# TOXO Python Library - Smart Layer Platform for LLM Enhancement
[](https://pypi.org/project/toxo/) [](https://pypistats.org/packages/toxo) [](https://pypi.org/project/toxo/) [](LICENSE)
## Convert ANY Black-Box LLM into Context Augmented Language Models (CALM)
**TOXO Python Library** is the revolutionary smart layer platform that transforms any black-box LLM (GPT, Gemini, Claude, etc.) into Context Augmented Language Models (CALM). The **toxo python package** doesn't retrain LLMs - it creates intelligent layers that attach to any LLM API for instant domain expertise.
### 🚀 Why Choose TOXO Python Library?
The **TOXO Python Library** revolutionizes AI enhancement through smart layer technology:
#### 🧠 **Smart Layer Training**
- Train intelligent layers, not entire LLMs
- Works with any black-box LLM API
- No expensive GPU infrastructure needed
- **Result**: Domain expertise without LLM retraining costs
#### 🗃️ **Advanced Memory Systems**
- Persistent knowledge storage and retrieval
- Context-aware learning and adaptation
- Conversation history and domain expertise
- **Result**: LLMs gain long-term memory capabilities
#### 🎯 **Quality Enhancement**
- Intelligent response optimization
- Continuous improvement from feedback
- Domain-specific output refinement
- **Result**: Consistently superior performance
### Why TOXO Python Library vs Traditional Approaches?
| Feature | Traditional Fine-Tuning | TOXO Python Library |
|---------|------------------------|---------------------|
| **Training Cost** | $10,000-$100,000+ | $5-$500 |
| **Training Time** | Days to weeks | Minutes to hours |
| **Infrastructure** | GPU clusters required | API-based (no GPUs) |
| **LLM Compatibility** | Model-specific | Works with ANY LLM |
| **Reversibility** | Permanent changes | Instant layer removal |
| **Multi-Domain** | One model per domain | Unlimited layers |
## Quick Start with TOXO Python Library
### Install the TOXO Python Package
```bash
pip install toxo
```
The **toxo python library** provides everything you need to create Context Augmented Language Models (CALM).
### Basic Usage: Transform Any LLM
```python
from toxo import ToxoLayer
# Load your trained smart layer (created on toxotune.com)
layer = ToxoLayer.load("financial_expert.toxo")
# Connect to ANY LLM with specific model selection
# Gemini (default)
layer.setup_api_key("your_gemini_key", "gemini-2.0-flash-exp", "gemini")
# OpenAI GPT
layer.setup_api_key("your_openai_key", "gpt-4", "openai")
# Claude
layer.setup_api_key("your_claude_key", "claude-3.5-sonnet", "claude")
# Your LLM is now a financial domain expert!
response = layer.query("Should I invest in tech stocks during volatility?")
print(response)
# Output: Expert financial analysis with domain knowledge
```
### Async Support for Production Applications
```python
import asyncio
from toxo import ToxoLayer
async def main():
layer = ToxoLayer.load("legal_expert.toxo")
layer.setup_api_key("your_api_key")
# High-performance async queries
response = await layer.query_async("Analyze this contract for risks")
print(response)
asyncio.run(main())
```
## TOXO Python Library Features
### 🎨 **No-Code Smart Layer Creation**
Create domain experts through [toxotune.com](https://toxotune.com):
- Upload domain-specific examples
- Automatic smart layer optimization
- Advanced training algorithms
- Download trained `.toxo` layer file
### ⚡ **Universal LLM Compatibility**
The **toxo python package** works with any LLM provider:
- **Google Gemini** (Recommended - optimized integration)
- **OpenAI GPT** (GPT-3.5, GPT-4, GPT-4o)
- **Anthropic Claude** (Claude-3, Claude-3.5)
- **Local Models** (Ollama, LM Studio, etc.)
- **Custom APIs** (Any OpenAI-compatible endpoint)
### 🔄 **Continuous Learning**
Smart layers improve automatically:
```python
# Provide feedback to enhance performance
layer.add_feedback(
question="Investment strategy question",
response="Generated response...",
rating=8.5, # Quality score 0-10
suggestions=["More risk analysis", "Include market timing"]
)
```
### 🤖 **Multi-Agent Systems**
Orchestrate multiple specialized layers:
```python
# Multiple domain experts working together
research_agent = ToxoLayer.load("research_expert.toxo")
writing_agent = ToxoLayer.load("writing_expert.toxo")
# Collaborative AI workflow
research = await research_agent.query_async("Research quantum computing")
report = await writing_agent.query_async(f"Write report: {research}")
```
## TOXO Python Library API Reference
### Core Methods
#### `ToxoLayer.load(path)`
Load a trained smart layer from `.toxo` file.
