diff --git a/agent.ipynb b/agent.ipynb
index 0b1cf33..a21417e 100644
--- a/agent.ipynb
+++ b/agent.ipynb
@@ -1,15 +1,5 @@
 {
  "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "0b0e47bb",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "\n"
-   ]
-  },
   {
    "cell_type": "markdown",
    "id": "7bb66df4",
@@ -99,15 +89,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "ae7b7284",
    "metadata": {},
-   "outputs": [],
    "source": [
     "import shutil\n",
     "\n",
     "shutil.copy(\"resources/company_policy.txt\", \"company_policy.txt\")"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -156,77 +146,77 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "51fa0c23",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# check prerequisites in README.md and create the env and the jupyter kernel"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "aa8411bd",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# Install the uipath package\n",
     "!uv add --active uipath-langchain"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "f3bffb31",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# Verify the uipath installation\n",
     "!uv run --active uipath -lv"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "d04410a8",
    "metadata": {},
-   "outputs": [],
    "source": [
     "!uv sync --upgrade --active"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "60a30976",
    "metadata": {},
-   "outputs": [],
    "source": [
     "#Initialize the UiPath LangChain agent. replace your name here\n",
     "!uv run --active uipath new companyAgent-<your-name>"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "b6a3d346",
    "metadata": {},
-   "outputs": [],
    "source": [
     "!uv add --active langchain-openai"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "961abd73",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# Install the langchain anthropic package\n",
     "!uv add --active langchain-anthropic"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -240,14 +230,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "1c497d67",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# Authenticate to UiPath Staging. Make sure to specify the name of the target Tenant \n",
     "!uv run --active uipath auth --staging --force --tenant \"AgentsProCode\""
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -277,10 +267,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "b1a94d9f",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# %%writefile -a main.py\n",
     "\n",
@@ -289,7 +277,8 @@
     "from pydantic import BaseModel\n",
     "from uipath_langchain.retrievers import ContextGroundingRetriever\n",
     "from langchain_core.documents import Document\n",
-    "from uipath.models import InvokeProcess, IngestionInProgressException\n",
+    "from uipath.platform.common import InvokeProcess\n",
+    "from uipath.platform.errors import IngestionInProgressException\n",
     "import httpx\n",
     "from uipath_langchain.chat.models import UiPathAzureChatOpenAI\n",
     "\n",
@@ -318,7 +307,9 @@
     "If not covered:\n",
     "<one line stating it’s not covered and what info is missing>\n",
     "\"\"\""
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -330,10 +321,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "5543ff14",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# %%writefile -a main.py\n",
     "\n",
@@ -358,14 +347,14 @@
     "    if not data_queried:\n",
     "        raise Exception(\"Ingestion is taking too long.\")\n",
     "    return  context_data"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "188c0841",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# %%writefile -a main.py\n",
     "\n",
@@ -400,7 +389,9 @@
     "    # result = await policy_agent.ainvoke(new_state)\n",
     "    result = await llm.ainvoke(messages)\n",
     "    return GraphOutput(response=result.content)"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -409,32 +400,38 @@
    "source": [
     "**Set the LLM model and its parameters**\n",
     "\n",
+    "> **Recommended: Use Option 2 (UiPathAzureChatOpenAI)** - No API key required, uses your existing UiPath authentication.\n",
+    "\n",
+    "> **Available Models:** For the list of available models, refer to the [list of available models (under \"agenthub\")](https://github.com/UiPath/gitops-centralized-cluster/blob/master/projects/prod/llms/llmgateway-service/llmgateway-service-values.yaml#L2301) or use `sdk.agenthub.get_available_llm_models()` to fetch available models programmatically.\n",
+    "\n",
+    "> **Note:** All `resources/mainX.py` files use `ChatOpenAI` by default. To use UiPath LLM instead (no API key needed), change `llm = ChatOpenAI(...)` to `llm = UiPathAzureChatOpenAI(...)` in the respective file before running.\n",
+    "\n",
+    "---\n",
+    "\n",
     "**Option 1.** Use generic chat models such as ChatOpenAI. The corresponding API Key needs to be provided and copied in the [`.env`](./.env) file.\n",
     "\n",
     "```env\n",
-    "OPENAI_API_KEY=sk-proj-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx\n"
+    "OPENAI_API_KEY=sk-proj-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "a0dc0411",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# TEMPORARY API KEY (FOR TESTING PURPOSES-WILL BE REMOVED AFTER THE SESSION)\n",
     "\n",
     "with open(\".env\", \"a\") as f:\n",
     "    f.write(\"\\nOPENAI_API_KEY=****\\n\")\n",
     "    f.write(\"UIPATH_FOLDER_PATH=Shared\\n\")"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "f7bfdb78",
    "metadata": {},
-   "outputs": [],
    "source": [
     "from langchain_openai import ChatOpenAI\n",
     "\n",
@@ -449,24 +446,26 @@
     "    timeout=30,\n",
     "    max_retries=2,\n",
     ")"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
    "id": "71fdb175",
    "metadata": {},
    "source": [
-    "**Option 2.**, UiPath provides two chat models: `UiPathAzureChatOpenAI` and `UiPathChat`. These are compatible with `LangGraph` as drop-in replacements. \n",
+    "**Option 2 (Recommended).** UiPath provides two chat models: `UiPathAzureChatOpenAI` and `UiPathChat`. These are compatible with `LangGraph` as drop-in replacements. \n",
+    "\n",
+    "**No API Key required** - uses your existing UiPath authentication token.\n",
     "\n",
-    "!No need to provide an API Key"
+    "> **Important:** If you want to use this option, you must also update `resources/main1.py` to use `UiPathAzureChatOpenAI` instead of `ChatOpenAI`, since that file gets copied to `main.py` later in the notebook."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "4cffe990",
