diff --git a/scratches/acano/langgraph_agent_simple.ipynb b/scratches/acano/langgraph_agent_simple.ipynb
index df15468..7ffdb09 100644
--- a/scratches/acano/langgraph_agent_simple.ipynb
+++ b/scratches/acano/langgraph_agent_simple.ipynb
@@ -303,1462 +303,6 @@
    "source": [
     "a = stream_graph_updates(user_input)"
    ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "367b898a",
-   "metadata": {},
-   "source": [
-    "### Evaluation"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "f4119e2c",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from dataclasses import dataclass\n",
-    "from typing import Any, Iterable\n",
-    "\n",
-    "import numpy as np\n",
-    "\n",
-    "import mteb\n",
-    "from mteb.types import Array\n",
-    "from mteb.models import SearchEncoderWrapper\n",
-    "\n",
-    "\n",
-    "def _l2_normalize(x: np.ndarray, eps: float = 1e-12) -> np.ndarray:\n",
-    "    norms = np.linalg.norm(x, axis=1, keepdims=True)\n",
-    "    return x / np.clip(norms, eps, None)\n",
-    "\n",
-    "\n",
-    "def _to_text_list(batch: dict[str, Any]) -> list[str]:\n",
-    "    \"\"\"\n",
-    "    MTEB batched inputs can be:\n",
-    "      - TextInput: {\"text\": [..]}\n",
-    "      - CorpusInput: {\"title\": [..], \"body\": [..], \"text\": [..]}\n",
-    "      - QueryInput: {\"query\": [..], \"instruction\": [..], \"text\": [..]}\n",
-    "    We prefer \"text\" if present; otherwise compose from title/body or query/instruction.\n",
-    "    \"\"\"\n",
-    "    if \"text\" in batch and batch[\"text\"] is not None:\n",
-    "        return list(batch[\"text\"])\n",
-    "\n",
-    "    if \"title\" in batch and \"body\" in batch:\n",
-    "        titles = batch[\"title\"] or [\"\"] * len(batch[\"body\"])\n",
-    "        bodies = batch[\"body\"] or [\"\"] * len(batch[\"title\"])\n",
-    "        return [f\"{t} {b}\".strip() for t, b in zip(titles, bodies)]\n",
-    "\n",
-    "    if \"query\" in batch:\n",
-    "        queries = list(batch[\"query\"])\n",
-    "        instructions = batch.get(\"instruction\")\n",
-    "        if instructions:\n",
-    "            return [f\"{i} {q}\".strip() for q, i in zip(queries, instructions)]\n",
-    "        return queries\n",
-    "\n",
-    "    raise ValueError(f\"Unsupported batch keys: {sorted(batch.keys())}\")\n",
-    "\n",
-    "\n",
-    "@dataclass\n",
-    "class OllamaLangChainEncoder:\n",
-    "    lc_embeddings: Any  # OllamaEmbeddings implements embed_documents()\n",
-    "    normalize: bool = True\n",
-    "\n",
-    "    # Optional metadata hook used by some wrappers; safe to keep as None for local runs\n",
-    "    mteb_model_meta: Any = None\n",
-    "\n",
-    "    def encode(\n",
-    "        self,\n",
-    "        inputs: Iterable[dict[str, Any]],\n",
-    "        *,\n",
-    "        task_metadata: Any,\n",
-    "        hf_split: str,\n",
-    "        hf_subset: str,\n",
-    "        prompt_type: Any = None,\n",
-    "        **kwargs: Any,\n",
-    "    ) -> Array:\n",
-    "        all_vecs: list[np.ndarray] = []\n",
-    "\n",
-    "        for batch in inputs:\n",
-    "            texts = _to_text_list(batch)\n",
-    "            vecs = self.lc_embeddings.embed_documents(texts)\n",
-    "            arr = np.asarray(vecs, dtype=np.float32)\n",
-    "            if self.normalize:\n",
-    "                arr = _l2_normalize(arr)\n",
-    "            all_vecs.append(arr)\n",
-    "\n",
-    "        if not all_vecs:\n",
-    "            return np.zeros((0, 0), dtype=np.float32)\n",
-    "\n",
-    "        return np.vstack(all_vecs)\n",
-    "\n",
-    "    def similarity(self, embeddings1: Array, embeddings2: Array) -> Array:\n",
-    "        a = np.asarray(embeddings1, dtype=np.float32)\n",
-    "        b = np.asarray(embeddings2, dtype=np.float32)\n",
-    "        if self.normalize:\n",
-    "            # dot == cosine if already normalized\n",
-    "            return a @ b.T\n",
-    "        a = _l2_normalize(a)\n",
-    "        b = _l2_normalize(b)\n",
-    "        return a @ b.T\n",
-    "\n",
-    "    def similarity_pairwise(self, embeddings1: Array, embeddings2: Array) -> Array:\n",
-    "        a = np.asarray(embeddings1, dtype=np.float32)\n",
-    "        b = np.asarray(embeddings2, dtype=np.float32)\n",
-    "        if not self.normalize:\n",
-    "            a = _l2_normalize(a)\n",
