Deterministic runtime for AI agents — enforce constraints, verify policies, audit decisions
Project description
chimera-runtime
Deterministic Runtime for AI Agents
Stop trusting LLMs. Start constraining them.
Quickstart • Constraints • Integrations • Dashboard • How It Works
The Problem
LLMs don't follow rules. They approximate them.
They hallucinate. They get prompt-injected. They break constraints silently. And yet, we hand them real-world decisions -- financial approvals, infrastructure changes, customer-facing actions -- and hope for the best.
Hope is not a runtime strategy.
The Solution
Chimera is a deterministic execution layer that sits between your AI agent and the real world.
Not a wrapper. Not a filter. Not another prompt engineering trick.
A runtime that enforces constraints outside the model, verifies policies with formal logic (Z3), and blocks invalid actions before they happen.
Every decision is: Checked. Proven. Enforced.
Agent Intent → Constraint Guard → ALLOW / BLOCK / ASK_HUMAN → Audit Record
No exceptions. No bypass. No "the model said it was fine."
Quickstart
pip install chimera-runtime
chimera-runtime init
chimera-runtime run
Three commands. Your agent is now constrained.
Define Constraints
Two paths. Same enforcement.
Option A: YAML Rules (zero dependencies)
# policies/governance.yaml
rules:
- name: manager_limit
when: "role == 'MANAGER' and amount > 250000"
then: BLOCK
message: "Managers cannot approve more than $250,000"
- name: weekend_freeze
when: "is_weekend == 'YES' and urgency != 'CRITICAL'"
then: BLOCK
message: "No changes on weekends unless critical"
Option B: CSL with Z3 Formal Verification (recommended)
CONFIG {
ENFORCEMENT_MODE: BLOCK
}
DOMAIN GovernanceGuard {
VARIABLES {
amount: 0..1000000
role: {"ANALYST", "MANAGER", "DIRECTOR", "VP", "CEO"}
}
STATE_CONSTRAINT manager_approval_limit {
WHEN role == "MANAGER"
THEN amount <= 250000
}
}
YAML gives you rules. CSL gives you mathematical proof that your constraints are consistent, reachable, and conflict-free -- before a single agent runs.
chimera-runtime verify policies/governance.csl
Framework Integrations
Chimera drops into whatever you're already using. No rewrites.
LangChain
from langchain_openai import ChatOpenAI
from chimera_runtime.integrations.langchain import wrap_tools, ChimeraCallbackHandler
guarded_tools = wrap_tools(your_tools, policy="./policies/governance.yaml")
handler = ChimeraCallbackHandler(policy="./policies/governance.yaml")
llm = ChatOpenAI(callbacks=[handler])
LangGraph
from chimera_runtime.integrations.langgraph import compliance_node
graph.add_node("constraint_gate", compliance_node(policy="./policies/governance.yaml"))
CrewAI
from chimera_runtime.integrations.crewai import wrap_crew_tools
guarded_tools = wrap_crew_tools(your_tools, policy="./policies/governance.yaml")
Direct Usage
from chimera_runtime import ChimeraAgent
agent = ChimeraAgent(
model="gpt-4o",
api_key="sk-...",
policy="./policies/governance.csl",
)
result = agent.decide(
"Approve $200k marketing spend for Q3",
context={"role": "MANAGER", "department": "MARKETING"},
)
print(result.result) # "ALLOWED"
print(result.action) # "Allocate $200k to digital channels"
Every tool call. Every decision. Through the constraint guard. No exceptions.
Dashboard
Full runtime control plane at compliance.chimera-protocol.com.
Real-time decision enforcement -- Live feed of every ALLOW, BLOCK, and ESCALATE. See exactly what your agents are doing and what they're being stopped from doing.
Policy management with formal verification -- Write, edit, and verify CSL policies. Z3 proves correctness before deployment. No untested constraints reach production.
Decision analytics & block rate heatmaps -- What's getting blocked, when, and why. Patterns across agents, frameworks, and time.