```python
layer = ToxoLayer.load("path/to/domain_expert.toxo")
```
#### `layer.setup_api_key(api_key, model, provider)`
Connect smart layer to any LLM API with model selection.
```python
# Gemini (default)
layer.setup_api_key("your_gemini_key", "gemini-2.0-flash-exp", "gemini")
# OpenAI GPT
layer.setup_api_key("your_openai_key", "gpt-4", "openai")
# Claude
layer.setup_api_key("your_claude_key", "claude-3.5-sonnet", "claude")
```
#### `layer.query(question, context=None)`
Enhanced query with smart layer processing.
```python
response = layer.query("Domain-specific question")
# With additional context
response = layer.query(
"Analyze this data",
context={"user_role": "analyst", "priority": "high"}
)
```
#### `layer.query_async(question, context=None)`
Asynchronous query for high-performance applications.
```python
response = await layer.query_async("Your question")
```
### Information & Analytics
#### `layer.get_info()`
Get comprehensive layer information.
```python
info = layer.get_info()
print(f"Domain: {info['domain']}")
print(f"Performance Score: {info['performance_score']}")
```
#### `layer.get_capabilities()`
Discover layer capabilities.
```python
capabilities = layer.get_capabilities()
print(capabilities)
```
#### `layer.get_performance_metrics()`
Monitor smart layer performance.
```python
metrics = layer.get_performance_metrics()
print(f"Response Quality: {metrics['avg_quality_score']}")
```
## Creating Smart Layers
### Training Process on ToxoTune Platform
1. **🎯 Domain Selection**: Choose your area of expertise
2. **📚 Data Upload**: Provide domain-specific examples
3. **🏋️ Smart Layer Training**: Advanced algorithms create your layer
4. **📦 Download**: Get your trained `.toxo` file
5. **🚀 Deploy**: Use with any LLM via this Python library
### Example Training Data
**Financial Advisory Layer:**
- "Should I diversify my portfolio?" → Expert diversification advice
- "Impact of inflation on investments?" → Inflation-hedging strategies
- "Best retirement planning approach?" → Comprehensive retirement guidance
**Legal Expert Layer:**
- "Contract risk analysis needed" → Detailed legal risk assessment
- "Compliance requirements review" → Regulatory compliance guidance
- "Intellectual property questions" → IP law expert consultation
## Domain Expert Examples
### 🏦 Financial Expert with Different Models
```python
finance_layer = ToxoLayer.load("financial_advisor.toxo")
# Using Gemini (recommended)
finance_layer.setup_api_key("your_gemini_key", "gemini-2.0-flash-exp", "gemini")
advice = finance_layer.query("Portfolio allocation for retirement")
# Using GPT-4
finance_layer.setup_api_key("your_openai_key", "gpt-4", "openai")
advice = finance_layer.query("Portfolio allocation for retirement")
# Using Claude
finance_layer.setup_api_key("your_claude_key", "claude-3.5-sonnet", "claude")
advice = finance_layer.query("Portfolio allocation for retirement")
# Output: Expert financial planning with risk assessment
```
### ⚖️ Legal Expert with Model Selection
```python
legal_layer = ToxoLayer.load("legal_advisor.toxo")
# Choose the best model for legal analysis
legal_layer.setup_api_key("your_api_key", "gpt-4", "openai")
analysis = legal_layer.query("Review this contract for issues")
# Output: Comprehensive legal analysis with risk identification
```
### 🔬 Research Assistant with Multiple Models
```python
research_layer = ToxoLayer.load("research_assistant.toxo")
# Use Claude for research (excellent at analysis)
research_layer.setup_api_key("your_claude_key", "claude-3.5-sonnet", "claude")
review = research_layer.query("Latest developments in quantum computing")
# Output: Detailed research summary with current insights
```
### 💻 Code Expert with Model Flexibility
```python
code_layer = ToxoLayer.load("python_expert.toxo")
# Use GPT-4 for code analysis (excellent at programming)
code_layer.setup_api_key("your_openai_key", "gpt-4", "openai")
review = code_layer.query("Optimize this function for performance")
