Return session name in runner response

langchain/client/runner_utils.py

@@ -422,21 +422,25 @@ async def arun_on_dataset(
             client will be created using the credentials in the environment.
 
     Returns:
-        A dictionary mapping example ids to the model outputs.
+        A dictionary containing the run's session name and the resulting model outputs.
     """
     client_ = client or LangChainPlusClient()
     session_name = _get_session_name(session_name, llm_or_chain_factory, dataset_name)
     dataset = client_.read_dataset(dataset_name=dataset_name)
     examples = client_.list_examples(dataset_id=str(dataset.id))
 
-    return await arun_on_examples(
+    results = await arun_on_examples(
         examples,
         llm_or_chain_factory,
         concurrency_level=concurrency_level,
         num_repetitions=num_repetitions,
         session_name=session_name,
         verbose=verbose,
     )
+    return {
+        "session_name": session_name,
+        "results": results,
+    }
 
 
 def run_on_dataset(
@@ -466,16 +470,20 @@ def run_on_dataset(
             will be created using the credentials in the environment.
 
     Returns:
-        A dictionary mapping example ids to the model outputs.
+        A dictionary containing the run's session name and the resulting model outputs.
     """
     client_ = client or LangChainPlusClient()
     session_name = _get_session_name(session_name, llm_or_chain_factory, dataset_name)
     dataset = client_.read_dataset(dataset_name=dataset_name)
     examples = client_.list_examples(dataset_id=str(dataset.id))
-    return run_on_examples(
+    results = run_on_examples(
         examples,
         llm_or_chain_factory,
         num_repetitions=num_repetitions,
         session_name=session_name,
         verbose=verbose,
     )
+    return {
+        "session_name": session_name,
+        "results": results,
+    }

langchain/experimental/client/tracing_datasets.ipynb

@@ -212,6 +212,8 @@
     "    error=False,  # Only runs that succeed\n",
     ")\n",
     "for run in runs:\n",
+    "    if run.outputs is None:\n",
+    "        continue\n",
     "    try:\n",
     "        client.create_example(\n",
     "            inputs=run.inputs, outputs=run.outputs, dataset_id=dataset.id\n",
@@ -388,7 +390,7 @@
        "        client will be created using the credentials in the environment.\n",
        "\n",
        "Returns:\n",
-       "    A dictionary mapping example ids to the model outputs.\n",
+       "    A dictionary containing the run's session name and the resulting model outputs.\n",
        "\u001b[0;31mFile:\u001b[0m      ~/code/lc/lckg/langchain/client/runner_utils.py\n",
        "\u001b[0;31mType:\u001b[0m      function"
       ]
@@ -438,16 +440,14 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Processed examples: 3\r"
+      "Processed examples: 4\r"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Chain failed for example 59fb1b4d-d935-4e43-b2a7-bc33fde841bb. Error: LLMMathChain._evaluate(\"\n",
-      "round(0.2791714614499425, 2)\n",
-      "\") raised error: 'VariableNode' object is not callable. Please try again with a valid numerical expression\n"
+      "Chain failed for example c855f923-4165-4fe0-a909-360749f3f764. Error: Could not parse LLM output: `The final answer is that there were no more points scored in the 2023 Super Bowl than in the 2022 Super Bowl.`\n"
      ]
     },
     {
@@ -459,13 +459,11 @@
     }
    ],
    "source": [
-    "evaluation_session_name = \"Search + Calculator Agent Evaluation\"\n",
     "chain_results = await arun_on_dataset(\n",
     "    dataset_name=dataset_name,\n",
     "    llm_or_chain_factory=chain_factory,\n",
     "    concurrency_level=5,  # Optional, sets the number of examples to run at a time\n",
     "    verbose=True,\n",
-    "    session_name=evaluation_session_name,  # Optional, a unique session name will be generated if not provided\n",
     "    client=client,\n",
     ")\n",
     "\n",
@@ -558,7 +556,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 16,
    "id": "4c94a738-dcd3-442e-b8e7-dd36459f56e3",
    "metadata": {
     "tags": []
@@ -567,7 +565,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "a185493c1af74cbaa0f9b10f32cf81c6",
+       "model_id": "9989f6507cd04ea7a09ea3c5723dc984",
        "version_major": 2,
        "version_minor": 0
       },
@@ -582,8 +580,10 @@
    "source": [
     "from tqdm.notebook import tqdm\n",
     "feedbacks = []\n",
-    "runs = client.list_runs(session_name=evaluation_session_name, execution_order=1, error=False)\n",
+    "runs = client.list_runs(session_name=chain_results[\"session_name\"], execution_order=1, error=False)\n",
     "for run in tqdm(runs):\n",
+    "    if run.outputs is None:\n",
+    "        continue\n",
     "    eval_feedback = []\n",
     "    for evaluator in evaluators:\n",
     "        eval_feedback.append(client.aevaluate_run(run, evaluator))\n",
@@ -592,26 +592,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": null,
    "id": "8696f167-dc75-4ef8-8bb3-ac1ce8324f30",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<a href=\"https://dev.langchain.plus\", target=\"_blank\" rel=\"noopener\">LangChain+ Client</a>"
-      ],
-      "text/plain": [
-       "LangChainPlusClient (API URL: https://dev.api.langchain.plus)"
-      ]
-     },
-     "execution_count": 29,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "client"
    ]

tests/unit_tests/client/test_runner_utils.py

@@ -201,4 +201,4 @@ async def mock_arun_chain(
             ]
             for uuid_ in uuids
         }
-        assert results == expected
+        assert results["results"] == expected