    "metadata": {},
-   "outputs": [],
    "source": [
     "from uipath_langchain.chat.models import UiPathAzureChatOpenAI\n",
     "\n",
@@ -478,7 +477,9 @@
     "    max_retries=2,\n",
     "    # other params...\n",
     ")"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -490,10 +491,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "96a5414c",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# %%writefile -a main.py\n",
     "\n",
@@ -503,7 +502,9 @@
     "\n",
     "builder.add_edge(START, \"policy\")\n",
     "builder.add_edge(\"policy\", END)"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -515,40 +516,35 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "6370f156",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# %%writefile -a main.py\n",
     "\n",
     "# Compile the graph\n",
     "graph = builder.compile()"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "8c841b19",
    "metadata": {},
+   "source": "# Copy the above python code to the main.py file\n\nimport shutil\nshutil.copyfile(\"resources/main1.py\", \"main.py\")",
    "outputs": [],
-   "source": [
-    "# Copy the above python code to the main.py file\n",
-    "\n",
-    "import shutil\n",
-    "shutil.copyfile(\"resources/main1.py\", \"main.py\")"
-   ]
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "4cfa1ed2",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# Initialize the project to make sure all file are up to date\n",
     "!uv run --active uipath init"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -570,10 +566,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "1738dcaa",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# See the Mermaid diagram\n",
     "from IPython.display import display, Markdown\n",
@@ -582,7 +576,9 @@
     "    mermaid_code = f.read()\n",
     "\n",
     "display(Markdown(f\"```mermaid\\n{mermaid_code}\\n```\"))"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -598,16 +594,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "24602b54",
    "metadata": {},
-   "outputs": [],
    "source": [
     "%%writefile input.json\n",
     "{\n",
     "  \"question\": \"What is the PTO policy for taking 3 days off\"\n",
     "}"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -621,25 +617,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "98f7e1fb",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# Re-initialize the project to make sure all file are up to date\n",
     "!uv run --active uipath init"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "db556fa4",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# Run the agent locally\n",
     "!uv run --active uipath run agent --file input.json"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -682,28 +678,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "9818da8c",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# Auto-increase the version of the package\n",
     "import re, pathlib\n",
     "p = pathlib.Path(\"pyproject.toml\"); t = p.read_text()\n",
     "n = re.sub(r'(?m)^(version\\s*=\\s*\")(\\d+)\\.(\\d+)\\.(\\d+)(\")', lambda m: f'{m.group(1)}{m.group(2)}.{m.group(3)}.{int(m.group(4))+1}{m.group(5)}', t, count=1)\n",
     "p.write_text(n); print(re.search(r'(?m)^version\\s*=\\s*\"([^\"]+)\"', t).group(1), \"->\", re.search(r'(?m)^version\\s*=\\s*\"([^\"]+)\"', n).group(1))"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "16a9ef22",
    "metadata": {},
-   "outputs": [],
    "source": [
     "!uv run --active uipath pack\n",
     "!uv run --active uipath publish --tenant"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -798,25 +794,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "9a37e909",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "\"CompanyPolicy\": {\n",
+    "{\n",
+    "  \"mcpServers\": {\n",
+    "    \"CompanyPolicy\": {\n",
     "      \"command\": \"npx\",\n",
     "      \"args\": [\n",
     "        \"-y\",\n",
     "        \"mcp-remote\",\n",
-    "        \"https:< UiPath MCP Server URL>\",\n",
+    "        \"<UiPath MCP Server URL>\",\n",
     "        \"--header\",\n",
     "        \"Authorization:${AUTH_HEADER}\"\n",
     "      ],\n",
     "      \"env\": {\n",
     "        \"AUTH_HEADER\": \"Bearer <YOUR Personal Access Token>\"\n",
     "      }\n",
-    "    }"
-   ]
+    "    }\n",
+    "  }\n",
+    "}"
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -874,18 +874,10 @@
     "---"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "74e728e4",
-   "metadata": {},
-   "source": []
-  },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "1ce2859b",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# Added GraphState with fields: question, category\n",
     "from pydantic import BaseModel\n",
@@ -894,14 +886,14 @@
     "    \"\"\"State for the company policy agent graph.\"\"\"\n",
     "    question: str\n",
     "    category: str | None = None\n"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "7c387bbb",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# Added supervisor_node to classify into Company Policy or Procurement\n",
     "from langchain_openai import ChatOpenAI\n",
@@ -919,14 +911,14 @@
     "    normalized = {c.lower(): c for c in categories}\n",
     "    category = normalized.get(label.lower(), \"Company Policy\")\n",
     "    return GraphState(question=state.question, category=category)\n"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "a49ae672",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# Added procurement_node (initially same prompt shape as policy)\n",
     "from uipath_langchain.retrievers import ContextGroundingRetriever\n",
@@ -956,14 +948,14 @@
     "    class GraphOutput(BaseModel):\n",
     "        response: str\n",
     "    return GraphOutput(response=result.content)\n"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "c4a68723",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# Added route_by_category(state) to return the next node key\n",
     "\n",
@@ -971,14 +963,14 @@
     "    if state.category and state.category.lower() == \"procurement\":\n",
     "        return \"procurement\"\n",
     "    return \"policy\"\n"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "9a575dfa",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# Rewired graph: START -> supervisor -> (policy | procurement) -> END (demo wiring)\n",
     "from importlib import reload\n",
@@ -1011,7 +1003,9 @@
     "builder_demo.add_edge(\"procurement\", END)\n",
     "\n",