-    "            b = _l2_normalize(b)\n",
-    "        return np.sum(a * b, axis=1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "f99b0712",
-   "metadata": {},
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-      ]
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-       "model_id": "00f6dfcba9a34d24827ff9929f23ac1e",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Filtering queries by qrels:   0%|          | 0/14918 [00:00<?, ? examples/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "cb9181bb83ff4d0585390b3fad7742bd",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Processing queries for dataloading:   0%|          | 0/14918 [00:00<?, ? examples/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "c7139c9c103b42709940168130dd84de",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Converting corpus dict:   0%|          | 0/50000 [00:00<?, ? examples/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "dafb9d036ed94575985b01f4f1b59858",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Converting corpus dict:   0%|          | 0/50000 [00:00<?, ? examples/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "994d09e7a4454b81b64bab20716967f8",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Converting corpus dict:   0%|          | 0/50000 [00:00<?, ? examples/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "ename": "KeyboardInterrupt",
-     "evalue": "",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
-      "\u001b[31mKeyboardInterrupt\u001b[39m                         Traceback (most recent call last)",
-      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[4]\u001b[39m\u001b[32m, line 10\u001b[39m\n\u001b[32m      2\u001b[39m search_model = SearchEncoderWrapper(encoder)\n\u001b[32m      4\u001b[39m tasks = mteb.get_tasks([\n\u001b[32m      5\u001b[39m     \u001b[33m\"\u001b[39m\u001b[33mCodeSearchNetRetrieval\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m      6\u001b[39m     \u001b[33m\"\u001b[39m\u001b[33mCodeSearchNetCCRetrieval\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m      7\u001b[39m     \u001b[33m\"\u001b[39m\u001b[33mAppsRetrieval\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m      8\u001b[39m     \u001b[33m\"\u001b[39m\u001b[33mStackOverflowDupQuestions\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m      9\u001b[39m ])\n\u001b[32m---> \u001b[39m\u001b[32m10\u001b[39m results = \u001b[43mmteb\u001b[49m\u001b[43m.\u001b[49m\u001b[43mevaluate\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m     11\u001b[39m \u001b[43m    \u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m=\u001b[49m\u001b[43msearch_model\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m     12\u001b[39m \u001b[43m    \u001b[49m\u001b[43mtasks\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtasks\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m     13\u001b[39m \u001b[43m    \u001b[49m\u001b[43mencode_kwargs\u001b[49m\u001b[43m=\u001b[49m\u001b[43m{\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mbatch_size\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[32;43m32\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mshow_progress_bar\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m}\u001b[49m\n\u001b[32m     14\u001b[39m \u001b[43m)\u001b[49m\n\u001b[32m     16\u001b[39m \u001b[38;5;28mprint\u001b[39m(results)\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/PycharmProjects/assistance-engine/.venv/lib/python3.11/site-packages/mteb/evaluate.py:388\u001b[39m, in \u001b[36mevaluate\u001b[39m\u001b[34m(model, tasks, co2_tracker, raise_error, encode_kwargs, cache, overwrite_strategy, prediction_folder, show_progress_bar, public_only, num_proc)\u001b[39m\n\u001b[32m    386\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m i, task \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(tasks_tqdm):\n\u001b[32m    387\u001b[39m     tasks_tqdm.set_description(\u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mEvaluating task \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mtask.metadata.name\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m)\n\u001b[32m--> \u001b[39m\u001b[32m388\u001b[39m     _res = \u001b[43mevaluate\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m    389\u001b[39m \u001b[43m        \u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    390\u001b[39m \u001b[43m        \u001b[49m\u001b[43mtask\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    