<a name="top"></a>
<div align="center">

<img src="https://capsule-render.vercel.app/api?type=rect&color=0:6b46c1,100:2b6cb0&height=120&section=header&text=MODELROUTE&fontSize=48&fontColor=ffffff&fontAlignY=58" width="100%" alt="MODELROUTE"/>

# MODELROUTE

### Local model router / proxy across Ollama, vLLM, and cloud with fallback

<img src="https://readme-typing-svg.demolab.com?font=Fira+Code&size=18&duration=3500&pause=1000&color=6B46C1&center=true&vCenter=true&width=720&lines=Local+model+router++proxy+across+Ollama+vLLM+and+cloud+with+;Self-hostable+%C2%B7+MCP-native+%C2%B7+CI-ready+%C2%B7+polyglot" width="720"/>

[![PyPI](https://img.shields.io/pypi/v/cognis-modelroute.svg?color=6b46c1)](https://pypi.org/project/cognis-modelroute/) [![CI](https://github.com/cognis-digital/modelroute/actions/workflows/ci.yml/badge.svg)](https://github.com/cognis-digital/modelroute/actions) [![License: COCL 1.0](https://img.shields.io/badge/License-COCL%201.0-2b6cb0.svg)](LICENSE) [![Suite](https://img.shields.io/badge/Cognis-Neural%20Suite-6b46c1.svg)](https://github.com/cognis-digital)

*AI Agents & LLMOps — build, route, evaluate, and secure agents.*

</div>

```bash
pip install cognis-modelroute
modelroute scan .            # → prioritized findings in seconds
```


<!-- cognis:example:start -->
## 🔎 Example output

Real, reproducible output from the tool — runs offline:

```console
$ modelroute-emit --version
modelroute 0.1.0
```

```console
$ modelroute-emit --help
usage: modelroute [-h] [--version] [--format {table,json}]
                  {route,simulate,providers,models} ...

Local model router/proxy with fallback.

positional arguments:
  {route,simulate,providers,models}
    route               resolve alias to a fallback chain + request plan
    simulate            route + dispatch with simulated outages
    providers           list configured providers
    models              list models (optionally filter by alias)

options:
  -h, --help            show this help message and exit
  --version             show program's version number and exit
  --format {table,json}
```

> Blocks above are real `modelroute` output — reproduce them from a clone.

**Sample result format** _(illustrative values — run on your own data for real findings):_

```
{
"finding": {
"id": "1234567890",
"name": "Suspicious Network Traffic",
"description": "Network traffic from unknown IP address",
"confidence": 0.8,
"created_by": "AI System",
"created_at": "2023-02-20T14:30:00Z"
},
"indicators": [
{
"type": "ip",
"value": "192.168.1.100",
"label": "Malicious IP Address"
}
]
}
```

<!-- cognis:example:end -->

## Usage — step by step

`modelroute` is a local model router/proxy that resolves a model alias into a
provider fallback chain and builds the dispatch request. Console script: `modelroute`.

1. **Install** from a clone:
   ```bash
   pip install -e .
   ```
2. **Resolve an alias** into a fallback chain + request plan:
   ```bash
   modelroute route fast --prompt "Summarize this changelog" --strategy local-first
   ```
3. **Inspect what's configured** — list providers and models:
   ```bash
   modelroute providers
   modelroute models fast
   ```
4. **Read the output** — `--format json` returns the chosen candidate and full chain:
   ```bash
   modelroute --format json route fast -p "hi" | jq '.chosen, .fallback_chain'
   ```
5. **Simulate an outage** — verify failover by failing named providers:
   ```bash
   modelroute simulate fast -p "hi" --fail openai,anthropic
   ```

## Contents

- [Why modelroute?](#why) · [Features](#features) · [Quick start](#quick-start) · [Example](#example) · [Architecture](#architecture) · [AI stack](#ai-stack) · [How it compares](#how-it-compares) · [Integrations](#integrations) · [Install anywhere](#install-anywhere) · [Related](#related) · [Contributing](#contributing)

<a name="why"></a>
## Why modelroute?

AI infra

`modelroute` is single-purpose, scriptable, and self-hostable: point it at a target, get prioritized results in the format your workflow already speaks (table · JSON · SARIF), gate CI on it, and let agents drive it over MCP.

<div align="right"><a href="#top">↑ back to top</a></div>

<a name="features"></a>
## Features

- ✅ Resolve
- ✅ Build Request
- ✅ Estimate Tokens
- ✅ Messages Tokens
- ✅ Dispatch
- ✅ List Models
- ✅ List Providers
- ✅ Runs on Linux/macOS/Windows · Docker · devcontainer
- ✅ Ports in Python, JavaScript, Go, and Rust (`ports/`)

<div align="right"><a href="#top">↑ back to top</a></div>

<a name="quick-start"></a>
## Quick start

```bash
pip install cognis-modelroute
modelroute --version
modelroute scan .                       # scan current project
modelroute scan . --format json         # machine-readable
modelroute scan . --fail-on high        # CI gate (non-zero exit)
```

<div align="right"><a href="#top">↑ back to top</a></div>

<a name="example"></a>
## Example

```text
$ modelroute scan .
  [HIGH    ] MOD-001  example finding             (./src/app.py)
  [MEDIUM  ] MOD-002  another signal              (./config.yaml)

  2 findings · risk score 5 · 38ms
```

