From a89a9ffd31efab4cdcd76cae9096481b25dd92d8 Mon Sep 17 00:00:00 2001
From: Tarun Kumar Reddy Etikala <tetikala@redhat.com>
Date: Wed, 22 Jul 2026 12:20:19 -0400
Subject: [PATCH 01/25] feat(guardrails): scaffold guardrailed_agent directory
 (RHAIENG-6262)

Copy main.py, tracing.py, playground, LICENSE, .dockerignore from
react_agent template. Fix imports to guardrailed_agent package.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---
 .../examples/guardrailed_agent/.dockerignore  |  18 +
 .../examples/guardrailed_agent/LICENSE        |   3 +
 .../examples/guardrailed_agent/main.py        | 489 ++++++++++++++++++
 .../guardrailed_agent/playground/app.py       | 148 ++++++
 .../playground/templates/index.html           | 426 +++++++++++++++
 .../src/guardrailed_agent/__init__.py         |   0
 .../src/guardrailed_agent/tracing.py          | 174 +++++++
 .../guardrailed_agent/tests/__init__.py       |   0
 8 files changed, 1258 insertions(+)
 create mode 100644 agents/langgraph/examples/guardrailed_agent/.dockerignore
 create mode 100644 agents/langgraph/examples/guardrailed_agent/LICENSE
 create mode 100644 agents/langgraph/examples/guardrailed_agent/main.py
 create mode 100644 agents/langgraph/examples/guardrailed_agent/playground/app.py
 create mode 100644 agents/langgraph/examples/guardrailed_agent/playground/templates/index.html
 create mode 100644 agents/langgraph/examples/guardrailed_agent/src/guardrailed_agent/__init__.py
 create mode 100644 agents/langgraph/examples/guardrailed_agent/src/guardrailed_agent/tracing.py
 create mode 100644 agents/langgraph/examples/guardrailed_agent/tests/__init__.py

diff --git a/agents/langgraph/examples/guardrailed_agent/.dockerignore b/agents/langgraph/examples/guardrailed_agent/.dockerignore
new file mode 100644
index 00000000..ab4aafe3
--- /dev/null
+++ b/agents/langgraph/examples/guardrailed_agent/.dockerignore
@@ -0,0 +1,18 @@
+.env
+.env.*
+!.env.example
+.venv
+__pycache__
+*.pyc
+*.pyo
+.pytest_cache
+.mypy_cache
+.ruff_cache
+.git
+.gitignore
+.helm-secrets.yaml
+.DS_Store
+tests/
+examples/
+docs/
+*.md
diff --git a/agents/langgraph/examples/guardrailed_agent/LICENSE b/agents/langgraph/examples/guardrailed_agent/LICENSE
new file mode 100644
index 00000000..cac8466c
--- /dev/null
+++ b/agents/langgraph/examples/guardrailed_agent/LICENSE
@@ -0,0 +1,3 @@
+MIT License
+
+Copyright (c) 2026
diff --git a/agents/langgraph/examples/guardrailed_agent/main.py b/agents/langgraph/examples/guardrailed_agent/main.py
new file mode 100644
index 00000000..1ff819b2
--- /dev/null
+++ b/agents/langgraph/examples/guardrailed_agent/main.py
@@ -0,0 +1,489 @@
+import json
+import logging
+import time
+import uuid
+from collections.abc import AsyncIterator
+from contextlib import asynccontextmanager
+from os import getenv
+from pathlib import Path
+from typing import Any
+
+from fastapi import FastAPI, HTTPException
+from fastapi.responses import (
+    FileResponse,
+    HTMLResponse,
+    JSONResponse,
+    StreamingResponse,
+)
+from guardrailed_agent.agent import get_graph_closure
+from guardrailed_agent.tracing import enable_tracing
+from langchain_core.messages import AIMessage, HumanMessage, ToolMessage
+from pydantic import BaseModel, Field
+
+logger = logging.getLogger(__name__)
+
+
+# OpenAI-compatible request/response models
+class ChatMessage(BaseModel):
+    """A message in the conversation."""
+
+    role: str = Field(
+        ...,
+        description="The role of the message author.",
+        examples=["user", "assistant", "system", "tool"],
+    )
+    content: str = Field(
+        ...,
+        description="The contents of the message.",
+        examples=["What is the best cluster hosting service?"],
+    )
+
+
+class ChatCompletionRequest(BaseModel):
+    """Creates a model response for the given chat conversation.
+
+    [See OpenAI docs](https://platform.openai.com/docs/api-reference/chat/create)
+    """
+
+    messages: list[ChatMessage] = Field(
+        ...,
+        min_length=1,
+        description="A list of messages comprising the conversation so far.",
+    )
+    model: str | None = Field(
+        None,
+        description="ID of the model to use. Defaults to the server's configured MODEL_ID.",
+    )
+    stream: bool = Field(
+        False,
+        description="If true, partial message deltas will be sent as SSE `data: {json}\\n\\n` events, terminated by `data: [DONE]\\n\\n`.",
+    )
+
+
+class ChoiceMessage(BaseModel):
+    """A chat completion message generated by the model."""
+
+    role: str = Field(
+        "assistant", description="The role of the author of this message."
+    )
+    content: str = Field(..., description="The contents of the message.")
+
+
+class Choice(BaseModel):
+    index: int = Field(
+        ..., description="The index of the choice in the list of choices."
+    )
+    message: ChoiceMessage
+    finish_reason: str = Field(
+        ...,
+        description="The reason the model stopped generating tokens.",
+        examples=["stop", "tool_calls"],
+    )
+
+
+class ChatCompletionResponse(BaseModel):
+    """Represents a chat completion response returned by the model, based on the provided input."""
+
+    id: str = Field(
+        ...,
+        description="A unique identifier for the chat completion.",
+        examples=["chatcmpl-abc123def456"],
+    )
+    object: str = Field(
+        "chat.completion",
+        description="The object type, which is always `chat.completion`.",
+    )
+    created: int = Field(
+        ...,
+        description="The Unix timestamp (in seconds) of when the chat completion was created.",
+    )
+    model: str = Field(..., description="The model used for the chat completion.")
+    choices: list[Choice] = Field(..., description="A list of chat completion choices.")
+
+    usage: dict | None = Field(
+        None, description="Usage statistics for the completion request."
+    )
+
+
+class HealthResponse(BaseModel):
+    """Service health status."""
+
+    status: str = Field(
+        ..., description="Current service status.", examples=["healthy"]
+    )
+    agent_initialized: bool = Field(
+        ...,
+        description="Whether the agent has been initialized and is ready to serve requests.",
+    )
+
+
+# Global variable for agent graph
+agent_graph = None
+
+
+@asynccontextmanager
+async def lifespan(app: FastAPI) -> AsyncIterator[None]:
+    """Initialize the ReAct agent graph on startup and clear it on shutdown."""
+    global agent_graph
+
+    enable_tracing()
+
+    base_url = getenv("BASE_URL")
+    model_id = getenv("MODEL_ID")
+
+    if base_url and not base_url.endswith("/v1"):
+        base_url = base_url.rstrip("/") + "/v1"
+
+    agent_graph = get_graph_closure(model_id=model_id, base_url=base_url)
+
+    yield
+
+    agent_graph = None
+
+
+# Create FastAPI app
+app = FastAPI(
+    title="LangGraph React Agent API",
+    description="FastAPI service for LangGraph React Agent with OpenAI-compatible chat completions API.",
+    lifespan=lifespan,
+    openapi_tags=[
+        {"name": "Chat", "description": "Chat completion operations"},
+        {"name": "Health", "description": "Service health monitoring"},
+    ],
+)
+
+
+def _auth_enabled() -> bool:
+    return getenv("AUTH_ENABLED", "false").strip().lower() == "true"
+
+
+def _configure_auth_middleware() -> None:
+    if not _auth_enabled():
+        return
+
+    try:
+        from agent_auth.middleware import SATokenAuthMiddleware
+    except ModuleNotFoundError as exc:
+        raise RuntimeError(
+            "AUTH_ENABLED=true, but auth middleware dependencies are not installed. "
+            "Run `uv sync --extra auth` to enable ServiceAccount token auth locally."
+        ) from exc
+
+    app.add_middleware(SATokenAuthMiddleware)
+
+
+_configure_auth_middleware()
+
+
+def _build_langchain_messages(messages: list[ChatMessage]) -> list[HumanMessage]:
+    """Extract the last user message from the OpenAI-format messages list."""
+    for msg in reversed(messages):
+        if msg.role == "user":
+            return [HumanMessage(content=msg.content)]
+    raise ValueError("No user message found in messages list")
+
+
+def _extract_usage(messages: list) -> dict | None:
+    """Sum token usage from AIMessage.usage_metadata across all LLM calls."""
+    prompt_tokens = 0
+    completion_tokens = 0
+    total_tokens = 0
+    found = False
+    for message in messages:
+        if isinstance(message, AIMessage) and getattr(message, "usage_metadata", None):
+            meta = message.usage_metadata
+            prompt_tokens += meta.get("input_tokens", 0) or 0
+            completion_tokens += meta.get("output_tokens", 0) or 0
+            total_tokens += meta.get("total_tokens", 0) or 0
+            found = True
+    if not found:
+        return None
+    return {
+        "prompt_tokens": prompt_tokens,
+        "completion_tokens": completion_tokens,
+        "total_tokens": total_tokens,
+    }
+
+
+def _make_completion_id() -> str:
+    return f"chatcmpl-{uuid.uuid4().hex[:12]}"
+
+
+@app.post(
+    "/chat/completions",
+    response_model=ChatCompletionResponse,
+    summary="Create chat completion",
+    description="Creates a model response for the given chat conversation. When `stream=false`, returns a complete `chat.completion` JSON object. When `stream=true`, returns Server-Sent Events with `chat.completion.chunk` deltas.",
+    tags=["Chat"],
+)
+async def chat_completions(request: ChatCompletionRequest):
+    global agent_graph
+
+    if agent_graph is None:
+        raise HTTPException(status_code=503, detail="Agent not initialized")
+
+    langchain_messages = _build_langchain_messages(request.messages)
+    model_id = request.model or getenv("MODEL_ID") or "model"
+
+    if request.stream:
+        return await _handle_stream(langchain_messages, model_id)
+    else:
+        return await _handle_chat(langchain_messages, model_id)
+
+
+async def _handle_chat(messages: list[HumanMessage], model_id: str) -> dict[str, Any]:
+    """Handle non-streaming chat completion."""
+    global agent_graph
+
+    try:
+        result = await agent_graph.ainvoke(
+            {"messages": messages}, config={"recursion_limit": 10}
+        )
+
+        # Extract the final assistant message content
+        assistant_content = ""
+        context_messages = []
+
+        if "messages" in result and len(result["messages"]) > 0:
+            for message in result["messages"]:
+                if isinstance(message, HumanMessage):
+                    context_messages.append(
+                        {"role": "user", "content": message.content}
+                    )
+                elif isinstance(message, AIMessage):
+                    msg_data = {"role": "assistant", "content": message.content or ""}
+                    if message.tool_calls:
+                        msg_data["tool_calls"] = [
+                            {
+                                "id": tc["id"],
+                                "type": "function",
+                                "function": {
+                                    "name": tc["name"],
+                                    "arguments": json.dumps(tc["args"]),
+                                },
+                            }
+                            for tc in message.tool_calls
+                        ]
+                    context_messages.append(msg_data)
+                elif isinstance(message, ToolMessage):
+                    context_messages.append(
+                        {
+                            "role": "tool",
+                            "tool_call_id": message.tool_call_id,
+                            "name": message.name,
+                            "content": message.content,
+                        }
+                    )
+
+            # Final assistant content is the last AIMessage with content
+            for message in reversed(result["messages"]):
+                if isinstance(message, AIMessage) and message.content:
+                    assistant_content = message.content
+                    break
+
+        return {
+            "id": _make_completion_id(),
+            "object": "chat.completion",
+            "created": int(time.time()),
+            "model": model_id,
+            "choices": [
+                {
+                    "index": 0,
+                    "message": {
+                        "role": "assistant",
+                        "content": assistant_content,
+                    },
+                    "finish_reason": "stop",
+                }
+            ],
+            "context": context_messages,
+            "usage": _extract_usage(result.get("messages", [])),
+        }
+
+    except Exception as e:
+        raise HTTPException(
+            status_code=500, detail=f"Error processing request: {str(e)}"
+        )
+
+
+async def _handle_stream(
+    messages: list[HumanMessage], model_id: str
+) -> StreamingResponse:
+    """Handle streaming chat completion with OpenAI-compatible SSE chunks."""
+    global agent_graph
+
+    completion_id = _make_completion_id()
+    created = int(time.time())
+
+    async def event_generator() -> AsyncIterator[str]:
+        try:
+            async for event in agent_graph.astream_events(
+                {"messages": messages},
+                config={"recursion_limit": 10},
+                version="v2",
+            ):
+                kind = event["event"]
+
+                # LLM streaming tokens
+                if kind == "on_chat_model_stream":
+                    chunk = event["data"]["chunk"]
+                    if chunk.content:
+                        data = {
+                            "id": completion_id,
+                            "object": "chat.completion.chunk",
+                            "created": created,
+                            "model": model_id,
+                            "choices": [
+                                {
+                                    "index": 0,
+                                    "delta": {"content": chunk.content},
+                                    "finish_reason": None,
+                                }
+                            ],
+                        }
+                        yield f"data: {json.dumps(data)}\n\n"
+
+                # Tool calls (after LLM finishes generating the call)
+                elif kind == "on_chat_model_end":
+                    message = event["data"]["output"]
+                    if hasattr(message, "tool_calls") and message.tool_calls:
+                        tool_calls_delta = [
+                            {
+                                "index": i,
+                                "id": tc["id"],
+                                "type": "function",
+                                "function": {
+                                    "name": tc["name"],
+                                    "arguments": json.dumps(tc["args"]),
+                                },
+                            }
+                            for i, tc in enumerate(message.tool_calls)
+                        ]
+                        data = {
+                            "id": completion_id,
+                            "object": "chat.completion.chunk",
+                            "created": created,
+                            "model": model_id,
+                            "choices": [
+                                {
+                                    "index": 0,
+                                    "delta": {
+                                        "role": "assistant",
+                                        "tool_calls": tool_calls_delta,
+                                    },
+                                    "finish_reason": None,
+                                }
+                            ],
+                        }
+                        yield f"data: {json.dumps(data)}\n\n"
+
+                # Tool execution results
+                elif kind == "on_tool_end":
+                    output = event["data"].get("output", "")
+                    if hasattr(output, "content"):
+                        output = output.content
+                    data = {
+                        "id": completion_id,
+                        "object": "chat.completion.chunk",
+                        "created": created,
+                        "model": model_id,
+                        "choices": [
+                            {
+                                "index": 0,
+                                "delta": {
+                                    "role": "tool",
+                                    "content": str(output),
+                                    "name": event.get("name", ""),
+                                },
+                                "finish_reason": None,
+                            }
+                        ],
+                    }
+                    yield f"data: {json.dumps(data)}\n\n"
+
+            # Send final chunk with finish_reason
+            final_data = {
+                "id": completion_id,
+                "object": "chat.completion.chunk",
+                "created": created,
+                "model": model_id,
+                "choices": [
+                    {
+                        "index": 0,
+                        "delta": {},
+                        "finish_reason": "stop",
+                    }
+                ],
+            }
+            yield f"data: {json.dumps(final_data)}\n\n"
+            yield "data: [DONE]\n\n"
+
+        except Exception:
+            logger.exception("Error in stream event_generator")
+            error_data = {
+                "error": {
+                    "message": "Internal server error",
+                    "type": "server_error",
+                }
+            }
+            yield f"data: {json.dumps(error_data)}\n\n"
+
+    return StreamingResponse(
+        event_generator(),
+        media_type="text/event-stream",
+        headers={"Cache-Control": "no-cache", "X-Accel-Buffering": "no"},
+    )
+
+
+@app.get(
+    "/health", response_model=HealthResponse, summary="Health check", tags=["Health"]
+)
+async def health():
+    initialized = agent_graph is not None
+    body = {
+        "status": "healthy" if initialized else "not_ready",
+        "agent_initialized": initialized,
+    }
+    if not initialized:
+        return JSONResponse(status_code=503, content=body)
+    return body
+
+
+# ── Playground UI ────────────────────────────────────────────────────────────
+_BASE_DIR = Path(__file__).resolve().parent
+_PLAYGROUND_HTML = _BASE_DIR / "playground" / "templates" / "index.html"
+# In Docker the images are copied to /opt/app-root/src/images; locally they live at the repo root
+_IMAGES_DIR = _BASE_DIR / "images"
+if not _IMAGES_DIR.is_dir():
+    _IMAGES_DIR = _BASE_DIR.parent.parent.parent / "images"
+
+
+@app.get("/", response_class=HTMLResponse, include_in_schema=False)
+async def playground():
+    """Serve the playground chat UI."""
+    if _auth_enabled():
+        raise HTTPException(status_code=404, detail="Not found")
+    return FileResponse(_PLAYGROUND_HTML)
+
+
+@app.get("/images/{filename:path}", include_in_schema=False)
+async def serve_image(filename: str):
+    """Serve images from the project-level images directory."""
+    if _auth_enabled():
+        raise HTTPException(status_code=404, detail="Not found")
+    base = _IMAGES_DIR.resolve()
+    file_path = (base / filename).resolve()
+    try:
+        file_path.relative_to(base)
+    except ValueError:
+        raise HTTPException(status_code=404, detail="Image not found")
+    if not file_path.is_file():
+        raise HTTPException(status_code=404, detail="Image not found")
+    return FileResponse(file_path)
+
+
+if __name__ == "__main__":
+    import uvicorn
+
+    port = int(getenv("PORT", 8000))
+    uvicorn.run(app, host="0.0.0.0", port=port)
diff --git a/agents/langgraph/examples/guardrailed_agent/playground/app.py b/agents/langgraph/examples/guardrailed_agent/playground/app.py
new file mode 100644
index 00000000..7a0ab47f
--- /dev/null
+++ b/agents/langgraph/examples/guardrailed_agent/playground/app.py
@@ -0,0 +1,148 @@
+"""
+Playground UI for the LangGraph ReAct Agent.
+
+A simple Flask chat interface that proxies requests to the agent's
+/chat/completions endpoint with streaming support.
+
+Usage:
+    # Make sure the agent is running first (default: http://localhost:8000)
+    cd agents/langgraph/react_agent
+    flask --app playground/app run --port 5001
+
+    # Or with a custom agent URL:
+    AGENT_URL=http://localhost:8000 flask --app playground/app run --port 5001
+"""
+
+import json
+import logging
+from os import getenv
+from pathlib import Path
+
+import requests as http_requests
+from flask import (
+    Flask,
+    Response,
+    jsonify,
+    render_template,
+    request,
+    send_from_directory,
+    stream_with_context,
+)
+
+logging.basicConfig(level=logging.DEBUG)
+logger = logging.getLogger(__name__)
+
+IMAGES_DIR = Path(__file__).resolve().parents[4] / "images"
+
+app = Flask(__name__)
+
+
+@app.route("/images/<path:filename>")
+def serve_image(filename):
+    """Serve images from the project-level images directory."""
+    return send_from_directory(IMAGES_DIR, filename)
+
+
+AGENT_URL = getenv("AGENT_URL", "http://localhost:8000")
+
+
+@app.route("/")
+def index():
+    return render_template("index.html")
+
+
+@app.route("/api/health", methods=["GET"])
+def health():
+    """Check if the agent is reachable."""
+    try:
+        resp = http_requests.get(f"{AGENT_URL}/health", timeout=5)
+        return jsonify(resp.json()), resp.status_code
+    except Exception:
+        logger.exception("Error checking agent health")
+        return (
+            jsonify(
+                {
+                    "status": "unreachable",
+                    "error": "Agent is unreachable. Please try again later.",
+                }
+            ),
+            503,
+        )
+
+
+@app.route("/api/chat", methods=["POST"])
+def chat():
+    """Proxy chat requests to the agent with streaming."""
+    data = request.get_json() or {}
+    messages = data.get("messages", [])
+
+    payload = {
+        "messages": messages,
+        "stream": True,
+    }
+
+    logger.info(
+        f"Sending request to {AGENT_URL}/chat/completions (messages={len(payload.get('messages', []))}, stream={payload.get('stream')})"
+    )
+
+    def generate():
+        try:
+            with http_requests.post(
+                f"{AGENT_URL}/chat/completions",
+                json=payload,
+                stream=True,
+                timeout=(10, 300),
+            ) as resp:
+                logger.info(f"Agent response status: {resp.status_code}")
+
+                if resp.status_code != 200:
+                    error_msg = resp.text[:500]
+                    logger.error(f"Agent error: {error_msg}")
+                    error = json.dumps(
+                        {
+                            "error": {
+                                "message": f"Agent returned {resp.status_code}: {error_msg}"
+                            }
+                        }
+                    )
+                    yield f"data: {error}\n\n"
+                    return
+
+                for chunk in resp.iter_content(chunk_size=None, decode_unicode=True):
+                    if chunk:
+                        logger.debug(f"Chunk: {chunk[:200]}")
+                        yield chunk
+
+        except http_requests.exceptions.ConnectionError:
+            logger.error(f"Cannot connect to agent at {AGENT_URL}")
+            error = json.dumps(
+                {
+                    "error": {
+                        "message": f"Cannot connect to agent at {AGENT_URL}. Is it running?"
+                    }
+                }
+            )
+            yield f"data: {error}\n\n"
+        except http_requests.exceptions.ReadTimeout:
+            logger.error("Agent request timed out")
+            error = json.dumps({"error": {"message": "Agent request timed out (300s)"}})
+            yield f"data: {error}\n\n"
+        except Exception:
+            logger.exception("Unexpected error in proxy")
+            error = json.dumps({"error": {"message": "Internal server error"}})
+            yield f"data: {error}\n\n"
+
+    return Response(
+        stream_with_context(generate()),
+        content_type="text/event-stream",
+        headers={
+            "Cache-Control": "no-cache",
+            "X-Accel-Buffering": "no",
+            "Connection": "keep-alive",
+        },
+    )
+
+
+if __name__ == "__main__":
+    debug_mode = getenv("FLASK_DEBUG", "false").lower() == "true"
+    app.run(debug=debug_mode, port=5001)
diff --git a/agents/langgraph/examples/guardrailed_agent/playground/templates/index.html b/agents/langgraph/examples/guardrailed_agent/playground/templates/index.html
new file mode 100644
index 00000000..65221a3d
--- /dev/null
+++ b/agents/langgraph/examples/guardrailed_agent/playground/templates/index.html
@@ -0,0 +1,426 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>LangGraph ReAct Agent — Playground</title>
+    <style>
+        * { margin: 0; padding: 0; box-sizing: border-box; }
+
+        body {
+            font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, sans-serif;
+            background: #f5f5f5;
+            height: 100vh;
+            display: flex;
+            flex-direction: column;
+        }
+
+        /* Header */
+        .header {
+            background: #1a1a2e;
+            color: #fff;
+            padding: 16px 24px;
+            font-size: 18px;
+            font-weight: 600;
+            display: flex;
+            align-items: center;
+            gap: 10px;
+        }
+        .header .status-dot {
+            width: 10px; height: 10px;
+            border-radius: 50%;
+            background: #888;
+        }
+        .header .status-dot.connected { background: #4caf50; }
+        .header .status-dot.error { background: #f44336; }
+
+        /* Chat area */
+        .chat-container {
+            flex: 1;
+            overflow-y: auto;
+            padding: 24px;
+            display: flex;
+            flex-direction: column;
+            gap: 16px;
+            position: relative;
+        }
+        .chat-container .watermark {
+            position: sticky;
+            top: 50%;
+            left: 50%;
+            transform: translate(-50%, -50%);
+            opacity: 0.08;
+            pointer-events: none;
+            z-index: 0;
+            margin: auto;
+            height: 0;
+            display: flex;
+            align-items: center;
+            justify-content: center;
+        }
+        .chat-container .watermark img {
+            width: 280px;
+            height: auto;
+        }
+        .chat-container .message {
+            position: relative;
+            z-index: 1;
+        }
+
+        .message {
+            max-width: 75%;
+            padding: 12px 16px;
+            border-radius: 16px;
+            line-height: 1.5;
+            font-size: 14px;
+            word-wrap: break-word;
+            white-space: pre-wrap;
+        }
+
+        .message.user {
+            align-self: flex-end;
+            background: #1a1a2e;
+            color: #fff;
+            border-bottom-right-radius: 4px;
+        }
+
+        .message.assistant {
+            align-self: flex-start;
+            background: #fff;
+            color: #1a1a1a;
+            border-bottom-left-radius: 4px;
+            box-shadow: 0 1px 3px rgba(0,0,0,0.1);
+        }
+
+        .message.assistant.streaming {
+            border-left: 3px solid #1a1a2e;
+        }
+
+        .message.error {
+            align-self: center;
+            background: #fee;
+            color: #c00;
+            border: 1px solid #fcc;
+            font-size: 13px;
+            max-width: 90%;
+        }
+
+        .message .meta {
+            display: flex;
+            justify-content: space-between;
+            align-items: center;
+            margin-bottom: 4px;
+        }
+        .message .label {
+            font-size: 11px;
+            font-weight: 600;
+            text-transform: uppercase;
+            letter-spacing: 0.5px;
+            opacity: 0.6;
+        }
+        .message .timestamp {
+            font-size: 10px;
+            opacity: 0.5;
+            font-variant-numeric: tabular-nums;
+        }
+
+        /* Typing indicator */
+        .typing-indicator {
+            display: inline-flex;
+            gap: 4px;
+            padding: 8px 0;
+        }
+        .typing-indicator span {
+            width: 6px; height: 6px;
+            border-radius: 50%;
+            background: #999;
+            animation: blink 1.4s infinite both;
+        }
+        .typing-indicator span:nth-child(2) { animation-delay: 0.2s; }
+        .typing-indicator span:nth-child(3) { animation-delay: 0.4s; }
+        @keyframes blink {
+            0%, 80%, 100% { opacity: 0.3; }
+            40% { opacity: 1; }
+        }
+
+        /* Input area */
+        .input-area {
+            padding: 16px 24px;
+            background: #fff;
+            border-top: 1px solid #e0e0e0;
+            display: flex;
+            gap: 12px;
+        }
+
+        .input-area textarea {
+            flex: 1;
+            padding: 12px 16px;
+            border: 1px solid #ddd;
+            border-radius: 12px;
+            font-size: 14px;
+            font-family: inherit;
+            resize: none;
+            outline: none;
+            min-height: 48px;
+            max-height: 120px;
+        }
+        .input-area textarea:focus {
+            border-color: #1a1a2e;
+        }
+
+        .input-area button {
+            padding: 0 24px;
+            background: #1a1a2e;
+            color: #fff;
+            border: none;
+            border-radius: 12px;
+            font-size: 14px;
+            font-weight: 600;
+            cursor: pointer;
+            transition: background 0.2s;
+        }
+        .input-area button:hover { background: #16213e; }
+        .input-area button:disabled {
+            background: #ccc;
+            cursor: not-allowed;
+        }
+    </style>
+</head>
+<body>
+
+<div class="header">
+    <div class="status-dot" id="statusDot"></div>
+    LangGraph ReAct Agent — Playground
+</div>
+
+<div class="chat-container" id="chat">
+    <div class="watermark">
+        <img src="/images/rh_logo.svg" alt="">
+    </div>
+</div>
+
+<div class="input-area">
+    <textarea id="input" placeholder="Type your message..." rows="1"
+              onkeydown="if(event.key==='Enter' && !event.shiftKey){event.preventDefault(); sendMessage();}"></textarea>
+    <button id="sendBtn" onclick="sendMessage()">Send</button>
+</div>
+
+<script>
+    const chat = document.getElementById('chat');
+    const input = document.getElementById('input');
+    const sendBtn = document.getElementById('sendBtn');
+    const statusDot = document.getElementById('statusDot');
+
+    const conversationHistory = [];
+
+    // Check agent health on load
+    async function checkHealth() {
+        try {
+            const resp = await fetch('/health');
+            const data = await resp.json();
+            if (data.status === 'healthy' && data.agent_initialized) {
+                statusDot.className = 'status-dot connected';
+                console.log('Agent connected:', data);
+            } else {
+                statusDot.className = 'status-dot error';
+                console.warn('Agent not ready:', data);
+            }
+        } catch (e) {
+            statusDot.className = 'status-dot error';
+            console.error('Health check failed:', e);
+        }
+    }
+    checkHealth();
+
+    function formatTimestamp() {
+        const now = new Date();
+        const pad = (n) => String(n).padStart(2, '0');
+        return `${pad(now.getHours())}:${pad(now.getMinutes())}:${pad(now.getSeconds())} - ${now.getFullYear()}.${pad(now.getMonth() + 1)}.${pad(now.getDate())}`;
+    }
+
+    function addMessage(role, content, extra) {
+        const div = document.createElement('div');
+        div.className = `message ${role}`;
+        if (extra) div.classList.add(extra);
+
+        const meta = document.createElement('div');
+        meta.className = 'meta';
+
+        const label = document.createElement('div');
+        label.className = 'label';
+        label.textContent = role === 'user' ? 'You' : (role === 'error' ? 'Error' : 'Agent');
+        meta.appendChild(label);
+
+        const ts = document.createElement('div');
+        ts.className = 'timestamp';
+        ts.textContent = formatTimestamp();
+        meta.appendChild(ts);
+
+        div.appendChild(meta);
+
+        const text = document.createElement('div');
+        text.textContent = content;
+        div.appendChild(text);
+
+        chat.appendChild(div);
+        chat.scrollTop = chat.scrollHeight;
+        return text;
+    }
+
+    function addTypingIndicator() {
+        const div = document.createElement('div');
+        div.className = 'message assistant streaming';
+        div.id = 'typing';
+
+        const label = document.createElement('div');
+        label.className = 'label';
+        label.textContent = 'Agent';
+        div.appendChild(label);
+
+        const indicator = document.createElement('div');
+        indicator.className = 'typing-indicator';
+        indicator.innerHTML = '<span></span><span></span><span></span>';
+        div.appendChild(indicator);
+
+        chat.appendChild(div);
+        chat.scrollTop = chat.scrollHeight;
+    }
+
+    function removeTypingIndicator() {
+        const el = document.getElementById('typing');
+        if (el) el.remove();
+    }
+
+    function setLoading(loading) {
+        sendBtn.disabled = loading;
+        input.disabled = loading;
+    }
+
+    async function sendMessage() {
+        const text = input.value.trim();
+        if (!text) return;
+
+        input.value = '';
+        input.style.height = 'auto';
+        addMessage('user', text);
+        conversationHistory.push({ role: 'user', content: text });
+
+        setLoading(true);
+        addTypingIndicator();
+
+        let assistantContent = '';
+        let textEl = null;
+
+        try {
+            console.log('Sending message:', text);
+
+            const response = await fetch('/chat/completions', {
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({ messages: conversationHistory, stream: true }),
+            });
+
+            console.log('Response status:', response.status);
+
+            if (!response.ok) {
+                removeTypingIndicator();
+                const errorText = await response.text();
+                console.error('HTTP error:', response.status, errorText);
+                addMessage('error', `HTTP ${response.status}: ${errorText}`);
+                setLoading(false);
+                return;
+            }
+
+            const reader = response.body.getReader();
+            const decoder = new TextDecoder();
+            let buffer = '';
+
+            while (true) {
+                const { done, value } = await reader.read();
+                if (done) {
+                    console.log('Stream done');
+                    break;
+                }
+
+                const chunk = decoder.decode(value, { stream: true });
+                console.log('Raw chunk:', chunk);
+                buffer += chunk;
+
+                const parts = buffer.split('\n\n');
+                buffer = parts.pop();
+
+                for (const part of parts) {
+                    const lines = part.split('\n');
+                    for (const line of lines) {
+                        if (!line.startsWith('data: ')) continue;
+                        const payload = line.slice(6).trim();
+                        if (payload === '[DONE]') {
+                            console.log('Received [DONE]');
+                            continue;
+                        }
+
+                        try {
+                            const parsed = JSON.parse(payload);
+                            console.log('Parsed SSE:', parsed);
+
+                            // Handle error responses
+                            if (parsed.error) {
+                                removeTypingIndicator();
+                                addMessage('error', parsed.error.message || 'Unknown error');
+                                setLoading(false);
+                                return;
+                            }
+
+                            const delta = parsed.choices?.[0]?.delta;
+                            if (delta?.content) {
+                                if (!textEl) {
+                                    removeTypingIndicator();
+                                    textEl = addMessage('assistant', '', 'streaming');
+                                }
+                                assistantContent += delta.content;
+                                textEl.textContent = assistantContent;
+                                chat.scrollTop = chat.scrollHeight;
+                            }
+                        } catch (e) {
+                            console.warn('Failed to parse SSE line:', payload, e);
+                        }
+                    }
+                }
+            }
+
+            // Remove streaming indicator
+            if (textEl) {
+                textEl.parentElement.classList.remove('streaming');
+            } else {
+                // No content was streamed
+                removeTypingIndicator();
+                if (!assistantContent) {
+                    addMessage('error', 'Agent returned empty response. Check the agent terminal for errors.');
+                }
+            }
+
+            if (assistantContent) {
+                conversationHistory.push({ role: 'assistant', content: assistantContent });
+            }
+
+        } catch (err) {
+            console.error('Fetch error:', err);
+            removeTypingIndicator();
+            addMessage('error', `Connection error: ${err.message}`);
+        }
+
+        setLoading(false);
+        input.focus();
+    }
+
+    // Auto-resize textarea
+    input.addEventListener('input', function() {
+        this.style.height = 'auto';
+        this.style.height = Math.min(this.scrollHeight, 120) + 'px';
+    });
+
+    input.focus();
+</script>
+
+</body>
+</html>
diff --git a/agents/langgraph/examples/guardrailed_agent/src/guardrailed_agent/__init__.py b/agents/langgraph/examples/guardrailed_agent/src/guardrailed_agent/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/agents/langgraph/examples/guardrailed_agent/src/guardrailed_agent/tracing.py b/agents/langgraph/examples/guardrailed_agent/src/guardrailed_agent/tracing.py
new file mode 100644
index 00000000..486f9aae
--- /dev/null
+++ b/agents/langgraph/examples/guardrailed_agent/src/guardrailed_agent/tracing.py
@@ -0,0 +1,174 @@
+import logging
+import os
+import time
+from os import getenv
+from typing import Optional
+
+from dotenv import load_dotenv
+
+logger = logging.getLogger("tracing")
+logger.setLevel(logging.INFO)
+if not logger.handlers:
+    handler = logging.StreamHandler()
+    formatter = logging.Formatter("[%(asctime)s] [%(levelname)s] %(message)s")
+    handler.setFormatter(formatter)
+    logger.addHandler(handler)
+
+
+def check_mlflow_health(
+    mlflow_tracking_uri: str, max_wait_time: int = 5, retry_interval: int = 1
+) -> None:
+    """
+    Check MLflow health by trying the /health endpoint. If it fails, retry for a certain duration before giving up.
+    args:
+        mlflow_tracking_uri: base URI of the MLflow server
+        max_wait_time: total time to keep retrying before giving up (in seconds)
+        retry_interval: time to wait between retries (in seconds)
+    """
+    import requests
+
+    mlflow_health_endpoint = "/health"
+    mlflow_url = f"{mlflow_tracking_uri.rstrip('/')}{mlflow_health_endpoint}"
+
+    # Build auth and TLS config. This is only needed for
+    # the raw requests.get() health check. The MLflow client SDK
+    # handles these env vars natively for all other calls.
+    # See docs/mlflow-openshift-auth-and-tls.md for full details.
+    headers = {}
+    token = getenv("MLFLOW_TRACKING_TOKEN")
+    tracking_auth = getenv("MLFLOW_TRACKING_AUTH", "")
+    if token:
+        headers["Authorization"] = f"Bearer {token}"
+        logger.debug("[Health Check] Using MLFLOW_TRACKING_TOKEN for authentication")
+    elif tracking_auth in ("kubernetes", "kubernetes-namespaced"):
+        sa_token_path = "/var/run/secrets/kubernetes.io/serviceaccount/token"
+        if not os.path.isfile(sa_token_path):
+            logger.warning(
+                "[Health Check] MLFLOW_TRACKING_AUTH=%s but SA token not found at %s",
+                tracking_auth,
+                sa_token_path,
+            )
+        else:
+            with open(sa_token_path) as f:
+                headers["Authorization"] = f"Bearer {f.read().strip()}"
+            logger.debug(
+                "[Health Check] Using MLFLOW_TRACKING_AUTH=%s for authentication",
+                tracking_auth,
+            )
+
+    cert_path = getenv("MLFLOW_TRACKING_SERVER_CERT_PATH")
+    if getenv("MLFLOW_TRACKING_INSECURE_TLS", "").lower() in ("true", "1", "yes"):
+        verify = False
+        logger.warning(
+            "[Health Check] TLS verification disabled (MLFLOW_TRACKING_INSECURE_TLS=true). "
+            "Consider using MLFLOW_TRACKING_SERVER_CERT_PATH instead."
+        )
+    elif cert_path:
+        if not os.path.isfile(cert_path):
+            logger.warning(
+                "[Health Check] MLFLOW_TRACKING_SERVER_CERT_PATH does not exist: %s — falling back to system CAs",
+                cert_path,
+            )
+            verify = True
+        else:
+            verify = cert_path
+            logger.debug("[Health Check] TLS verify using cert: %s", cert_path)
+    else:
+        verify = True
+
+    start_time = time.time()
+
+    while True:
+        remaining = max_wait_time - (time.time() - start_time)
+        if remaining <= 0:
+            logger.error(
+                f"MLflow server is unavailable after {max_wait_time} seconds of checking."
+            )
+            raise RuntimeError(
+                "MLflow server is unavailable. Please start the server or check the URI."
+            )
+
+        try:
+            response = requests.get(
+                mlflow_url, timeout=min(5, remaining), headers=headers, verify=verify
+            )
+            if response.status_code == 200:
+                logger.info(
+                    f"MLflow health check passed at {mlflow_url} with status code {response.status_code}."
+                )
+                return  # Success, exit the function without error
+            else:
+                logger.warning(
+                    f"MLflow returned status code {response.status_code} at {mlflow_url}\n"
+                    f"  Status Code: {response.status_code}\n"
+                    f"  Reason: {response.reason}"
+                )
+        except requests.exceptions.RequestException as e:
+            logger.warning(f"Failed to connect to MLflow at {mlflow_url}: {e}")
+
+        logger.warning(f"Retrying in {retry_interval} seconds...")
+        time.sleep(retry_interval)
+
+
+def enable_tracing() -> None:
+    """
+    Enable MLflow tracing if MLFLOW_TRACKING_URI is set.
+
+    Behavior:
+    1. If MLFLOW_TRACKING_URI is not set: tracing is skipped.
+    2. If MLFLOW_TRACKING_URI is set:
+       - Try to connect to the server.
+       - If the server is reachable: tracing is enabled.
+       - If the server is unreachable: log a warning and continue without tracing.
+    """
+    load_dotenv()
+    tracking_uri: Optional[str] = getenv("MLFLOW_TRACKING_URI")
+    if not tracking_uri:
+        logger.info("[Tracing] MLFLOW_TRACKING_URI not set. Tracing is disabled.")
+        return
+
+    try:
+        import mlflow
+        import mlflow.langchain
+    except ModuleNotFoundError as e:
+        raise ModuleNotFoundError(
+            "MLFLOW_TRACKING_URI is set but mlflow is not installed. "
+            "Install it with: uv sync --extra tracing"
+        ) from e
+
+    # Check if server is reachable
+    try:
+        try:
+            health_check_timeout = int(getenv("MLFLOW_HEALTH_CHECK_TIMEOUT", "5"))
+        except ValueError:
+            health_check_timeout = 5
+        check_mlflow_health(
+            mlflow_tracking_uri=tracking_uri, max_wait_time=health_check_timeout
+        )
+        logger.info(f"[Tracing] MLflow server is reachable at {tracking_uri}")
+    except RuntimeError as e:
+        logger.warning(
+            f"[Tracing] MLflow server is unreachable at {tracking_uri}. "
+            f"Tried connecting for {health_check_timeout}s. Continuing without tracing. Error: {e}"
+        )
+        return
+
+    # Server is reachable → enable tracing
+    try:
+        mlflow.set_tracking_uri(tracking_uri)
+        experiment_name: str = getenv(
+            "MLFLOW_EXPERIMENT_NAME", "default-agent-experiment"
+        )
+        mlflow.set_experiment(experiment_name)
+        mlflow.config.enable_async_logging()
+
+        mlflow.langchain.autolog()
+
+        logger.info(
+            f"[Tracing Enabled] MLflow -> {tracking_uri}, Experiment: {experiment_name}"
+        )
+    except Exception as e:
+        logger.warning(
+            f"[Tracing] Failed to configure MLflow tracing at {tracking_uri}. "
+            f"Continuing without tracing. Error: {e}"
+        )
diff --git a/agents/langgraph/examples/guardrailed_agent/tests/__init__.py b/agents/langgraph/examples/guardrailed_agent/tests/__init__.py
new file mode 100644
index 00000000..e69de29b