391\u001b[39m \u001b[43m        \u001b[49m\u001b[43mco2_tracker\u001b[49m\u001b[43m=\u001b[49m\u001b[43mco2_tracker\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    392\u001b[39m \u001b[43m        \u001b[49m\u001b[43mraise_error\u001b[49m\u001b[43m=\u001b[49m\u001b[43mraise_error\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    393\u001b[39m \u001b[43m        \u001b[49m\u001b[43mencode_kwargs\u001b[49m\u001b[43m=\u001b[49m\u001b[43mencode_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    394\u001b[39m \u001b[43m        \u001b[49m\u001b[43mcache\u001b[49m\u001b[43m=\u001b[49m\u001b[43mcache\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    395\u001b[39m \u001b[43m        \u001b[49m\u001b[43moverwrite_strategy\u001b[49m\u001b[43m=\u001b[49m\u001b[43moverwrite_strategy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    396\u001b[39m \u001b[43m        \u001b[49m\u001b[43mprediction_folder\u001b[49m\u001b[43m=\u001b[49m\u001b[43mprediction_folder\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    397\u001b[39m \u001b[43m        \u001b[49m\u001b[43mshow_progress_bar\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[32m    398\u001b[39m \u001b[43m        \u001b[49m\u001b[43mpublic_only\u001b[49m\u001b[43m=\u001b[49m\u001b[43mpublic_only\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    399\u001b[39m \u001b[43m        \u001b[49m\u001b[43mnum_proc\u001b[49m\u001b[43m=\u001b[49m\u001b[43mnum_proc\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    400\u001b[39m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    401\u001b[39m     evaluate_results.extend(_res.task_results)\n\u001b[32m    402\u001b[39m     \u001b[38;5;28;01mif\u001b[39;00m _res.exceptions:\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/PycharmProjects/assistance-engine/.venv/lib/python3.11/site-packages/mteb/evaluate.py:487\u001b[39m, in \u001b[36mevaluate\u001b[39m\u001b[34m(model, tasks, co2_tracker, raise_error, encode_kwargs, cache, overwrite_strategy, prediction_folder, show_progress_bar, public_only, num_proc)\u001b[39m\n\u001b[32m    485\u001b[39m         result = TaskError(task_name=task.metadata.name, exception=\u001b[38;5;28mstr\u001b[39m(e))\n\u001b[32m    486\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m487\u001b[39m     result = \u001b[43m_evaluate_task\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m    488\u001b[39m \u001b[43m        \u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    489\u001b[39m \u001b[43m        \u001b[49m\u001b[43msplits\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmissing_eval\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    490\u001b[39m \u001b[43m        \u001b[49m\u001b[43mtask\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtask\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    491\u001b[39m \u001b[43m        \u001b[49m\u001b[43mco2_tracker\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[32m    492\u001b[39m \u001b[43m        \u001b[49m\u001b[43mencode_kwargs\u001b[49m\u001b[43m=\u001b[49m\u001b[43mencode_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    493\u001b[39m \u001b[43m        \u001b[49m\u001b[43mprediction_folder\u001b[49m\u001b[43m=\u001b[49m\u001b[43mprediction_folder\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    494\u001b[39m \u001b[43m        \u001b[49m\u001b[43mpublic_only\u001b[49m\u001b[43m=\u001b[49m\u001b[43mpublic_only\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    495\u001b[39m \u001b[43m        \u001b[49m\u001b[43mnum_proc\u001b[49m\u001b[43m=\u001b[49m\u001b[43mnum_proc\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    496\u001b[39m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    497\u001b[39m logger.info(\u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33m✓ Finished evaluation for \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mtask.metadata.name\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m)\n\u001b[32m    499\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(result, TaskError):\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/PycharmProjects/assistance-engine/.venv/lib/python3.11/site-packages/mteb/evaluate.py:161\u001b[39m, in \u001b[36m_evaluate_task\u001b[39m\u001b[34m(model, task, splits, co2_tracker, encode_kwargs, prediction_folder, public_only, num_proc)\u001b[39m\n\u001b[32m    159\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m split, hf_subsets \u001b[38;5;129;01min\u001b[39;00m splits.items():\n\u001b[32m    160\u001b[39m     tick = time()\n\u001b[32m--> \u001b[39m\u001b[32m161\u001b[39m     task_results[split] = \u001b[43mtask\u001b[49m\u001b[43m.