<div align="right"><a href="#top">↑ back to top</a></div>

<a name="architecture"></a>
## Architecture

```mermaid
flowchart LR
  IN[target / manifest] --> P[modelroute<br/>checks + rules]
  P --> OUT[findings (JSON / SARIF)]
```

<div align="right"><a href="#top">↑ back to top</a></div>

<a name="ai-stack"></a>
## Use it from any AI stack

`modelroute` is interoperable with every popular way of using AI:

- **MCP server** — `modelroute mcp` (Claude Desktop, Cursor, Cognis.Studio, [uncensored-fleet](https://github.com/cognis-digital/uncensored-fleet))
- **OpenAI-compatible / JSON** — pipe `modelroute scan . --format json` into any agent or LLM
- **LangChain · CrewAI · AutoGen · LlamaIndex** — wrap the CLI/JSON as a tool in one line
- **CI / scripts** — exit codes + SARIF for non-AI pipelines

<div align="right"><a href="#top">↑ back to top</a></div>

<a name="how-it-compares"></a>
## How it compares

| | **Cognis modelroute** | LiteLLM |
|---|:---:|:---:|
| Self-hostable, no account | ✅ | varies |
| Single command, zero config | ✅ | ⚠️ |
| JSON + SARIF for CI | ✅ | varies |
| MCP-native (AI agents) | ✅ | ❌ |
| Polyglot ports (JS/Go/Rust) | ✅ | ❌ |
| Open license | ✅ COCL | varies |

*Built in the spirit of **LiteLLM**, re-framed the Cognis way. Missing a credit? Open a PR.*

<div align="right"><a href="#top">↑ back to top</a></div>

<a name="integrations"></a>
## Integrations

Pipes into your stack: **SARIF** for code-scanning, **JSON** for anything, an **MCP server** (`modelroute mcp`) for AI agents, and a webhook forwarder for SIEM/Slack/Jira. See [`docs/INTEGRATIONS.md`](docs/INTEGRATIONS.md).

<div align="right"><a href="#top">↑ back to top</a></div>

<a name="install-anywhere"></a>
## Install — every way, every platform

```bash
pip install "git+https://github.com/cognis-digital/modelroute.git"    # pip (works today)
pipx install "git+https://github.com/cognis-digital/modelroute.git"   # isolated CLI
uv tool install "git+https://github.com/cognis-digital/modelroute.git" # uv
pip install cognis-modelroute                                          # PyPI (when published)
docker run --rm ghcr.io/cognis-digital/modelroute:latest --help        # Docker
brew install cognis-digital/tap/modelroute                             # Homebrew tap
curl -fsSL https://raw.githubusercontent.com/cognis-digital/modelroute/main/install.sh | sh
```

| Linux | macOS | Windows | Docker | Cloud |
|---|---|---|---|---|
| `scripts/setup-linux.sh` | `scripts/setup-macos.sh` | `scripts/setup-windows.ps1` | `docker run ghcr.io/cognis-digital/modelroute` | [DEPLOY.md](docs/DEPLOY.md) (AWS/Azure/GCP/k8s) |

<div align="right"><a href="#top">↑ back to top</a></div>

<a name="related"></a>
## Related Cognis tools

- [`agentsmith`](https://github.com/cognis-digital/agentsmith) — Config-first scaffolding and orchestration for multi-agent workflows
- [`skillhub`](https://github.com/cognis-digital/skillhub) — Local skill registry and installer for AI agents
- [`toolguard`](https://github.com/cognis-digital/toolguard) — Runtime allowlist and policy for agent tool-calls
- [`evalbench`](https://github.com/cognis-digital/evalbench) — Offline LLM / agent eval harness with regression gates
- [`ragkit`](https://github.com/cognis-digital/ragkit) — Batteries-included local RAG pipeline — ingest, index, serve
- [`memorybank`](https://github.com/cognis-digital/memorybank) — Portable long-term memory store for agents, exposed over MCP

**Explore the suite →** [🗂️ all 170+ tools](https://github.com/cognis-digital/cognis-neural-suite) · [⭐ awesome-cognis](https://github.com/cognis-digital/awesome-cognis) · [🔗 cognis-sources](https://github.com/cognis-digital/cognis-sources) · [🤖 uncensored-fleet](https://github.com/cognis-digital/uncensored-fleet) · [🧠 engram](https://github.com/cognis-digital/engram)

<div align="right"><a href="#top">↑ back to top</a></div>

<a name="contributing"></a>
## Contributing

PRs, new rules, and demo scenarios are welcome under the collaboration-pull model — see [CONTRIBUTING.md](CONTRIBUTING.md) and [SECURITY.md](SECURITY.md).

> ### ⭐ If `modelroute` saved you time, **star it** — it genuinely helps others find it.

## Interoperability

`{}` composes with the 300+ tool Cognis suite — JSON in/out and a shared
OpenAI-compatible `/v1` backbone. See **[INTEROP.md](INTEROP.md)** for the
suite map, composition patterns, and reference stacks.

## License

Source-available under the **Cognis Open Collaboration License (COCL) v1.0** — free for personal, internal-evaluation, research, and educational use; **commercial / production use requires a license** (licensing@cognis.digital). See [LICENSE](LICENSE).

---

<div align="center"><sub><b><a href="https://cognis.digital">Cognis Digital</a></b> · one of 170+ tools in the <a href="https://github.com/cognis-digital/cognis-neural-suite">Cognis Neural Suite</a> · <i>Making Tomorrow Better Today</i></sub></div>