     "demo_graph = builder_demo.compile()\n"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -1031,36 +1025,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "08bfc764",
    "metadata": {},
+   "source": "# Update the main.py\nfrom pathlib import Path\nsrc = Path(\"resources/main2_multiple_agents.py\")\ndst = Path(\"main.py\")\ndst.write_text(src.read_text(), encoding=\"utf-8\")\nprint(\"Synchronized main.py from resources/main2_multiple_agents.py\")",
    "outputs": [],
-   "source": [
-    "# Update the main.py\n",
-    "from pathlib import Path\n",
-    "src = Path(\"resources/main2_multiple_agents.py\")\n",
-    "dst = Path(\"main.py\")\n",
-    "dst.write_text(src.read_text(), encoding=\"utf-8\")\n",
-    "print(\"Synchronized main.py from resources/main2_multiple_agents.py\")\n"
-   ]
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "600974ff",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# Re-initialize the project to make sure all file are up to date\n",
     "!uv run --active uipath init"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "2a52d9b8",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# See the Mermaid diagram\n",
     "from IPython.display import display, Markdown\n",
@@ -1069,7 +1054,9 @@
     "    mermaid_code = f.read()\n",
     "\n",
     "display(Markdown(f\"```mermaid\\n{mermaid_code}\\n```\"))"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -1081,26 +1068,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "460efe5f",
    "metadata": {},
-   "outputs": [],
    "source": [
     "%%writefile input.json\n",
     "{\n",
     "  \"question\": \"Can I buy an OpenAI subscription for company use?\"\n",
     "}"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "ccda1b76",
    "metadata": {},
-   "outputs": [],
    "source": [
     "!uv run --active uipath run agent --file input.json"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -1122,26 +1109,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "e951ca8e",
    "metadata": {},
-   "outputs": [],
    "source": [
     "%%writefile input.json\n",
     "{\n",
     "  \"question\": \"What is the PTO policy for taking 3 days off?\"\n",
     "}"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "af599acf",
    "metadata": {},
-   "outputs": [],
    "source": [
     "!uv run --active uipath run agent --file input.json"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -1192,37 +1179,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "efd48c77",
    "metadata": {},
+   "source": "# Update main.py with Validation node\n\nfrom pathlib import Path\nsrc = Path(\"resources/main3_validation.py\")\ndst = Path(\"main.py\")\ndst.write_text(src.read_text(), encoding=\"utf-8\")\nprint(\"Synchronized main.py from resources/main3_validation.py\")",
    "outputs": [],
-   "source": [
-    "# Update main.py with Validation node\n",
-    "\n",
-    "from pathlib import Path\n",
-    "src = Path(\"resources/main3_validation.py\")\n",
-    "dst = Path(\"main.py\")\n",
-    "dst.write_text(src.read_text(), encoding=\"utf-8\")\n",
-    "print(\"Synchronized main.py from resources/main3_validation.py\")\n"
-   ]
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "3cb685d3",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# Re-initialize the project to make sure all file are up to date\n",
     "!uv run --active uipath init"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "bd77e103",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# See the Mermaid diagram\n",
     "from IPython.display import display, Markdown\n",
@@ -1231,7 +1208,9 @@
     "    mermaid_code = f.read()\n",
     "\n",
     "display(Markdown(f\"```mermaid\\n{mermaid_code}\\n```\"))\n"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -1243,26 +1222,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "a60b1e07",
    "metadata": {},
-   "outputs": [],
    "source": [
     "%%writefile input.json\n",
     "{\n",
     "  \"question\": \"Can I buy an OpenAI subscription for company use?\"\n",
     "}"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "59c13fe5",
    "metadata": {},
-   "outputs": [],
    "source": [
     "!uv run --active uipath run agent --file input.json\n"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -1284,10 +1263,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "49f9df01",
    "metadata": {},
-   "outputs": [],
    "source": [
     "%%writefile input.json\n",
     "{\n",
@@ -1295,17 +1272,19 @@
     "  \"email\": \"eusebiu.jecan@uipath.com\",\n",
     "  \"code\": \"4827\"\n",
     "}"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "b99b8fc6",
    "metadata": {},
-   "outputs": [],
    "source": [
     "!uv run --active uipath run agent --file input.json"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -1361,37 +1340,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "2c4d7dcb",
    "metadata": {},
+   "source": "# Update main.py with HR Agent\n\nfrom pathlib import Path\nsrc = Path(\"resources/main4_hr.py\")\ndst = Path(\"main.py\")\ndst.write_text(src.read_text(), encoding=\"utf-8\")\nprint(\"Synchronized main.py from resources/main4_hr.py\")",
    "outputs": [],
-   "source": [
-    "# Update main.py with Validation node\n",
-    "\n",
-    "from pathlib import Path\n",
-    "src = Path(\"resources/main4_hr.py\")\n",
-    "dst = Path(\"main.py\")\n",
-    "dst.write_text(src.read_text(), encoding=\"utf-8\")\n",
-    "print(\"Synchronized main.py from resources/main4_hr.py\")"
-   ]
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "51588be7",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# Re-initialize the project to make sure all file are up to date\n",
     "!uv run --active uipath init"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "77bc25c8",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# See the Mermaid diagram\n",
     "from IPython.display import display, Markdown\n",
@@ -1400,14 +1369,14 @@
     "    mermaid_code = f.read()\n",
     "\n",
     "display(Markdown(f\"```mermaid\\n{mermaid_code}\\n```\"))"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "84cfbb86",
    "metadata": {},
-   "outputs": [],
    "source": [
     "%%writefile input.json\n",
     "{\n",
@@ -1415,17 +1384,19 @@
     "  \"email\": \"eusebiu.jecan@uipath.com\",\n",
     "  \"code\": \"4827\"\n",
     "}"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "879457a4",
    "metadata": {},
-   "outputs": [],
    "source": [
     "!uv run --active uipath run agent --file input.json"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -1470,37 +1441,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "cf539f3a",