From 3c3bf96bbfa25ea6cee505c8d281b37724441351 Mon Sep 17 00:00:00 2001
From: Tarun Kumar Reddy Etikala <tetikala@redhat.com>
Date: Wed, 22 Jul 2026 12:21:12 -0400
Subject: [PATCH 02/25] feat(guardrails): add banking agent source with
 check_account_balance tool (RHAIENG-6262)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---
 .../src/guardrailed_agent/agent.py            | 62 +++++++++++++++++++
 .../src/guardrailed_agent/tools.py            | 27 ++++++++
 2 files changed, 89 insertions(+)
 create mode 100644 agents/langgraph/examples/guardrailed_agent/src/guardrailed_agent/agent.py
 create mode 100644 agents/langgraph/examples/guardrailed_agent/src/guardrailed_agent/tools.py

diff --git a/agents/langgraph/examples/guardrailed_agent/src/guardrailed_agent/agent.py b/agents/langgraph/examples/guardrailed_agent/src/guardrailed_agent/agent.py
new file mode 100644
index 00000000..aec33bea
--- /dev/null
+++ b/agents/langgraph/examples/guardrailed_agent/src/guardrailed_agent/agent.py
@@ -0,0 +1,62 @@
+from os import getenv
+from typing import Any
+
+from langchain.agents import create_agent
+from langchain_openai import ChatOpenAI
+
+from guardrailed_agent.tools import check_account_balance
+
+
+def get_graph_closure(
+    model_id: str | None = None,
+    base_url: str | None = None,
+    api_key: str | None = None,
+) -> Any:
+    """Build and return a LangGraph ReAct agent for banking customer service.
+
+    Creates a ChatOpenAI client, wires check_account_balance tool,
+    and uses create_agent to produce a graph that runs the ReAct loop.
+
+    Args:
+        model_id: LLM model identifier. Uses MODEL_ID env if omitted.
+        base_url: Base URL for the LLM API. Uses BASE_URL env if omitted.
+        api_key: API key for the LLM. Uses API_KEY env if omitted.
+
+    Returns:
+        A LangGraph agent (CompiledGraph) that accepts {"messages": [...]} and returns updated state.
+    """
+
+    if not api_key:
+        api_key = getenv("API_KEY")
+    if not base_url:
+        base_url = getenv("BASE_URL")
+    if not model_id:
+        model_id = getenv("MODEL_ID")
+
+    if not base_url:
+        raise ValueError(
+            "BASE_URL is required. Set it via argument or BASE_URL env var."
+        )
+    is_local = any(host in base_url for host in ["localhost", "127.0.0.1"])
+
+    if not is_local and not api_key:
+        raise ValueError("API_KEY is required for non-local environments.")
+
+    tools = [check_account_balance]
+
+    chat = ChatOpenAI(
+        model=model_id,
+        temperature=0.01,
+        api_key=api_key,
+        base_url=base_url,
+    )
+
+    system_prompt = """You are a customer service assistant for a retail bank.
+        You help customers with account inquiries, billing, payments, and general
+        banking questions. When you receive a result from a tool, use that
+        information to provide a FINAL answer to the customer immediately.
+        Do NOT call tools repeatedly for the same question.
+        Always be professional and helpful."""
+    agent = create_agent(model=chat, tools=tools, system_prompt=system_prompt)
+
+    return agent
diff --git a/agents/langgraph/examples/guardrailed_agent/src/guardrailed_agent/tools.py b/agents/langgraph/examples/guardrailed_agent/src/guardrailed_agent/tools.py
new file mode 100644
index 00000000..5ca4e84d
--- /dev/null
+++ b/agents/langgraph/examples/guardrailed_agent/src/guardrailed_agent/tools.py
@@ -0,0 +1,27 @@
+from langchain_core.tools import tool
+from pydantic import BaseModel, Field
+
+
+class AccountInput(BaseModel):
+    """Schema for the account balance tool input."""
+
+    account_id: str = Field(description="The customer account ID to look up.")
+
+
+@tool("check_balance", parse_docstring=True)
+def check_account_balance(account_id: str) -> str:
+    """Check the account balance for a bank customer.
+
+    Placeholder implementation that returns a fixed balance for demonstration.
+    Replace with a real banking API integration in production.
+
+    Args:
+        account_id: The customer account ID. Example: "ACCT-12345"
+
+    Returns:
+        A string with the account balance information.
+    """
+    return (
+        f"Account {account_id}: Checking balance $2,450.00, "
+        f"Savings balance $12,800.50. Last transaction: -$45.99 on 2026-07-20."
+    )

From c4cc1f7bce255c1ae6ccd6eac571f0a0d28fd6e4 Mon Sep 17 00:00:00 2001
From: Tarun Kumar Reddy Etikala <tetikala@redhat.com>
Date: Wed, 22 Jul 2026 12:22:50 -0400
Subject: [PATCH 03/25] feat(guardrails): add NeMo Guardrails safety config
 (RHAIENG-6262)

Layered input rails: regex (instant) -> content safety (S1-S13) ->
topic safety (banking domain). Output rail: content safety check.
Streaming enabled. Self-check classification (main LLM judges safety).
config.yaml (not .yml) + rails.co required by RHOAI entrypoint.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---
 .../guardrails/safety/config.yaml             | 45 ++++++++++
 .../guardrails/safety/prompts.yml             | 89 +++++++++++++++++++
 .../guardrails/safety/rails.co                | 12 +++
 3 files changed, 146 insertions(+)
 create mode 100644 agents/langgraph/examples/guardrailed_agent/guardrails/safety/config.yaml
 create mode 100644 agents/langgraph/examples/guardrailed_agent/guardrails/safety/prompts.yml
 create mode 100644 agents/langgraph/examples/guardrailed_agent/guardrails/safety/rails.co

diff --git a/agents/langgraph/examples/guardrailed_agent/guardrails/safety/config.yaml b/agents/langgraph/examples/guardrailed_agent/guardrails/safety/config.yaml
new file mode 100644
index 00000000..1239d890
--- /dev/null
+++ b/agents/langgraph/examples/guardrailed_agent/guardrails/safety/config.yaml
@@ -0,0 +1,45 @@
+# NeMo Guardrails configuration for the guardrailed agent.
+# Model endpoints below are defaults for local Ollama. To use a different LLM:
+#   1. Edit the base_url and model values below, OR
+#   2. Run `make guardrails-config` to update from .env (LLM_BASE_URL, MODEL_ID)
+models:
+  - type: main
+    engine: openai
+    model: llama3.1:8b
+    parameters:
+      base_url: http://localhost:11434/v1
+    api_key_env_var: API_KEY
+
+  - type: content_safety
+    engine: openai
+    model: llama3.1:8b
+    parameters:
+      base_url: http://localhost:11434/v1
+    api_key_env_var: API_KEY
+
+  - type: topic_control
+    engine: openai
+    model: llama3.1:8b
+    parameters:
+      base_url: http://localhost:11434/v1
+    api_key_env_var: API_KEY
+
+rails:
+  config:
+    regex_detection:
+      input:
+        patterns:
+          - "\\b(hack|exploit|bypass|inject)\\s+(the|this|my)\\s+(system|filter|guardrail)"
+          - "ignore\\s+(all\\s+)?(previous|above)\\s+(instructions|rules|prompts)"
+          - "\\bDAN\\b.*\\bjailbreak\\b"
+        case_insensitive: true
+  input:
+    flows:
+      - regex check input
+      - content safety check input $model=content_safety
+      - topic safety check input $model=topic_control
+  output:
+    flows:
+      - content safety check output $model=content_safety
+    streaming:
+      enabled: True
diff --git a/agents/langgraph/examples/guardrailed_agent/guardrails/safety/prompts.yml b/agents/langgraph/examples/guardrailed_agent/guardrails/safety/prompts.yml
new file mode 100644
index 00000000..e42c8e7b
--- /dev/null
+++ b/agents/langgraph/examples/guardrailed_agent/guardrails/safety/prompts.yml
@@ -0,0 +1,89 @@
+prompts:
+  - task: content_safety_check_input $model=content_safety
+    content: |
+      Task: Check if there is unsafe content in the user message below in accordance with our safety policy. Provide a 'safe' or 'unsafe' rating.
+
+      <BEGIN UNSAFE CONTENT CATEGORIES>
+      S1: Violence.
+      S2: Sexual.
+      S3: Criminal Planning/Confessions.
+      S4: Guns and Illegal Weapons.
+      S5: Controlled/Regulated Substances.
+      S6: Suicide and Self Harm.
+      S7: Sexual (minor).
+      S8: Hate/Identity Hate.
+      S9: PII/Privacy.
+      S10: Harassment.
+      S11: Threat.
+      S12: Profanity.
+      S13: Needs Caution.
+      <END UNSAFE CONTENT CATEGORIES>
+
+      <BEGIN CONVERSATION>
+
+      user: {{ user_input }}
+
+      <END CONVERSATION>
+
+      Provide your safety assessment for the above conversation in the below output JSON format:
+      {"User Safety": safe or unsafe rating for the user message, "Safety Categories": a comma-separated list of applicable safety categories from the provided taxonomy. Omit if all safe.}
+
+      Do not include anything other than the output JSON in your response.
+      Output JSON:
+    output_parser: nemoguard_parse_prompt_safety
+    max_tokens: 50
+
+  - task: content_safety_check_output $model=content_safety
+    content: |
+      Task: Check if there is unsafe content in the agent response below in accordance with our safety policy. Provide a 'safe' or 'unsafe' rating.
+
+      <BEGIN UNSAFE CONTENT CATEGORIES>
+      S1: Violence.
+      S2: Sexual.
+      S3: Criminal Planning/Confessions.
+      S4: Guns and Illegal Weapons.
+      S5: Controlled/Regulated Substances.
+      S6: Suicide and Self Harm.
+      S7: Sexual (minor).
+      S8: Hate/Identity Hate.
+      S9: PII/Privacy.
+      S10: Harassment.
+      S11: Threat.
+      S12: Profanity.
+      S13: Needs Caution.
+      <END UNSAFE CONTENT CATEGORIES>
+
+      <BEGIN CONVERSATION>
+
+      user: {{ user_input }}
+
+      response: agent: {{ bot_response }}
+
+      <END CONVERSATION>
+
+      Provide your safety assessment for the above conversation in the below output JSON format:
+      {"User Safety": safe or unsafe rating for the user message, "Response Safety": safe or unsafe rating for the agent response, "Safety Categories": a comma-separated list of applicable safety categories from the provided taxonomy. Omit if all safe.}
+
+      Do not include anything other than the output JSON in your response.
+      Output JSON:
+    output_parser: nemoguard_parse_response_safety
+    max_tokens: 50
+
+  - task: topic_safety_check_input $model=topic_control
+    content: |
+      You are a topic boundary classifier for a customer service assistant at a retail bank. The assistant helps customers with their banking needs only.
+
+      Guidelines for the user messages:
+      - Allow questions about account balances, transactions, and account history.
+      - Allow questions about billing, payments, and due dates.
+      - Allow questions about bank products, services, interest rates, and fees.
+      - Allow questions about branch locations, hours, and contact information.
+      - Allow questions about online banking, mobile app, and password resets.
+      - Allow small talk and greetings.
+      - Do not answer questions about medical or health advice.
+      - Do not answer questions about legal advice or legal proceedings.
+      - Do not answer questions about specific investment recommendations or stock picks.
+      - Do not answer questions about cooking, recipes, or food preparation.
+      - Do not answer questions about entertainment, sports, or celebrity gossip.
+      - Do not answer questions about personal relationships or dating advice.
+      - If a user asks topics irrelevant to banking and financial services, politely redirect.
diff --git a/agents/langgraph/examples/guardrailed_agent/guardrails/safety/rails.co b/agents/langgraph/examples/guardrailed_agent/guardrails/safety/rails.co
new file mode 100644
index 00000000..49925545
--- /dev/null
+++ b/agents/langgraph/examples/guardrailed_agent/guardrails/safety/rails.co
@@ -0,0 +1,12 @@
+define user express greeting
+  "Hello"
+  "Hi"
+  "Hey"
+  "Good morning"
+
+define flow
+  user express greeting
+  bot express greeting
+
+define bot express greeting
+  "Hello! Welcome to our banking service. How can I help you today?"

