[AgentDeployer] Notebook prompt fix

modules/src/agent_deployer/agent_deployer.ipynb

@@ -10,18 +10,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
    "id": "be42e7c5-b2af-476f-8041-c17be56edb52",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "> 2025-12-03 07:17:36,530 [info] Project loaded successfully: {\"project_name\":\"langchain-example-10\"}\n"
-     ]
-    }
-   ],
    "source": [
     "%config Completer.use_jedi = False\n",
     "\n",
@@ -31,7 +21,9 @@
     "image = \"mlrun/mlrun\"\n",
     "project_name = \"langchain-example\"\n",
     "project = get_or_create_project(project_name, context=\"./\", allow_cross_project=True)"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -43,17 +35,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
    "id": "a47d7789-2ea2-493e-8905-f53b978e2abd",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# Create project secrets for project\n",
     "secrets = {\"OPENAI_API_KEY\": \"\", # add your OpenAI API key here\n",
     "          \"OPENAI_BASE_URL\": \"\" # add your OpenAI base url here if needed\n",
     "          }\n",
     "project.set_secrets(secrets=secrets, provider=\"kubernetes\")"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -65,10 +57,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "25cbd982-86de-43b5-91ef-24fc60b2d758",
    "metadata": {},
-   "outputs": [],
    "source": [
     "%%writefile langchain_model.py\n",
     "\n",
@@ -197,7 +187,9 @@
     "        result[\"total_cost_usd\"] = input_cost + output_cost\n",
     "        return result\n",
     "            "
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -209,20 +201,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 81,
    "id": "691e9068-ec9c-40d6-9ac8-e6c3e605b44c",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "> 2025-12-03 10:55:46,194 [info] Project loaded successfully: {\"project_name\":\"langchain-example-10\"}\n",
-      "> 2025-12-03 10:55:46,463 [info] Model monitoring credentials were set successfully. Please keep in mind that if you already had model monitoring functions / model monitoring infra / tracked model server deployed on your project, you will need to redeploy them. For redeploying the model monitoring infra, first disable it using `project.disable_model_monitoring()` and then enable it using `project.enable_model_monitoring()`.\n",
-      "details: MLRunConflictError(\"The following model-montioring infrastructure functions are already deployed, aborting: ['model-monitoring-controller', 'model-monitoring-writer']\\nIf you want to redeploy the model-monitoring controller (maybe with different base-period), use update_model_monitoring_controller.If you want to redeploy all of model-monitoring infrastructure, call disable_model_monitoringbefore calling enable_model_monitoring again.\")\n"
-     ]
-    }
-   ],
    "source": [
     "module = mlrun.import_module(\"hub://agent_deployer\")\n",
     "\n",
@@ -237,11 +217,11 @@
     "            prompt_template= \"\"\"\n",
     "            Answer the following questions as best you can.\n",
     "            You have access to the following tools:\n",
-    "            {tools}\n",
+    "            {{tools}}\n",
     "            Use the following format:\n",
     "            Question: the input question you must answer\n",
     "            Thought: you should always think about what to do\n",
-    "            Action: the action to take, should be one of [{tool_names}]\n",
+    "            Action: the action to take, should be one of [{{tool_names}}]\n",
     "            Action Input: the input to the action\n",
     "            Observation: the result of the action\n",
     "            ... (this Thought/Action/Action Input/Observation can repeat N times)\n",
@@ -252,16 +232,18 @@
     "            Question: {input}\n",
     "            Thought:{agent_scratchpad}\n",
     "            \"\"\",\n",
-    ")"
-   ]
+    ")\n"
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
-   "execution_count": 82,
    "id": "0bb1c4d1-5d7c-4d1c-bf51-8f53b319e91f",
    "metadata": {},
+   "source": "func = agent.deploy_function(enable_tracking=True)",
    "outputs": [],
-   "source": "func = agent.deploy_function(enable_tracking=True)"
+   "execution_count": null
   },
   {
    "metadata": {},
@@ -272,10 +254,10 @@
   {
    "metadata": {},
    "cell_type": "code",
+   "source": "func.invoke(\"./\", {\"question\" : \"If a pizza costs $18.75 and I want to buy 3, what is the total cost?\"})",
+   "id": "ac5c3ba174d2cf8b",
    "outputs": [],
-   "execution_count": null,
-   "source": "func.invoke(\"./\", {\"question\" : \"If a pizza costs $18.75 and I want to buy 3, plus a 15% tip, what is the total cost?\"})",
-   "id": "ac5c3ba174d2cf8b"
+   "execution_count": null
   },
   {
    "metadata": {},
@@ -289,8 +271,6 @@
   {
    "metadata": {},
    "cell_type": "code",
-   "outputs": [],
-   "execution_count": null,
    "source": [
     "%%writefile monitoring_application.py\n",
     "\n",
@@ -405,7 +385,9 @@
     "            value=value,\n",
     "        )\n"
    ],
-   "id": "377487422f5ed289"
+   "id": "377487422f5ed289",
+   "outputs": [],
+   "execution_count": null
   },
   {
    "metadata": {},
@@ -416,8 +398,6 @@
   {
    "metadata": {},
    "cell_type": "code",
-   "outputs": [],
-   "execution_count": null,
    "source": [
     "llm_monitoring_app = project.set_model_monitoring_function(\n",
     "    func=\"monitoring_application.py\",\n",
@@ -428,7 +408,9 @@
     "\n",
     "project.deploy_function(llm_monitoring_app)"
    ],
-   "id": "9d6ad2a4a47a44bd"
+   "id": "9d6ad2a4a47a44bd",
+   "outputs": [],
+   "execution_count": null
   }
  ],
  "metadata": {