\u001b[49m\u001b[43mevaluate\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m    162\u001b[39m \u001b[43m        \u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    163\u001b[39m \u001b[43m        \u001b[49m\u001b[43msplit\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    164\u001b[39m \u001b[43m        \u001b[49m\u001b[43msubsets_to_run\u001b[49m\u001b[43m=\u001b[49m\u001b[43mhf_subsets\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    165\u001b[39m \u001b[43m        \u001b[49m\u001b[43mencode_kwargs\u001b[49m\u001b[43m=\u001b[49m\u001b[43mencode_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    166\u001b[39m \u001b[43m        \u001b[49m\u001b[43mprediction_folder\u001b[49m\u001b[43m=\u001b[49m\u001b[43mprediction_folder\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    167\u001b[39m \u001b[43m        \u001b[49m\u001b[43mnum_proc\u001b[49m\u001b[43m=\u001b[49m\u001b[43mnum_proc\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    168\u001b[39m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    169\u001b[39m     tock = time()\n\u001b[32m    171\u001b[39m     logger.debug(\n\u001b[32m    172\u001b[39m         \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mEvaluation for \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mtask.metadata.name\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m on \u001b[39m\u001b[38;5;132;01m{\u001b[39;00msplit\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m took \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mtock\u001b[38;5;250m \u001b[39m-\u001b[38;5;250m \u001b[39mtick\u001b[38;5;132;01m:\u001b[39;00m\u001b[33m.2f\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m seconds\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m    173\u001b[39m     )\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/PycharmProjects/assistance-engine/.venv/lib/python3.11/site-packages/mteb/abstasks/retrieval.py:342\u001b[39m, in \u001b[36mAbsTaskRetrieval.evaluate\u001b[39m\u001b[34m(self, model, split, subsets_to_run, encode_kwargs, prediction_folder, num_proc, **kwargs)\u001b[39m\n\u001b[32m    339\u001b[39m \u001b[38;5;66;03m# TODO: convert all tasks directly https://github.com/embeddings-benchmark/mteb/issues/2030\u001b[39;00m\n\u001b[32m    340\u001b[39m \u001b[38;5;28mself\u001b[39m.convert_v1_dataset_format_to_v2(num_proc=num_proc)\n\u001b[32m--> \u001b[39m\u001b[32m342\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m.\u001b[49m\u001b[43mevaluate\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m    343\u001b[39m \u001b[43m    \u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    344\u001b[39m \u001b[43m    \u001b[49m\u001b[43msplit\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    345\u001b[39m \u001b[43m    \u001b[49m\u001b[43msubsets_to_run\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    346\u001b[39m \u001b[43m    \u001b[49m\u001b[43mencode_kwargs\u001b[49m\u001b[43m=\u001b[49m\u001b[43mencode_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    347\u001b[39m \u001b[43m    \u001b[49m\u001b[43mprediction_folder\u001b[49m\u001b[43m=\u001b[49m\u001b[43mprediction_folder\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    348\u001b[39m \u001b[43m    \u001b[49m\u001b[43mnum_proc\u001b[49m\u001b[43m=\u001b[49m\u001b[43mnum_proc\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    349\u001b[39m \u001b[43m    \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    350\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/PycharmProjects/assistance-engine/.venv/lib/python3.11/site-packages/mteb/abstasks/abstask.py:199\u001b[39m, in \u001b[36mAbsTask.evaluate\u001b[39m\u001b[34m(self, model, split, subsets_to_run, encode_kwargs, prediction_folder, num_proc, **kwargs)\u001b[39m\n\u001b[32m    197\u001b[39m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m    198\u001b[39m         data_split = \u001b[38;5;28mself\u001b[39m.dataset[hf_subset][split]\n\u001b[32m--> \u001b[39m\u001b[32m199\u001b[39m     scores[hf_subset] = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_evaluate_subset\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m    