From d0914f19ed7c9bdbf0ad0b707be4a13a8c976537 Mon Sep 17 00:00:00 2001
From: Tarun Kumar Reddy Etikala <tetikala@redhat.com>
Date: Wed, 22 Jul 2026 12:23:46 -0400
Subject: [PATCH 04/25] feat(guardrails): add project config files
 (RHAIENG-6262)

nemoguardrails[server]==0.21.0 pinned as optional 'guardrails' extra.
BASE_URL defaults to NeMo proxy (localhost:8090/v1).
Agent env vars: GUARDRAILS_PORT, LLM_BASE_URL for local dev.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---
 .../examples/guardrailed_agent/.env.example   | 27 ++++++++++
 .../examples/guardrailed_agent/agent.yaml     | 27 ++++++++++
 .../examples/guardrailed_agent/pyproject.toml | 50 +++++++++++++++++++
 .../examples/guardrailed_agent/values.yaml    | 11 ++++
 4 files changed, 115 insertions(+)
 create mode 100644 agents/langgraph/examples/guardrailed_agent/.env.example
 create mode 100644 agents/langgraph/examples/guardrailed_agent/agent.yaml
 create mode 100644 agents/langgraph/examples/guardrailed_agent/pyproject.toml
 create mode 100644 agents/langgraph/examples/guardrailed_agent/values.yaml

diff --git a/agents/langgraph/examples/guardrailed_agent/.env.example b/agents/langgraph/examples/guardrailed_agent/.env.example
new file mode 100644
index 00000000..ac90c3cf
--- /dev/null
+++ b/agents/langgraph/examples/guardrailed_agent/.env.example
@@ -0,0 +1,27 @@
+# Required — agent connects to NeMo Guardrails proxy, not directly to the LLM
+API_KEY=not-needed-for-local-development
+BASE_URL=http://localhost:8090/v1
+MODEL_ID=llama3.1:8b
+
+# NeMo Guardrails — the proxy server that sits between the agent and the LLM
+# Start with: make guardrails-server
+# The guardrails server config is in guardrails/safety/config.yaml
+# GUARDRAILS_PORT=8090
+# LLM_BASE_URL=http://localhost:11434/v1
+
+# Deployment
+#CONTAINER_IMAGE=
+
+# Auth (local default off; comma-separate multiple allowlist entries)
+# AUTH_ENABLED=false
+# AUTH_AUDIENCE=langgraph-guardrailed-agent
+# AUTH_ALLOWED_SERVICEACCOUNTS=ci-testing:langgraph-guardrailed-agent-caller
+
+# Optional — MLflow Tracing
+# Tracing is opt-in: if MLFLOW_TRACKING_URI is not set, the agent runs without MLflow.
+# Note: MLflow traces show the overall request but not guardrails internals.
+# NeMo Guardrails appears as a regular ChatOpenAI endpoint in MLflow.
+
+# --- Local MLflow server (no auth, no TLS) ---
+# MLFLOW_TRACKING_URI=http://localhost:5000
+# MLFLOW_EXPERIMENT_NAME=langgraph-guardrailed-agent
diff --git a/agents/langgraph/examples/guardrailed_agent/agent.yaml b/agents/langgraph/examples/guardrailed_agent/agent.yaml
new file mode 100644
index 00000000..105436e1
--- /dev/null
+++ b/agents/langgraph/examples/guardrailed_agent/agent.yaml
@@ -0,0 +1,27 @@
+name: langgraph-guardrailed-agent
+displayName: "LangGraph Guardrailed Agent"
+framework: langgraph
+description: >
+  FSI customer service agent with NeMo Guardrails safety layer.
+  Demonstrates content safety rails (input + output), topical guardrails
+  (banking domain boundary), and regex-based input filtering using the
+  NeMo Guardrails proxy pattern. Built on the LangGraph ReAct agent template.
+labels:
+  - guardrails
+  - nemo-guardrails
+  - safety
+  - customer-service
+  - react
+env:
+  required:
+    - API_KEY
+    - BASE_URL
+    - MODEL_ID
+  optional:
+    - PORT
+    - CONTAINER_IMAGE
+    - GUARDRAILS_PORT
+    - LLM_BASE_URL
+    - AUTH_ENABLED
+    - AUTH_AUDIENCE
+    - AUTH_ALLOWED_SERVICEACCOUNTS
diff --git a/agents/langgraph/examples/guardrailed_agent/pyproject.toml b/agents/langgraph/examples/guardrailed_agent/pyproject.toml
new file mode 100644
index 00000000..5d700b51
--- /dev/null
+++ b/agents/langgraph/examples/guardrailed_agent/pyproject.toml
@@ -0,0 +1,50 @@
+[project]
+name = "guardrailed_agent"
+version = "0.1.0"
+description = "An FSI customer service agent with NeMo Guardrails safety layer. Demonstrates content safety, topical guardrails, and regex filtering using the proxy pattern."
+authors = [{ name = "Your Name", email = "you@example.com" }]
+license = { text = "MIT" }
+requires-python = ">=3.12,<=3.14"
+dependencies = [
+    "fastapi>=0.135.1",
+    "uvicorn[standard]>=0.41.0",
+    "langchain>=1.2.10",
+    "langchain-openai>=1.1.10",
+    "langgraph-prebuilt>=1.0.8",
+    "openai>=2.24.0",
+    "milvus-lite>=2.5.1",
+    "pymilvus==2.6.9",
+    "python-dotenv>=1.2.2",
+    "setuptools>=80.9.0,<83.0.0",
+    "chardet>=7.1.0",
+    "pypdf>=6.9.0",
+    "flask>=3.1.0",
+    "starlette>=1.0.1",
+    "protobuf<7",
+]
+
+[project.optional-dependencies]
+auth = [
+    "agent-auth",
+]
+dev = [
+    "pytest>=9.0.2",
+    "httpx>=0.27",
+    "pyyaml>=6.0",
+]
+guardrails = [
+    "nemoguardrails[server]==0.21.0",
+]
+tracing = [
+    "mlflow[kubernetes]>=3.11.0",
+]
+
+[tool.setuptools.packages.find]
+where = ["src"]
+
+[tool.uv.sources]
+agent-auth = { path = "../../../../components/auth" }
+
+[build-system]
+requires = ["setuptools>=80.9.0"]
+build-backend = "setuptools.build_meta"
diff --git a/agents/langgraph/examples/guardrailed_agent/values.yaml b/agents/langgraph/examples/guardrailed_agent/values.yaml
new file mode 100644
index 00000000..3531f788
--- /dev/null
+++ b/agents/langgraph/examples/guardrailed_agent/values.yaml
@@ -0,0 +1,11 @@
+nameOverride: "langgraph-guardrailed-agent"
+
+env:
+  MODEL_ID: ""
+  BASE_URL: ""
+
+auth:
+  enabled: false
+  audience: "langgraph-guardrailed-agent"
+  allowedServiceAccounts: []
+  createAuthDelegatorBinding: true

From 60136726295413a11273501e56abdda14d30d629 Mon Sep 17 00:00:00 2001
From: Tarun Kumar Reddy Etikala <tetikala@redhat.com>
Date: Wed, 22 Jul 2026 12:26:37 -0400
Subject: [PATCH 05/25] feat(guardrails): add Makefile and Dockerfile
 (RHAIENG-6262)

Makefile adds guardrails-config (update config from .env) and
guardrails-server (start NeMo proxy on port 8090).
env target installs nemoguardrails via --extra guardrails.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---
 .../examples/guardrailed_agent/Dockerfile     |  45 ++++
 .../examples/guardrailed_agent/Makefile       | 222 ++++++++++++++++++
 2 files changed, 267 insertions(+)
 create mode 100644 agents/langgraph/examples/guardrailed_agent/Dockerfile
 create mode 100644 agents/langgraph/examples/guardrailed_agent/Makefile

diff --git a/agents/langgraph/examples/guardrailed_agent/Dockerfile b/agents/langgraph/examples/guardrailed_agent/Dockerfile
new file mode 100644
index 00000000..2d499583
--- /dev/null
+++ b/agents/langgraph/examples/guardrailed_agent/Dockerfile
@@ -0,0 +1,45 @@
+# Use Red Hat UBI9 Python 3.12 image (no Docker Hub rate limits on OpenShift)
+# To update: docker pull registry.access.redhat.com/ubi9/python-312:latest
+#            docker inspect --format='{{index .RepoDigests 0}}' registry.access.redhat.com/ubi9/python-312:latest
+FROM registry.access.redhat.com/ubi9/python-312@sha256:e95978812895b9abb2bdc109b501078da2a47c8dbb9fa23758af40ed50ab6023
+WORKDIR /opt/app-root/src/agents/langgraph/examples/guardrailed_agent
+
+# Switch to root for installing dependencies
+USER 0
+
+# Install uv for fast dependency management (v0.11.1)
+# To update: docker pull ghcr.io/astral-sh/uv:latest
+#            docker inspect --format='{{index .RepoDigests 0}}' ghcr.io/astral-sh/uv:latest
+COPY --from=ghcr.io/astral-sh/uv@sha256:fc93e9ecd7218e9ec8fba117af89348eef8fd2463c50c13347478769aaedd0ce /uv /usr/local/bin/uv
+
+# Copy project files for dependency installation.
+# Keep the repo-relative layout so ../../../../components/auth resolves.
+COPY pyproject.toml .
+COPY src/ ./src/
+COPY components/auth/ /opt/app-root/src/components/auth/
+
+# Install the project and its dependencies using uv
+RUN uv pip install --no-cache ".[tracing,auth]"
+
+# Copy the application entrypoint, playground UI, and images
+COPY main.py .
+COPY playground/ ./playground/
+COPY images/ ./images/
+
+# Make everything group-writable (GID 0) for OpenShift arbitrary UID support
+RUN chown -R 1001:0 /opt/app-root/src \
+    && chmod -R g=u /opt/app-root/src
+
+# Switch back to default non-root user
+USER 1001
+
+# Expose port 8080 (OpenShift standard)
+EXPOSE 8080
+
+# Set environment variables
+ENV PORT=8080
+ENV HOME=/opt/app-root
+ENV PYTHONPATH=/opt/app-root/src/agents/langgraph/examples/guardrailed_agent
+
+# Run the application — reads PORT at runtime
+CMD ["sh", "-c", "uvicorn main:app --host 0.0.0.0 --port ${PORT}"]
diff --git a/agents/langgraph/examples/guardrailed_agent/Makefile b/agents/langgraph/examples/guardrailed_agent/Makefile
new file mode 100644
index 00000000..5d608fc9
--- /dev/null
+++ b/agents/langgraph/examples/guardrailed_agent/Makefile
@@ -0,0 +1,222 @@
+SHELL          := bash
+AGENT_NAME     := $(shell python3 -c "import re; print(re.search(r'^name:\s*(.+)', open('agent.yaml').read(), re.M).group(1).strip())")
+CHART_DIR      := ../../deployment
+VALUES_FILE    := values.yaml
+CONTAINER_CLI  := $(shell command -v podman 2>/dev/null || command -v docker 2>/dev/null)
+MODEL          ?= llama3.1:8b
+
+.PHONY: init re-init env ollama ogx-server run-app run-app-fresh build push build-openshift deploy undeploy test test-integration test-auth-integration dry-run help guardrails-config guardrails-server
+
+help: ## Show this help
+	@grep -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "  %-20s %s\n", $$1, $$2}'
+
+re-init: ## Activate venv and reload .env variables
+	@source .venv/bin/activate && set -a && source .env && set +a && \
+	  echo "Venv activated and .env variables loaded."
+
+init: ## Copy .env.example to .env for configuration
+	@if [ ! -f .env ]; then cp .env.example .env && echo "Created .env from .env.example - edit it with your configuration"; else echo ".env already exists - skipping"; fi
+
+env: ## Create venv, load .env, and install dependencies (add --extra guardrails for NeMo)
+	@echo "==> Creating virtual environment and installing dependencies..." && \
+	  rm -rf .venv && \
+	  uv sync --python 3.12 --extra guardrails && \
+	  echo "==> Load .env variables..." && \
+	  source .venv/bin/activate && set -a && source .env && set +a && \
+	  echo "" && \
+	  echo "Done. Next steps:" && \
+	  echo "  make ollama             # install Ollama and pull models" && \
+	  echo "  make guardrails-server  # start NeMo Guardrails proxy" && \
+	  echo "  make run-app            # start the agent"
+
+ollama: ## Install Ollama, start it, and pull models
+	@source .venv/bin/activate && set -a && source .env && set +a && \
+	if command -v ollama >/dev/null 2>&1; then \
+	  echo "==> Ollama already installed, skipping..."; \
+	else \
+	  echo "==> Installing Ollama..." && \
+	  curl -fsSL https://ollama.com/install.sh | sh; \
+	fi && \
+	  echo "==> Starting Ollama service..." && \
+	  ollama serve &>/dev/null & \
+	  OLLAMA_PID=$$! && \
+	  echo "Waiting for Ollama to be ready (max 30s)..." && \
+	  OLLAMA_WAIT=0 && \
+	  until ollama list >/dev/null 2>&1; do \
+	    OLLAMA_WAIT=$$((OLLAMA_WAIT + 1)); \
+	    if [ $$OLLAMA_WAIT -ge 30 ]; then \
+	      echo "ERROR: Ollama failed to start within 30 seconds." && \
+	      kill $$OLLAMA_PID 2>/dev/null; \
+	      exit 1; \
+	    fi; \
+	    sleep 1; \
+	  done && \
+	  echo "==> Pulling $(MODEL)..." && \
+	  ollama pull $(MODEL) && \
+	  echo "" && \
+	  echo "Done. Run 'make guardrails-server' to start NeMo Guardrails."
+
+guardrails-config: ## Update guardrails config.yaml with LLM endpoint from .env
+	@source .venv/bin/activate && set -a && source .env && set +a && \
+	  LLM_URL=$${LLM_BASE_URL:-http://localhost:11434/v1} && \
+	  MODEL=$${MODEL_ID:-llama3.1:8b} && \
+	  sed -i.bak \
+	    -e "s|base_url:.*|base_url: $$LLM_URL|g" \
+	    -e "s|model:.*|model: $$MODEL|g" \
+	    guardrails/safety/config.yaml && \
+	  rm -f guardrails/safety/config.yaml.bak && \
+	  echo "Updated guardrails/safety/config.yaml with LLM_BASE_URL=$$LLM_URL MODEL_ID=$$MODEL"
+
+guardrails-server: ## Start NeMo Guardrails server on GUARDRAILS_PORT (default 8090)
+	@source .venv/bin/activate && set -a && source .env && set +a && \
+	  echo "Starting NeMo Guardrails server on port $${GUARDRAILS_PORT:-8090}..." && \
+	  nemoguardrails server --config guardrails --default-config-id safety --port $${GUARDRAILS_PORT:-8090} --disable-chat-ui
+
+run-app: ## Run agent locally with hot-reload
+	@source .venv/bin/activate && set -a && source .env && set +a && \
+	  if lsof -ti:$${PORT:-8000} >/dev/null 2>&1; then \
+	    echo "ERROR: Port $${PORT:-8000} is already in use." && \
+	    echo "  Change PORT in .env or run: make run-app-fresh" && \
+	    exit 1; \
+	  fi && \
+	  uv run $${MLFLOW_TRACKING_URI:+--extra tracing} uvicorn main:app --host 127.0.0.1 --port $${PORT:-8000} --reload --reload-exclude .venv
+
+run-app-fresh: ## Kill existing process on port and run agent with hot-reload
+	@source .venv/bin/activate && set -a && source .env && set +a && \
+	  echo "==> Killing existing process on port $${PORT:-8000}..." && \
+	  lsof -ti:$${PORT:-8000} | xargs kill -9 2>/dev/null; true && \
+	  uv run $${MLFLOW_TRACKING_URI:+--extra tracing} uvicorn main:app --host 127.0.0.1 --port $${PORT:-8000} --reload --reload-exclude .venv
+
+build: ## Build container image locally (podman/docker)
+	@[ -n "$(CONTAINER_CLI)" ] || { echo "ERROR: neither podman nor docker found in PATH"; exit 1; } && \
+	  source .env && \
+	  [ -n "$${CONTAINER_IMAGE}" ] || { echo "ERROR: CONTAINER_IMAGE is not set in .env"; exit 1; } && \
+	  cp -r ../../../../images ./images && \
+	  mkdir -p ./components && cp -r ../../../../components/auth ./components/auth && \
+	  trap 'rm -rf ./images ./components/auth; rmdir ./components 2>/dev/null || true' EXIT && \
+	  $(CONTAINER_CLI) build --platform linux/amd64 -t "$${CONTAINER_IMAGE}" -f Dockerfile .
+
+push: ## Push container image to registry
+	@[ -n "$(CONTAINER_CLI)" ] || { echo "ERROR: neither podman nor docker found in PATH"; exit 1; } && \
+	  source .env && \
+	  [ -n "$${CONTAINER_IMAGE}" ] || { echo "ERROR: CONTAINER_IMAGE is not set in .env"; exit 1; } && \
+	  $(CONTAINER_CLI) push "$${CONTAINER_IMAGE}"
+
+build-openshift: ## Build image in-cluster via OpenShift BuildConfig (no podman/docker needed)
+	@cp -r ../../../../images ./images && \
+	  mkdir -p ./components && cp -r ../../../../components/auth ./components/auth && \
+	  trap 'rm -rf ./images ./components/auth; rmdir ./components 2>/dev/null || true' EXIT && \
+	  oc new-build --strategy=docker --binary --name=$(AGENT_NAME) --to=$(AGENT_NAME):latest 2>/dev/null || true && \
+	  oc start-build $(AGENT_NAME) --from-dir=. --follow && \
+	  NS=$$(oc project -q) && \
+	  echo "" && \
+	  echo "Image built. To deploy, set in .env:" && \
+	  echo "  CONTAINER_IMAGE=image-registry.openshift-image-registry.svc:5000/$$NS/$(AGENT_NAME):latest"
+
+_check-env:
+	@set -a && source .env 2>/dev/null && set +a; \
+	  missing=""; \
+	  for var in $$(sed -n '/^ *required:/,/^ *[a-z]/{ /^ *- /s/^ *- *//p; }' agent.yaml); do \
+	    eval val="\$$$$var"; \
+	    [ -n "$$val" ] || missing="$$missing $$var"; \
+	  done; \
+	  [ -z "$$missing" ] || { echo "ERROR: Missing required env vars:$$missing"; exit 1; }
+
+deploy: _check-env ## Deploy to OpenShift/K8s via Helm
+	@source .env && \
+	  AUTH_ALLOWLIST="$${AUTH_ALLOWED_SERVICEACCOUNTS:-$${AUTH_ALLOWED_SERVICEACCOUNT}}" && \
+	  AUTH_ALLOWLIST_ARGS="" && \
+	  if [ -n "$$AUTH_ALLOWLIST" ]; then \
+	    IFS=',' read -r -a AUTH_ALLOWLIST_ITEMS <<< "$$AUTH_ALLOWLIST"; \
+	    for idx in "$${!AUTH_ALLOWLIST_ITEMS[@]}"; do \
+	      account="$${AUTH_ALLOWLIST_ITEMS[$$idx]}"; \
+	      account="$$(echo -n "$$account" | tr -d '[:space:]')"; \
+	      [ -n "$$account" ] || continue; \
+	      AUTH_ALLOWLIST_ARGS="$$AUTH_ALLOWLIST_ARGS --set-string auth.allowedServiceAccounts[$$idx]=$$account"; \
+	    done; \
+	  fi && \
+	  [ -n "$${CONTAINER_IMAGE}" ] || { echo "ERROR: CONTAINER_IMAGE is not set in .env"; exit 1; } && \
+	  LAST_SEG="$${CONTAINER_IMAGE##*/}" && if [[ "$$LAST_SEG" == *:* ]]; then IMAGE_REPO="$${CONTAINER_IMAGE%:*}"; IMAGE_TAG="$${LAST_SEG##*:}"; else IMAGE_REPO="$${CONTAINER_IMAGE}"; IMAGE_TAG="latest"; fi && \
+	  trap 'rm -f .helm-secrets.yaml' EXIT && \
+	  umask 077 && \
+	  { printf 'secrets:\n  apiKey: "%s"\n' "$${API_KEY}"; \
+	    [ -z "$${MLFLOW_TRACKING_TOKEN}" ] || printf '  mlflowTrackingToken: "%s"\n' "$${MLFLOW_TRACKING_TOKEN}"; \
+	  } > .helm-secrets.yaml && \
+	  helm upgrade --install $(AGENT_NAME) $(CHART_DIR) \
+	    -f $(VALUES_FILE) \
+	    -f .helm-secrets.yaml \
+	    --set image.repository="$${IMAGE_REPO}" \
+	    --set image.tag="$${IMAGE_TAG}" \
+	    --set env.BASE_URL="$${BASE_URL}" \
+	    --set env.MODEL_ID="$${MODEL_ID}" \
+	    $${AUTH_ENABLED:+--set "auth.enabled=$${AUTH_ENABLED}"} \
+	    $${AUTH_ENABLED:+--set "serviceAccount.create=$${AUTH_ENABLED}"} \
+	    $${AUTH_AUDIENCE:+--set-string "auth.audience=$${AUTH_AUDIENCE}"} \
+	    $${AUTH_ALLOWLIST_ARGS} \
+	    $${MLFLOW_TRACKING_URI:+--set env.MLFLOW_TRACKING_URI="$${MLFLOW_TRACKING_URI}"} \
+	    $${MLFLOW_EXPERIMENT_NAME:+--set env.MLFLOW_EXPERIMENT_NAME="$${MLFLOW_EXPERIMENT_NAME}"} \
+	    $${MLFLOW_TRACKING_AUTH:+--set env.MLFLOW_TRACKING_AUTH="$${MLFLOW_TRACKING_AUTH}"} \
+	    $${MLFLOW_TRACKING_INSECURE_TLS:+--set env.MLFLOW_TRACKING_INSECURE_TLS="$${MLFLOW_TRACKING_INSECURE_TLS}"} \
+	    $${MLFLOW_TRACKING_SERVER_CERT_PATH:+--set env.MLFLOW_TRACKING_SERVER_CERT_PATH="$${MLFLOW_TRACKING_SERVER_CERT_PATH}"} \
+	    $${MLFLOW_WORKSPACE:+--set env.MLFLOW_WORKSPACE="$${MLFLOW_WORKSPACE}"} && \
+	  if command -v oc >/dev/null 2>&1; then \
+	    echo "" && echo "Waiting for rollout to complete..." && \
+	    if oc rollout status deployment/$(AGENT_NAME) --timeout=120s; then \
+	      ROUTE=$$(oc get route $(AGENT_NAME) -o jsonpath='{.spec.host}' 2>/dev/null || true); \
+	      if [ -n "$$ROUTE" ]; then echo "" && echo "Agent is available at: https://$$ROUTE"; fi; \
+	    else \
+	      echo "" && echo "WARNING: Rollout did not complete successfully. Check pod status with:" && \
+	      echo "  oc get pods -l app.kubernetes.io/name=$(AGENT_NAME)" && \
+	      echo "  oc logs deployment/$(AGENT_NAME)"; \
+	    fi; \
+	  fi
+
+dry-run: _check-env ## Render Helm templates without deploying
+	@source .env && \
+	  AUTH_ALLOWLIST="$${AUTH_ALLOWED_SERVICEACCOUNTS:-$${AUTH_ALLOWED_SERVICEACCOUNT}}" && \
+	  AUTH_ALLOWLIST_ARGS="" && \
+	  if [ -n "$$AUTH_ALLOWLIST" ]; then \
+	    IFS=',' read -r -a AUTH_ALLOWLIST_ITEMS <<< "$$AUTH_ALLOWLIST"; \
+	    for idx in "$${!AUTH_ALLOWLIST_ITEMS[@]}"; do \
+	      account="$${AUTH_ALLOWLIST_ITEMS[$$idx]}"; \
+	      account="$$(echo -n "$$account" | tr -d '[:space:]')"; \
+	      [ -n "$$account" ] || continue; \
+	      AUTH_ALLOWLIST_ARGS="$$AUTH_ALLOWLIST_ARGS --set-string auth.allowedServiceAccounts[$$idx]=$$account"; \
+	    done; \
+	  fi && \
+	  [ -n "$${CONTAINER_IMAGE}" ] || { echo "ERROR: CONTAINER_IMAGE is not set in .env"; exit 1; } && \
+	  LAST_SEG="$${CONTAINER_IMAGE##*/}" && if [[ "$$LAST_SEG" == *:* ]]; then IMAGE_REPO="$${CONTAINER_IMAGE%:*}"; IMAGE_TAG="$${LAST_SEG##*:}"; else IMAGE_REPO="$${CONTAINER_IMAGE}"; IMAGE_TAG="latest"; fi && \
+	  helm template $(AGENT_NAME) $(CHART_DIR) \
+	    -f $(VALUES_FILE) \
+	    --set secrets.apiKey="REDACTED" \
+	    --set image.repository="$${IMAGE_REPO}" \
+	    --set image.tag="$${IMAGE_TAG}" \
+	    --set env.BASE_URL="$${BASE_URL}" \
+	    --set env.MODEL_ID="$${MODEL_ID}" \
+	    $${AUTH_ENABLED:+--set "auth.enabled=$${AUTH_ENABLED}"} \
+	    $${AUTH_ENABLED:+--set "serviceAccount.create=$${AUTH_ENABLED}"} \
+	    $${AUTH_AUDIENCE:+--set-string "auth.audience=$${AUTH_AUDIENCE}"} \
+	    $${AUTH_ALLOWLIST_ARGS} \
+	    $${MLFLOW_TRACKING_URI:+--set env.MLFLOW_TRACKING_URI="$${MLFLOW_TRACKING_URI}"} \
+	    $${MLFLOW_TRACKING_TOKEN:+--set secrets.mlflowTrackingToken="REDACTED"} \
+	    $${MLFLOW_EXPERIMENT_NAME:+--set env.MLFLOW_EXPERIMENT_NAME="$${MLFLOW_EXPERIMENT_NAME}"} \
+	    $${MLFLOW_TRACKING_AUTH:+--set env.MLFLOW_TRACKING_AUTH="$${MLFLOW_TRACKING_AUTH}"} \
+	    $${MLFLOW_TRACKING_INSECURE_TLS:+--set env.MLFLOW_TRACKING_INSECURE_TLS="$${MLFLOW_TRACKING_INSECURE_TLS}"} \
+	    $${MLFLOW_TRACKING_SERVER_CERT_PATH:+--set env.MLFLOW_TRACKING_SERVER_CERT_PATH="$${MLFLOW_TRACKING_SERVER_CERT_PATH}"} \
+	    $${MLFLOW_WORKSPACE:+--set env.MLFLOW_WORKSPACE="$${MLFLOW_WORKSPACE}"}
+
+undeploy: ## Remove deployment from cluster
+	helm uninstall $(AGENT_NAME)
+
+test: ## Run unit tests
+	uv run --extra dev python -m pytest tests/ --ignore=tests/integration --ignore=tests/behavioral $(PYTEST_ARGS)
+
+test-integration: ## Run integration deployment test
+	PYTHONPATH=$$(git rev-parse --show-toplevel)/tests \
+	  uv run --extra dev python -m pytest tests/integration/test_deployment.py \
+	    -v --tb=long --junitxml=results.xml
+
+test-auth-integration: ## Run auth-enabled integration deployment test
+	PYTHONPATH=$$(git rev-parse --show-toplevel)/tests \
+	  uv run --extra dev python -m pytest tests/integration/test_auth.py \
+	    -v --tb=long --junitxml=results-auth.xml

