# HACS Core
**Foundation models for Healthcare Agent Communication Standard**
Core Pydantic models and base classes that define the healthcare AI communication protocol.
## 🏥 **Healthcare Models**
Essential healthcare data structures optimized for AI agent communication:
- **Patient** - Demographics, contact info, clinical context
- **Observation** - Clinical measurements, lab results, vital signs
- **Encounter** - Healthcare visits, episodes of care
- **Actor** - Healthcare providers with role-based permissions
- **MemoryBlock** - Structured memory for AI clinical reasoning
- **Evidence** - Clinical guidelines, research, decision support
## 🎯 **Key Features**
- **FHIR Compatible** - Full alignment with healthcare standards
- **AI Optimized** - Structured for LLM processing and tool calling
- **Validation Built-in** - Healthcare-specific validation rules
- **Actor Security** - Role-based access control for clinical data
- **Memory System** - Episodic, procedural, and executive memory types
## 📦 **Installation**
```bash
pip install hacs-core
```
## 🚀 **Quick Start**
```python
from hacs_core import Patient, Observation, Actor, MemoryBlock
# Healthcare provider
physician = Actor(
name="Dr. Sarah Chen",
role="PHYSICIAN",
organization="Mount Sinai Health System"
)
# Patient record
patient = Patient(
full_name="Maria Rodriguez",
birth_date="1985-03-15",
gender="female",
active=True
)
# Clinical observation
bp_reading = Observation(
code_text="Blood Pressure",
value="145/90",
unit="mmHg",
status="final",
patient_id=patient.id
)
# Clinical memory
memory = MemoryBlock(
content="Patient presents with elevated BP, discussed lifestyle modifications",
memory_type="episodic",
importance_score=0.8
)
```
## 🔗 **Integration**
HACS Core models work seamlessly with:
- **MCP Tools** - 25+ healthcare tools via Model Context Protocol
- **LangGraph** - AI agent workflows with clinical memory
- **PostgreSQL** - Persistent storage with pgvector
- **FHIR Systems** - Healthcare standards compliance
## 📄 **License**
Apache-2.0 License - see [LICENSE](../../LICENSE) for details.
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"description": "# HACS Core\n\n**Foundation models for Healthcare Agent Communication Standard**\n\nCore Pydantic models and base classes that define the healthcare AI communication protocol.\n\n## \ud83c\udfe5 **Healthcare Models**\n\nEssential healthcare data structures optimized for AI agent communication:\n\n- **Patient** - Demographics, contact info, clinical context\n- **Observation** - Clinical measurements, lab results, vital signs\n- **Encounter** - Healthcare visits, episodes of care\n- **Actor** - Healthcare providers with role-based permissions\n- **MemoryBlock** - Structured memory for AI clinical reasoning\n- **Evidence** - Clinical guidelines, research, decision support\n\n## \ud83c\udfaf **Key Features**\n\n- **FHIR Compatible** - Full alignment with healthcare standards\n- **AI Optimized** - Structured for LLM processing and tool calling\n- **Validation Built-in** - Healthcare-specific validation rules\n- **Actor Security** - Role-based access control for clinical data\n- **Memory System** - Episodic, procedural, and executive memory types\n\n## \ud83d\udce6 **Installation**\n\n```bash\npip install hacs-core\n```\n\n## \ud83d\ude80 **Quick Start**\n\n```python\nfrom hacs_core import Patient, Observation, Actor, MemoryBlock\n\n# Healthcare provider\nphysician = Actor(\n name=\"Dr. Sarah Chen\",\n role=\"PHYSICIAN\",\n organization=\"Mount Sinai Health System\"\n)\n\n# Patient record\npatient = Patient(\n full_name=\"Maria Rodriguez\",\n birth_date=\"1985-03-15\",\n gender=\"female\",\n active=True\n)\n\n# Clinical observation\nbp_reading = Observation(\n code_text=\"Blood Pressure\",\n value=\"145/90\",\n unit=\"mmHg\",\n status=\"final\",\n patient_id=patient.id\n)\n\n# Clinical memory\nmemory = MemoryBlock(\n content=\"Patient presents with elevated BP, discussed lifestyle modifications\",\n memory_type=\"episodic\",\n importance_score=0.8\n)\n```\n\n## \ud83d\udd17 **Integration**\n\nHACS Core models work seamlessly with:\n- **MCP Tools** - 25+ healthcare tools via Model Context Protocol\n- **LangGraph** - AI agent workflows with clinical memory\n- **PostgreSQL** - Persistent storage with pgvector\n- **FHIR Systems** - Healthcare standards compliance\n\n## \ud83d\udcc4 **License**\n\nApache-2.0 License - see [LICENSE](../../LICENSE) for details.\n",
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