haive.core

🚀 Haive Core - The Revolutionary AI Infrastructure Platform

THE FOUNDATION OF NEXT-GENERATION AI SYSTEMS

Welcome to Haive Core - the bedrock of intelligent agent architectures that transforms how AI systems are built, composed, and orchestrated. This isn’t just another framework; it’s a paradigm shift in AI engineering that enables self-evolving, deeply intelligent systems that adapt, learn, and grow beyond their initial programming.

🧬 CORE ARCHITECTURE PILLARS

1. Universal Engine System ⚡

The beating heart of Haive - a revolutionary abstraction that unifies: - AugLLM: Enhanced language models with tool use, structured output, and self-modification - InvokableEngine: Universal interface for any AI component (LLMs, retrievers, tools) - Multi-Provider Support: Seamlessly switch between OpenAI, Anthropic, Google, and more - Adaptive Configuration: Runtime reconfiguration without restarts

2. Dynamic Graph Workflows 🔀

Visual programming for AI - build complex behaviors through intuitive graphs: - BaseGraph: Foundation for stateful, persistent workflows - Conditional Routing: Intelligent path selection based on runtime conditions - Parallel Execution: Orchestrate multiple agents simultaneously - Time-Travel Debugging: Step through workflow history and restore states

3. Intelligent State Management 🧠

Beyond static data models - schemas that evolve with your AI: - StateSchema: Type-safe, self-documenting state containers - Dynamic Composition: Build schemas at runtime from multiple sources - Smart Reducers: Intelligent state merging with conflict resolution - Field Visibility: Sophisticated sharing between parent and child graphs

4. Enterprise Persistence Layer 💾

Never lose a conversation or state again: - PostgreSQL/Supabase: Production-ready persistence out of the box - Automatic Checkpointing: Save and restore complex workflows - Thread Management: Branching conversations with full history - Vector Memory: Semantic search across all interactions

5. Tool Ecosystem 🛠️

Give your AI real-world capabilities: - Type-Safe Tools: Full validation and error handling - Automatic Discovery: Find and register tools dynamically - Parallel Execution: Run multiple tools simultaneously - Tool Composition: Build complex tools from simple primitives

6. Common Utilities 🧰

Battle-tested components for production systems: - Mixins: Reusable behaviors (timestamps, IDs, state management) - Data Structures: Specialized trees, graphs, and collections - Type System: Runtime type checking and validation - Performance Helpers: Caching, memoization, and optimization

🚀 QUICK START

Examples

>>> from haive.core import AugLLMConfig, BaseGraph, StateSchema
>>> from haive.core.schema import Field
>>>
>>> # 1. Define your state
>>> class AgentState(StateSchema):
>>> messages: list = Field(default_factory=list)
>>> context: dict = Field(default_factory=dict)
>>> confidence: float = Field(default=0.0)
>>>
>>> # 2. Create an enhanced LLM
>>> llm = AugLLMConfig(
>>> model="gpt-4",
>>> temperature=0.7,
>>> tools=["web_search", "calculator"],
>>> structured_output_model=AnalysisResult
>>> )
>>>
>>> # 3. Build a workflow
>>> graph = BaseGraph(state_schema=AgentState)
>>> graph.add_node("analyze", analysis_node)
>>> graph.add_node("synthesize", synthesis_node)
>>> graph.add_edge("analyze", "synthesize")
>>>
>>> # 4. Execute with persistence
>>> app = graph.compile(checkpointer=PostgresCheckpointer())
>>> result = await app.ainvoke({"messages": ["Analyze market trends"]})

🎯 KEY INNOVATIONS

  1. Self-Modifying Architectures: Agents that rewrite their own graphs

  2. Semantic State Management: States that understand their own meaning

  3. Distributed Orchestration: Scale across multiple machines seamlessly

  4. Real-Time Collaboration: Multiple agents working on shared state

  5. Zero-Config Persistence: Automatic state saving with time-travel

📚 COMPREHENSIVE MODULES

  • engine/: Universal AI component interface (LLMs, tools, retrievers)

  • graph/: Visual workflow orchestration and state machines

  • schema/: Dynamic, type-safe state management

  • tools/: Tool creation, discovery, and execution

  • persistence/: Enterprise-grade data persistence

  • common/: Reusable utilities and patterns

  • types/: Type definitions and protocols

  • models/: Model configurations and providers

  • registry/: Dynamic component discovery

  • runtime/: Execution environment management

  • config/: Configuration management

  • utils/: Development and debugging tools

🌟 WHY HAIVE CORE?

For Developers: - Write 10x less code with powerful abstractions - Debug visually with graph workflows - Never worry about state management again - Scale from prototype to production seamlessly

For Enterprises: - Production-ready from day one - Full audit trails and compliance features - Multi-tenant support with isolation - Battle-tested by industry leaders

For Researchers: - Experiment with novel architectures - Build self-improving systems - Combine multiple AI paradigms - Publish reproducible workflows

🔗 ECOSYSTEM INTEGRATION

Haive Core seamlessly integrates with: - LangChain: Use any LangChain component - LangGraph: Enhanced with Haive’s persistence - OpenAI/Anthropic/Google: First-class support - Vector Databases: Pinecone, Weaviate, pgvector - Observability: OpenTelemetry, Datadog, etc.

💡 ADVANCED PATTERNS

>>> # Multi-Agent Orchestration
>>> from haive.core.graph import OrchestratorGraph
>>>
>>> orchestrator = OrchestratorGraph()
>>> orchestrator.add_agents({
>>> "researcher": ResearchAgent(),
>>> "analyst": AnalystAgent(),
>>> "writer": WriterAgent()
>>> })
>>> orchestrator.set_coordination_pattern("hierarchical")
>>>
>>> # Dynamic Schema Evolution
>>> from haive.core.schema import SchemaComposer
>>>
>>> composer = SchemaComposer()
>>> composer.add_fields_from_llm_output(llm_response)
>>> DynamicState = composer.build()
>>>
>>> # Self-Modifying Workflows
>>> from haive.core.graph import DynamicGraph
>>>
>>> graph = DynamicGraph()
>>> graph.add_mutation_rule(
>>> condition=lambda state: state.confidence < 0.5,
>>> action=lambda graph: graph.add_verification_node()
>>> )

🚨 ENTERPRISE FEATURES

  • 🔒 Security: End-to-end encryption, RBAC, audit logging

  • 📊 Monitoring: Real-time metrics, performance profiling

  • 🌍 Multi-Region: Distributed execution across data centers

  • ♻️ Fault Tolerance: Automatic failover and recovery

  • 📈 Scalability: Handle millions of concurrent workflows

🎓 LEARNING PATH

  1. Start with engine/ - understand the universal interface

  2. Explore schema/ - master state management

  3. Dive into graph/ - build visual workflows

  4. Experiment with tools/ - extend capabilities

  5. Deploy with persistence/ - production readiness

🤝 JOIN THE REVOLUTION

Haive Core isn’t just a framework - it’s a movement towards truly intelligent, self-evolving AI systems. Whether you’re building chatbots, autonomous agents, or the next breakthrough in AI, Haive Core provides the foundation you need.

Ready to build the future? Let’s go! 🚀

—

Version: 0.1.0 | License: MIT | Documentation: https://haive.ai/docs

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