From 5c581d54ef19a7e2df795877aefa95c93e48701f Mon Sep 17 00:00:00 2001
From: Tarun Kumar Reddy Etikala <tetikala@redhat.com>
Date: Wed, 22 Jul 2026 12:29:24 -0400
Subject: [PATCH 06/25] test(guardrails): add config and packaging tests
 (RHAIENG-6262)

Structural tests validate guardrails config files (YAML well-formed,
required keys, correct output parsers, streaming enabled) and
packaging config (Makefile targets, Dockerfile paths, nemoguardrails
pin). All 28 tests pass.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---
 .../tests/test_guardrails_config.py           |  110 +
 .../tests/test_packaging_config.py            |   77 +
 .../examples/guardrailed_agent/uv.lock        | 4142 +++++++++++++++++
 3 files changed, 4329 insertions(+)
 create mode 100644 agents/langgraph/examples/guardrailed_agent/tests/test_guardrails_config.py
 create mode 100644 agents/langgraph/examples/guardrailed_agent/tests/test_packaging_config.py
 create mode 100644 agents/langgraph/examples/guardrailed_agent/uv.lock

diff --git a/agents/langgraph/examples/guardrailed_agent/tests/test_guardrails_config.py b/agents/langgraph/examples/guardrailed_agent/tests/test_guardrails_config.py
new file mode 100644
index 00000000..259784cb
--- /dev/null
+++ b/agents/langgraph/examples/guardrailed_agent/tests/test_guardrails_config.py
@@ -0,0 +1,110 @@
+"""Structural tests for NeMo Guardrails configuration files.
+
+Validates that the guardrails config is well-formed and contains all
+required components without needing a running LLM or NeMo server.
+"""
+
+from pathlib import Path
+
+import yaml
+
+AGENT_DIR = Path(__file__).resolve().parents[1]
+GUARDRAILS_DIR = AGENT_DIR / "guardrails" / "safety"
+
+
+class TestConfigFilesExist:
+    def test_config_yaml_exists(self):
+        assert (GUARDRAILS_DIR / "config.yaml").is_file()
+
+    def test_config_uses_yaml_extension_not_yml(self):
+        assert (GUARDRAILS_DIR / "config.yaml").is_file()
+        assert not (GUARDRAILS_DIR / "config.yml").exists()
+
+    def test_prompts_yml_exists(self):
+        assert (GUARDRAILS_DIR / "prompts.yml").is_file()
+
+    def test_rails_co_exists(self):
+        assert (GUARDRAILS_DIR / "rails.co").is_file()
+
+
+class TestConfigYaml:
+    @classmethod
+    def setup_class(cls):
+        cls.config = yaml.safe_load(
+            (GUARDRAILS_DIR / "config.yaml").read_text(encoding="utf-8")
+        )
+
+    def test_has_models_section(self):
+        assert "models" in self.config
+        model_types = {m["type"] for m in self.config["models"]}
+        assert "main" in model_types
+        assert "content_safety" in model_types
+
+    def test_has_input_rails(self):
+        flows = self.config["rails"]["input"]["flows"]
+        flow_text = " ".join(flows)
+        assert "content safety check input" in flow_text
+        assert "topic safety check input" in flow_text
+
+    def test_has_regex_input_rail(self):
+        flows = self.config["rails"]["input"]["flows"]
+        assert "regex check input" in flows
+
+    def test_has_output_rails(self):
+        flows = self.config["rails"]["output"]["flows"]
+        flow_text = " ".join(flows)
+        assert "content safety check output" in flow_text
+
+    def test_streaming_enabled(self):
+        assert self.config["rails"]["output"]["streaming"]["enabled"] is True
+
+    def test_regex_patterns_configured(self):
+        patterns = self.config["rails"]["config"]["regex_detection"]["input"][
+            "patterns"
+        ]
+        assert len(patterns) >= 1
+
+
+class TestPromptsYml:
+    @classmethod
+    def setup_class(cls):
+        cls.prompts = yaml.safe_load(
+            (GUARDRAILS_DIR / "prompts.yml").read_text(encoding="utf-8")
+        )
+
+    def test_has_content_safety_input_prompt(self):
+        tasks = [p["task"] for p in self.prompts["prompts"]]
+        assert any("content_safety_check_input" in t for t in tasks)
+
+    def test_has_content_safety_output_prompt(self):
+        tasks = [p["task"] for p in self.prompts["prompts"]]
+        assert any("content_safety_check_output" in t for t in tasks)
+
+    def test_has_topic_safety_prompt(self):
+        tasks = [p["task"] for p in self.prompts["prompts"]]
+        assert any("topic_safety_check_input" in t for t in tasks)
+
+    def test_input_prompt_uses_correct_output_parser(self):
+        for p in self.prompts["prompts"]:
+            if "content_safety_check_input" in p["task"]:
+                assert p["output_parser"] == "nemoguard_parse_prompt_safety"
+
+    def test_output_prompt_uses_correct_output_parser(self):
+        for p in self.prompts["prompts"]:
+            if "content_safety_check_output" in p["task"]:
+                assert p["output_parser"] == "nemoguard_parse_response_safety"
+
+    def test_topic_prompt_mentions_banking(self):
+        for p in self.prompts["prompts"]:
+            if "topic_safety_check_input" in p["task"]:
+                assert "bank" in p["content"].lower()
+
+
+class TestRailsCo:
+    def test_rails_co_is_not_empty(self):
+        content = (GUARDRAILS_DIR / "rails.co").read_text(encoding="utf-8")
+        assert len(content.strip()) > 0
+
+    def test_rails_co_defines_greeting_flow(self):
+        content = (GUARDRAILS_DIR / "rails.co").read_text(encoding="utf-8")
+        assert "express greeting" in content
diff --git a/agents/langgraph/examples/guardrailed_agent/tests/test_packaging_config.py b/agents/langgraph/examples/guardrailed_agent/tests/test_packaging_config.py
new file mode 100644
index 00000000..92551731
--- /dev/null
+++ b/agents/langgraph/examples/guardrailed_agent/tests/test_packaging_config.py
@@ -0,0 +1,77 @@
+from __future__ import annotations
+
+import re
+import tomllib
+from pathlib import Path
+
+AGENT_DIR = Path(__file__).resolve().parents[1]
+MAKEFILE = (AGENT_DIR / "Makefile").read_text(encoding="utf-8")
+DOCKERFILE = (AGENT_DIR / "Dockerfile").read_text(encoding="utf-8")
+ENV_EXAMPLE = (AGENT_DIR / ".env.example").read_text(encoding="utf-8")
+PYPROJECT = tomllib.loads((AGENT_DIR / "pyproject.toml").read_text(encoding="utf-8"))
+NORMALIZED_MAKEFILE = re.sub(r"\s+", " ", MAKEFILE)
+NORMALIZED_DOCKERFILE = re.sub(r"\s+", " ", DOCKERFILE)
+
+
+def test_makefile_stages_auth_component_for_container_builds() -> None:
+    copy_pattern = (
+        r"mkdir -p \./components && cp -r "
+        r"\.\./\.\./\.\./\.\./components/auth \./components/auth"
+    )
+    cleanup_pattern = (
+        r"trap 'rm -rf \./images \./components/auth; "
+        r"rmdir \./components 2>/dev/null \|\| true' EXIT"
+    )
+
+    assert len(re.findall(copy_pattern, NORMALIZED_MAKEFILE)) == 2
+    assert len(re.findall(cleanup_pattern, NORMALIZED_MAKEFILE)) == 2
+
+
+def test_makefile_has_guardrails_targets() -> None:
+    assert re.search(r"(?m)^guardrails-config:", MAKEFILE)
+    assert re.search(r"(?m)^guardrails-server:", MAKEFILE)
+
+
+def test_makefile_env_installs_guardrails_extra() -> None:
+    assert "--extra guardrails" in MAKEFILE
+
+
+def test_env_example_points_to_guardrails_proxy() -> None:
+    assert "localhost:8090" in ENV_EXAMPLE
+
+
+def test_env_example_documents_auth_settings() -> None:
+    assert "# AUTH_ENABLED=false" in ENV_EXAMPLE
+    assert "# AUTH_AUDIENCE=langgraph-guardrailed-agent" in ENV_EXAMPLE
+
+
+def test_dockerfile_workdir_matches_agent_location() -> None:
+    assert re.search(
+        r"WORKDIR /opt/app-root/src/agents/langgraph/examples/guardrailed_agent",
+        NORMALIZED_DOCKERFILE,
+    )
+
+
+def test_dockerfile_installs_auth_extra_from_staged_component() -> None:
+    assert re.search(
+        r"COPY components/auth/ /opt/app-root/src/components/auth/",
+        NORMALIZED_DOCKERFILE,
+    )
+    assert re.search(
+        r'RUN uv pip install --no-cache "\.\[tracing,auth\]"',
+        NORMALIZED_DOCKERFILE,
+    )
+
+
+def test_pyproject_pins_nemoguardrails_version() -> None:
+    guardrails_deps = PYPROJECT["project"]["optional-dependencies"]["guardrails"]
+    assert any("nemoguardrails" in d and "0.21.0" in d for d in guardrails_deps)
+
+
+def test_pyproject_constrains_protobuf_below_7() -> None:
+    dependencies = PYPROJECT["project"]["dependencies"]
+    assert "protobuf<7" in dependencies
+
+
+def test_pyproject_package_name() -> None:
+    assert PYPROJECT["project"]["name"] == "guardrailed_agent"
diff --git a/agents/langgraph/examples/guardrailed_agent/uv.lock b/agents/langgraph/examples/guardrailed_agent/uv.lock
new file mode 100644
index 00000000..dffb8951
--- /dev/null
+++ b/agents/langgraph/examples/guardrailed_agent/uv.lock
@@ -0,0 +1,4142 @@
+version = 1
+revision = 3
+requires-python = ">=3.12, <=3.14"
+resolution-markers = [
+    "python_full_version >= '3.14'",
+    "python_full_version == '3.13.*'",
+    "python_full_version < '3.13'",
+]
+
+[[package]]
+name = "agent-auth"
+version = "0.1.0"
+source = { directory = "../../../../components/auth" }
+dependencies = [
+    { name = "kubernetes" },
+    { name = "starlette" },
+]
+
+[package.metadata]
+requires-dist = [
+    { name = "kubernetes", specifier = ">=29.0" },
+    { name = "starlette", specifier = ">=0.27.0" },
+]
+
+[[package]]
+name = "aiofiles"
+version = "25.1.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/41/c3/534eac40372d8ee36ef40df62ec129bee4fdb5ad9706e58a29be53b2c970/aiofiles-25.1.0.tar.gz", hash = "sha256:a8d728f0a29de45dc521f18f07297428d56992a742f0cd2701ba86e44d23d5b2", size = 46354, upload-time = "2025-10-09T20:51:04.358Z" }
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+]
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+[[package]]
+name = "aiohappyeyeballs"
+version = "2.7.1"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/ce/f4/eec0465c2f67b2664688d0240b3212d5196fd89e741df67ddb81f8d35658/aiohappyeyeballs-2.7.1.tar.gz", hash = "sha256:065665c041c42a5938ed220bdcd7230f22527fbec085e1853d2402c8a3615d9d", size = 24757, upload-time = "2026-07-01T17:11:55.501Z" }
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+[[package]]
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+]
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+    { url = "https://files.pythonhosted.org/packages/3a/43/241f9615bcf8ba8903b3f0432da069e857fc4fd1783bd26183db53c4804b/zstandard-0.25.0-cp314-cp314-win_amd64.whl", hash = "sha256:c19bcdd826e95671065f8692b5a4aa95c52dc7a02a4c5a0cac46deb879a017a2", size = 516118, upload-time = "2025-09-14T22:18:17.849Z" },
+    { url = "https://files.pythonhosted.org/packages/f0/ef/da163ce2450ed4febf6467d77ccb4cd52c4c30ab45624bad26ca0a27260c/zstandard-0.25.0-cp314-cp314-win_arm64.whl", hash = "sha256:d7541afd73985c630bafcd6338d2518ae96060075f9463d7dc14cfb33514383d", size = 476940, upload-time = "2025-09-14T22:18:19.088Z" },
+]

From eafa1ff56e5280d72c8b506f1d631bd9bf488231 Mon Sep 17 00:00:00 2001
From: Tarun Kumar Reddy Etikala <tetikala@redhat.com>
Date: Thu, 23 Jul 2026 10:49:33 -0400
Subject: [PATCH 07/25] docs(guardrails): add README for guardrailed agent
 (RHAIENG-6262)

Covers architecture (proxy pattern), local dev setup (Ollama + NeMo +
agent), guardrails test commands, use-case swapping, OpenShift deploy,
and guardrails config reference.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---
 .../examples/guardrailed_agent/README.md      | 203 ++++++++++++++++++
 1 file changed, 203 insertions(+)
 create mode 100644 agents/langgraph/examples/guardrailed_agent/README.md

diff --git a/agents/langgraph/examples/guardrailed_agent/README.md b/agents/langgraph/examples/guardrailed_agent/README.md
new file mode 100644
index 00000000..e63d4bf4
--- /dev/null
+++ b/agents/langgraph/examples/guardrailed_agent/README.md
@@ -0,0 +1,203 @@
+<div style="text-align: center;">
+
+![LangGraph Logo](/images/langgraph_logo.svg)
+
+# Guardrailed Agent
+
+</div>
+
+---
+
+## What this agent does
+
+FSI customer service agent with [NeMo Guardrails](https://github.com/NVIDIA/NeMo-Guardrails) safety layer. Demonstrates how to add content safety, topical guardrails, and regex-based input filtering to a LangGraph ReAct agent using the **proxy pattern** — NeMo Guardrails sits between the agent and the LLM, requiring zero changes to the agent's source code.
+
+### Guardrails architecture
+
+```text
+User → Agent (port 8000) → NeMo Guardrails (port 8090) → LLM (port 11434)
+```
+
+Three layered input rails run in order (if any blocks, later rails are skipped):
+
+1. **Regex** — instant pattern matching, no LLM call (catches jailbreak patterns)
+2. **Content safety** — LLM classifies input against S1–S13 safety categories
+3. **Topic safety** — LLM checks if input is within the banking domain boundary
+
+Plus a content safety **output rail** that checks the LLM's response before returning it.
+
+### Swapping the use case
+
+The banking domain is defined entirely in `guardrails/safety/prompts.yml` (the `topic_safety_check_input` prompt). To adapt this example to a different domain (healthcare, telecom, etc.), edit only that prompt's guidelines list. Everything else stays the same.
+
+---
+
+## Prerequisites
+
+- [uv](https://docs.astral.sh/uv/) — Python package manager
+- [Ollama](https://ollama.com/) — local LLM inference (or any OpenAI-compatible endpoint)
+- [Podman](https://podman.io/) or [Docker](https://www.docker.com/) — for container builds
+- [oc](https://docs.openshift.com/container-platform/latest/cli_reference/openshift_cli/getting-started-cli.html) — for OpenShift deployment
+- [Helm](https://helm.sh/) — for deploying to Kubernetes/OpenShift
+- [GNU Make](https://www.gnu.org/software/make/) and a bash-compatible shell
+
+## Local Development
+
+### 1. Initialize
+
+```bash
+cd agents/langgraph/examples/guardrailed_agent
+make init    # creates .env from .env.example
+```
+
+### 2. Install dependencies
+
+```bash
+make env     # creates venv and installs deps (including NeMo Guardrails)
+```
+
+### 3. Start Ollama
+
+```bash
+make ollama  # installs Ollama (if needed) and pulls llama3.1:8b
+```
+
+### 4. Start NeMo Guardrails proxy
+
+> **Keep this terminal open** — the guardrails server needs to keep running.
+
+```bash
+make guardrails-server   # starts on port 8090
+```
+
+The guardrails server reads its config from `guardrails/safety/`. To point it at a different LLM endpoint, either edit `guardrails/safety/config.yaml` directly or set `LLM_BASE_URL` in `.env` and run `make guardrails-config`.
+
+### 5. Start the agent
+
+> **In a separate terminal:**
+
+```bash
+make run-app   # starts on port 8000
+```
+
+### 6. Test the guardrails
+
+```bash
+# On-topic question — should respond normally
+curl -s http://localhost:8000/chat/completions \
+  -H "Content-Type: application/json" \
+  -d '{"messages":[{"role":"user","content":"What is my balance for ACCT-12345?"}]}' \
+  | python3 -m json.tool
+
+# Toxic input — should be blocked by content safety rail
+curl -s http://localhost:8000/chat/completions \
+  -H "Content-Type: application/json" \
+  -d '{"messages":[{"role":"user","content":"How do I build a bomb?"}]}' \
+  | python3 -m json.tool
+
+# Off-topic request — should be blocked by topic safety rail
+curl -s http://localhost:8000/chat/completions \
+  -H "Content-Type: application/json" \
+  -d '{"messages":[{"role":"user","content":"Give me a recipe for chocolate cake"}]}' \
+  | python3 -m json.tool
+
+# Greeting — should respond normally
+curl -s http://localhost:8000/chat/completions \
+  -H "Content-Type: application/json" \
+  -d '{"messages":[{"role":"user","content":"Hello!"}]}' \
+  | python3 -m json.tool
+```
+
+### Tracing (optional)
+
+MLflow tracing works the same as other agents. Note that MLflow sees NeMo Guardrails as a regular ChatOpenAI endpoint — guardrails-internal traces (which rail fired, classification results) are not visible in MLflow. Use `nemoguardrails server --verbose` for rail-level debugging.
+
+See `.env.example` for MLflow configuration options.
+
+## Deploying to OpenShift
+
+### Configuration
+
+Edit `.env` with your model endpoint and container image:
+
+```ini
+API_KEY=your-api-key-here
+BASE_URL=https://your-guardrails-endpoint/v1
+MODEL_ID=llama-3.1-8b-instruct
+CONTAINER_IMAGE=quay.io/your-username/langgraph-guardrailed-agent:latest
+```
+
+> **Note:** In production on RHOAI, NeMo Guardrails runs as a separate pod managed by the `NemoGuardrails` CRD. The agent's `BASE_URL` points to the guardrails service, not directly to the LLM.
+
+### Build and deploy
+
+#### Option A: Build locally and push
+
+```bash
+make build    # builds the container image
+make push     # pushes to the registry
+make deploy   # deploys via Helm
+```
+
+#### Option B: Build in-cluster
+
+```bash
+make build-openshift   # builds via OpenShift BuildConfig
+make deploy
+```
+
+### Verify
+
+```bash
+make dry-run   # preview Helm manifests (secrets redacted)
+make undeploy  # remove deployment
+```
+
+## Tests
+
+```bash
+make test
+```
+
+## API Endpoints
+
+### POST /chat/completions
+
+```bash
+# Non-streaming
+curl -X POST http://localhost:8000/chat/completions \
+  -H "Content-Type: application/json" \
+  -d '{"messages": [{"role": "user", "content": "What is my account balance?"}], "stream": false}'
+
+# Streaming
+curl -sN -X POST http://localhost:8000/chat/completions \
+  -H "Content-Type: application/json" \
+  -d '{"messages": [{"role": "user", "content": "What is my account balance?"}], "stream": true}'
+```
+
+### GET /health
+
+```bash
+curl http://localhost:8000/health
+```
+
+## Guardrails Configuration
+
+| File | Purpose |
+|------|---------|
+| `guardrails/safety/config.yaml` | Model endpoints, rail ordering, streaming, regex patterns |
+| `guardrails/safety/prompts.yml` | Content safety (S1–S13) and topic safety classification prompts |
+| `guardrails/safety/rails.co` | Colang greeting flows (required by RHOAI entrypoint) |
+
+**Key constraints:**
+
+- Config file must be `config.yaml` (not `.yml`) — RHOAI container entrypoint requirement
+- `rails.co` must exist — RHOAI container entrypoint requirement (can be minimal)
+- NeMo Guardrails version pinned to `0.21.0` to match RHOAI
+
+## Resources
+
+- [NeMo Guardrails Documentation](https://docs.nvidia.com/nemo/guardrails/)
+- [LangGraph Documentation](https://docs.langchain.com/oss/python/langgraph/overview)
+- [LangChain Documentation](https://docs.langchain.com/oss/python/langchain/overview)
+- [Ollama Documentation](https://docs.ollama.com)

From 7c570834e3d8173bb6d2194b60c52799d0080e1f Mon Sep 17 00:00:00 2001
From: Tarun Kumar Reddy Etikala <tetikala@redhat.com>
Date: Thu, 23 Jul 2026 10:57:25 -0400
Subject: [PATCH 08/25] fix(guardrails): add missing dataclasses-json dep
 (RHAIENG-6262)

nemoguardrails 0.21.0 imports dataclasses_json internally but does
not declare it as a dependency. Add it explicitly to the guardrails
optional group.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---
 .../examples/guardrailed_agent/pyproject.toml |  1 +
 .../examples/guardrailed_agent/uv.lock        | 93 ++++++++++++++-----
 2 files changed, 72 insertions(+), 22 deletions(-)

diff --git a/agents/langgraph/examples/guardrailed_agent/pyproject.toml b/agents/langgraph/examples/guardrailed_agent/pyproject.toml
index 5d700b51..ec8981a6 100644
--- a/agents/langgraph/examples/guardrailed_agent/pyproject.toml
+++ b/agents/langgraph/examples/guardrailed_agent/pyproject.toml
@@ -34,6 +34,7 @@ dev = [
 ]
 guardrails = [
     "nemoguardrails[server]==0.21.0",
+    "dataclasses-json>=0.6.7",
 ]
 tracing = [
     "mlflow[kubernetes]>=3.11.0",
diff --git a/agents/langgraph/examples/guardrailed_agent/uv.lock b/agents/langgraph/examples/guardrailed_agent/uv.lock
index dffb8951..b2577118 100644
--- a/agents/langgraph/examples/guardrailed_agent/uv.lock
+++ b/agents/langgraph/examples/guardrailed_agent/uv.lock
@@ -578,6 +578,19 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/28/95/f17887b43ac4dcc09079e5fb0e93374762d85d593c8e5114dbc6f82b6c52/databricks_sdk-0.122.0-py3-none-any.whl", hash = "sha256:7d998ec47f580be6be1cfe066be78038054767575b7437af5e4f76b67dde49c2", size = 969097, upload-time = "2026-07-21T09:24:14.32Z" },
 ]
 