    "metadata": {},
+   "source": "# Update main.py with Permission Check for HR\n\nfrom pathlib import Path\nsrc = Path(\"resources/main5_permission_check_hr.py\")\ndst = Path(\"main.py\")\ndst.write_text(src.read_text(), encoding=\"utf-8\")\nprint(\"Synchronized main.py from resources/main5_permission_check_hr.py\")",
    "outputs": [],
-   "source": [
-    "# Update main.py with Validation node\n",
-    "\n",
-    "from pathlib import Path\n",
-    "src = Path(\"resources/main5_permission_check_hr.py\")\n",
-    "dst = Path(\"main.py\")\n",
-    "dst.write_text(src.read_text(), encoding=\"utf-8\")\n",
-    "print(\"Synchronized main.py from resources/main5_permission_check_hr.py\")"
-   ]
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "765c2e5e",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# Re-initialize the project to make sure all file are up to date\n",
     "!uv run --active uipath init"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "91b8ccd6",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# See the Mermaid diagram\n",
     "from IPython.display import display, Markdown\n",
@@ -1509,7 +1470,9 @@
     "    mermaid_code = f.read()\n",
     "\n",
     "display(Markdown(f\"```mermaid\\n{mermaid_code}\\n```\"))"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -1521,10 +1484,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "13694a3f",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# Create a local HR authorization file (allow-list)\n",
     "import json, os, textwrap\n",
@@ -1541,14 +1502,14 @@
     "    json.dump(auth, f, indent=2)\n",
     "\n",
     "print(\"Created hr_auth.json with allow-list:\", auth[\"allowed_emails\"])"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "2163b6b2",
    "metadata": {},
-   "outputs": [],
    "source": [
     "%%writefile input.json\n",
     "{\n",
@@ -1556,17 +1517,19 @@
     "  \"email\": \"eusebiu.jecan@uipath.com\",\n",
     "  \"code\": \"4827\"\n",
     "}"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "e91028f9",
    "metadata": {},
-   "outputs": [],
    "source": [
     "!uv run --active uipath run agent --file input.json"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -1580,10 +1543,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "d03ca464",
    "metadata": {},
-   "outputs": [],
    "source": [
     "%%writefile input.json\n",
     "{\n",
@@ -1591,17 +1552,19 @@
     "  \"email\": \"somenone@uipath.com\",\n",
     "  \"code\": \"4827\"\n",
     "}"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "7bcfb714",
    "metadata": {},
-   "outputs": [],
    "source": [
     "!uv run --active uipath run agent --file input.json"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -1631,27 +1594,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
    "id": "741940fa",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Synchronized main.py from resources/main6_HITL.py\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Update main.py with Human in the loop\n",
-    "\n",
-    "from pathlib import Path\n",
-    "src = Path(\"resources/main6_HITL.py\")\n",
-    "dst = Path(\"main.py\")\n",
-    "dst.write_text(src.read_text(), encoding=\"utf-8\")\n",
-    "print(\"Synchronized main.py from resources/main6_HITL.py\")"
-   ]
+   "source": "# Update main.py with Human in the loop\n\nfrom pathlib import Path\nsrc = Path(\"resources/main6_HITL.py\")\ndst = Path(\"main.py\")\ndst.write_text(src.read_text(), encoding=\"utf-8\")\nprint(\"Synchronized main.py from resources/main6_HITL.py\")",
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -1663,22 +1610,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "68e23bbe",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# Re-initialize the project to make sure all file are up to date\n",
     "\n",
     "!uv run --active uipath init"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "6edb1216",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# Visualize the current graph (Mermaid)\n",
     "from IPython.display import display, Markdown\n",
@@ -1687,14 +1632,14 @@
     "    mermaid_code = f.read()\n",
     "\n",
     "display(Markdown(f\"```mermaid\\n{mermaid_code}\\n```\"))"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "66d07bdc",
    "metadata": {},
-   "outputs": [],
    "source": [
     "%%writefile input.json\n",
     "{\n",
@@ -1702,14 +1647,14 @@
     "  \"email\": \"eusebiu.jecan@uipath.com\",\n",
     "  \"code\": \"4827\"\n",
     "}"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "c15c4ecc",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# Ensure only the correct UIPATH_URL is enabled in .env\n",
     "lines = []\n",
@@ -1725,22 +1670,14 @@
     "with open(\".env\", \"w\", encoding=\"utf-8\") as f:\n",
     "    f.writelines(lines)\n",
     "print(\"Updated .env with the correct UIPATH_URL\")\n"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
    "id": "fbf1ac6e",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Updated HITL assignee email in main.py to: eusebiu.jecan@uipath.com\n"
-     ]
-    }
-   ],
    "source": [
     "# Set the HITL assignee email \n",
     "HITL_ASSIGNEE_EMAIL = \"<your-email>\"  # <--- Change this value with teh e-mail you signed up within UiPath\n",
@@ -1763,27 +1700,29 @@
     "\n",
     "main_path.write_text(\"\\n\".join(lines), encoding=\"utf-8\")\n",
     "print(f\"Updated HITL assignee email in main.py to: {HITL_ASSIGNEE_EMAIL}\")"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "054bdf9c",
    "metadata": {},
-   "outputs": [],
    "source": [
     "!uv run --active uipath run agent --file input.json"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "15399994",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "!uv run --active uipath run --resume "
-   ]
+    "!uv run --active uipath run agent --resume "
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -1807,9 +1746,9 @@
    "notebook_metadata_filter": "-all"
   },
   "kernelspec": {
-   "display_name": ".venv",
+   "display_name": "FUSION2025",
    "language": "python",
-   "name": "python3"
+   "name": "jupyter-uv-env"
   },
   "language_info": {
    "codemirror_mode": {
@@ -1821,7 +1760,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.13.4"
+   "version": "3.11.13"
   }
  },
  "nbformat": 4,
diff --git a/hello-world.ipynb b/hello-world.ipynb
index 62984f8..d73e681 100644
--- a/hello-world.ipynb
+++ b/hello-world.ipynb
@@ -261,7 +261,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "!uv run uipath run --file input.json"
+    "!uv run uipath run agent --file input.json"
    ]
   },
   {
