in 2024"}]
)
print(response)

Table of Contents

• Features
• Installation
• Quick Start
• Available Models
• Usage Examples
• Error Handling
• Advanced Features
• Pricing
• Configuration
• Deployment
• Contributing
• License
• Support

Features

🌐 Web-enhanced responses with real-time data

🧮 Advanced token accounting system

⚡ Streaming support with partial responses

🔒 Enterprise-grade security (SOC 2 compliant)

📈 Built-in usage analytics

♻️ Automatic retries with exponential backoff

Installation

pip install botintel

Quick Start

from botintel import Client

# Initialize with API key
client = Client(api_key="bix-your-api-key-here")

# Basic chat completion
response = client.chat.completions.create(
    model="botintel-v3",
    messages=[
        {"role": "system", "content": "You are a senior developer"},
        {"role": "user", "content": "Explain monorepo architecture"}
    ]
)

print(f"Response: {response.choices[0].message.content}")
print(f"Tokens Used: {response.usage.total_tokens}")

Available Models

Model Name	Context Window	Best For	Web Access
botintel-v3	8K tokens	General purpose AI	❌
botintel-pro	32K tokens	Technical problem solving	❌
botintel-v3-search	4K tokens	Real-time information	✅
imagen-1	N/A	Basic image generation	❌
imagen-2	N/A	Advanced image generation (latest and most improved)	❌

Usage Examples

Web-Enhanced Search

response = client.chat.completions.create(
    model="botintel-v3-search",
    messages=[
        {"role": "user", "content": "Current USD to EUR exchange rate"}
    ],
    web_search=True,
    cite_sources=True
)

print(response.choices[0].message.content)
# Output might include: [Source: European Central Bank, 2024-03-15]

Technical Analysis (Pro Model)

response = client.chat.completions.create(
    model="botintel-pro",
    messages=[
        {"role": "user", "content": "Optimize this Python code..."},
        {"role": "assistant", "content": "Current code: ..."},
    ],
    temperature=0.2,
    max_tokens=1000
)

Error Handling

from botintel import exceptions

try:
    response = client.chat.completions.create(...)
except exceptions.InsufficientBalanceError as e:
    print(f"Payment required: {e.balance_needed}")
    # Auto-recharge logic here
except exceptions.RateLimitError as e:
    print(f"Retry after: {e.retry_after} seconds")
except exceptions.APIError as e:
    print(f"Server error: {e.status_code}")

Advanced Features

Streaming Responses

stream = client.chat.completions.create(
    model="botintel-v3",
    messages=[{"role": "user", "content": "Tell me a story..."}],
    stream=True,
    temperature=0.7
)

for chunk in stream:
    print(chunk.choices[0].delta.content, end="", flush=True)

Usage Analytics

# Get current balance
balance = client.get_balance()
print(f"Remaining balance: ${balance:.2f}")

# Get usage statistics
usage = client.get_usage(start_date="2024-01-01")
print(f"Total tokens used: {usage.total_tokens}")

Pricing

Model	Input ($/1k tokens)	Output ($/1k tokens)
botintel-v3	0.27	1.10
botintel-pro	0.55	2.19
botintel-search	0.35	1.45
Volume discounts available for >1M tokens/month

Configuration

client = Client(
    api_key="your_key",
    base_url="https://api.botintel.ai/v1",  # Custom endpoint
    timeout=30.0,          # Request timeout in seconds
    max_retries=5,         # Automatic retries
    cache_enabled=True,    # Response caching
    debug=False            # Enable debug logging
)

Deployment

Recommended Architecture

                          +-----------------+
                          |   Load Balancer |
                          +--------+--------+
                                   |
                          +--------+--------+
                          |    API Servers   |
                          +--------+--------+
                                   |
                          +--------+--------+
                          |  PostgreSQL DB  |
                          +-----------------+
                          |   Redis Cache   |
                          +-----------------+

Docker Setup

# Dockerfile.prod
FROM python:3.11-slim

WORKDIR /app
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

COPY . .

CMD ["gunicorn", "app:create_app()", "--bind", "0.0.0.0:8000", "--workers", "4"]

Contributing

• Fork the repository
• Create feature branch (git checkout -b feature/amazing-feature)
• Commit changes (git commit -m 'Add amazing feature')
• Push to branch (git push origin feature/amazing-feature)
• Open Pull Request

License

MIT License - See LICENSE for details.

Support

📧 Enterprise Support: [e-mail]

💬 Community: Discord Server

📄 Documentation

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To use this README:

1. Save as README.md
2. Update placeholder URLs (status page, docs, etc.)
3. Add your LICENSE file
4. Customize deployment details as needed

The file includes:

• Interactive code examples
• Detailed model comparisons
• Error handling patterns
• Deployment architecture diagrams
• Complete pricing information
• Docker configuration examples
• Support resources