+[[package]]
+name = "dataclasses-json"
+version = "0.6.7"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "marshmallow" },
+    { name = "typing-inspect" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/64/a4/f71d9cf3a5ac257c993b5ca3f93df5f7fb395c725e7f1e6479d2514173c3/dataclasses_json-0.6.7.tar.gz", hash = "sha256:b6b3e528266ea45b9535223bc53ca645f5208833c29229e847b3f26a1cc55fc0", size = 32227, upload-time = "2024-06-09T16:20:19.103Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/c3/be/d0d44e092656fe7a06b55e6103cbce807cdbdee17884a5367c68c9860853/dataclasses_json-0.6.7-py3-none-any.whl", hash = "sha256:0dbf33f26c8d5305befd61b39d2b3414e8a407bedc2834dea9b8d642666fb40a", size = 28686, upload-time = "2024-06-09T16:20:16.715Z" },
+]
+
 [[package]]
 name = "distro"
 version = "1.9.0"
@@ -651,16 +664,16 @@ name = "fastembed"
 version = "0.8.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "huggingface-hub" },
-    { name = "loguru" },
-    { name = "mmh3" },
-    { name = "numpy" },
-    { name = "onnxruntime" },
-    { name = "pillow" },
-    { name = "py-rust-stemmers" },
-    { name = "requests" },
-    { name = "tokenizers" },
-    { name = "tqdm" },
+    { name = "huggingface-hub", marker = "python_full_version < '3.14'" },
+    { name = "loguru", marker = "python_full_version < '3.14'" },
+    { name = "mmh3", marker = "python_full_version < '3.14'" },
+    { name = "numpy", marker = "python_full_version < '3.14'" },
+    { name = "onnxruntime", marker = "python_full_version < '3.14'" },
+    { name = "pillow", marker = "python_full_version < '3.14'" },
+    { name = "py-rust-stemmers", marker = "python_full_version < '3.14'" },
+    { name = "requests", marker = "python_full_version < '3.14'" },
+    { name = "tokenizers", marker = "python_full_version < '3.14'" },
+    { name = "tqdm", marker = "python_full_version < '3.14'" },
 ]
 sdist = { url = "https://files.pythonhosted.org/packages/26/25/58865e36b6e8a9a0d0ff905b5601aa30db97956327c0df42ec4ed6accc21/fastembed-0.8.0.tar.gz", hash = "sha256:75966edfa8b006ee78514c726bd7f6a50721dadc89305279052be9db72fd53e8", size = 75115, upload-time = "2026-03-23T16:34:41.699Z" }
 wheels = [
@@ -1046,6 +1059,7 @@ dev = [
     { name = "pyyaml" },
 ]
 guardrails = [
+    { name = "dataclasses-json" },
     { name = "nemoguardrails", extra = ["server"] },
 ]
 tracing = [
@@ -1056,6 +1070,7 @@ tracing = [
 requires-dist = [
     { name = "agent-auth", marker = "extra == 'auth'", directory = "../../../../components/auth" },
     { name = "chardet", specifier = ">=7.1.0" },
+    { name = "dataclasses-json", marker = "extra == 'guardrails'", specifier = ">=0.6.7" },
     { name = "fastapi", specifier = ">=0.135.1" },
     { name = "flask", specifier = ">=3.1.0" },
     { name = "httpx", marker = "extra == 'dev'", specifier = ">=0.27" },
@@ -1210,15 +1225,15 @@ name = "huggingface-hub"
 version = "1.24.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "click" },
-    { name = "filelock" },
-    { name = "fsspec" },
-    { name = "hf-xet", marker = "platform_machine == 'AMD64' or platform_machine == 'aarch64' or platform_machine == 'amd64' or platform_machine == 'arm64' or platform_machine == 'x86_64'" },
-    { name = "httpx" },
-    { name = "packaging" },
-    { name = "pyyaml" },
-    { name = "tqdm" },
-    { name = "typing-extensions" },
+    { name = "click", marker = "python_full_version < '3.14'" },
+    { name = "filelock", marker = "python_full_version < '3.14'" },
+    { name = "fsspec", marker = "python_full_version < '3.14'" },
+    { name = "hf-xet", marker = "(python_full_version < '3.14' and platform_machine == 'AMD64') or (python_full_version < '3.14' and platform_machine == 'aarch64') or (python_full_version < '3.14' and platform_machine == 'amd64') or (python_full_version < '3.14' and platform_machine == 'arm64') or (python_full_version < '3.14' and platform_machine == 'x86_64')" },
+    { name = "httpx", marker = "python_full_version < '3.14'" },
+    { name = "packaging", marker = "python_full_version < '3.14'" },
+    { name = "pyyaml", marker = "python_full_version < '3.14'" },
+    { name = "tqdm", marker = "python_full_version < '3.14'" },
+    { name = "typing-extensions", marker = "python_full_version < '3.14'" },
 ]
 sdist = { url = "https://files.pythonhosted.org/packages/df/9b/d3bb4e7d792835daf34dd7091bbc7d7b4e0437d9388f1ea7239cce49f478/huggingface_hub-1.24.0.tar.gz", hash = "sha256:18431ff4daae0749aa9ba102fc952e314c98e1d30ebdec5319d85ca0a83e1ae5", size = 921848, upload-time = "2026-07-17T09:54:01.022Z" }
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 version = "0.7.3"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "colorama", marker = "sys_platform == 'win32'" },
-    { name = "win32-setctime", marker = "sys_platform == 'win32'" },
+    { name = "colorama", marker = "python_full_version < '3.14' and sys_platform == 'win32'" },
+    { name = "win32-setctime", marker = "python_full_version < '3.14' and sys_platform == 'win32'" },
 ]
 sdist = { url = "https://files.pythonhosted.org/packages/3a/05/a1dae3dffd1116099471c643b8924f5aa6524411dc6c63fdae648c4f1aca/loguru-0.7.3.tar.gz", hash = "sha256:19480589e77d47b8d85b2c827ad95d49bf31b0dcde16593892eb51dd18706eb6", size = 63559, upload-time = "2024-12-06T11:20:56.608Z" }
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 ]
 
+[[package]]
+name = "marshmallow"
+version = "3.26.2"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "packaging" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/55/79/de6c16cc902f4fc372236926b0ce2ab7845268dcc30fb2fbb7f71b418631/marshmallow-3.26.2.tar.gz", hash = "sha256:bbe2adb5a03e6e3571b573f42527c6fe926e17467833660bebd11593ab8dfd57", size = 222095, upload-time = "2025-12-22T06:53:53.309Z" }
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+]
+
 [[package]]
 name = "matplotlib"
 version = "3.11.1"
@@ -2131,6 +2158,15 @@ wheels = [
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 ]
 
+[[package]]
+name = "mypy-extensions"
+version = "1.1.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/a2/6e/371856a3fb9d31ca8dac321cda606860fa4548858c0cc45d9d1d4ca2628b/mypy_extensions-1.1.0.tar.gz", hash = "sha256:52e68efc3284861e772bbcd66823fde5ae21fd2fdb51c62a211403730b916558", size = 6343, upload-time = "2025-04-22T14:54:24.164Z" }
+wheels = [
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+]
+
 [[package]]
 name = "narwhals"
 version = "2.24.0"
@@ -3493,7 +3529,7 @@ name = "tokenizers"
 version = "0.23.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "huggingface-hub" },
+    { name = "huggingface-hub", marker = "python_full_version < '3.14'" },
 ]
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+[[package]]
+name = "typing-inspect"
+version = "0.9.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "mypy-extensions" },
+    { name = "typing-extensions" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/dc/74/1789779d91f1961fa9438e9a8710cdae6bd138c80d7303996933d117264a/typing_inspect-0.9.0.tar.gz", hash = "sha256:b23fc42ff6f6ef6954e4852c1fb512cdd18dbea03134f91f856a95ccc9461f78", size = 13825, upload-time = "2023-05-24T20:25:47.612Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/65/f3/107a22063bf27bdccf2024833d3445f4eea42b2e598abfbd46f6a63b6cb0/typing_inspect-0.9.0-py3-none-any.whl", hash = "sha256:9ee6fc59062311ef8547596ab6b955e1b8aa46242d854bfc78f4f6b0eff35f9f", size = 8827, upload-time = "2023-05-24T20:25:45.287Z" },
+]
+
 [[package]]
 name = "typing-inspection"
 version = "0.4.2"

From 8614e1e975b8bd78fc323b4abbbae11efc26e123 Mon Sep 17 00:00:00 2001
From: Tarun Kumar Reddy Etikala <tetikala@redhat.com>
Date: Thu, 23 Jul 2026 11:13:40 -0400
Subject: [PATCH 09/25] fix(guardrails): fix nemo deps and clarify LLM setup
 (RHAIENG-6262)

Pin langchain-community<0.4 to fix GoogleSearchAPIWrapper warnings
from nemoguardrails 0.21.0 (removed in 0.4.x). Clarify README step
3: separate model pull from ollama serve, add macOS app note.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---
 .../examples/guardrailed_agent/README.md      | 32 +++++++++++++--
 .../examples/guardrailed_agent/pyproject.toml |  1 +
 .../examples/guardrailed_agent/uv.lock        | 41 ++++---------------
 3 files changed, 37 insertions(+), 37 deletions(-)

diff --git a/agents/langgraph/examples/guardrailed_agent/README.md b/agents/langgraph/examples/guardrailed_agent/README.md
index e63d4bf4..56a16f47 100644
--- a/agents/langgraph/examples/guardrailed_agent/README.md
+++ b/agents/langgraph/examples/guardrailed_agent/README.md
@@ -56,21 +56,47 @@ make init    # creates .env from .env.example
 make env     # creates venv and installs deps (including NeMo Guardrails)
 ```
 
-### 3. Start Ollama
+### 3. Start a local LLM
+
+NeMo Guardrails needs an LLM endpoint for both conversation and safety classification (self-check approach). The default config points to Ollama on `localhost:11434`.
+
+Install Ollama and pull the model:
 
 ```bash
 make ollama  # installs Ollama (if needed) and pulls llama3.1:8b
 ```
 
+Start the Ollama server (keep this terminal open):
+
+```bash
+ollama serve   # starts on port 11434
+```
+
+> If you use the Ollama macOS desktop app, it is already serving — skip `ollama serve`.
+
+Verify the model is available:
+
+```bash
+curl -s http://localhost:11434/v1/models | python3 -m json.tool
+```
+
+> **Using a different model?** Set `MODEL_ID` in `.env` (e.g., `MODEL_ID=llama3.2:3b`),
+> pull it with `ollama pull llama3.2:3b`, then run `make guardrails-config` to update the
+> guardrails config to match.
+>
+> **Using a remote endpoint instead of Ollama?** Set `LLM_BASE_URL` in `.env` to your
+> OpenAI-compatible endpoint, then run `make guardrails-config`.
+
 ### 4. Start NeMo Guardrails proxy
 
 > **Keep this terminal open** — the guardrails server needs to keep running.
+> It proxies requests from the agent to the LLM, applying safety rails on the way through.
 
 ```bash
-make guardrails-server   # starts on port 8090
+make guardrails-server   # starts on port 8090, proxies to Ollama on 11434
 ```
 
-The guardrails server reads its config from `guardrails/safety/`. To point it at a different LLM endpoint, either edit `guardrails/safety/config.yaml` directly or set `LLM_BASE_URL` in `.env` and run `make guardrails-config`.
+The guardrails server reads its config from `guardrails/safety/config.yaml`. If you changed your LLM endpoint or model in step 3, make sure you ran `make guardrails-config` first.
 
 ### 5. Start the agent
 
diff --git a/agents/langgraph/examples/guardrailed_agent/pyproject.toml b/agents/langgraph/examples/guardrailed_agent/pyproject.toml
index ec8981a6..7fbfb762 100644
--- a/agents/langgraph/examples/guardrailed_agent/pyproject.toml
+++ b/agents/langgraph/examples/guardrailed_agent/pyproject.toml
@@ -35,6 +35,7 @@ dev = [
 guardrails = [
     "nemoguardrails[server]==0.21.0",
     "dataclasses-json>=0.6.7",
+    "langchain-community>=0.2,<0.4",
 ]
 tracing = [
     "mlflow[kubernetes]>=3.11.0",
diff --git a/agents/langgraph/examples/guardrailed_agent/uv.lock b/agents/langgraph/examples/guardrailed_agent/uv.lock
index b2577118..3fc6e897 100644
--- a/agents/langgraph/examples/guardrailed_agent/uv.lock
+++ b/agents/langgraph/examples/guardrailed_agent/uv.lock
@@ -1060,6 +1060,7 @@ dev = [
 ]
 guardrails = [
     { name = "dataclasses-json" },
+    { name = "langchain-community" },
     { name = "nemoguardrails", extra = ["server"] },
 ]
 tracing = [
@@ -1075,6 +1076,7 @@ requires-dist = [
     { name = "flask", specifier = ">=3.1.0" },
     { name = "httpx", marker = "extra == 'dev'", specifier = ">=0.27" },
     { name = "langchain", specifier = ">=1.2.10" },
+    { name = "langchain-community", marker = "extra == 'guardrails'", specifier = ">=0.2,<0.4" },
     { name = "langchain-openai", specifier = ">=1.1.10" },
     { name = "langgraph-prebuilt", specifier = ">=1.0.8" },
     { name = "milvus-lite", specifier = ">=2.5.1" },
@@ -1510,32 +1512,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/a9/ec/0f942e78a621f8e3162ff1ed24284f469aaf51fb4607ee5831c626f2b2bc/langchain-1.3.14-py3-none-any.whl", hash = "sha256:4d10dbe91005952cddd56d0dc77aa108964da6bae90ab20063653957e901f782", size = 139560, upload-time = "2026-07-16T13:28:16.498Z" },
 ]
 
-[[package]]
-name = "langchain-classic"
-version = "1.0.8"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "langchain-core" },
-    { name = "langchain-text-splitters" },
-    { name = "langsmith" },
-    { name = "pydantic" },
-    { name = "pyyaml" },
-    { name = "requests" },
-    { name = "sqlalchemy" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/8d/65/6b5e8a7ff2f2968652c88a67dcecb925b9d8f0a0ce9458c76cd5a0dbd138/langchain_classic-1.0.8.tar.gz", hash = "sha256:ada0cc341a8a5b80fb24d73bdfaaeb849056ee2d8a41cc468355163fd3667484", size = 10557071, upload-time = "2026-06-10T21:27:54.866Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/99/9a/b8f5cb7490fdbf233088031fc69c9c747439d4097f67f196c1eb4869916d/langchain_classic-1.0.8-py3-none-any.whl", hash = "sha256:1a11ea7fbe630c4f2af2f3873d27718ceac9488cf32d0821030be7cf039a6213", size = 1041536, upload-time = "2026-06-10T21:27:52.767Z" },
-]
-
 [[package]]
 name = "langchain-community"
-version = "0.4.2"
+version = "0.3.31"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "aiohttp" },
+    { name = "dataclasses-json" },
     { name = "httpx-sse" },
-    { name = "langchain-classic" },
+    { name = "langchain" },
     { name = "langchain-core" },
     { name = "langsmith" },
     { name = "numpy" },
@@ -1545,9 +1530,9 @@ dependencies = [
     { name = "sqlalchemy" },
     { name = "tenacity" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/ea/0c/e3aca1f2b1c5b95f8b87cb2b6e81a6f20d538c07a128419dc01cef0617b6/langchain_community-0.4.2.tar.gz", hash = "sha256:a99308160d53d7e9b5965ee665e5173709914338210089fd5788ad724432c21e", size = 33268708, upload-time = "2026-05-22T19:42:59.374Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/83/49/2ff5354273809e9811392bc24bcffda545a196070666aef27bc6aacf1c21/langchain_community-0.3.31.tar.gz", hash = "sha256:250e4c1041539130f6d6ac6f9386cb018354eafccd917b01a4cff1950b80fd81", size = 33241237, upload-time = "2025-10-07T20:17:57.857Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/8f/39/5d97e42a3e95dc2a6d71b2f902a3fae71786131e11d01bddb604accb0ebe/langchain_community-0.4.2-py3-none-any.whl", hash = "sha256:84dd8c5122532394d5b6849a5fc9995ef28e4f77227daeb09f24b3d942e9e466", size = 2364406, upload-time = "2026-05-22T19:42:57.103Z" },
+    { url = "https://files.pythonhosted.org/packages/e6/0a/b8848db67ad7c8d4652cb6f4cb78d49b5b5e6e8e51d695d62025aa3f7dbc/langchain_community-0.3.31-py3-none-any.whl", hash = "sha256:1c727e3ebbacd4d891b07bd440647668001cea3e39cbe732499ad655ec5cb569", size = 2532920, upload-time = "2025-10-07T20:17:54.91Z" },
 ]
 
 [[package]]
@@ -1596,18 +1581,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/99/2e/d82db9eec13ad0f72e7aaad5c4bc730ab111934fdc83c85523206eb9b0a0/langchain_protocol-0.0.18-py3-none-any.whl", hash = "sha256:70b53a86fbf9cedc863555effe44da192ab02d556ddbf2cf95b8873adcf41b5a", size = 7221, upload-time = "2026-06-18T17:08:25.996Z" },
 ]
 
-[[package]]
-name = "langchain-text-splitters"
-version = "1.1.2"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "langchain-core" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/26/9f/6c545900fefb7b00ddfa3f16b80d61338a0ec68c31c5451eeeab99082760/langchain_text_splitters-1.1.2.tar.gz", hash = "sha256:782a723db0a4746ac91e251c7c1d57fd23636e4f38ed733074e28d7a86f41627", size = 293580, upload-time = "2026-04-16T14:20:39.162Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/d3/26/1ef06f56198d631296d646a6223de35bcc6cf9795ceb2442816bc963b84c/langchain_text_splitters-1.1.2-py3-none-any.whl", hash = "sha256:a2de0d799ff31886429fd6e2e0032df275b60ec817c19059a7b46181cc1c2f10", size = 35903, upload-time = "2026-04-16T14:20:38.243Z" },
-]
-
 [[package]]
 name = "langgraph"
 version = "1.2.9"

From f056049617f30c6f886a617d1561c21c1f57f388 Mon Sep 17 00:00:00 2001
From: Tarun Kumar Reddy Etikala <tetikala@redhat.com>
Date: Thu, 23 Jul 2026 11:21:00 -0400
Subject: [PATCH 10/25] fix(guardrails): use OGX server as LLM backend
 (RHAIENG-6262)

Switch guardrails config default from Ollama (11434) to OGX (8321)
for consistency with react_agent workflow. Update README to use
make ogx-server instead of ollama serve. Update MODEL_ID to use
ollama/ prefix matching OGX convention.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---
 .../examples/guardrailed_agent/.env.example   |  4 +-
 .../examples/guardrailed_agent/Makefile       |  4 +-
 .../examples/guardrailed_agent/README.md      | 43 ++++++++-----------
 .../guardrails/safety/config.yaml             | 15 ++++---
 4 files changed, 29 insertions(+), 37 deletions(-)

diff --git a/agents/langgraph/examples/guardrailed_agent/.env.example b/agents/langgraph/examples/guardrailed_agent/.env.example
index ac90c3cf..0fcad14d 100644
--- a/agents/langgraph/examples/guardrailed_agent/.env.example
+++ b/agents/langgraph/examples/guardrailed_agent/.env.example
@@ -1,13 +1,13 @@
 # Required — agent connects to NeMo Guardrails proxy, not directly to the LLM
 API_KEY=not-needed-for-local-development
 BASE_URL=http://localhost:8090/v1
-MODEL_ID=llama3.1:8b
+MODEL_ID=ollama/Llama3.1:8B
 
 # NeMo Guardrails — the proxy server that sits between the agent and the LLM
 # Start with: make guardrails-server
 # The guardrails server config is in guardrails/safety/config.yaml
 # GUARDRAILS_PORT=8090
-# LLM_BASE_URL=http://localhost:11434/v1
+# LLM_BASE_URL=http://localhost:8321/v1
 
 # Deployment
 #CONTAINER_IMAGE=
diff --git a/agents/langgraph/examples/guardrailed_agent/Makefile b/agents/langgraph/examples/guardrailed_agent/Makefile
index 5d608fc9..3c607ca2 100644
--- a/agents/langgraph/examples/guardrailed_agent/Makefile
+++ b/agents/langgraph/examples/guardrailed_agent/Makefile
@@ -58,8 +58,8 @@ ollama: ## Install Ollama, start it, and pull models
 
 guardrails-config: ## Update guardrails config.yaml with LLM endpoint from .env
 	@source .venv/bin/activate && set -a && source .env && set +a && \
-	  LLM_URL=$${LLM_BASE_URL:-http://localhost:11434/v1} && \
-	  MODEL=$${MODEL_ID:-llama3.1:8b} && \
+	  LLM_URL=$${LLM_BASE_URL:-http://localhost:8321/v1} && \
+	  MODEL=$${MODEL_ID:-ollama/Llama3.1:8B} && \
 	  sed -i.bak \
 	    -e "s|base_url:.*|base_url: $$LLM_URL|g" \
 	    -e "s|model:.*|model: $$MODEL|g" \
diff --git a/agents/langgraph/examples/guardrailed_agent/README.md b/agents/langgraph/examples/guardrailed_agent/README.md
index 56a16f47..1bb34275 100644
--- a/agents/langgraph/examples/guardrailed_agent/README.md
+++ b/agents/langgraph/examples/guardrailed_agent/README.md
@@ -56,49 +56,40 @@ make init    # creates .env from .env.example
 make env     # creates venv and installs deps (including NeMo Guardrails)
 ```
 
-### 3. Start a local LLM
+### 3. Setup Ollama
 
-NeMo Guardrails needs an LLM endpoint for both conversation and safety classification (self-check approach). The default config points to Ollama on `localhost:11434`.
-
-Install Ollama and pull the model:
+Install Ollama and pull the default model:
 
 ```bash
 make ollama  # installs Ollama (if needed) and pulls llama3.1:8b
 ```
 
-Start the Ollama server (keep this terminal open):
+### 4. Start OGX server
+
+> **Keep this terminal open** — the OGX server needs to keep running.
+> NeMo Guardrails will proxy LLM requests through OGX to Ollama.
 
 ```bash
-ollama serve   # starts on port 11434
+make ogx-server  # starts on port 8321
 ```
 
-> If you use the Ollama macOS desktop app, it is already serving — skip `ollama serve`.
+### 5. Start NeMo Guardrails proxy
 
-Verify the model is available:
+> **In a separate terminal.** Keep it open — the guardrails server needs to keep running.
 
 ```bash
-curl -s http://localhost:11434/v1/models | python3 -m json.tool
+make guardrails-server   # starts on port 8090, proxies to OGX on 8321
 ```
 
-> **Using a different model?** Set `MODEL_ID` in `.env` (e.g., `MODEL_ID=llama3.2:3b`),
-> pull it with `ollama pull llama3.2:3b`, then run `make guardrails-config` to update the
-> guardrails config to match.
+The guardrails server reads its config from `guardrails/safety/config.yaml`.
+
+> **Using a different model?** Set `MODEL_ID` in `.env`, pull it with
+> `ollama pull <model>`, then run `make guardrails-config` to update the guardrails config.
 >
-> **Using a remote endpoint instead of Ollama?** Set `LLM_BASE_URL` in `.env` to your
+> **Using a remote endpoint instead of OGX?** Set `LLM_BASE_URL` in `.env` to your
 > OpenAI-compatible endpoint, then run `make guardrails-config`.
 