diff --git a/resources/main1.py b/resources/main1.py
index cbd0408..479a617 100644
--- a/resources/main1.py
+++ b/resources/main1.py
@@ -4,7 +4,8 @@
 from pydantic import BaseModel
 from uipath_langchain.retrievers import ContextGroundingRetriever
 from langchain_core.documents import Document
-from uipath.models import InvokeProcess, IngestionInProgressException
+from uipath.platform.common import InvokeProcess
+from uipath.platform.errors import IngestionInProgressException
 import httpx
 from uipath_langchain.chat.models import UiPathAzureChatOpenAI
 from langchain_openai import ChatOpenAI
diff --git a/resources/main2_multiple_agents.py b/resources/main2_multiple_agents.py
index 1d9949a..b038e3c 100644
--- a/resources/main2_multiple_agents.py
+++ b/resources/main2_multiple_agents.py
@@ -3,7 +3,8 @@
 from pydantic import BaseModel
 from uipath_langchain.retrievers import ContextGroundingRetriever
 from langchain_core.documents import Document
-from uipath.models import InvokeProcess, IngestionInProgressException
+from uipath.platform.common import InvokeProcess
+from uipath.platform.errors import IngestionInProgressException
 import httpx
 from uipath_langchain.chat.models import UiPathAzureChatOpenAI
 from langchain_openai import ChatOpenAI
diff --git a/resources/main3_validation.py b/resources/main3_validation.py
index 5dec6ec..befc1e3 100644
--- a/resources/main3_validation.py
+++ b/resources/main3_validation.py
@@ -3,7 +3,8 @@
 from pydantic import BaseModel
 from uipath_langchain.retrievers import ContextGroundingRetriever
 from langchain_core.documents import Document
-from uipath.models import InvokeProcess, IngestionInProgressException
+from uipath.platform.common import InvokeProcess
+from uipath.platform.errors import IngestionInProgressException
 import httpx
 from uipath_langchain.chat.models import UiPathAzureChatOpenAI
 from langchain_openai import ChatOpenAI
diff --git a/resources/main4_hr.py b/resources/main4_hr.py
index b6aa767..ba9d090 100644
--- a/resources/main4_hr.py
+++ b/resources/main4_hr.py
@@ -3,7 +3,8 @@
 from pydantic import BaseModel
 from uipath_langchain.retrievers import ContextGroundingRetriever
 from langchain_core.documents import Document
-from uipath.models import InvokeProcess, IngestionInProgressException
+from uipath.platform.common import InvokeProcess
+from uipath.platform.errors import IngestionInProgressException
 import httpx
 from uipath_langchain.chat.models import UiPathAzureChatOpenAI
 from langchain_openai import ChatOpenAI
diff --git a/resources/main5_permission_check_hr.py b/resources/main5_permission_check_hr.py
index ec1d861..0dbbc0a 100644
--- a/resources/main5_permission_check_hr.py
+++ b/resources/main5_permission_check_hr.py
@@ -3,7 +3,8 @@
 from pydantic import BaseModel
 from uipath_langchain.retrievers import ContextGroundingRetriever
 from langchain_core.documents import Document
-from uipath.models import InvokeProcess, IngestionInProgressException
+from uipath.platform.common import InvokeProcess
+from uipath.platform.errors import IngestionInProgressException
 import httpx
 from uipath_langchain.chat.models import UiPathAzureChatOpenAI
 from langchain_openai import ChatOpenAI
diff --git a/resources/main6_HITL.py b/resources/main6_HITL.py
index 959d103..1d32a47 100644
--- a/resources/main6_HITL.py
+++ b/resources/main6_HITL.py
@@ -3,13 +3,14 @@
 from pydantic import BaseModel, Field
 from uipath_langchain.retrievers import ContextGroundingRetriever
 from langchain_core.documents import Document
-from uipath.models import InvokeProcess, IngestionInProgressException
+from uipath.platform.common import InvokeProcess
+from uipath.platform.errors import IngestionInProgressException
 import httpx
 from uipath_langchain.chat.models import UiPathAzureChatOpenAI
 from langchain_openai import ChatOpenAI
 import logging
 import time
-from uipath.models import CreateAction
+from uipath.platform.common import CreateTask
 from langgraph.types import interrupt
 from typing import Literal
 
@@ -180,13 +181,12 @@ async def supervisor_node(state: GraphState) -> GraphState:
     human_feedback = None
 
     if result["confidence"] < 99:
-        action_data = interrupt(CreateAction(app_name="SimpleApprovalApp",
+        action_data = interrupt(CreateTask(app_name="SimpleApprovalApp",
                                              title="Action Required: Review classification",
                                              data={
                                                  "Content": f"I classified the question '{state.question}' \n as {result['category']} \n Is this ok? My confidence score is only {result['confidence']}"},
                                              app_folder_path="Shared/ApprovalApp",
-                                             assignee="eusebiu.jecan@uipath.com",
-                                             app_version=4
+                                             assignee="eusebiu.jecan@uipath.com"
                                              ))
         if not bool(action_data["Approved"]):
             human_feedback = action_data["Comment"]
diff --git a/src/company-agent/.env b/src/company-agent/.env
index 4e0ada4..e789f9e 100644
--- a/src/company-agent/.env
+++ b/src/company-agent/.env
@@ -3,4 +3,3 @@ UIPATH_URL=https://alpha.uipath.com/Ada/GiuliaTenant
 UIPATH_TENANT_ID=3c05bc70-6a91-4ccd-996a-95b90d11f829
 UIPATH_ORGANIZATION_ID=b7006b1c-11c3-4a80-802e-fee0ebf9c360
 UIPATH_FOLDER_NAME=Shared
-OPENAI_API_KEY=****
diff --git a/src/company-agent/main.py b/src/company-agent/main.py
deleted file mode 100644
index 542d958..0000000
--- a/src/company-agent/main.py
+++ /dev/null
@@ -1,456 +0,0 @@
-# from langchain_anthropic import ChatAnthropic
-from langgraph.graph import END, START, StateGraph
-from pydantic import BaseModel, Field
-from uipath_langchain.retrievers import ContextGroundingRetriever
-from langchain_core.documents import Document
-from uipath.models import InvokeProcess, IngestionInProgressException
-import httpx
-from uipath_langchain.chat.models import UiPathAzureChatOpenAI
-from langchain_openai import ChatOpenAI
-import logging
-import time
-from uipath.models import CreateAction
-from langgraph.types import interrupt
-from typing import Literal
-
-import os
-import json
-
-from dotenv import load_dotenv
-
-load_dotenv()
-
-
-class IndexNotFound(Exception):
-    pass
-
-
-logger = logging.getLogger(__name__)
-
-# Define system prompt for company policy agent
-system_prompt = """
-You are an advanced AI assistant specializing in answering questions about internal company policies. 