Framework integration wizard -- Four steps to wire Chimera into LangChain, LangGraph, CrewAI, LlamaIndex, or AutoGen.
How It Works
1. Define constraints in CSL
2. Z3 verifies correctness (reachability, consistency, conflict-freedom)
3. Runtime enforces at execution time
The model never sees the constraints. The model never evaluates the constraints. The model's opinion on whether it should be allowed to do something is irrelevant.
Constraints live outside the model. Enforcement happens outside the model. The model is a generator. Chimera is the governor.
CLI Reference
| Command | Description |
|---|---|
chimera-runtime init |
Initialize project with config and starter policy |
chimera-runtime run |
Interactive agent with real-time constraint enforcement |
chimera-runtime run --daemon |
Pipe mode for JSON stdin/stdout |
chimera-runtime stop [--force] |
Graceful or immediate halt |
chimera-runtime verify [POLICY] |
Verify CSL policy (syntax + Z3 + IR) |
chimera-runtime test [--skip-llm] |
End-to-end system test |
chimera-runtime audit --stats |
Aggregate decision statistics |
chimera-runtime audit --last 10 |
Recent decisions table |
chimera-runtime audit --export FILE |
Export records (json/compact/stats) |
chimera-runtime policy new NAME |
Create policy from template |
chimera-runtime policy list |
List and verify all policies |
chimera-runtime policy simulate FILE '{"k":"v"}' |
Test policy against input |
chimera-runtime explain --id ID |
Generate Art. 86 HTML explanation |
chimera-runtime docs generate |
Generate technical documentation |
chimera-runtime license status |
Show current license tier |
chimera-runtime license activate KEY |
Activate a license |
chimera-runtime license deactivate |
Remove license key |
EU AI Act
Compliance is a consequence -- not the product.
When you enforce deterministic constraints, maintain complete audit trails, and provide human oversight by design, you don't need to bolt on compliance after the fact. You already have it.
| Article | Requirement | How Chimera Delivers It |
|---|---|---|
| Art. 9 | Risk management | Formal verification (Z3) proves policy correctness before deployment |
| Art. 12 | Record-keeping | Complete DecisionAuditRecord for every decision, automatically |
| Art. 13 | Transparency | Full decision explanations, audit queries, HTML reports |
| Art. 14 | Human oversight | ASK_HUMAN escalation, confirm/override/halt with audit trail |
| Art. 15 | Accuracy & security | Deterministic constraint gate -- not probabilistic filtering |
| Art. 19 | Retention | Configurable retention with automatic enforcement |
| Art. 86 | Right to explanation | Self-contained HTML reports per decision |
| Annex IV | Technical documentation | Auto-generated (14/19 sections) |
Supported Frameworks & Providers
| Integration | Install | Notes |
|---|---|---|
| LangChain | pip install chimera-runtime[langchain] |
Tool wrapper + callback handler |
| LangGraph | pip install chimera-runtime[langgraph] |
Node guard + state checkpoint |
| LlamaIndex | pip install chimera-runtime[llamaindex] |
Tool spec + callback handler |
| CrewAI | pip install chimera-runtime[crewai] |
Tool wrapper for crews |
| AutoGen | pip install chimera-runtime[autogen] |
Agent wrapper |
| OpenAI | pip install chimera-runtime[openai] |
gpt-4o, gpt-4o-mini, o1, o3 |
| Anthropic | pip install chimera-runtime[anthropic] |
claude-sonnet-4-20250514, claude-opus-4-20250514 |
pip install chimera-runtime[google] |
gemini-2.0-flash, gemini-2.5-pro | |
| Ollama | pip install chimera-runtime[ollama] |
llama3, mistral, qwen (local) |
| CSL-Core | pip install chimera-runtime[csl] |
Z3 formal verification engine |
Development
git clone https://github.com/akarlaraytu/chimera-runtime
cd chimera-runtime
pip install -e ".[dev,all]"
pytest tests/ -v
License
Apache License 2.0 -- see LICENSE for details.
LLMs generate. Chimera governs.
Built by Aytug Akarlar
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