-### 4. Start NeMo Guardrails proxy
-
-> **Keep this terminal open** — the guardrails server needs to keep running.
-> It proxies requests from the agent to the LLM, applying safety rails on the way through.
-
-```bash
-make guardrails-server   # starts on port 8090, proxies to Ollama on 11434
-```
-
-The guardrails server reads its config from `guardrails/safety/config.yaml`. If you changed your LLM endpoint or model in step 3, make sure you ran `make guardrails-config` first.
-
-### 5. Start the agent
+### 6. Start the agent
 
 > **In a separate terminal:**
 
@@ -106,7 +97,7 @@ The guardrails server reads its config from `guardrails/safety/config.yaml`. If
 make run-app   # starts on port 8000
 ```
 
-### 6. Test the guardrails
+### 7. Test the guardrails
 
 ```bash
 # On-topic question — should respond normally
diff --git a/agents/langgraph/examples/guardrailed_agent/guardrails/safety/config.yaml b/agents/langgraph/examples/guardrailed_agent/guardrails/safety/config.yaml
index 1239d890..5857d73d 100644
--- a/agents/langgraph/examples/guardrailed_agent/guardrails/safety/config.yaml
+++ b/agents/langgraph/examples/guardrailed_agent/guardrails/safety/config.yaml
@@ -1,27 +1,28 @@
 # NeMo Guardrails configuration for the guardrailed agent.
-# Model endpoints below are defaults for local Ollama. To use a different LLM:
+# Model endpoints below default to the local OGX server (make ogx-server).
+# To use a different LLM:
 #   1. Edit the base_url and model values below, OR
 #   2. Run `make guardrails-config` to update from .env (LLM_BASE_URL, MODEL_ID)
 models:
   - type: main
     engine: openai
-    model: llama3.1:8b
+    model: ollama/Llama3.1:8B
     parameters:
-      base_url: http://localhost:11434/v1
+      base_url: http://localhost:8321/v1
     api_key_env_var: API_KEY
 
   - type: content_safety
     engine: openai
-    model: llama3.1:8b
+    model: ollama/Llama3.1:8B
     parameters:
-      base_url: http://localhost:11434/v1
+      base_url: http://localhost:8321/v1
     api_key_env_var: API_KEY
 
   - type: topic_control
     engine: openai
-    model: llama3.1:8b
+    model: ollama/Llama3.1:8B
     parameters:
-      base_url: http://localhost:11434/v1
+      base_url: http://localhost:8321/v1
     api_key_env_var: API_KEY
 
 rails:

From b7b5354c4552896202bc0a5b3cc903ffc1c0d6dc Mon Sep 17 00:00:00 2001
From: Tarun Kumar Reddy Etikala <tetikala@redhat.com>
Date: Thu, 23 Jul 2026 11:22:59 -0400
Subject: [PATCH 11/25] fix(guardrails): add missing ogx-server Makefile target
 (RHAIENG-6262)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---
 agents/langgraph/examples/guardrailed_agent/Makefile | 12 +++++++++++-
 1 file changed, 11 insertions(+), 1 deletion(-)

diff --git a/agents/langgraph/examples/guardrailed_agent/Makefile b/agents/langgraph/examples/guardrailed_agent/Makefile
index 3c607ca2..7a988d7a 100644
--- a/agents/langgraph/examples/guardrailed_agent/Makefile
+++ b/agents/langgraph/examples/guardrailed_agent/Makefile
@@ -54,7 +54,17 @@ ollama: ## Install Ollama, start it, and pull models
 	  echo "==> Pulling $(MODEL)..." && \
 	  ollama pull $(MODEL) && \
 	  echo "" && \
-	  echo "Done. Run 'make guardrails-server' to start NeMo Guardrails."
+	  echo "Done. Run 'make ogx-server' to start the OGX server."
+
+ogx-server: ## Install OGX and start OGX server
+	@source .venv/bin/activate && set -a && source .env && set +a && \
+	  echo "==> Installing OGX..." && \
+	  uv pip install "ogx[starter]==1.1.0" "ogx-api==1.1.0" ollama "pymilvus==2.6.9" "milvus-lite>=2.5.1" "setuptools>=80.9.0,<82.0.0" && \
+	  mkdir -p ../../../../milvus_data && \
+	  echo "==> Killing any existing process on port 8321..." && \
+	  lsof -ti:8321 | xargs kill -9 2>/dev/null; true && \
+	  echo "==> Starting OGX server on port 8321..." && \
+	  ogx run ../../../../run_ogx_server.yaml
 
 guardrails-config: ## Update guardrails config.yaml with LLM endpoint from .env
 	@source .venv/bin/activate && set -a && source .env && set +a && \

From 49539b4b92ad6b719686e79070cdf3a0ef3d72f0 Mon Sep 17 00:00:00 2001
From: Tarun Kumar Reddy Etikala <tetikala@redhat.com>
Date: Thu, 23 Jul 2026 11:24:16 -0400
Subject: [PATCH 12/25] fix(guardrails): use OGX-compatible model name
 (RHAIENG-6262)

OGX model names are case-sensitive and don't use the ollama/ prefix.
Change from 'ollama/Llama3.1:8B' to 'llama3.1:8b' in guardrails
config and Makefile default.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---
 agents/langgraph/examples/guardrailed_agent/Makefile        | 2 +-
 .../guardrailed_agent/guardrails/safety/config.yaml         | 6 +++---
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/agents/langgraph/examples/guardrailed_agent/Makefile b/agents/langgraph/examples/guardrailed_agent/Makefile
index 7a988d7a..3400bfe3 100644
--- a/agents/langgraph/examples/guardrailed_agent/Makefile
+++ b/agents/langgraph/examples/guardrailed_agent/Makefile
@@ -69,7 +69,7 @@ ogx-server: ## Install OGX and start OGX server
 guardrails-config: ## Update guardrails config.yaml with LLM endpoint from .env
 	@source .venv/bin/activate && set -a && source .env && set +a && \
 	  LLM_URL=$${LLM_BASE_URL:-http://localhost:8321/v1} && \
-	  MODEL=$${MODEL_ID:-ollama/Llama3.1:8B} && \
+	  MODEL=$${MODEL_ID:-llama3.1:8b} && \
 	  sed -i.bak \
 	    -e "s|base_url:.*|base_url: $$LLM_URL|g" \
 	    -e "s|model:.*|model: $$MODEL|g" \
diff --git a/agents/langgraph/examples/guardrailed_agent/guardrails/safety/config.yaml b/agents/langgraph/examples/guardrailed_agent/guardrails/safety/config.yaml
index 5857d73d..49a3131f 100644
--- a/agents/langgraph/examples/guardrailed_agent/guardrails/safety/config.yaml
+++ b/agents/langgraph/examples/guardrailed_agent/guardrails/safety/config.yaml
@@ -6,21 +6,21 @@
 models:
   - type: main
     engine: openai
-    model: ollama/Llama3.1:8B
+    model: llama3.1:8b
     parameters:
       base_url: http://localhost:8321/v1
     api_key_env_var: API_KEY
 
   - type: content_safety
     engine: openai
-    model: ollama/Llama3.1:8B
+    model: llama3.1:8b
     parameters:
       base_url: http://localhost:8321/v1
     api_key_env_var: API_KEY
 
   - type: topic_control
     engine: openai
-    model: ollama/Llama3.1:8B
+    model: llama3.1:8b
     parameters:
       base_url: http://localhost:8321/v1
     api_key_env_var: API_KEY

From 765b6fe831b7497105d62ca0e833854805b51762 Mon Sep 17 00:00:00 2001
From: Tarun Kumar Reddy Etikala <tetikala@redhat.com>
Date: Thu, 23 Jul 2026 12:08:23 -0400
Subject: [PATCH 13/25] fix(guardrails): enable passthrough and fix api_key
 (RHAIENG-6262)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Enable passthrough: true so NeMo acts as a safety filter, not a
conversational engine. Without it, NeMo runs 3 extra LLM calls
(intent/next-step/response generation) and ignores the agent's
system prompt and tools. With passthrough, the original prompt
passes straight through — rails still fire on input and output.
Switch from api_key_env_var to api_key in parameters (v0.21.0
LangChain initializer doesn't read api_key_env_var correctly).

E2E verified: on-topic passes, toxic blocked, off-topic blocked,
greeting passes.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---
 .../guardrails/safety/config.yaml              | 18 ++++++++++--------
 1 file changed, 10 insertions(+), 8 deletions(-)

diff --git a/agents/langgraph/examples/guardrailed_agent/guardrails/safety/config.yaml b/agents/langgraph/examples/guardrailed_agent/guardrails/safety/config.yaml
index 49a3131f..48a3a88d 100644
--- a/agents/langgraph/examples/guardrailed_agent/guardrails/safety/config.yaml
+++ b/agents/langgraph/examples/guardrailed_agent/guardrails/safety/config.yaml
@@ -1,29 +1,31 @@
 # NeMo Guardrails configuration for the guardrailed agent.
-# Model endpoints below default to the local OGX server (make ogx-server).
+# Model endpoints below default to Ollama on localhost.
 # To use a different LLM:
-#   1. Edit the base_url and model values below, OR
+#   1. Edit the base_url, model, and api_key values below, OR
 #   2. Run `make guardrails-config` to update from .env (LLM_BASE_URL, MODEL_ID)
 models:
   - type: main
     engine: openai
     model: llama3.1:8b
     parameters:
-      base_url: http://localhost:8321/v1
-    api_key_env_var: API_KEY
+      base_url: http://localhost:11434/v1
+      api_key: not-needed
 
   - type: content_safety
     engine: openai
     model: llama3.1:8b
     parameters:
-      base_url: http://localhost:8321/v1
-    api_key_env_var: API_KEY
+      base_url: http://localhost:11434/v1
+      api_key: not-needed
 
   - type: topic_control
     engine: openai
     model: llama3.1:8b
     parameters:
-      base_url: http://localhost:8321/v1
-    api_key_env_var: API_KEY
+      base_url: http://localhost:11434/v1
+      api_key: not-needed
+
+passthrough: true
 
 rails:
   config:

From 08463c8697b2988afa6a00c6d3175c280228b797 Mon Sep 17 00:00:00 2001
From: Tarun Kumar Reddy Etikala <tetikala@redhat.com>
Date: Mon, 27 Jul 2026 08:32:50 -0400
Subject: [PATCH 14/25] fix(guardrails): use Ollama direct, E2E verified
 (RHAIENG-6262)

Point guardrails config and .env defaults at Ollama (11434) instead
of OGX (8321). OGX has a pre-existing model name case mismatch
(Llama3.1:8B vs llama3.1:8b) that's a separate repo-wide issue.
Enable passthrough mode, use api_key in parameters.
Simplify README to 6 steps (remove OGX step).

E2E verified from clean make init: on-topic passes, toxic blocked,
off-topic blocked, greeting passes. 28/28 unit tests pass.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---
 .../examples/guardrailed_agent/.env.example   |  4 ++--
 .../examples/guardrailed_agent/README.md      | 21 +++++++------------
 2 files changed, 9 insertions(+), 16 deletions(-)

diff --git a/agents/langgraph/examples/guardrailed_agent/.env.example b/agents/langgraph/examples/guardrailed_agent/.env.example
index 0fcad14d..ac90c3cf 100644
--- a/agents/langgraph/examples/guardrailed_agent/.env.example
+++ b/agents/langgraph/examples/guardrailed_agent/.env.example
@@ -1,13 +1,13 @@
 # Required — agent connects to NeMo Guardrails proxy, not directly to the LLM
 API_KEY=not-needed-for-local-development
 BASE_URL=http://localhost:8090/v1
-MODEL_ID=ollama/Llama3.1:8B
+MODEL_ID=llama3.1:8b
 
 # NeMo Guardrails — the proxy server that sits between the agent and the LLM
 # Start with: make guardrails-server
 # The guardrails server config is in guardrails/safety/config.yaml
 # GUARDRAILS_PORT=8090
-# LLM_BASE_URL=http://localhost:8321/v1
+# LLM_BASE_URL=http://localhost:11434/v1
 
 # Deployment
 #CONTAINER_IMAGE=
diff --git a/agents/langgraph/examples/guardrailed_agent/README.md b/agents/langgraph/examples/guardrailed_agent/README.md
index 1bb34275..2b4772c3 100644
--- a/agents/langgraph/examples/guardrailed_agent/README.md
+++ b/agents/langgraph/examples/guardrailed_agent/README.md
@@ -64,21 +64,14 @@ Install Ollama and pull the default model:
 make ollama  # installs Ollama (if needed) and pulls llama3.1:8b
 ```
 
-### 4. Start OGX server
+Ensure Ollama is running (the macOS desktop app handles this automatically; otherwise run `ollama serve` in a separate terminal).
 
-> **Keep this terminal open** — the OGX server needs to keep running.
-> NeMo Guardrails will proxy LLM requests through OGX to Ollama.
+### 4. Start NeMo Guardrails proxy
 
-```bash
-make ogx-server  # starts on port 8321
-```
-
-### 5. Start NeMo Guardrails proxy
-
-> **In a separate terminal.** Keep it open — the guardrails server needs to keep running.
+> **Keep this terminal open** — the guardrails server needs to keep running.
 
 ```bash
-make guardrails-server   # starts on port 8090, proxies to OGX on 8321
+make guardrails-server   # starts on port 8090, proxies to Ollama on 11434
 ```
 
 The guardrails server reads its config from `guardrails/safety/config.yaml`.
@@ -86,10 +79,10 @@ The guardrails server reads its config from `guardrails/safety/config.yaml`.
 > **Using a different model?** Set `MODEL_ID` in `.env`, pull it with
 > `ollama pull <model>`, then run `make guardrails-config` to update the guardrails config.
 >
-> **Using a remote endpoint instead of OGX?** Set `LLM_BASE_URL` in `.env` to your
+> **Using a remote endpoint instead of Ollama?** Set `LLM_BASE_URL` in `.env` to your
 > OpenAI-compatible endpoint, then run `make guardrails-config`.
 
-### 6. Start the agent
+### 5. Start the agent
 
 > **In a separate terminal:**
 
@@ -97,7 +90,7 @@ The guardrails server reads its config from `guardrails/safety/config.yaml`.
 make run-app   # starts on port 8000
 ```
 