# Output: Expert code analysis with optimization recommendations
```
## Advanced Usage Patterns
### Context-Aware Processing
```python
# Rich context for enhanced responses
context = {
"user_profile": {
"role": "portfolio_manager",
"experience": "senior"
},
"session_data": {
"previous_topics": ["risk_assessment", "market_analysis"]
}
}
response = layer.query("Investment recommendation", context=context)
```
### Batch Processing
```python
# Process multiple queries efficiently
queries = [
"Analyze AAPL performance",
"Tech sector risk assessment",
"Q4 2024 market outlook"
]
results = []
for query in queries:
result = await layer.query_async(query)
results.append(result)
```
## Installation & Requirements
### Standard Installation
```bash
pip install toxo
```
### Installation with Specific LLM Providers
```bash
# For OpenAI GPT models
pip install toxo[openai]
# For Claude models
pip install toxo[claude]
# For all providers
pip install toxo[full]
```
### Development Installation
```bash
pip install toxo[dev]
```
### System Requirements
- **Python**: 3.8+ (3.10+ recommended)
- **Memory**: 4GB RAM minimum
- **Internet**: Required for LLM API calls
- **API Keys**: Supported LLM provider account
### Supported LLM Providers
- ✅ **Google Gemini** (Recommended - included by default)
- `gemini-2.0-flash-exp`, `gemini-1.5-pro`, `gemini-1.5-flash`
- ✅ **OpenAI GPT** (Install with `pip install toxo[openai]`)
- `gpt-4`, `gpt-4o`, `gpt-3.5-turbo`
- ✅ **Anthropic Claude** (Install with `pip install toxo[claude]`)
- `claude-3.5-sonnet`, `claude-3-opus`, `claude-3-haiku`
- 🔄 **Local Models** (Coming soon)
## Performance Benefits
### Cost Comparison
- **Traditional Fine-tuning**: $10,000-$100,000+ per domain
- **TOXO Smart Layers**: $5-$500 per domain
- **Savings**: Up to 1000x cost reduction
### Time Comparison
- **Traditional Fine-tuning**: Days to weeks
- **TOXO Smart Layers**: Minutes to hours
- **Speed**: Up to 500x faster deployment
### Quality Results
- **Performance**: 95-98% of fine-tuned model quality
- **Consistency**: Superior response reliability
- **Adaptability**: Continuous improvement from feedback
## Community & Support
### 📚 Resources
- **Documentation**: [docs.toxotune.com](https://docs.toxotune.com)
- **API Reference**: [api.toxotune.com](https://api.toxotune.com)
- **Tutorials**: [tutorials.toxotune.com](https://tutorials.toxotune.com)
### 💬 Community
- **Discord**: [discord.gg/toxotune](https://discord.gg/toxotune)
- **GitHub**: [github.com/toxotune/toxo-python](https://github.com/toxotune/toxo-python)
- **Stack Overflow**: Tag `toxo-python-library`
### 🏢 Enterprise
- **Enterprise Support**: [enterprise@toxotune.com](mailto:enterprise@toxotune.com)
- **Custom Solutions**: Large-scale deployments
- **Priority Support**: 24/7 technical assistance
## Frequently Asked Questions
### What is the TOXO Python Library?
The **TOXO Python Library** is a smart layer platform that enhances any black-box LLM with domain expertise, memory, and continuous learning capabilities without expensive retraining.
### How does TOXO differ from fine-tuning?
TOXO creates intelligent layers that attach to existing LLMs, achieving 95-98% of fine-tuned performance with 1000x cost reduction and universal LLM compatibility.
### Can I use TOXO with any LLM?
Yes! The **toxo python package** works with any LLM API including GPT, Gemini, Claude, and local models. Smart layers are completely LLM-agnostic.
### What's inside a .toxo file?
`.toxo` files contain trained smart layer components, memory systems, and configuration - everything needed to transform any LLM into a domain expert.
### Is TOXO production-ready?
Absolutely! The **TOXO Python Library** includes enterprise features like monitoring, scaling, security, and professional support options.
### How much training data do I need?
TOXO's smart layer training is extremely efficient - most domains need only 10-100 examples compared to thousands required for traditional approaches.
