add routing service (#814)

fixes https://github.com/katanemo/plano/issues/810

demos/llm_routing/model_routing_service/README.md

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+# Model Routing Service Demo
+
+This demo shows how to use the `/routing/v1/*` endpoints to get routing decisions without proxying requests to an LLM. The endpoint accepts standard LLM request formats and returns which model Plano's router would select.
+
+## Setup
+
+Make sure you have Plano CLI installed (`pip install planoai` or `uv tool install planoai`).
+
+```bash
+export OPENAI_API_KEY=<your-key>
+export ANTHROPIC_API_KEY=<your-key>
+```
+
+Start Plano:
+```bash
+cd demos/llm_routing/model_routing_service
+planoai up config.yaml
+```
+
+## Run the demo
+
+```bash
+./demo.sh
+```
+
+## Endpoints
+
+All three LLM API formats are supported:
+
+| Endpoint | Format |
+|---|---|
+| `POST /routing/v1/chat/completions` | OpenAI Chat Completions |
+| `POST /routing/v1/messages` | Anthropic Messages |
+| `POST /routing/v1/responses` | OpenAI Responses API |
+
+## Example
+
+```bash
+curl http://localhost:12000/routing/v1/chat/completions \
+  -H "Content-Type: application/json" \
+  -d '{
+    "model": "gpt-4o-mini",
+    "messages": [{"role": "user", "content": "Write a Python function for binary search"}]
+  }'
+```
+
+Response:
+```json
+{
+    "model": "anthropic/claude-sonnet-4-20250514",
+    "route": "code_generation",
+    "trace_id": "c16d1096c1af4a17abb48fb182918a88"
+}
+```
+
+The response tells you which model would handle this request and which route was matched, without actually making the LLM call.
+
+## Demo Output
+
+```
+=== Model Routing Service Demo ===
+
+--- 1. Code generation query (OpenAI format) ---
+{
+    "model": "anthropic/claude-sonnet-4-20250514",
+    "route": "code_generation",
+    "trace_id": "c16d1096c1af4a17abb48fb182918a88"
+}
+
+--- 2. Complex reasoning query (OpenAI format) ---
+{
+    "model": "openai/gpt-4o",
+    "route": "complex_reasoning",
+    "trace_id": "30795e228aff4d7696f082ed01b75ad4"
+}
+
+--- 3. Simple query - no routing match (OpenAI format) ---
+{
+    "model": "none",
+    "route": null,
+    "trace_id": "ae0b6c3b220d499fb5298ac63f4eac0e"
+}
+
+--- 4. Code generation query (Anthropic format) ---
+{
+    "model": "anthropic/claude-sonnet-4-20250514",
+    "route": "code_generation",
+    "trace_id": "26be822bbdf14a3ba19fe198e55ea4a9"
+}
+
+=== Demo Complete ===
+```

demos/llm_routing/model_routing_service/config.yaml

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+version: v0.3.0
+
+listeners:
+  - type: model
+    name: model_listener
+    port: 12000
+
+model_providers:
+
+  - model: openai/gpt-4o-mini
+    access_key: $OPENAI_API_KEY
+    default: true
+
+  - model: openai/gpt-4o
+    access_key: $OPENAI_API_KEY
+    routing_preferences:
+      - name: complex_reasoning
+        description: complex reasoning tasks, multi-step analysis, or detailed explanations
+
+  - model: anthropic/claude-sonnet-4-20250514
+    access_key: $ANTHROPIC_API_KEY
+    routing_preferences:
+      - name: code_generation
+        description: generating new code, writing functions, or creating boilerplate
+
+tracing:
+  random_sampling: 100

demos/llm_routing/model_routing_service/demo.sh

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+#!/bin/bash
+set -e
+
+PLANO_URL="${PLANO_URL:-http://localhost:12000}"
+
+echo "=== Model Routing Service Demo ==="
+echo ""
+echo "This demo shows how to use the /routing/v1/* endpoints to get"
+echo "routing decisions without actually proxying the request to an LLM."
+echo ""
+
+# --- Example 1: OpenAI Chat Completions format ---
+echo "--- 1. Code generation query (OpenAI format) ---"
+echo ""
+curl -s "$PLANO_URL/routing/v1/chat/completions" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "model": "gpt-4o-mini",
+    "messages": [
+      {"role": "user", "content": "Write a Python function that implements binary search on a sorted array"}
+    ]
+  }' | python3 -m json.tool
+echo ""
+
+# --- Example 2: Complex reasoning query ---
+echo "--- 2. Complex reasoning query (OpenAI format) ---"
+echo ""
+curl -s "$PLANO_URL/routing/v1/chat/completions" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "model": "gpt-4o-mini",
+    "messages": [
+      {"role": "user", "content": "Explain the trade-offs between microservices and monolithic architectures, considering scalability, team structure, and operational complexity"}
+    ]
+  }' | python3 -m json.tool
+echo ""
+
+# --- Example 3: Simple query (no routing match) ---
+echo "--- 3. Simple query - no routing match (OpenAI format) ---"
+echo ""
+curl -s "$PLANO_URL/routing/v1/chat/completions" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "model": "gpt-4o-mini",
+    "messages": [
+      {"role": "user", "content": "What is the capital of France?"}
+    ]
+  }' | python3 -m json.tool
+echo ""
+
+# --- Example 4: Anthropic Messages format ---
+echo "--- 4. Code generation query (Anthropic format) ---"
+echo ""
+curl -s "$PLANO_URL/routing/v1/messages" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "model": "gpt-4o-mini",
+    "max_tokens": 1024,
+    "messages": [
+      {"role": "user", "content": "Create a REST API endpoint in Rust using actix-web that handles user registration"}
+    ]
+  }' | python3 -m json.tool
+echo ""
+
+echo "=== Demo Complete ==="