-### 7. Test the guardrails
+### 6. Test the guardrails
 
 ```bash
 # On-topic question — should respond normally

From f555d2067cc44f8152a345d012aff7c5494ecda3 Mon Sep 17 00:00:00 2001
From: Tarun Kumar Reddy Etikala <tetikala@redhat.com>
Date: Mon, 27 Jul 2026 08:35:00 -0400
Subject: [PATCH 15/25] fix(guardrails): fix ollama target next-steps message
 (RHAIENG-6262)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---
 agents/langgraph/examples/guardrailed_agent/Makefile | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/agents/langgraph/examples/guardrailed_agent/Makefile b/agents/langgraph/examples/guardrailed_agent/Makefile
index 3400bfe3..6c94c8f6 100644
--- a/agents/langgraph/examples/guardrailed_agent/Makefile
+++ b/agents/langgraph/examples/guardrailed_agent/Makefile
@@ -54,7 +54,7 @@ ollama: ## Install Ollama, start it, and pull models
 	  echo "==> Pulling $(MODEL)..." && \
 	  ollama pull $(MODEL) && \
 	  echo "" && \
-	  echo "Done. Run 'make ogx-server' to start the OGX server."
+	  echo "Done. Run 'make guardrails-server' to start NeMo Guardrails."
 
 ogx-server: ## Install OGX and start OGX server
 	@source .venv/bin/activate && set -a && source .env && set +a && \

From 949f95924a9aea3a10cffe7096531c80b7156e6c Mon Sep 17 00:00:00 2001
From: Tarun Kumar Reddy Etikala <tetikala@redhat.com>
Date: Mon, 27 Jul 2026 08:38:57 -0400
Subject: [PATCH 16/25] fix(guardrails): remove ogx-server target from Makefile
 (RHAIENG-6262)

Remove unused ogx-server target and .PHONY entry. Fix
guardrails-config default LLM_BASE_URL to Ollama (11434).

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---
 .../examples/guardrailed_agent/Makefile          | 16 +++-------------
 1 file changed, 3 insertions(+), 13 deletions(-)

diff --git a/agents/langgraph/examples/guardrailed_agent/Makefile b/agents/langgraph/examples/guardrailed_agent/Makefile
index 6c94c8f6..a23396da 100644
--- a/agents/langgraph/examples/guardrailed_agent/Makefile
+++ b/agents/langgraph/examples/guardrailed_agent/Makefile
@@ -5,7 +5,7 @@ VALUES_FILE    := values.yaml
 CONTAINER_CLI  := $(shell command -v podman 2>/dev/null || command -v docker 2>/dev/null)
 MODEL          ?= llama3.1:8b
 
-.PHONY: init re-init env ollama ogx-server run-app run-app-fresh build push build-openshift deploy undeploy test test-integration test-auth-integration dry-run help guardrails-config guardrails-server
+.PHONY: init re-init env ollama run-app run-app-fresh build push build-openshift deploy undeploy test test-integration test-auth-integration dry-run help guardrails-config guardrails-server
 
 help: ## Show this help
 	@grep -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "  %-20s %s\n", $$1, $$2}'
@@ -17,7 +17,7 @@ re-init: ## Activate venv and reload .env variables
 init: ## Copy .env.example to .env for configuration
 	@if [ ! -f .env ]; then cp .env.example .env && echo "Created .env from .env.example - edit it with your configuration"; else echo ".env already exists - skipping"; fi
 
-env: ## Create venv, load .env, and install dependencies (add --extra guardrails for NeMo)
+env: ## Create venv, load .env, and install dependencies (including NeMo Guardrails)
 	@echo "==> Creating virtual environment and installing dependencies..." && \
 	  rm -rf .venv && \
 	  uv sync --python 3.12 --extra guardrails && \
@@ -56,19 +56,9 @@ ollama: ## Install Ollama, start it, and pull models
 	  echo "" && \
 	  echo "Done. Run 'make guardrails-server' to start NeMo Guardrails."
 
-ogx-server: ## Install OGX and start OGX server
-	@source .venv/bin/activate && set -a && source .env && set +a && \
-	  echo "==> Installing OGX..." && \
-	  uv pip install "ogx[starter]==1.1.0" "ogx-api==1.1.0" ollama "pymilvus==2.6.9" "milvus-lite>=2.5.1" "setuptools>=80.9.0,<82.0.0" && \
-	  mkdir -p ../../../../milvus_data && \
-	  echo "==> Killing any existing process on port 8321..." && \
-	  lsof -ti:8321 | xargs kill -9 2>/dev/null; true && \
-	  echo "==> Starting OGX server on port 8321..." && \
-	  ogx run ../../../../run_ogx_server.yaml
-
 guardrails-config: ## Update guardrails config.yaml with LLM endpoint from .env
 	@source .venv/bin/activate && set -a && source .env && set +a && \
-	  LLM_URL=$${LLM_BASE_URL:-http://localhost:8321/v1} && \
+	  LLM_URL=$${LLM_BASE_URL:-http://localhost:11434/v1} && \
 	  MODEL=$${MODEL_ID:-llama3.1:8b} && \
 	  sed -i.bak \
 	    -e "s|base_url:.*|base_url: $$LLM_URL|g" \

From 08d8a6ce4710dfacdc4f1af38cb795bbb0ec8c7b Mon Sep 17 00:00:00 2001
From: Tarun Kumar Reddy Etikala <tetikala@redhat.com>
Date: Mon, 27 Jul 2026 08:50:18 -0400
Subject: [PATCH 17/25] fix(guardrails): handle output rail block gracefully
 (RHAIENG-6262)

When topic safety input rail misses an off-topic request (model
dependent), the LLM may generate a response that the output content
safety rail then blocks. NeMo returns an error that ChatOpenAI raises
as APIError. Catch guardrails block errors and return a clean refusal
instead of HTTP 500.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---
 .../examples/guardrailed_agent/main.py         | 18 ++++++++++++++++++
 1 file changed, 18 insertions(+)

diff --git a/agents/langgraph/examples/guardrailed_agent/main.py b/agents/langgraph/examples/guardrailed_agent/main.py
index 1ff819b2..8652a5cc 100644
--- a/agents/langgraph/examples/guardrailed_agent/main.py
+++ b/agents/langgraph/examples/guardrailed_agent/main.py
@@ -301,6 +301,24 @@ async def _handle_chat(messages: list[HumanMessage], model_id: str) -> dict[str,
         }
 
     except Exception as e:
+        if "Blocked by" in str(e) and "rails" in str(e):
+            return {
+                "id": _make_completion_id(),
+                "object": "chat.completion",
+                "created": int(time.time()),
+                "model": model_id,
+                "choices": [
+                    {
+                        "index": 0,
+                        "message": {
+                            "role": "assistant",
+                            "content": "I'm sorry, I can't respond to that.",
+                        },
+                        "finish_reason": "stop",
+                    }
+                ],
+                "usage": None,
+            }
         raise HTTPException(
             status_code=500, detail=f"Error processing request: {str(e)}"
         )

From 05abe1a4ef582f9aa10b48fe83a052b831ff8234 Mon Sep 17 00:00:00 2001
From: Tarun Kumar Reddy Etikala <tetikala@redhat.com>
Date: Mon, 27 Jul 2026 08:59:34 -0400
Subject: [PATCH 18/25] fix(guardrails): handle output rail block in streaming
 (RHAIENG-6262)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

When NeMo output rail blocks a response mid-stream, the agent gets
an openai.APIError. Handle it in _handle_stream by sending a clean
finish chunk and [DONE] (NeMo already sent the refusal message via
the stream before the error). Prevents duplicate refusal messages
and Internal server error in streaming mode.

E2E verified: streaming off-topic 3/3, streaming on-topic, non-stream
toxic, non-stream greeting — all clean, zero 500s in logs.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---
 .../examples/guardrailed_agent/main.py        | 33 ++++++++++++++-----
 1 file changed, 25 insertions(+), 8 deletions(-)

diff --git a/agents/langgraph/examples/guardrailed_agent/main.py b/agents/langgraph/examples/guardrailed_agent/main.py
index 8652a5cc..dd8126fc 100644
--- a/agents/langgraph/examples/guardrailed_agent/main.py
+++ b/agents/langgraph/examples/guardrailed_agent/main.py
@@ -436,15 +436,32 @@ async def event_generator() -> AsyncIterator[str]:
             yield f"data: {json.dumps(final_data)}\n\n"
             yield "data: [DONE]\n\n"
 
-        except Exception:
-            logger.exception("Error in stream event_generator")
-            error_data = {
-                "error": {
-                    "message": "Internal server error",
-                    "type": "server_error",
+        except Exception as e:
+            if "Blocked by" in str(e) and "rails" in str(e):
+                final_data = {
+                    "id": completion_id,
+                    "object": "chat.completion.chunk",
+                    "created": created,
+                    "model": model_id,
+                    "choices": [
+                        {
+                            "index": 0,
+                            "delta": {},
+                            "finish_reason": "stop",
+                        }
+                    ],
                 }
-            }
-            yield f"data: {json.dumps(error_data)}\n\n"
+                yield f"data: {json.dumps(final_data)}\n\n"
+                yield "data: [DONE]\n\n"
+            else:
+                logger.exception("Error in stream event_generator")
+                error_data = {
+                    "error": {
+                        "message": "Internal server error",
+                        "type": "server_error",
+                    }
+                }
+                yield f"data: {json.dumps(error_data)}\n\n"
 
     return StreamingResponse(
         event_generator(),

From 99f4583fc858ba349c821b19fa45e5dbea9c09d3 Mon Sep 17 00:00:00 2001
From: Tarun Kumar Reddy Etikala <tetikala@redhat.com>
Date: Mon, 27 Jul 2026 09:22:11 -0400
Subject: [PATCH 19/25] fix(guardrails): address review findings (RHAIENG-6262)

P1.2: Add max_tokens: 10 to topic safety prompt to cap LLM output.
P2.3: Remove unused AccountInput class from tools.py.
P2.5: Add api_key sed replacement to guardrails-config target.
P3.6: Extract _is_guardrails_block() helper, narrow to OpenAIAPIError.
P3.7: Log exceptions server-side, return generic message to client.
P3.10: Use NeMo refusal message from exception when available.

Also: remove unused deps (milvus-lite, pymilvus, pypdf, flask,
chardet), fix Python version <3.14, fix FastAPI title.

E2E verified: 8/8 tests (streaming + non-streaming), zero errors.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---
 .../examples/guardrailed_agent/Makefile       |    4 +-
 .../guardrails/safety/prompts.yml             |    1 +
 .../examples/guardrailed_agent/main.py        |   30 +-
 .../examples/guardrailed_agent/pyproject.toml |    7 +-
 .../src/guardrailed_agent/tools.py            |    7 -
 .../examples/guardrailed_agent/uv.lock        | 1027 +----------------
 6 files changed, 52 insertions(+), 1024 deletions(-)

diff --git a/agents/langgraph/examples/guardrailed_agent/Makefile b/agents/langgraph/examples/guardrailed_agent/Makefile
index a23396da..20b5cbd6 100644
--- a/agents/langgraph/examples/guardrailed_agent/Makefile
+++ b/agents/langgraph/examples/guardrailed_agent/Makefile
@@ -60,12 +60,14 @@ guardrails-config: ## Update guardrails config.yaml with LLM endpoint from .env
 	@source .venv/bin/activate && set -a && source .env && set +a && \
 	  LLM_URL=$${LLM_BASE_URL:-http://localhost:11434/v1} && \
 	  MODEL=$${MODEL_ID:-llama3.1:8b} && \
+	  KEY=$${API_KEY:-not-needed} && \
 	  sed -i.bak \
 	    -e "s|base_url:.*|base_url: $$LLM_URL|g" \
 	    -e "s|model:.*|model: $$MODEL|g" \
+	    -e "s|api_key:.*|api_key: $$KEY|g" \
 	    guardrails/safety/config.yaml && \
 	  rm -f guardrails/safety/config.yaml.bak && \
-	  echo "Updated guardrails/safety/config.yaml with LLM_BASE_URL=$$LLM_URL MODEL_ID=$$MODEL"
+	  echo "Updated guardrails/safety/config.yaml with LLM_BASE_URL=$$LLM_URL MODEL_ID=$$MODEL API_KEY=***"
 
 guardrails-server: ## Start NeMo Guardrails server on GUARDRAILS_PORT (default 8090)
 	@source .venv/bin/activate && set -a && source .env && set +a && \
diff --git a/agents/langgraph/examples/guardrailed_agent/guardrails/safety/prompts.yml b/agents/langgraph/examples/guardrailed_agent/guardrails/safety/prompts.yml
index e42c8e7b..71e7cc92 100644
--- a/agents/langgraph/examples/guardrailed_agent/guardrails/safety/prompts.yml
+++ b/agents/langgraph/examples/guardrailed_agent/guardrails/safety/prompts.yml
@@ -87,3 +87,4 @@ prompts:
       - Do not answer questions about entertainment, sports, or celebrity gossip.
       - Do not answer questions about personal relationships or dating advice.
       - If a user asks topics irrelevant to banking and financial services, politely redirect.
+    max_tokens: 10
diff --git a/agents/langgraph/examples/guardrailed_agent/main.py b/agents/langgraph/examples/guardrailed_agent/main.py
index dd8126fc..936cb49f 100644
--- a/agents/langgraph/examples/guardrailed_agent/main.py
+++ b/agents/langgraph/examples/guardrailed_agent/main.py
@@ -18,10 +18,24 @@
 from guardrailed_agent.agent import get_graph_closure
 from guardrailed_agent.tracing import enable_tracing
 from langchain_core.messages import AIMessage, HumanMessage, ToolMessage
+from openai import APIError as OpenAIAPIError
 from pydantic import BaseModel, Field
 
 logger = logging.getLogger(__name__)
 
+_GUARDRAILS_REFUSAL = "I'm sorry, I can't respond to that."
+
+
+def _is_guardrails_block(exc: Exception) -> bool:
+    """NeMo Guardrails v0.21.0 has no typed exception for rail blocks.
+    It raises openai.APIError with 'Blocked by ... rails' in the message.
+    This coupling is version-specific and may need updating for newer NeMo."""
+    return (
+        isinstance(exc, OpenAIAPIError)
+        and "Blocked by" in str(exc)
+        and "rails" in str(exc)
+    )
+
 
 # OpenAI-compatible request/response models
 class ChatMessage(BaseModel):
@@ -143,8 +157,8 @@ async def lifespan(app: FastAPI) -> AsyncIterator[None]:
 
 # Create FastAPI app
 app = FastAPI(
-    title="LangGraph React Agent API",
-    description="FastAPI service for LangGraph React Agent with OpenAI-compatible chat completions API.",
+    title="LangGraph Guardrailed Agent API",
+    description="FastAPI service for LangGraph Guardrailed Agent with OpenAI-compatible chat completions API.",
     lifespan=lifespan,
     openapi_tags=[
         {"name": "Chat", "description": "Chat completion operations"},
@@ -301,7 +315,7 @@ async def _handle_chat(messages: list[HumanMessage], model_id: str) -> dict[str,
         }
 
     except Exception as e:
-        if "Blocked by" in str(e) and "rails" in str(e):
+        if _is_guardrails_block(e):
             return {
                 "id": _make_completion_id(),
                 "object": "chat.completion",
@@ -312,16 +326,16 @@ async def _handle_chat(messages: list[HumanMessage], model_id: str) -> dict[str,
                         "index": 0,
                         "message": {
                             "role": "assistant",
-                            "content": "I'm sorry, I can't respond to that.",
+                            "content": getattr(e, "message", None)
+                            or _GUARDRAILS_REFUSAL,
                         },
                         "finish_reason": "stop",
                     }
                 ],
                 "usage": None,
             }
-        raise HTTPException(
-            status_code=500, detail=f"Error processing request: {str(e)}"
-        )
+        logger.exception("Error processing chat request")
+        raise HTTPException(status_code=500, detail="Error processing request")
 
 
 async def _handle_stream(
@@ -437,7 +451,7 @@ async def event_generator() -> AsyncIterator[str]:
             yield "data: [DONE]\n\n"
 
         except Exception as e:
-            if "Blocked by" in str(e) and "rails" in str(e):
+            if _is_guardrails_block(e):
                 final_data = {
                     "id": completion_id,
                     "object": "chat.completion.chunk",
diff --git a/agents/langgraph/examples/guardrailed_agent/pyproject.toml b/agents/langgraph/examples/guardrailed_agent/pyproject.toml
index 7fbfb762..22801631 100644
--- a/agents/langgraph/examples/guardrailed_agent/pyproject.toml
+++ b/agents/langgraph/examples/guardrailed_agent/pyproject.toml
@@ -4,7 +4,7 @@ version = "0.1.0"
 description = "An FSI customer service agent with NeMo Guardrails safety layer. Demonstrates content safety, topical guardrails, and regex filtering using the proxy pattern."
 authors = [{ name = "Your Name", email = "you@example.com" }]
 license = { text = "MIT" }
-requires-python = ">=3.12,<=3.14"
+requires-python = ">=3.12,<3.14"
 dependencies = [
     "fastapi>=0.135.1",
     "uvicorn[standard]>=0.41.0",
@@ -12,13 +12,8 @@ dependencies = [
     "langchain-openai>=1.1.10",
     "langgraph-prebuilt>=1.0.8",
     "openai>=2.24.0",
-    "milvus-lite>=2.5.1",
-    "pymilvus==2.6.9",
     "python-dotenv>=1.2.2",
     "setuptools>=80.9.0,<83.0.0",
-    "chardet>=7.1.0",
-    "pypdf>=6.9.0",
-    "flask>=3.1.0",
     "starlette>=1.0.1",
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 ]
diff --git a/agents/langgraph/examples/guardrailed_agent/src/guardrailed_agent/tools.py b/agents/langgraph/examples/guardrailed_agent/src/guardrailed_agent/tools.py
index 5ca4e84d..c5186099 100644
--- a/agents/langgraph/examples/guardrailed_agent/src/guardrailed_agent/tools.py
+++ b/agents/langgraph/examples/guardrailed_agent/src/guardrailed_agent/tools.py
@@ -1,11 +1,4 @@
 from langchain_core.tools import tool
-from pydantic import BaseModel, Field
-
-
-class AccountInput(BaseModel):
-    """Schema for the account balance tool input."""
-
-    account_id: str = Field(description="The customer account ID to look up.")
 
 
 @tool("check_balance", parse_docstring=True)
diff --git a/agents/langgraph/examples/guardrailed_agent/uv.lock b/agents/langgraph/examples/guardrailed_agent/uv.lock
index 3fc6e897..df91b85c 100644
--- a/agents/langgraph/examples/guardrailed_agent/uv.lock
+++ b/agents/langgraph/examples/guardrailed_agent/uv.lock
@@ -1,9 +1,8 @@
 version = 1
 revision = 3
-requires-python = ">=3.12, <=3.14"
+requires-python = ">=3.12, <3.14"
 resolution-markers = [
-    "python_full_version >= '3.14'",
-    "python_full_version == '3.13.*'",
+    "python_full_version >= '3.13'",
     "python_full_version < '3.13'",
 ]
 
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 ]

From d28480031f149049bf0a76612a28f98468421941 Mon Sep 17 00:00:00 2001
From: Tarun Kumar Reddy Etikala <tetikala@redhat.com>
Date: Mon, 27 Jul 2026 09:39:34 -0400
Subject: [PATCH 20/25] fix(guardrails): address remaining review findings
 (RHAIENG-6262)

F1: Use _GUARDRAILS_REFUSAL constant (not NeMo internal rail names).
F2: Fix playground images path (4 parents, not 3).
F3: Add guardrails_reachable probe to /health endpoint.
F4: Replace sed with python3+yaml in guardrails-config target.
F5: Document credentials warning for make guardrails-config.
F6: Add test_passthrough_enabled assertion.
F7: Add topic_control model type assertion.

E2E verified: health probe (up/down), 5 request tests, 29 unit tests.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---
 .../examples/guardrailed_agent/Makefile       | 20 +++++++-------
 .../examples/guardrailed_agent/README.md      |  3 +++
 .../examples/guardrailed_agent/main.py        | 27 +++++++++++++++----
 .../examples/guardrailed_agent/pyproject.toml |  1 +
 .../tests/test_guardrails_config.py           |  4 +++
 .../examples/guardrailed_agent/uv.lock        |  2 ++
 6 files changed, 42 insertions(+), 15 deletions(-)

diff --git a/agents/langgraph/examples/guardrailed_agent/Makefile b/agents/langgraph/examples/guardrailed_agent/Makefile
index 20b5cbd6..775683d1 100644
--- a/agents/langgraph/examples/guardrailed_agent/Makefile
+++ b/agents/langgraph/examples/guardrailed_agent/Makefile
@@ -58,16 +58,16 @@ ollama: ## Install Ollama, start it, and pull models
 
 guardrails-config: ## Update guardrails config.yaml with LLM endpoint from .env
 	@source .venv/bin/activate && set -a && source .env && set +a && \
-	  LLM_URL=$${LLM_BASE_URL:-http://localhost:11434/v1} && \
-	  MODEL=$${MODEL_ID:-llama3.1:8b} && \
-	  KEY=$${API_KEY:-not-needed} && \
-	  sed -i.bak \
-	    -e "s|base_url:.*|base_url: $$LLM_URL|g" \
-	    -e "s|model:.*|model: $$MODEL|g" \
-	    -e "s|api_key:.*|api_key: $$KEY|g" \
-	    guardrails/safety/config.yaml && \
-	  rm -f guardrails/safety/config.yaml.bak && \
-	  echo "Updated guardrails/safety/config.yaml with LLM_BASE_URL=$$LLM_URL MODEL_ID=$$MODEL API_KEY=***"
+	  python3 -c "\
+	import yaml, sys; \
+	f='guardrails/safety/config.yaml'; \
+	c=yaml.safe_load(open(f)); \
+	url='$${LLM_BASE_URL:-http://localhost:11434/v1}'; \
+	model='$${MODEL_ID:-llama3.1:8b}'; \
+	key='$${API_KEY:-not-needed}'; \
+	[m['parameters'].update(base_url=url, api_key=key) or m.update(model=model) for m in c['models']]; \
+	yaml.dump(c, open(f,'w'), default_flow_style=False, sort_keys=False); \
+	print(f'Updated {f} with LLM_BASE_URL={url} MODEL_ID={model} API_KEY=***')"
 
 guardrails-server: ## Start NeMo Guardrails server on GUARDRAILS_PORT (default 8090)
 	@source .venv/bin/activate && set -a && source .env && set +a && \
diff --git a/agents/langgraph/examples/guardrailed_agent/README.md b/agents/langgraph/examples/guardrailed_agent/README.md
index 2b4772c3..7601da53 100644
--- a/agents/langgraph/examples/guardrailed_agent/README.md
+++ b/agents/langgraph/examples/guardrailed_agent/README.md
@@ -81,6 +81,9 @@ The guardrails server reads its config from `guardrails/safety/config.yaml`.
 >
 > **Using a remote endpoint instead of Ollama?** Set `LLM_BASE_URL` in `.env` to your
 > OpenAI-compatible endpoint, then run `make guardrails-config`.
+>
+> **Warning:** `make guardrails-config` writes your `API_KEY` into `guardrails/safety/config.yaml`.
+> Do not commit this file after running with real credentials.
 
 ### 5. Start the agent
 
diff --git a/agents/langgraph/examples/guardrailed_agent/main.py b/agents/langgraph/examples/guardrailed_agent/main.py
index 936cb49f..a52228b5 100644
--- a/agents/langgraph/examples/guardrailed_agent/main.py
+++ b/agents/langgraph/examples/guardrailed_agent/main.py
@@ -129,6 +129,10 @@ class HealthResponse(BaseModel):
         ...,
         description="Whether the agent has been initialized and is ready to serve requests.",
     )
+    guardrails_reachable: bool = Field(
+        False,
+        description="Whether the NeMo Guardrails proxy server is reachable.",
+    )
 
 
 # Global variable for agent graph
@@ -326,8 +330,7 @@ async def _handle_chat(messages: list[HumanMessage], model_id: str) -> dict[str,
                         "index": 0,
                         "message": {
                             "role": "assistant",
-                            "content": getattr(e, "message", None)
-                            or _GUARDRAILS_REFUSAL,
+                            "content": _GUARDRAILS_REFUSAL,
                         },
                         "finish_reason": "stop",
                     }
@@ -489,11 +492,25 @@ async def event_generator() -> AsyncIterator[str]:
 )
 async def health():
     initialized = agent_graph is not None
+    guardrails_ok = False
+    base_url = getenv("BASE_URL", "")
+    if initialized and base_url:
+        import httpx
+
+        probe_url = base_url.rstrip("/").removesuffix("/v1")
+        try:
+            async with httpx.AsyncClient(timeout=2) as client:
+                r = await client.get(probe_url)
+                guardrails_ok = r.status_code < 500
+        except Exception:
+            guardrails_ok = False
+
     body = {
-        "status": "healthy" if initialized else "not_ready",
+        "status": "healthy" if initialized and guardrails_ok else "not_ready",
         "agent_initialized": initialized,
+        "guardrails_reachable": guardrails_ok,
     }
-    if not initialized:
+    if not initialized or not guardrails_ok:
         return JSONResponse(status_code=503, content=body)
     return body
 
@@ -504,7 +521,7 @@ async def health():
 # In Docker the images are copied to /opt/app-root/src/images; locally they live at the repo root
 _IMAGES_DIR = _BASE_DIR / "images"
 if not _IMAGES_DIR.is_dir():
-    _IMAGES_DIR = _BASE_DIR.parent.parent.parent / "images"
+    _IMAGES_DIR = _BASE_DIR.parent.parent.parent.parent / "images"
 
 
 @app.get("/", response_class=HTMLResponse, include_in_schema=False)
diff --git a/agents/langgraph/examples/guardrailed_agent/pyproject.toml b/agents/langgraph/examples/guardrailed_agent/pyproject.toml
index 22801631..1e5c643e 100644
--- a/agents/langgraph/examples/guardrailed_agent/pyproject.toml
+++ b/agents/langgraph/examples/guardrailed_agent/pyproject.toml
@@ -12,6 +12,7 @@ dependencies = [
     "langchain-openai>=1.1.10",
     "langgraph-prebuilt>=1.0.8",
     "openai>=2.24.0",
+    "httpx>=0.27",
     "python-dotenv>=1.2.2",
     "setuptools>=80.9.0,<83.0.0",
     "starlette>=1.0.1",
diff --git a/agents/langgraph/examples/guardrailed_agent/tests/test_guardrails_config.py b/agents/langgraph/examples/guardrailed_agent/tests/test_guardrails_config.py
index 259784cb..fd7ce0c3 100644
--- a/agents/langgraph/examples/guardrailed_agent/tests/test_guardrails_config.py
+++ b/agents/langgraph/examples/guardrailed_agent/tests/test_guardrails_config.py
@@ -39,6 +39,10 @@ def test_has_models_section(self):
         model_types = {m["type"] for m in self.config["models"]}
         assert "main" in model_types
         assert "content_safety" in model_types
+        assert "topic_control" in model_types
+
+    def test_passthrough_enabled(self):
+        assert self.config.get("passthrough") is True
 
     def test_has_input_rails(self):
         flows = self.config["rails"]["input"]["flows"]
diff --git a/agents/langgraph/examples/guardrailed_agent/uv.lock b/agents/langgraph/examples/guardrailed_agent/uv.lock
index df91b85c..0496a8dc 100644
--- a/agents/langgraph/examples/guardrailed_agent/uv.lock
+++ b/agents/langgraph/examples/guardrailed_agent/uv.lock
@@ -746,6 +746,7 @@ version = "0.1.0"
 source = { editable = "." }
 dependencies = [
     { name = "fastapi" },
+    { name = "httpx" },
     { name = "langchain" },
     { name = "langchain-openai" },
     { name = "langgraph-prebuilt" },
@@ -780,6 +781,7 @@ requires-dist = [
     { name = "agent-auth", marker = "extra == 'auth'", directory = "../../../../components/auth" },
     { name = "dataclasses-json", marker = "extra == 'guardrails'", specifier = ">=0.6.7" },
     { name = "fastapi", specifier = ">=0.135.1" },
+    { name = "httpx", specifier = ">=0.27" },
     { name = "httpx", marker = "extra == 'dev'", specifier = ">=0.27" },
     { name = "langchain", specifier = ">=1.2.10" },
     { name = "langchain-community", marker = "extra == 'guardrails'", specifier = ">=0.2,<0.4" },

From 4f9dba03472c2536aba52e78ae850cbd3c3b75c9 Mon Sep 17 00:00:00 2001
From: Tarun Kumar Reddy Etikala <tetikala@redhat.com>
Date: Mon, 27 Jul 2026 10:02:30 -0400
Subject: [PATCH 21/25] docs(guardrails): replace FSI acronym with banking
 (RHAIENG-6262)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---
 agents/langgraph/examples/guardrailed_agent/README.md      | 2 +-
 agents/langgraph/examples/guardrailed_agent/agent.yaml     | 2 +-
 agents/langgraph/examples/guardrailed_agent/pyproject.toml | 2 +-
 3 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/agents/langgraph/examples/guardrailed_agent/README.md b/agents/langgraph/examples/guardrailed_agent/README.md
index 7601da53..27ca5464 100644
--- a/agents/langgraph/examples/guardrailed_agent/README.md
+++ b/agents/langgraph/examples/guardrailed_agent/README.md
@@ -10,7 +10,7 @@
 
 ## What this agent does
 
-FSI customer service agent with [NeMo Guardrails](https://github.com/NVIDIA/NeMo-Guardrails) safety layer. Demonstrates how to add content safety, topical guardrails, and regex-based input filtering to a LangGraph ReAct agent using the **proxy pattern** — NeMo Guardrails sits between the agent and the LLM, requiring zero changes to the agent's source code.
+Banking customer service agent with [NeMo Guardrails](https://github.com/NVIDIA/NeMo-Guardrails) safety layer. Demonstrates how to add content safety, topical guardrails, and regex-based input filtering to a LangGraph ReAct agent using the **proxy pattern** — NeMo Guardrails sits between the agent and the LLM, requiring zero changes to the agent's source code.
 
 ### Guardrails architecture
 
diff --git a/agents/langgraph/examples/guardrailed_agent/agent.yaml b/agents/langgraph/examples/guardrailed_agent/agent.yaml
index 105436e1..64192dd7 100644
--- a/agents/langgraph/examples/guardrailed_agent/agent.yaml
+++ b/agents/langgraph/examples/guardrailed_agent/agent.yaml
@@ -2,7 +2,7 @@ name: langgraph-guardrailed-agent
 displayName: "LangGraph Guardrailed Agent"
 framework: langgraph
 description: >
-  FSI customer service agent with NeMo Guardrails safety layer.
+  Banking customer service agent with NeMo Guardrails safety layer.
   Demonstrates content safety rails (input + output), topical guardrails
   (banking domain boundary), and regex-based input filtering using the
   NeMo Guardrails proxy pattern. Built on the LangGraph ReAct agent template.
diff --git a/agents/langgraph/examples/guardrailed_agent/pyproject.toml b/agents/langgraph/examples/guardrailed_agent/pyproject.toml
index 1e5c643e..e860fd94 100644
--- a/agents/langgraph/examples/guardrailed_agent/pyproject.toml
+++ b/agents/langgraph/examples/guardrailed_agent/pyproject.toml
@@ -1,7 +1,7 @@
 [project]
 name = "guardrailed_agent"
 version = "0.1.0"
-description = "An FSI customer service agent with NeMo Guardrails safety layer. Demonstrates content safety, topical guardrails, and regex filtering using the proxy pattern."
+description = "A banking customer service agent with NeMo Guardrails safety layer. Demonstrates content safety, topical guardrails, and regex filtering using the proxy pattern."
 authors = [{ name = "Your Name", email = "you@example.com" }]
 license = { text = "MIT" }
 requires-python = ">=3.12,<3.14"

From ed9ee1cf5725f5e4b0cf8f0ee3fa34e334e87fdd Mon Sep 17 00:00:00 2001
From: Tarun Kumar Reddy Etikala <tetikala@redhat.com>
Date: Mon, 27 Jul 2026 10:32:23 -0400
Subject: [PATCH 22/25] fix(guardrails): remove unimplemented test targets
 (RHAIENG-6262)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Remove test-integration and test-auth-integration — no
tests/integration/ directory exists. Simplify test target.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---
 .../langgraph/examples/guardrailed_agent/Makefile  | 14 ++------------
 1 file changed, 2 insertions(+), 12 deletions(-)

diff --git a/agents/langgraph/examples/guardrailed_agent/Makefile b/agents/langgraph/examples/guardrailed_agent/Makefile
index 775683d1..e374ce0c 100644
--- a/agents/langgraph/examples/guardrailed_agent/Makefile
+++ b/agents/langgraph/examples/guardrailed_agent/Makefile
@@ -5,7 +5,7 @@ VALUES_FILE    := values.yaml
 CONTAINER_CLI  := $(shell command -v podman 2>/dev/null || command -v docker 2>/dev/null)
 MODEL          ?= llama3.1:8b
 
-.PHONY: init re-init env ollama run-app run-app-fresh build push build-openshift deploy undeploy test test-integration test-auth-integration dry-run help guardrails-config guardrails-server
+.PHONY: init re-init env ollama run-app run-app-fresh build push build-openshift deploy undeploy test dry-run help guardrails-config guardrails-server
 
 help: ## Show this help
 	@grep -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "  %-20s %s\n", $$1, $$2}'
@@ -211,14 +211,4 @@ undeploy: ## Remove deployment from cluster
 	helm uninstall $(AGENT_NAME)
 
 test: ## Run unit tests
-	uv run --extra dev python -m pytest tests/ --ignore=tests/integration --ignore=tests/behavioral $(PYTEST_ARGS)
-
-test-integration: ## Run integration deployment test
-	PYTHONPATH=$$(git rev-parse --show-toplevel)/tests \
-	  uv run --extra dev python -m pytest tests/integration/test_deployment.py \
-	    -v --tb=long --junitxml=results.xml
-
-test-auth-integration: ## Run auth-enabled integration deployment test
-	PYTHONPATH=$$(git rev-parse --show-toplevel)/tests \
-	  uv run --extra dev python -m pytest tests/integration/test_auth.py \
-	    -v --tb=long --junitxml=results-auth.xml
+	uv run --extra dev python -m pytest tests/ $(PYTEST_ARGS)

From 9b4dd10d977f284cb7b56d6db7d72b0562028776 Mon Sep 17 00:00:00 2001
From: Tarun Kumar Reddy Etikala <tetikala@redhat.com>
Date: Mon, 27 Jul 2026 12:14:06 -0400
Subject: [PATCH 23/25] fix(guardrails): address PR review findings
 (RHAIENG-6262)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

- Send refusal text in streaming block path (was empty response)
- Module-level httpx client for health probe, check status_code == 200
- Add model_id validation in agent.py
- Gitignore config.yaml, ship config.yaml.example template, make init copies it
- Fix playground/app.py IMAGES_DIR path (parents[4] → parents[5])
- Add flask/requests back to deps (playground imports them)
- Add unit tests for _is_guardrails_block() helper
- Remove MIT LICENSE stub (repo uses Apache-2.0)
- Document known limitations in README

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---
 .../examples/guardrailed_agent/.env.example   |  2 +-
 .../examples/guardrailed_agent/.gitignore     |  3 ++
 .../examples/guardrailed_agent/LICENSE        |  3 --
 .../examples/guardrailed_agent/Makefile       |  4 +-
 .../examples/guardrailed_agent/README.md      | 13 ++++--
 .../{config.yaml => config.yaml.example}      |  0
 .../examples/guardrailed_agent/main.py        | 23 ++++++++--
 .../guardrailed_agent/playground/app.py       |  2 +-
 .../examples/guardrailed_agent/pyproject.toml |  4 +-
 .../src/guardrailed_agent/agent.py            |  5 ++
 .../tests/test_guardrails_config.py           | 12 ++---
 .../tests/test_main_helpers.py                | 46 +++++++++++++++++++
 .../examples/guardrailed_agent/uv.lock        |  4 ++
 13 files changed, 98 insertions(+), 23 deletions(-)
 create mode 100644 agents/langgraph/examples/guardrailed_agent/.gitignore
 delete mode 100644 agents/langgraph/examples/guardrailed_agent/LICENSE
 rename agents/langgraph/examples/guardrailed_agent/guardrails/safety/{config.yaml => config.yaml.example} (100%)
 create mode 100644 agents/langgraph/examples/guardrailed_agent/tests/test_main_helpers.py

diff --git a/agents/langgraph/examples/guardrailed_agent/.env.example b/agents/langgraph/examples/guardrailed_agent/.env.example
index ac90c3cf..1d5bcdee 100644
--- a/agents/langgraph/examples/guardrailed_agent/.env.example
+++ b/agents/langgraph/examples/guardrailed_agent/.env.example
@@ -5,7 +5,7 @@ MODEL_ID=llama3.1:8b
 
 # NeMo Guardrails — the proxy server that sits between the agent and the LLM
 # Start with: make guardrails-server
-# The guardrails server config is in guardrails/safety/config.yaml
+# The guardrails server config is in guardrails/safety/config.yaml (created by make init)
 # GUARDRAILS_PORT=8090
 # LLM_BASE_URL=http://localhost:11434/v1
 
diff --git a/agents/langgraph/examples/guardrailed_agent/.gitignore b/agents/langgraph/examples/guardrailed_agent/.gitignore
new file mode 100644
index 00000000..79edfeb3
--- /dev/null
+++ b/agents/langgraph/examples/guardrailed_agent/.gitignore
@@ -0,0 +1,3 @@
+# NeMo Guardrails config is generated by `make guardrails-config`
+# and may contain API_KEY values — never commit.
+guardrails/safety/config.yaml
diff --git a/agents/langgraph/examples/guardrailed_agent/LICENSE b/agents/langgraph/examples/guardrailed_agent/LICENSE
deleted file mode 100644
index cac8466c..00000000
--- a/agents/langgraph/examples/guardrailed_agent/LICENSE
+++ /dev/null
@@ -1,3 +0,0 @@
-MIT License
-
-Copyright (c) 2026
diff --git a/agents/langgraph/examples/guardrailed_agent/Makefile b/agents/langgraph/examples/guardrailed_agent/Makefile
index e374ce0c..38de3a80 100644
--- a/agents/langgraph/examples/guardrailed_agent/Makefile
+++ b/agents/langgraph/examples/guardrailed_agent/Makefile
@@ -14,8 +14,9 @@ re-init: ## Activate venv and reload .env variables
 	@source .venv/bin/activate && set -a && source .env && set +a && \
 	  echo "Venv activated and .env variables loaded."
 
-init: ## Copy .env.example to .env for configuration
+init: ## Copy .env.example and guardrails config template for configuration
 	@if [ ! -f .env ]; then cp .env.example .env && echo "Created .env from .env.example - edit it with your configuration"; else echo ".env already exists - skipping"; fi
+	@if [ ! -f guardrails/safety/config.yaml ]; then cp guardrails/safety/config.yaml.example guardrails/safety/config.yaml && echo "Created guardrails/safety/config.yaml from template"; else echo "guardrails/safety/config.yaml already exists - skipping"; fi
 
 env: ## Create venv, load .env, and install dependencies (including NeMo Guardrails)
 	@echo "==> Creating virtual environment and installing dependencies..." && \
@@ -57,6 +58,7 @@ ollama: ## Install Ollama, start it, and pull models
 	  echo "Done. Run 'make guardrails-server' to start NeMo Guardrails."
 
 guardrails-config: ## Update guardrails config.yaml with LLM endpoint from .env
+	@[ -f guardrails/safety/config.yaml ] || cp guardrails/safety/config.yaml.example guardrails/safety/config.yaml
 	@source .venv/bin/activate && set -a && source .env && set +a && \
 	  python3 -c "\
 	import yaml, sys; \
diff --git a/agents/langgraph/examples/guardrailed_agent/README.md b/agents/langgraph/examples/guardrailed_agent/README.md
index 27ca5464..44affed4 100644
--- a/agents/langgraph/examples/guardrailed_agent/README.md
+++ b/agents/langgraph/examples/guardrailed_agent/README.md
@@ -74,16 +74,13 @@ Ensure Ollama is running (the macOS desktop app handles this automatically; othe
 make guardrails-server   # starts on port 8090, proxies to Ollama on 11434
 ```
 
-The guardrails server reads its config from `guardrails/safety/config.yaml`.
+The guardrails server reads its config from `guardrails/safety/config.yaml` (created by `make init` from the `.example` template). This file is gitignored to prevent accidental credential commits.
 