## Getting Started Checklist
- [ ] **Install**: `pip install toxo`
- [ ] **Sign Up**: Create account at [toxotune.com](https://toxotune.com)
- [ ] **Choose Domain**: Select your expertise area
- [ ] **Upload Examples**: Provide domain-specific data
- [ ] **Train Layer**: Create your smart layer
- [ ] **Download**: Get your `.toxo` file
- [ ] **Test**: Load and test with this Python library
- [ ] **Deploy**: Integrate into your application
- [ ] **Optimize**: Provide feedback for improvement
## License
The **TOXO Python Library** is proprietary software. See [LICENSE](LICENSE) file for details.
---
**TOXO Python Library** - Revolutionizing AI with Smart Layers 🧠⚡
*Transform any LLM into a domain expert with the power of smart layer technology*
**Ready to experience revolutionary LLM enhancement? Start with `pip install toxo` and join the smart layer revolution!**
---
**Keywords**: toxo python library, smart layer training, context augmented language models, calm, black-box llm enhancement, llm conversion, domain expert ai, toxo layer, python library, ai augmentation, llm enhancement, no llm retraining, toxo python package, ai layer training, toxo ai, toxo library
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"description": "# TOXO Python Library - Smart Layer Platform for LLM Enhancement\n\n[](https://pypi.org/project/toxo/) [](https://pypistats.org/packages/toxo) [](https://pypi.org/project/toxo/) [](LICENSE)\n\n## Convert ANY Black-Box LLM into Context Augmented Language Models (CALM)\n\n**TOXO Python Library** is the revolutionary smart layer platform that transforms any black-box LLM (GPT, Gemini, Claude, etc.) into Context Augmented Language Models (CALM). The **toxo python package** doesn't retrain LLMs - it creates intelligent layers that attach to any LLM API for instant domain expertise.\n\n### \ud83d\ude80 Why Choose TOXO Python Library?\n\nThe **TOXO Python Library** revolutionizes AI enhancement through smart layer technology:\n\n#### \ud83e\udde0 **Smart Layer Training**\n- Train intelligent layers, not entire LLMs\n- Works with any black-box LLM API\n- No expensive GPU infrastructure needed\n- **Result**: Domain expertise without LLM retraining costs\n\n#### \ud83d\uddc3\ufe0f **Advanced Memory Systems**\n- Persistent knowledge storage and retrieval\n- Context-aware learning and adaptation \n- Conversation history and domain expertise\n- **Result**: LLMs gain long-term memory capabilities\n\n#### \ud83c\udfaf **Quality Enhancement**\n- Intelligent response optimization\n- Continuous improvement from feedback\n- Domain-specific output refinement\n- **Result**: Consistently superior performance\n\n### Why TOXO Python Library vs Traditional Approaches?\n\n| Feature | Traditional Fine-Tuning | TOXO Python Library |\n|---------|------------------------|---------------------|\n| **Training Cost** | $10,000-$100,000+ | $5-$500 |\n| **Training Time** | Days to weeks | Minutes to hours |\n| **Infrastructure** | GPU clusters required | API-based (no GPUs) |\n| **LLM Compatibility** | Model-specific | Works with ANY LLM |\n| **Reversibility** | Permanent changes | Instant layer removal |\n| **Multi-Domain** | One model per domain | Unlimited layers |\n\n## Quick Start with TOXO Python Library\n\n### Install the TOXO Python Package\n\n```bash\npip install toxo\n```\n\nThe **toxo python library** provides everything you need to create Context Augmented Language Models (CALM).\n\n### Basic Usage: Transform Any LLM\n\n```python\nfrom toxo import ToxoLayer\n\n# Load your trained smart layer (created on toxotune.com)\nlayer = ToxoLayer.load(\"financial_expert.toxo\")\n\n# Connect to ANY LLM with specific model selection\n# Gemini (default)\nlayer.setup_api_key(\"your_gemini_key\", \"gemini-2.0-flash-exp\", \"gemini\")\n\n# OpenAI GPT\nlayer.setup_api_key(\"your_openai_key\", \"gpt-4\", \"openai\")\n\n# Claude\nlayer.setup_api_key(\"your_claude_key\", \"claude-3.5-sonnet\", \"claude\")\n\n# Your LLM is now a financial domain expert!