-Structure your responses as follows:
-
-Answer:
-<1–3 sentence conclusion>
-
-Policy evidence:
-- "<exact quote>"
-  Reference: <section/bullet>
-
-Conditions/Exceptions:
-- <condition or threshold>
-
-Next steps:
-- <action 1>
-- <action 2>
-
-If not covered:
-<one line stating it’s not covered and what info is missing>
-"""
-
-# llm = ChatAnthropic(model="claude-3-5-sonnet-latest")
-llm = UiPathAzureChatOpenAI()
-# llm = ChatOpenAI(
-#     model="gpt-5",
-#     temperature=0,
-#     max_tokens=4000,
-#     timeout=30,
-#     max_retries=2,
-# )
-
-
-class LlmOutput(BaseModel):
-    """A model representing the categorization of a user question."""
-
-    category: Literal["Company Policy", "Procurement", "HR"] = Field(
-        ...,
-        description="The category of the user's question. Must be one of 'Company Policy', 'Procurement', or 'HR'."
-    )
-    confidence: float = Field(
-        ...,
-        description="Confidence score for the categorization, ranging from 0 (no confidence) to 100 (high confidence).",
-        ge=0,
-        le=100,
-    )
-
-
-async def get_context_data_async(retriever: ContextGroundingRetriever, question: str) -> list[Document]:
-    no_of_retries = 5
-    context_data = None
-    data_queried = False
-    while no_of_retries != 0:
-        try:
-            context_data = await retriever.ainvoke(question)
-            data_queried = True
-            break
-        except IngestionInProgressException as ex:
-            logger.info(ex.message)
-            no_of_retries -= 1
-            logger.info(f"{no_of_retries} retries left")
-            time.sleep(5)
-        except httpx.HTTPStatusError as err:
-            if err.response.status_code == 404:
-                raise IndexNotFound
-            raise
-    if not data_queried:
-        raise Exception("Ingestion is taking too long.")
-    return context_data
-
-
-class GraphState(BaseModel):
-    """State for the company policy agent graph."""
-    question: str
-    category: str | None = None
-    human_feedback: str | None = None
-    # Human-in-the-loop fields (used by procurement flow)
-    email: str | None = None
-    code: str | None = None
-
-
-class GraphOutput(BaseModel):
-    """Output for the company policy agent graph."""
-    response: str
-
-
-def is_valid_company_email(email: str | None) -> bool:
-    """Validate that the email is in the uipath.com domain."""
-    if not email or "@" not in email:
-        return False
-    return email.strip().lower().endswith("@uipath.com")
-
-
-def is_valid_code(code: str | None) -> bool:
-    """Validate a 4-digit code that is not all the same digit and not consecutive (e.g., 1234)."""
-    if not code or len(code) != 4 or not code.isdigit():
-        return False
-    # Reject all identical digits (e.g., 1111)
-    if len(set(code)) == 1:
-        return False
-    # Reject strictly ascending consecutive sequences (e.g., 0123, 1234, ..., 6789)
-    digits = [int(c) for c in code]
-    if all(digits[i + 1] - digits[i] == 1 for i in range(3)):
-        return False
-    return True
-
-
-async def policy_node(state: GraphState) -> GraphOutput:
-    retriever = ContextGroundingRetriever(
-        index_name="company-policy-index",
-        folder_path="Shared",
-        number_of_results=100,
-    )
-    try:
-        context_docs = await get_context_data_async(retriever, state.question)
-    except IndexNotFound:
-        context_docs = []
-
-    messages = [
-        {"role": "system", "content": system_prompt},
-        {"role": "user", "content": state.question},
-    ]
-    if state.category:
-        messages.append({"role": "user", "content": f"Category: {state.category}"})
-    if context_docs:
-        messages.append({"role": "user", "content": context_docs[0].page_content})
-
-    """Process a company policy question and return a structured answer."""
-    result = await llm.ainvoke(messages)
-    return GraphOutput(response=result.content)
-
-
-async def supervisor_node(state: GraphState) -> GraphState:
-    import os
-
-    for name, value in os.environ.items():
-        print("{0}: {1}".format(name, value))
-    """Supervisor: classify the question and store the category for routing."""
-    messages = [
-        {"role": "system", "content": (
-            "Classify the user's question into one of: Company Policy, Procurement, HR. "
-            "Reply with only the exact label."