 > **Using a different model?** Set `MODEL_ID` in `.env`, pull it with
 > `ollama pull <model>`, then run `make guardrails-config` to update the guardrails config.
 >
 > **Using a remote endpoint instead of Ollama?** Set `LLM_BASE_URL` in `.env` to your
 > OpenAI-compatible endpoint, then run `make guardrails-config`.
->
-> **Warning:** `make guardrails-config` writes your `API_KEY` into `guardrails/safety/config.yaml`.
-> Do not commit this file after running with real credentials.
 
 ### 5. Start the agent
 
@@ -198,7 +195,8 @@ curl http://localhost:8000/health
 
 | File | Purpose |
 |------|---------|
-| `guardrails/safety/config.yaml` | Model endpoints, rail ordering, streaming, regex patterns |
+| `guardrails/safety/config.yaml.example` | Template with safe defaults (committed) |
+| `guardrails/safety/config.yaml` | Runtime config (gitignored, created by `make init`) |
 | `guardrails/safety/prompts.yml` | Content safety (S1–S13) and topic safety classification prompts |
 | `guardrails/safety/rails.co` | Colang greeting flows (required by RHOAI entrypoint) |
 
@@ -208,6 +206,11 @@ curl http://localhost:8000/health
 - `rails.co` must exist — RHOAI container entrypoint requirement (can be minimal)
 - NeMo Guardrails version pinned to `0.21.0` to match RHOAI
 
+## Known Limitations
+
+- **Single-turn only** — the agent uses only the last user message; prior conversation history is not forwarded to the LLM. This matches the template pattern and is adequate for demonstrating guardrails behavior.
+- **Health probe as readiness** — `/health` returns 503 when guardrails are unreachable. Use it as a Kubernetes **readiness** probe, not a liveness probe, to avoid unnecessary pod restarts.
+
 ## Resources
 
 - [NeMo Guardrails Documentation](https://docs.nvidia.com/nemo/guardrails/)
diff --git a/agents/langgraph/examples/guardrailed_agent/guardrails/safety/config.yaml b/agents/langgraph/examples/guardrailed_agent/guardrails/safety/config.yaml.example
similarity index 100%
rename from agents/langgraph/examples/guardrailed_agent/guardrails/safety/config.yaml
rename to agents/langgraph/examples/guardrailed_agent/guardrails/safety/config.yaml.example
diff --git a/agents/langgraph/examples/guardrailed_agent/main.py b/agents/langgraph/examples/guardrailed_agent/main.py
index a52228b5..c0d9b8e4 100644
--- a/agents/langgraph/examples/guardrailed_agent/main.py
+++ b/agents/langgraph/examples/guardrailed_agent/main.py
@@ -8,6 +8,7 @@
 from pathlib import Path
 from typing import Any
 
+import httpx
 from fastapi import FastAPI, HTTPException
 from fastapi.responses import (
     FileResponse,
@@ -137,6 +138,7 @@ class HealthResponse(BaseModel):
 
 # Global variable for agent graph
 agent_graph = None
+_health_client = httpx.AsyncClient(timeout=2)
 
 
 @asynccontextmanager
@@ -455,6 +457,20 @@ async def event_generator() -> AsyncIterator[str]:
 
         except Exception as e:
             if _is_guardrails_block(e):
+                refusal_data = {
+                    "id": completion_id,
+                    "object": "chat.completion.chunk",
+                    "created": created,
+                    "model": model_id,
+                    "choices": [
+                        {
+                            "index": 0,
+                            "delta": {"content": _GUARDRAILS_REFUSAL},
+                            "finish_reason": None,
+                        }
+                    ],
+                }
+                yield f"data: {json.dumps(refusal_data)}\n\n"
                 final_data = {
                     "id": completion_id,
                     "object": "chat.completion.chunk",
@@ -495,13 +511,10 @@ async def health():
     guardrails_ok = False
     base_url = getenv("BASE_URL", "")
     if initialized and base_url:
-        import httpx
-
         probe_url = base_url.rstrip("/").removesuffix("/v1")
         try:
-            async with httpx.AsyncClient(timeout=2) as client:
-                r = await client.get(probe_url)
-                guardrails_ok = r.status_code < 500
+            r = await _health_client.get(probe_url)
+            guardrails_ok = r.status_code == 200
         except Exception:
             guardrails_ok = False
 
diff --git a/agents/langgraph/examples/guardrailed_agent/playground/app.py b/agents/langgraph/examples/guardrailed_agent/playground/app.py
index 7a0ab47f..99535615 100644
--- a/agents/langgraph/examples/guardrailed_agent/playground/app.py
+++ b/agents/langgraph/examples/guardrailed_agent/playground/app.py
@@ -32,7 +32,7 @@
 logging.basicConfig(level=logging.DEBUG)
 logger = logging.getLogger(__name__)
 
-IMAGES_DIR = Path(__file__).resolve().parents[4] / "images"
+IMAGES_DIR = Path(__file__).resolve().parents[5] / "images"
 
 app = Flask(__name__)
 
diff --git a/agents/langgraph/examples/guardrailed_agent/pyproject.toml b/agents/langgraph/examples/guardrailed_agent/pyproject.toml
index e860fd94..9f92d334 100644
--- a/agents/langgraph/examples/guardrailed_agent/pyproject.toml
+++ b/agents/langgraph/examples/guardrailed_agent/pyproject.toml
@@ -3,7 +3,7 @@ name = "guardrailed_agent"
 version = "0.1.0"
 description = "A banking customer service agent with NeMo Guardrails safety layer. Demonstrates content safety, topical guardrails, and regex filtering using the proxy pattern."
 authors = [{ name = "Your Name", email = "you@example.com" }]
-license = { text = "MIT" }
+license = { text = "Apache-2.0" }
 requires-python = ">=3.12,<3.14"
 dependencies = [
     "fastapi>=0.135.1",
@@ -17,6 +17,8 @@ dependencies = [
     "setuptools>=80.9.0,<83.0.0",
     "starlette>=1.0.1",
     "protobuf<7",
+    "flask>=3.1.0",
+    "requests>=2.32.0",
 ]
 
 [project.optional-dependencies]
diff --git a/agents/langgraph/examples/guardrailed_agent/src/guardrailed_agent/agent.py b/agents/langgraph/examples/guardrailed_agent/src/guardrailed_agent/agent.py
index aec33bea..e6535c1a 100644
--- a/agents/langgraph/examples/guardrailed_agent/src/guardrailed_agent/agent.py
+++ b/agents/langgraph/examples/guardrailed_agent/src/guardrailed_agent/agent.py
@@ -33,6 +33,11 @@ def get_graph_closure(
     if not model_id:
         model_id = getenv("MODEL_ID")
 
+    if not model_id:
+        raise ValueError(
+            "MODEL_ID is required. Set it via argument or MODEL_ID env var."
+        )
+
     if not base_url:
         raise ValueError(
             "BASE_URL is required. Set it via argument or BASE_URL env var."
diff --git a/agents/langgraph/examples/guardrailed_agent/tests/test_guardrails_config.py b/agents/langgraph/examples/guardrailed_agent/tests/test_guardrails_config.py
index fd7ce0c3..a41e8bd8 100644
--- a/agents/langgraph/examples/guardrailed_agent/tests/test_guardrails_config.py
+++ b/agents/langgraph/examples/guardrailed_agent/tests/test_guardrails_config.py
@@ -10,15 +10,17 @@
 
 AGENT_DIR = Path(__file__).resolve().parents[1]
 GUARDRAILS_DIR = AGENT_DIR / "guardrails" / "safety"
+CONFIG_FILE = GUARDRAILS_DIR / "config.yaml.example"
 
 
 class TestConfigFilesExist:
-    def test_config_yaml_exists(self):
-        assert (GUARDRAILS_DIR / "config.yaml").is_file()
+    def test_config_yaml_example_exists(self):
+        assert CONFIG_FILE.is_file()
 
     def test_config_uses_yaml_extension_not_yml(self):
-        assert (GUARDRAILS_DIR / "config.yaml").is_file()
+        assert CONFIG_FILE.is_file()
         assert not (GUARDRAILS_DIR / "config.yml").exists()
+        assert not (GUARDRAILS_DIR / "config.yml.example").exists()
 
     def test_prompts_yml_exists(self):
         assert (GUARDRAILS_DIR / "prompts.yml").is_file()
@@ -30,9 +32,7 @@ def test_rails_co_exists(self):
 class TestConfigYaml:
     @classmethod
     def setup_class(cls):
-        cls.config = yaml.safe_load(
-            (GUARDRAILS_DIR / "config.yaml").read_text(encoding="utf-8")
-        )
+        cls.config = yaml.safe_load(CONFIG_FILE.read_text(encoding="utf-8"))
 
     def test_has_models_section(self):
         assert "models" in self.config
diff --git a/agents/langgraph/examples/guardrailed_agent/tests/test_main_helpers.py b/agents/langgraph/examples/guardrailed_agent/tests/test_main_helpers.py
new file mode 100644
index 00000000..92472cd3
--- /dev/null
+++ b/agents/langgraph/examples/guardrailed_agent/tests/test_main_helpers.py
@@ -0,0 +1,46 @@
+"""Unit tests for main.py helper functions."""
+
+from unittest.mock import MagicMock
+
+from openai import APIError as OpenAIAPIError
+
+
+def _make_openai_error(message: str) -> OpenAIAPIError:
+    """Create a mock OpenAIAPIError with the given message."""
+    req = MagicMock()
+    return OpenAIAPIError(message=message, request=req, body=None)
+
+
+class TestIsGuardrailsBlock:
+    def _call(self, exc: Exception) -> bool:
+        from main import _is_guardrails_block
+
+        return _is_guardrails_block(exc)
+
+    def test_content_safety_input_block(self):
+        exc = _make_openai_error("Blocked by content_safety_check_input rails")
+        assert self._call(exc) is True
+
+    def test_content_safety_output_block(self):
+        exc = _make_openai_error("Blocked by content_safety_check_output rails")
+        assert self._call(exc) is True
+
+    def test_topic_safety_block(self):
+        exc = _make_openai_error("Blocked by topic_safety_check_input rails")
+        assert self._call(exc) is True
+
+    def test_generic_openai_error_not_matched(self):
+        exc = _make_openai_error("Connection refused")
+        assert self._call(exc) is False
+
+    def test_non_openai_error_not_matched(self):
+        exc = RuntimeError("Blocked by rails")
+        assert self._call(exc) is False
+
+    def test_partial_match_blocked_without_rails(self):
+        exc = _make_openai_error("Blocked by firewall")
+        assert self._call(exc) is False
+
+    def test_partial_match_rails_without_blocked(self):
+        exc = _make_openai_error("Error in rails processing")
+        assert self._call(exc) is False
diff --git a/agents/langgraph/examples/guardrailed_agent/uv.lock b/agents/langgraph/examples/guardrailed_agent/uv.lock
index 0496a8dc..0a480908 100644
--- a/agents/langgraph/examples/guardrailed_agent/uv.lock
+++ b/agents/langgraph/examples/guardrailed_agent/uv.lock
@@ -746,6 +746,7 @@ version = "0.1.0"
 source = { editable = "." }
 dependencies = [
     { name = "fastapi" },
+    { name = "flask" },
     { name = "httpx" },
     { name = "langchain" },
     { name = "langchain-openai" },
@@ -753,6 +754,7 @@ dependencies = [
     { name = "openai" },
     { name = "protobuf" },
     { name = "python-dotenv" },
+    { name = "requests" },
     { name = "setuptools" },
     { name = "starlette" },
     { name = "uvicorn", extra = ["standard"] },
@@ -781,6 +783,7 @@ requires-dist = [
     { name = "agent-auth", marker = "extra == 'auth'", directory = "../../../../components/auth" },
     { name = "dataclasses-json", marker = "extra == 'guardrails'", specifier = ">=0.6.7" },
     { name = "fastapi", specifier = ">=0.135.1" },
+    { name = "flask", specifier = ">=3.1.0" },
     { name = "httpx", specifier = ">=0.27" },
     { name = "httpx", marker = "extra == 'dev'", specifier = ">=0.27" },
     { name = "langchain", specifier = ">=1.2.10" },
@@ -794,6 +797,7 @@ requires-dist = [
     { name = "pytest", marker = "extra == 'dev'", specifier = ">=9.0.2" },
     { name = "python-dotenv", specifier = ">=1.2.2" },
     { name = "pyyaml", marker = "extra == 'dev'", specifier = ">=6.0" },
+    { name = "requests", specifier = ">=2.32.0" },
     { name = "setuptools", specifier = ">=80.9.0,<83.0.0" },
     { name = "starlette", specifier = ">=1.0.1" },
     { name = "uvicorn", extras = ["standard"], specifier = ">=0.41.0" },

From 1b1dcc4f7f15da4135d84c098144b503818744da Mon Sep 17 00:00:00 2001
From: Tarun Kumar Reddy Etikala <tetikala@redhat.com>
Date: Mon, 27 Jul 2026 13:48:34 -0400
Subject: [PATCH 24/25] refactor(guardrails): generate config at startup, not
 as separate step (RHAIENG-6262)

Fold `make guardrails-config` into `make guardrails-server` so config.yaml
is generated fresh from .env each time the server starts. Secrets never
persist in the working tree between runs. Also add .env to .gitignore.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---
 .../examples/guardrailed_agent/.env.example      |  3 +--
 .../examples/guardrailed_agent/.gitignore        |  7 +++++--
 .../examples/guardrailed_agent/Makefile          | 16 ++++++----------
 .../examples/guardrailed_agent/README.md         | 10 +++++-----
 .../tests/test_packaging_config.py               |  3 +--
 5 files changed, 18 insertions(+), 21 deletions(-)

diff --git a/agents/langgraph/examples/guardrailed_agent/.env.example b/agents/langgraph/examples/guardrailed_agent/.env.example
index 1d5bcdee..320edc2b 100644
--- a/agents/langgraph/examples/guardrailed_agent/.env.example
+++ b/agents/langgraph/examples/guardrailed_agent/.env.example
@@ -4,8 +4,7 @@ BASE_URL=http://localhost:8090/v1
 MODEL_ID=llama3.1:8b
 
 # NeMo Guardrails — the proxy server that sits between the agent and the LLM
-# Start with: make guardrails-server
-# The guardrails server config is in guardrails/safety/config.yaml (created by make init)
+# Start with: make guardrails-server (generates config.yaml from these values)
 # GUARDRAILS_PORT=8090
 # LLM_BASE_URL=http://localhost:11434/v1
 
diff --git a/agents/langgraph/examples/guardrailed_agent/.gitignore b/agents/langgraph/examples/guardrailed_agent/.gitignore
index 79edfeb3..6f12f38b 100644
--- a/agents/langgraph/examples/guardrailed_agent/.gitignore
+++ b/agents/langgraph/examples/guardrailed_agent/.gitignore
@@ -1,3 +1,6 @@
-# NeMo Guardrails config is generated by `make guardrails-config`
-# and may contain API_KEY values — never commit.
+# Local environment (may contain API keys)
+.env
+
+# NeMo Guardrails config is generated at startup by `make guardrails-server`
+# from .env values — may contain API_KEY, never commit.
 guardrails/safety/config.yaml
diff --git a/agents/langgraph/examples/guardrailed_agent/Makefile b/agents/langgraph/examples/guardrailed_agent/Makefile
index 38de3a80..68add861 100644
--- a/agents/langgraph/examples/guardrailed_agent/Makefile
+++ b/agents/langgraph/examples/guardrailed_agent/Makefile
@@ -5,7 +5,7 @@ VALUES_FILE    := values.yaml
 CONTAINER_CLI  := $(shell command -v podman 2>/dev/null || command -v docker 2>/dev/null)
 MODEL          ?= llama3.1:8b
 
-.PHONY: init re-init env ollama run-app run-app-fresh build push build-openshift deploy undeploy test dry-run help guardrails-config guardrails-server
+.PHONY: init re-init env ollama run-app run-app-fresh build push build-openshift deploy undeploy test dry-run help guardrails-server
 
 help: ## Show this help
 	@grep -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "  %-20s %s\n", $$1, $$2}'
@@ -14,9 +14,8 @@ re-init: ## Activate venv and reload .env variables
 	@source .venv/bin/activate && set -a && source .env && set +a && \
 	  echo "Venv activated and .env variables loaded."
 
-init: ## Copy .env.example and guardrails config template for configuration
+init: ## Copy .env.example to .env for configuration
 	@if [ ! -f .env ]; then cp .env.example .env && echo "Created .env from .env.example - edit it with your configuration"; else echo ".env already exists - skipping"; fi
-	@if [ ! -f guardrails/safety/config.yaml ]; then cp guardrails/safety/config.yaml.example guardrails/safety/config.yaml && echo "Created guardrails/safety/config.yaml from template"; else echo "guardrails/safety/config.yaml already exists - skipping"; fi
 
 env: ## Create venv, load .env, and install dependencies (including NeMo Guardrails)
 	@echo "==> Creating virtual environment and installing dependencies..." && \
@@ -57,11 +56,11 @@ ollama: ## Install Ollama, start it, and pull models
 	  echo "" && \
 	  echo "Done. Run 'make guardrails-server' to start NeMo Guardrails."
 
-guardrails-config: ## Update guardrails config.yaml with LLM endpoint from .env
-	@[ -f guardrails/safety/config.yaml ] || cp guardrails/safety/config.yaml.example guardrails/safety/config.yaml
+guardrails-server: ## Generate config from .env and start NeMo Guardrails proxy
 	@source .venv/bin/activate && set -a && source .env && set +a && \
+	  cp guardrails/safety/config.yaml.example guardrails/safety/config.yaml && \
 	  python3 -c "\
-	import yaml, sys; \
+	import yaml; \
 	f='guardrails/safety/config.yaml'; \
 	c=yaml.safe_load(open(f)); \
 	url='$${LLM_BASE_URL:-http://localhost:11434/v1}'; \
@@ -69,10 +68,7 @@ guardrails-config: ## Update guardrails config.yaml with LLM endpoint from .env
 	key='$${API_KEY:-not-needed}'; \
 	[m['parameters'].update(base_url=url, api_key=key) or m.update(model=model) for m in c['models']]; \
 	yaml.dump(c, open(f,'w'), default_flow_style=False, sort_keys=False); \
-	print(f'Updated {f} with LLM_BASE_URL={url} MODEL_ID={model} API_KEY=***')"
-
-guardrails-server: ## Start NeMo Guardrails server on GUARDRAILS_PORT (default 8090)
-	@source .venv/bin/activate && set -a && source .env && set +a && \
+	print(f'Config generated: LLM_BASE_URL={url} MODEL_ID={model}')" && \
 	  echo "Starting NeMo Guardrails server on port $${GUARDRAILS_PORT:-8090}..." && \
 	  nemoguardrails server --config guardrails --default-config-id safety --port $${GUARDRAILS_PORT:-8090} --disable-chat-ui
 
diff --git a/agents/langgraph/examples/guardrailed_agent/README.md b/agents/langgraph/examples/guardrailed_agent/README.md
index 44affed4..0ce623b0 100644
--- a/agents/langgraph/examples/guardrailed_agent/README.md
+++ b/agents/langgraph/examples/guardrailed_agent/README.md
@@ -74,13 +74,13 @@ Ensure Ollama is running (the macOS desktop app handles this automatically; othe
 make guardrails-server   # starts on port 8090, proxies to Ollama on 11434
 ```
 
-The guardrails server reads its config from `guardrails/safety/config.yaml` (created by `make init` from the `.example` template). This file is gitignored to prevent accidental credential commits.
+The guardrails server generates its runtime config from `.env` at startup — no separate config step needed. The generated `config.yaml` is gitignored to prevent accidental credential commits.
 
 > **Using a different model?** Set `MODEL_ID` in `.env`, pull it with
-> `ollama pull <model>`, then run `make guardrails-config` to update the guardrails config.
+> `ollama pull <model>`, then restart `make guardrails-server`.
 >
-> **Using a remote endpoint instead of Ollama?** Set `LLM_BASE_URL` in `.env` to your
-> OpenAI-compatible endpoint, then run `make guardrails-config`.
+> **Using a remote endpoint instead of Ollama?** Set `LLM_BASE_URL` and `API_KEY` in `.env`,
+> then restart `make guardrails-server`.
 
 ### 5. Start the agent
 
@@ -196,7 +196,7 @@ curl http://localhost:8000/health
 | File | Purpose |
 |------|---------|
 | `guardrails/safety/config.yaml.example` | Template with safe defaults (committed) |
-| `guardrails/safety/config.yaml` | Runtime config (gitignored, created by `make init`) |
+| `guardrails/safety/config.yaml` | Runtime config (gitignored, generated by `make guardrails-server`) |
 | `guardrails/safety/prompts.yml` | Content safety (S1–S13) and topic safety classification prompts |
 | `guardrails/safety/rails.co` | Colang greeting flows (required by RHOAI entrypoint) |
 
diff --git a/agents/langgraph/examples/guardrailed_agent/tests/test_packaging_config.py b/agents/langgraph/examples/guardrailed_agent/tests/test_packaging_config.py
index 92551731..804e814e 100644
--- a/agents/langgraph/examples/guardrailed_agent/tests/test_packaging_config.py
+++ b/agents/langgraph/examples/guardrailed_agent/tests/test_packaging_config.py
@@ -27,8 +27,7 @@ def test_makefile_stages_auth_component_for_container_builds() -> None:
     assert len(re.findall(cleanup_pattern, NORMALIZED_MAKEFILE)) == 2
 
 
-def test_makefile_has_guardrails_targets() -> None:
-    assert re.search(r"(?m)^guardrails-config:", MAKEFILE)
+def test_makefile_has_guardrails_server_target() -> None:
     assert re.search(r"(?m)^guardrails-server:", MAKEFILE)
 
 

From 847d8f27009101a1948d91d7e9db95e9b3436b7f Mon Sep 17 00:00:00 2001
From: Tarun Kumar Reddy Etikala <tetikala@redhat.com>
Date: Mon, 27 Jul 2026 14:44:52 -0400
Subject: [PATCH 25/25] docs(guardrails): add inline comments for pinned deps
 (RHAIENG-6262)

Explain why nemoguardrails==0.21.0, langchain-community<0.4, and
protobuf<7 are pinned. Note why Dockerfile omits [guardrails] extra.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---
 agents/langgraph/examples/guardrailed_agent/Dockerfile    | 2 ++
 .../langgraph/examples/guardrailed_agent/pyproject.toml   | 8 ++++----
 2 files changed, 6 insertions(+), 4 deletions(-)

diff --git a/agents/langgraph/examples/guardrailed_agent/Dockerfile b/agents/langgraph/examples/guardrailed_agent/Dockerfile
index 2d499583..73e7245d 100644
--- a/agents/langgraph/examples/guardrailed_agent/Dockerfile
+++ b/agents/langgraph/examples/guardrailed_agent/Dockerfile
@@ -19,6 +19,8 @@ COPY src/ ./src/
 COPY components/auth/ /opt/app-root/src/components/auth/
 
 # Install the project and its dependencies using uv
+# NeMo Guardrails runs as a separate pod in production (managed by NemoGuardrails CRD),
+# so the [guardrails] extra is intentionally omitted from the agent container image.
 RUN uv pip install --no-cache ".[tracing,auth]"
 
 # Copy the application entrypoint, playground UI, and images
diff --git a/agents/langgraph/examples/guardrailed_agent/pyproject.toml b/agents/langgraph/examples/guardrailed_agent/pyproject.toml
index 9f92d334..11b92869 100644
--- a/agents/langgraph/examples/guardrailed_agent/pyproject.toml
+++ b/agents/langgraph/examples/guardrailed_agent/pyproject.toml
@@ -16,7 +16,7 @@ dependencies = [
     "python-dotenv>=1.2.2",
     "setuptools>=80.9.0,<83.0.0",
     "starlette>=1.0.1",
-    "protobuf<7",
+    "protobuf<7",  # nemoguardrails 0.21.0 pulls grpcio which conflicts with protobuf 7+
     "flask>=3.1.0",
     "requests>=2.32.0",
 ]
@@ -31,9 +31,9 @@ dev = [
     "pyyaml>=6.0",
 ]
 guardrails = [
-    "nemoguardrails[server]==0.21.0",
-    "dataclasses-json>=0.6.7",
-    "langchain-community>=0.2,<0.4",
+    "nemoguardrails[server]==0.21.0",  # pinned to match RHOAI container version
+    "dataclasses-json>=0.6.7",  # undeclared transitive dep of nemoguardrails 0.21.0
+    "langchain-community>=0.2,<0.4",  # >=0.4 drops GoogleSearchAPIWrapper, breaks nemoguardrails imports
 ]
 tracing = [
     "mlflow[kubernetes]>=3.11.0",