Claif Knollm¶
The World's Most Comprehensive LLM Provider Catalog¶
Claif Knollm is your ultimate resource for navigating the rapidly evolving landscape of Large Language Models. Built on extensive research of 40+ LLM providers, 10,000+ models, and 15+ Python libraries, Knollm provides intelligent routing, cost optimization, and comprehensive provider intelligence.
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:material-database:{ .lg .middle } Complete Model Catalog
Browse and search through the most comprehensive database of LLM models from providers like OpenAI, Anthropic, Google, and 37 others.
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:material-router-network:{ .lg .middle } Intelligent Routing
Automatically route requests to optimal providers based on cost, speed, quality, and availability with advanced failover capabilities.
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:material-code-tags:{ .lg .middle } Python Library Guide
Expert analysis of 15+ Python libraries for LLM integration, from simple HTTP clients to comprehensive frameworks.
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:material-chart-line:{ .lg .middle } Cost Optimization
Find the cheapest models for your needs and optimize costs across multiple providers with real-time pricing data.
Key Features¶
🌍 Universal Provider Support¶
Connect to 40+ LLM providers through a unified interface with automatic failover and load balancing.
🧠 Smart Model Selection¶
Intelligent routing based on your requirements: cost, speed, quality, capabilities, and context window needs.
💰 Cost Intelligence¶
Real-time pricing data and cost optimization recommendations across all providers.
📊 Comprehensive Analytics¶
Monitor performance, track costs, and optimize your LLM usage with detailed analytics.
🔄 Automatic Failover¶
Built-in redundancy ensures your applications stay online even when providers have issues.
🐍 Python-First Design¶
Native Python integration with type hints, async/await support, and Pydantic models.
Quick Start¶
Installation¶
Basic Usage¶
from claif_knollm import KnollmClient, ModelRegistry
# Initialize the client with intelligent routing
client = KnollmClient(routing_strategy="cost_optimized")
# Search for models
registry = ModelRegistry()
models = registry.search_models(
query="gpt-4",
max_cost_per_1k_tokens=0.01,
required_capabilities=["function_calling"]
)
# Make a completion request
response = await client.create_completion(
messages=[{"role": "user", "content": "Hello, world!"}],
model="gpt-4o-mini" # Or let Knollm choose automatically
)
CLI Usage¶
# List all providers
knollm providers list --tier premium
# Search for models
knollm models search --capability vision --max-cost 0.02
# Get library recommendations
knollm libraries recommend --use-case "structured_output"
# Find cheapest models
knollm models cheapest --capability function_calling
What Makes Knollm Special?¶
📋 Comprehensive Data Collection¶
Knollm is built on months of research collecting and analyzing data from:
- 40+ LLM API providers including OpenAI, Anthropic, Google, Mistral, and many more
- 10,000+ individual models with detailed capability analysis
- 15+ Python libraries with expert ratings and recommendations
- Real-time pricing data and performance metrics
🔬 Expert Analysis¶
Every provider and library in Knollm has been:
- Tested and evaluated by experts
- Rated on a comprehensive 7-star scale
- Analyzed for pros, cons, and ideal use cases
- Documented with practical examples
🚀 Production-Ready Intelligence¶
Knollm isn't just a catalog - it's a production-ready system with:
- Intelligent routing algorithms
- Automatic failover and redundancy
- Cost optimization strategies
- Performance monitoring and analytics
- Caching and rate limiting
Provider Ecosystem¶
Knollm supports the complete spectrum of LLM providers:
| Provider | Models | Specialty |
|---|---|---|
| OpenAI | 25+ | GPT-4, DALL-E |
| Anthropic | 12+ | Claude, Constitutional AI |
| 15+ | Gemini, PaLM |
| Provider | Models | Specialty |
|---|---|---|
| Groq | 20+ | Ultra-fast inference |
| Cerebras | 8+ | High-speed processing |
| DeepSeek | 15+ | Code generation |
| Provider | Models | Specialty |
|---|---|---|
| Hugging Face | 100+ | Open models |
| Together AI | 50+ | Open source hosting |
| Replicate | 80+ | Community models |
| Provider | Models | Specialty |
|---|---|---|
| Mistral | 12+ | European AI |
| Cohere | 8+ | Enterprise focus |
| AI21 | 6+ | Jurrasic models |
Python Library Ecosystem¶
Expert analysis of the complete Python ecosystem for LLM integration:
- httpx ⭐⭐⭐⭐⭐⭐⭐ - Modern async/sync HTTP
- requests ⭐⭐⭐⭐⭐ - Simple synchronous HTTP
- aiohttp ⭐⭐⭐⭐⭐⭐ - High-performance async
- openai ⭐⭐⭐⭐⭐⭐⭐ - Official OpenAI library
- instructor ⭐⭐⭐⭐⭐⭐ - Structured output with Pydantic
- litellm ⭐⭐⭐⭐⭐⭐ - Universal provider interface
- pydantic_ai ⭐⭐⭐⭐⭐⭐ - Type-safe AI framework
- langchain ⭐⭐⭐⭐ - Comprehensive ecosystem
- llamaindex ⭐⭐⭐⭐ - RAG specialist
- outlines ⭐⭐⭐⭐⭐⭐ - Guaranteed structured output
- guidance ⭐⭐⭐⭐⭐ - Constrained generation
- portkey-ai ⭐⭐⭐⭐⭐⭐ - Enterprise AI gateway
Why Use Claif Knollm?¶
For Developers¶
- Save weeks of research with expert-curated provider data
- Reduce integration time with unified interfaces
- Avoid vendor lock-in with multi-provider support
- Optimize costs automatically with intelligent routing
For Organizations¶
- Ensure reliability with automatic failover
- Control costs with real-time optimization
- Monitor usage with comprehensive analytics
- Scale efficiently across multiple providers
For Researchers¶
- Access comprehensive data on the LLM ecosystem
- Compare providers objectively with standardized metrics
- Stay updated with automated data collection
- Benchmark performance across different models
Getting Started¶
Ready to dive in? Here's your path to mastering Knollm:
- Installation → - Get Knollm up and running
- Quick Start → - Your first Knollm application
- Provider Guide → - Understand the provider ecosystem
- Model Database → - Explore 10,000+ models
- Python Libraries → - Choose the right tools
- Best Practices → - Production deployment tips
💡 Pro Tip
Start with the Quick Start guide to build your first multi-provider LLM application in under 5 minutes!