-        )},
-        {"role": "user", "content": state.question},
-    ]
-    if state.human_feedback:
-        messages.append({"role": "user", "content": f"You predicted {state.category} which is not correct. Please consider the following feedback:  '{state.human_feedback}'"})
-    print(messages)
-    result = await llm.with_structured_output(LlmOutput).ainvoke(messages)
-    human_feedback = None
-
-    # Temporarily disable HITL for testing - set to very low threshold
-    # Original: if result["confidence"] < 99:
-    if result["confidence"] < 50:
-        action_data = interrupt(CreateAction(app_name="App",
-                                             title="Action Required: Review classification",
-                                             data={
-                                                 "Content": f"I classified the question '{state.question}' \n as {result['category']} \n Is this ok? My confidence score is only {result['confidence']}"},
-                                             app_folder_path="Shared/ApprovalApp/SimpleApprovalAppSolution",
-                                             assignee="cosmin.paunel@uipath.com",
-                                             app_version=4
-                                             ))
-        print(f"Action response: {action_data}")
-        # Check for approval - action_data might have different key names depending on the app
-        # Common keys: "Approved", "approved", "IsApproved", "approval", "status"
-        if action_data:
-            approved = action_data.get("Approved") or action_data.get("approved") or action_data.get("IsApproved")
-            if approved is not None and not bool(approved):
-                human_feedback = action_data.get("Comment", action_data.get("comment", ""))
-    return GraphState(question=state.question, category=result["category"], human_feedback=human_feedback)
-
-
-def route_by_category(state: GraphState) -> str:
-    """Return the route key to dispatch to the specialized agent."""
-    if state.category and state.category.lower() == "procurement":
-        return "procurement"
-    if state.category and state.category.lower() == "hr":
-        return "hr"
-    return "policy"
-
-
-async def procurement_node(state: GraphState) -> GraphOutput:
-    """Procurement specialized agent (assumes prior verification)."""
-    email = state.email
-    code = state.code
-
-    retriever = ContextGroundingRetriever(
-        index_name="procurement-index",
-        folder_path="Shared",
-        number_of_results=100,
-    )
-    try:
-        context_docs = await get_context_data_async(retriever, state.question)
-    except IndexNotFound:
-        context_docs = []
-
-    messages = [
-        {"role": "system", "content": system_prompt},
-        {"role": "user", "content": state.question},
-    ]
-    messages.append({"role": "user", "content": "Agent: Procurement"})
-    if state.category:
-        messages.append({"role": "user", "content": f"Category: {state.category}"})
-    # Attach verified email/code context (not used as secrets; only provenance)
-    if email:
-        messages.append({"role": "user", "content": f"Verified email: {email}"})
-    if code:
-        messages.append({"role": "user", "content": "Verification code provided (stored transiently)"})
-    if context_docs:
-        messages.append({"role": "user", "content": context_docs[0].page_content})
-
-    result = await llm.ainvoke(messages)
-    return GraphOutput(response=result.content)
-
-
-async def hr_node(state: GraphState) -> GraphOutput:
-    """HR specialized agent (no context grounding).
-
-    Chooses an HR system/tool (e.g., Workday) based on the question using:
-    - A local JSON catalog file if present (./hr_tools.json or ./resources/hr_tools.json)
-    - Otherwise a built-in default mapping
-    The model is prompted to return a compact JSON plan with the chosen tool and action.
-    """
-
-    # Load optional local catalog
-    default_catalog = {
-        "workday": {
-            "areas": [
-                "pto", "leave", "vacation", "time off", "absence",
-                "benefits", "payroll", "compensation", "recruiting", "onboarding"
-            ]
-        },
-        "servicenow_hrsd": {
-            "areas": ["hr ticket", "policy request", "case", "issue", "access request"]
-        },
-        "bamboohr": {
-            "areas": ["employee directory", "time off", "basic hr records"]
-        },
-        "greenhouse": {
-            "areas": ["recruiting", "interview", "schedule", "offer"]
-        }
-    }
-
-    catalog = default_catalog
-    for path in [
-        os.path.join(os.getcwd(), "hr_tools.json"),
-        os.path.join(os.getcwd(), "resources", "hr_tools.json"),
-    ]:
-        if os.path.exists(path):
-            try:
-                with open(path, "r", encoding="utf-8") as f:
-                    catalog = json.load(f)
-                break
-            except Exception:
-                catalog = default_catalog
-
-    planning_prompt = (
-        "You are an HR routing module. Choose the best target system/tool from the provided catalog "
-        "for the user's request and propose a single concrete action. Respond with ONLY valid JSON "
-        "in the following schema: {\n"
-        "  \"tool\": <one of the catalog keys>,\n"
-        "  \"action\": <short command-like phrase>,\n"
-        "  \"parameters\": {<key-value minimal fields>},\n"
-        "  \"reason\": <one sentence rationale>\n"
-        "}. If out of scope, set tool to \"none\" and explain in reason."
-    )
-
-    messages = [
-        {"role": "system", "content": planning_prompt},
-        {"role": "user", "content": f"Catalog: {json.dumps(catalog)}"},
-        {"role": "user", "content": f"Question: {state.question}"},
-    ]
-
-    result = await llm.ainvoke(messages)
-    content = result.content or "{}"
-
-    plan = None
-    try:
-        plan = json.loads(content)
-    except Exception:
-        # Try to recover from responses wrapped in code fences
-        if "{" in content and "}" in content:
-            try:
-                start = content.find("{")
-                end = content.rfind("}") + 1
-                plan = json.loads(content[start:end])
-            except Exception:
-                plan = None
-
-    if not isinstance(plan, dict):
-        return GraphOutput(response="Tool selected for the ask is: none")
-
-    tool = plan.get("tool", "none")
-    return GraphOutput(response=f"Tool selected for the ask is: {tool}")
-
-
-async def permission_check_local_DB(state: GraphState):
-    """HR permission gate using a local JSON DB of allowed emails.