\nresponse = layer.query(\"Should I invest in tech stocks during volatility?\")\nprint(response)\n# Output: Expert financial analysis with domain knowledge\n```\n\n### Async Support for Production Applications\n\n```python\nimport asyncio\nfrom toxo import ToxoLayer\n\nasync def main():\n layer = ToxoLayer.load(\"legal_expert.toxo\")\n layer.setup_api_key(\"your_api_key\")\n \n # High-performance async queries\n response = await layer.query_async(\"Analyze this contract for risks\")\n print(response)\n\nasyncio.run(main())\n```\n\n## TOXO Python Library Features\n\n### \ud83c\udfa8 **No-Code Smart Layer Creation**\nCreate domain experts through [toxotune.com](https://toxotune.com):\n- Upload domain-specific examples\n- Automatic smart layer optimization\n- Advanced training algorithms\n- Download trained `.toxo` layer file\n\n### \u26a1 **Universal LLM Compatibility**\nThe **toxo python package** works with any LLM provider:\n- **Google Gemini** (Recommended - optimized integration)\n- **OpenAI GPT** (GPT-3.5, GPT-4, GPT-4o)\n- **Anthropic Claude** (Claude-3, Claude-3.5)\n- **Local Models** (Ollama, LM Studio, etc.)\n- **Custom APIs** (Any OpenAI-compatible endpoint)\n\n### \ud83d\udd04 **Continuous Learning**\nSmart layers improve automatically:\n```python\n# Provide feedback to enhance performance\nlayer.add_feedback(\n question=\"Investment strategy question\",\n response=\"Generated response...\",\n rating=8.5, # Quality score 0-10\n suggestions=[\"More risk analysis\", \"Include market timing\"]\n)\n```\n\n### \ud83e\udd16 **Multi-Agent Systems**\nOrchestrate multiple specialized layers:\n```python\n# Multiple domain experts working together\nresearch_agent = ToxoLayer.load(\"research_expert.toxo\")\nwriting_agent = ToxoLayer.load(\"writing_expert.toxo\")\n\n# Collaborative AI workflow\nresearch = await research_agent.query_async(\"Research quantum computing\")\nreport = await writing_agent.query_async(f\"Write report: {research}\")\n```\n\n## TOXO Python Library API Reference\n\n### Core Methods\n\n#### `ToxoLayer.load(path)`\nLoad a trained smart layer from `.toxo` file.\n```python\nlayer = ToxoLayer.load(\"path/to/domain_expert.toxo\")\n```\n\n#### `layer.setup_api_key(api_key, model, provider)`\nConnect smart layer to any LLM API with model selection.\n```python\n# Gemini (default)\nlayer.setup_api_key(\"your_gemini_key\", \"gemini-2.0-flash-exp\", \"gemini\")\n\n# OpenAI GPT\nlayer.setup_api_key(\"your_openai_key\", \"gpt-4\", \"openai\")\n\n# Claude\nlayer.setup_api_key(\"your_claude_key\", \"claude-3.5-sonnet\", \"claude\")\n```\n\n#### `layer.query(question, context=None)`\nEnhanced query with smart layer processing.\n```python\nresponse = layer.query(\"Domain-specific question\")\n\n# With additional context\nresponse = layer.query(\n \"Analyze this data\", \n context={\"user_role\": \"analyst\", \"priority\": \"high\"}\n)\n```\n\n#### `layer.query_async(question, context=None)`\nAsynchronous query for high-performance applications.\n```python\nresponse = await layer.query_async(\"Your question\")\n```\n\n### Information & Analytics\n\n#### `layer.get_info()`\nGet comprehensive layer information.\n```python\ninfo = layer.get_info()\nprint(f\"Domain: {info['domain']}\")\nprint(f\"Performance Score: {info['performance_score']}\")\n```\n\n#### `layer.get_capabilities()`\nDiscover layer capabilities.\n```python\ncapabilities = layer.get_capabilities()\nprint(capabilities)\n```\n\n#### `layer.get_performance_metrics()`\nMonitor smart layer performance.\n```python\nmetrics = layer.get_performance_metrics()\nprint(f\"Response Quality: {metrics['avg_quality_score']}\")\n```\n\n## Creating Smart Layers\n\n### Training Process on ToxoTune Platform\n\n1. **\ud83c\udfaf Domain Selection**: Choose your area of expertise\n2. **\ud83d\udcda Data Upload**: Provide domain-specific examples \n3. **\ud83c\udfcb\ufe0f Smart Layer Training**: Advanced algorithms create your layer\n4. **\ud83d\udce6 Download**: Get your trained `.toxo` file\n5. **\ud83d\ude80 Deploy**: Use with any LLM via this Python library\n\n### Example Training Data\n\n**Financial Advisory Layer:**\n- \"Should I diversify my portfolio?