-
-    File lookup order: ./hr_auth.json, ./resources/hr_auth.json
-    Expected format: {"allowed_emails": ["user@company.com", ...]}
-
-    - If email is missing or not in the allow-list: return GraphOutput("Not authorised")
-    - If allowed: pass state through unchanged
-    """
-    email = (state.email or "").strip().lower()
-    allowlist: list[str] = []
-
-    for path in [
-        os.path.join(os.getcwd(), "hr_auth.json"),
-        os.path.join(os.getcwd(), "resources", "hr_auth.json"),
-    ]:
-        if os.path.exists(path):
-            try:
-                with open(path, "r", encoding="utf-8") as f:
-                    data = json.load(f)
-                    allowlist = [e.strip().lower() for e in data.get("allowed_emails", []) if isinstance(e, str)]
-                break
-            except Exception:
-                allowlist = []
-
-    if not email or email not in allowlist:
-        return GraphOutput(response="Not authorised")
-
-    return state
-
-
-async def verify_credentials_node(state: GraphState):
-    """Verification gate: validate optional email/code for procurement path.
-
-    - If missing: fail fast with concise message
-    - If invalid: fail fast with concise message
-    - If valid: pass state through unchanged
-    """
-    email = state.email
-    code = state.code
-    if email is None or code is None:
-        return GraphOutput(response="Failed: E-mail and CODE are required for procurement.")
-    if not is_valid_company_email(email) or not is_valid_code(code):
-        return GraphOutput(response="Failed: E-mail and CODE are invalid.")
-    return state
-
-
-# Conditional routing after verification to respect LangGraph pattern
-def route_after_verification(state) -> str:
-    """Route based on verification result.
-
-    - If verification failed, prior node returned GraphOutput → end
-    - If verification passed, prior node returned GraphState → procurement
-    """
-    if isinstance(state, GraphOutput):
-        return "end"
-    if isinstance(state, dict) and "response" in state:
-        return "end"
-    if isinstance(state, GraphState):
-        if not is_valid_company_email(state.email) or not is_valid_code(state.code):
-            return "end"
-    return "procurement"
-
-def decide_next_node(state: GraphState) -> Literal["supervisor", "next_node"]:
-    if state.human_feedback:
-        return "supervisor"
-    return "next_node"
-
-
-def route_by_category_node(state: GraphState) -> dict:
-    category_lower = state.category.lower()
-    # Map variations to canonical names
-    category_map = {
-        "company policy": "policy",
-        "policy": "policy",
-        "procurement": "procurement",
-        "hr": "hr",
-        "human resources": "hr",
-    }
-
-    if category_lower not in category_map:
-        raise ValueError(
-            f"Invalid category '{state.category}'. Expected one of: 'policy', 'procurement', 'hr'."
-        )
-    return {"route": category_map[category_lower]}
-
-
-# Build the state graph with conditional routing
-builder = StateGraph(GraphState, output=GraphOutput)
-builder.add_node("supervisor", supervisor_node)
-builder.add_node("policy", policy_node)
-builder.add_node("verify_credentials", verify_credentials_node)
-builder.add_node("procurement", procurement_node)
-builder.add_node("hr", hr_node)
-builder.add_node("permission_check_local_DB", permission_check_local_DB)
-builder.add_node("route_by_category", route_by_category_node)
-
-builder.add_edge(START, "supervisor")
-builder.add_conditional_edges(
-    "supervisor",
-    decide_next_node,
-    {
-        "supervisor": "supervisor",
-        "next_node": "route_by_category",
-    },
-)
-builder.add_conditional_edges(
-    "route_by_category",
-    route_by_category,
-    {
-        "policy": "policy",
-        "procurement": "verify_credentials",
-        "hr": "permission_check_local_DB",
-    },
-)
-builder.add_edge("policy", END)
-builder.add_conditional_edges(
-    "verify_credentials",
-    route_after_verification,
-    {
-        "procurement": "procurement",
-        "end": END,
-    },
-)
-builder.add_edge("procurement", END)
-builder.add_edge("permission_check_local_DB", "hr")
-builder.add_edge("hr", END)
-
-# Compile the graph
-graph = builder.compile()
diff --git a/src/company-agent/pyproject.toml b/src/company-agent/pyproject.toml
index b3b22e1..ebcdc8b 100644
--- a/src/company-agent/pyproject.toml
+++ b/src/company-agent/pyproject.toml
@@ -4,17 +4,17 @@ version = "0.1.0"
 description = "Company policy agent with supervisor routing and node-level evaluation support"
 authors = [{ name = "UiPath", email = "support@uipath.com" }]
 dependencies = [
-    "uipath",
-    "uipath-langchain",
-    "langchain-core>=0.3.33",
-    "langchain-openai>=0.3.33",
-    "langchain-anthropic>=0.3.8",
-    "langgraph>=0.2.62",
-    "python-dotenv>=1.0.0",
-    "pydantic>=2.0.0",
-    "httpx>=0.27.0",
+    "uipath~=2.5.30",
+    "uipath-langchain~=0.4.27",
+    "langchain-core~=0.3.33",
+    "langchain-openai~=0.3.33",
+    "langchain-anthropic~=0.3.8",
+    "langgraph~=0.2.62",
+    "python-dotenv~=1.0.0",
+    "pydantic~=2.0.0",
+    "httpx~=0.27.0",
 ]
-requires-python = ">=3.10"
+requires-python = ">=3.11"
 
 [tool.uv.sources]
 uipath = { path = "../../../uipath-python", editable = true }