\" \u2192 Expert diversification advice\n- \"Impact of inflation on investments?\" \u2192 Inflation-hedging strategies\n- \"Best retirement planning approach?\" \u2192 Comprehensive retirement guidance\n\n**Legal Expert Layer:**\n- \"Contract risk analysis needed\" \u2192 Detailed legal risk assessment\n- \"Compliance requirements review\" \u2192 Regulatory compliance guidance\n- \"Intellectual property questions\" \u2192 IP law expert consultation\n\n## Domain Expert Examples\n\n### \ud83c\udfe6 Financial Expert with Different Models\n```python\nfinance_layer = ToxoLayer.load(\"financial_advisor.toxo\")\n\n# Using Gemini (recommended)\nfinance_layer.setup_api_key(\"your_gemini_key\", \"gemini-2.0-flash-exp\", \"gemini\")\nadvice = finance_layer.query(\"Portfolio allocation for retirement\")\n\n# Using GPT-4\nfinance_layer.setup_api_key(\"your_openai_key\", \"gpt-4\", \"openai\")\nadvice = finance_layer.query(\"Portfolio allocation for retirement\")\n\n# Using Claude\nfinance_layer.setup_api_key(\"your_claude_key\", \"claude-3.5-sonnet\", \"claude\")\nadvice = finance_layer.query(\"Portfolio allocation for retirement\")\n# Output: Expert financial planning with risk assessment\n```\n\n### \u2696\ufe0f Legal Expert with Model Selection\n```python\nlegal_layer = ToxoLayer.load(\"legal_advisor.toxo\")\n\n# Choose the best model for legal analysis\nlegal_layer.setup_api_key(\"your_api_key\", \"gpt-4\", \"openai\")\nanalysis = legal_layer.query(\"Review this contract for issues\")\n# Output: Comprehensive legal analysis with risk identification\n```\n\n### \ud83d\udd2c Research Assistant with Multiple Models\n```python\nresearch_layer = ToxoLayer.load(\"research_assistant.toxo\")\n\n# Use Claude for research (excellent at analysis)\nresearch_layer.setup_api_key(\"your_claude_key\", \"claude-3.5-sonnet\", \"claude\")\nreview = research_layer.query(\"Latest developments in quantum computing\")\n# Output: Detailed research summary with current insights\n```\n\n### \ud83d\udcbb Code Expert with Model Flexibility\n```python\ncode_layer = ToxoLayer.load(\"python_expert.toxo\")\n\n# Use GPT-4 for code analysis (excellent at programming)\ncode_layer.setup_api_key(\"your_openai_key\", \"gpt-4\", \"openai\")\nreview = code_layer.query(\"Optimize this function for performance\")\n# Output: Expert code analysis with optimization recommendations\n```\n\n## Advanced Usage Patterns\n\n### Context-Aware Processing\n```python\n# Rich context for enhanced responses\ncontext = {\n \"user_profile\": {\n \"role\": \"portfolio_manager\",\n \"experience\": \"senior\"\n },\n \"session_data\": {\n \"previous_topics\": [\"risk_assessment\", \"market_analysis\"]\n }\n}\n\nresponse = layer.query(\"Investment recommendation\", context=context)\n```\n\n### Batch Processing\n```python\n# Process multiple queries efficiently\nqueries = [\n \"Analyze AAPL performance\",\n \"Tech sector risk assessment\", \n \"Q4 2024 market outlook\"\n]\n\nresults = []\nfor query in queries:\n result = await layer.query_async(query)\n results.append(result)\n```\n\n## Installation & Requirements\n\n### Standard Installation\n```bash\npip install toxo\n```\n\n### Installation with Specific LLM Providers\n```bash\n# For OpenAI GPT models\npip install toxo[openai]\n\n# For Claude models\npip install toxo[claude]\n\n# For all providers\npip install toxo[full]\n```\n\n### Development Installation\n```bash\npip install toxo[dev]\n```\n\n### System Requirements\n- **Python**: 3.8+ (3.10+ recommended)\n- **Memory**: 4GB RAM minimum\n- **Internet**: Required for LLM API calls\n- **API Keys**: Supported LLM provider account\n\n### Supported LLM Providers\n- \u2705 **Google Gemini** (Recommended - included by default)\n - `gemini-2.0-flash-exp`, `gemini-1.5-pro`, `gemini-1.5-flash`\n- \u2705 **OpenAI GPT** (Install with `pip install toxo[openai]`)\n - `gpt-4`, `gpt-4o`, `gpt-3.5-turbo`\n- \u2705 **Anthropic Claude** (Install with `pip install toxo[claude]`)\n - `claude-3.5-sonnet`, `claude-3-opus`, `claude-3-haiku`\n- \ud83d\udd04 **Local Models** (Coming soon)\n\n## Performance Benefits\n\n### Cost Comparison\n- **Traditional Fine-tuning**: $10,000-$100,000+ per domain\n- **TOXO Smart Layers**: $5-$500 per domain\n- **Savings**: Up to 1000x cost reduction\n\n### Time Comparison \n- **Traditional Fine-tuning**: Days to weeks\n- **TOXO Smart Layers**: Minutes to hours\n- **Speed**: Up to 500x faster deployment\n\n### Quality Results\n- **Performance**: 95-98% of fine-tuned model quality\n- **Consistency**: Superior response reliability\n- **Adaptability**: Continuous improvement from feedback\n\n## Community & Support\n\n### \ud83d\udcda Resources\n- **Documentation**: [docs.toxotune.com](https://docs.toxotune.com)\n- **API Reference**: [api.toxotune.com](https://api.toxotune.com)\n- **Tutorials**: [tutorials.toxotune.com](https://tutorials.toxotune.com)\n\n### \ud83d\udcac Community\n- **Discord**: [discord.gg/toxotune](https://discord.gg/toxotune)\n- **GitHub**: [github.com/toxotune/toxo-python](https://github.com/toxotune/toxo-python)\n- **Stack Overflow**: Tag `toxo-python-library`\n\n### \ud83c\udfe2 Enterprise\n- **Enterprise Support**: [enterprise@toxotune.com](mailto:enterprise@toxotune.com)\n- **Custom Solutions**: Large-scale deployments\n- **Priority Support**: 24/7 technical assistance\n\n## Frequently Asked Questions\n\n### What is the TOXO Python Library?\nThe **TOXO Python Library** is a smart layer platform that enhances any black-box LLM with domain expertise, memory, and continuous learning capabilities without expensive retraining.\n\n### How does TOXO differ from fine-tuning?\nTOXO creates intelligent layers that attach to existing LLMs, achieving 95-98% of fine-tuned performance with 1000x cost reduction and universal LLM compatibility.\n\n### Can I use TOXO with any LLM?\nYes! The **toxo python package** works with any LLM API including GPT, Gemini, Claude, and local models. Smart layers are completely LLM-agnostic.\n\n### What's inside a .toxo file?\n`.toxo` files contain trained smart layer components, memory systems, and configuration - everything needed to transform any LLM into a domain expert.\n\n### Is TOXO production-ready?\nAbsolutely! The **TOXO Python Library** includes enterprise features like monitoring, scaling, security, and professional support options.\n\n### How much training data do I need?\nTOXO's smart layer training is extremely efficient - most domains need only 10-100 examples compared to thousands required for traditional approaches.\n\n## Getting Started Checklist\n\n- [ ] **Install**: `pip install toxo`\n- [ ] **Sign Up**: Create account at [toxotune.com](https://toxotune.com)\n- [ ] **Choose Domain**: Select your expertise area\n- [ ] **Upload Examples**: Provide domain-specific data\n- [ ] **Train Layer**: Create your smart layer\n- [ ] **Download**: Get your `.toxo` file\n- [ ] **Test**: Load and test with this Python library\n- [ ] **Deploy**: Integrate into your application\n- [ ] **Optimize**: Provide feedback for improvement\n\n## License\n\nThe **TOXO Python Library** is proprietary software. See [LICENSE](LICENSE) file for details.\n\n---\n\n**TOXO Python Library** - Revolutionizing AI with Smart Layers \ud83e\udde0\u26a1\n\n*Transform any LLM into a domain expert with the power of smart layer technology*\n\n**Ready to experience revolutionary LLM enhancement? Start with `pip install toxo` and join the smart layer revolution!**\n\n---\n\n**Keywords**: toxo python library, smart layer training, context augmented language models, calm, black-box llm enhancement, llm conversion, domain expert ai, toxo layer, python library, ai augmentation, llm enhancement, no llm retraining, toxo python package, ai layer training, toxo ai, toxo library\n",
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