200\u001b[39m \u001b[43m        \u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    201\u001b[39m \u001b[43m        \u001b[49m\u001b[43mdata_split\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    202\u001b[39m \u001b[43m        \u001b[49m\u001b[43mhf_split\u001b[49m\u001b[43m=\u001b[49m\u001b[43msplit\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    203\u001b[39m \u001b[43m        \u001b[49m\u001b[43mhf_subset\u001b[49m\u001b[43m=\u001b[49m\u001b[43mhf_subset\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    204\u001b[39m \u001b[43m        \u001b[49m\u001b[43mencode_kwargs\u001b[49m\u001b[43m=\u001b[49m\u001b[43mencode_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    205\u001b[39m \u001b[43m        \u001b[49m\u001b[43mprediction_folder\u001b[49m\u001b[43m=\u001b[49m\u001b[43mprediction_folder\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    206\u001b[39m \u001b[43m        \u001b[49m\u001b[43mnum_proc\u001b[49m\u001b[43m=\u001b[49m\u001b[43mnum_proc\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    207\u001b[39m \u001b[43m        \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    208\u001b[39m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    209\u001b[39m     \u001b[38;5;28mself\u001b[39m._add_main_score(scores[hf_subset])\n\u001b[32m    210\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m scores\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/PycharmProjects/assistance-engine/.venv/lib/python3.11/site-packages/mteb/abstasks/retrieval.py:409\u001b[39m, in \u001b[36mAbsTaskRetrieval._evaluate_subset\u001b[39m\u001b[34m(self, model, data_split, encode_kwargs, hf_split, hf_subset, prediction_folder, num_proc, **kwargs)\u001b[39m\n\u001b[32m    404\u001b[39m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\n\u001b[32m    405\u001b[39m         \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mRetrievalEvaluator expects a SearchInterface, Encoder, or CrossEncoder, got \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mtype\u001b[39m(model)\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m\n\u001b[32m    406\u001b[39m     )\n\u001b[32m    408\u001b[39m start_time = time()\n\u001b[32m--> \u001b[39m\u001b[32m409\u001b[39m results = \u001b[43mretriever\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m    410\u001b[39m \u001b[43m    \u001b[49m\u001b[43msearch_model\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    411\u001b[39m \u001b[43m    \u001b[49m\u001b[43mencode_kwargs\u001b[49m\u001b[43m=\u001b[49m\u001b[43mencode_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    412\u001b[39m \u001b[43m    \u001b[49m\u001b[43mnum_proc\u001b[49m\u001b[43m=\u001b[49m\u001b[43mnum_proc\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    413\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    414\u001b[39m end_time = time()\n\u001b[32m    415\u001b[39m logger.debug(\n\u001b[32m    416\u001b[39m     \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mRunning retrieval task - Time taken to retrieve: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mend_time\u001b[38;5;250m \u001b[39m-\u001b[38;5;250m \u001b[39mstart_time\u001b[38;5;132;01m:\u001b[39;00m\u001b[33m.2f\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m seconds\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m    417\u001b[39m )\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/PycharmProjects/assistance-engine/.venv/lib/python3.11/site-packages/mteb/_evaluators/retrieval_evaluator.py:70\u001b[39m, in \u001b[36mRetrievalEvaluator.__call__\u001b[39m\u001b[34m(self, search_model, encode_kwargs, num_proc)\u001b[39m\n\u001b[32m     61\u001b[39m search_model.index(\n\u001b[32m     62\u001b[39m     corpus=\u001b[38;5;28mself\u001b[39m.corpus,\n\u001b[32m     63\u001b[39m     task_metadata=\u001b[38;5;28mself\u001b[39m.task_metadata,\n\u001b[32m   (...)\u001b[39m\u001b[32m     67\u001b[39m     num_proc=num_proc,\n\u001b[32m     68\u001b[39m )\n\u001b[32m     69\u001b[39m logger.info(\u001b[33m\"\u001b[39m\u001b[33mRunning retrieval task - Searching queries...\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m---> \u001b[39m\u001b[32m70\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43msearch_model\u001b[49m\u001b[43m.\u001b[49m\u001b[43msearch\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m     71\u001b[39m \u001b[43m    \u001b[49m\u001b[43mqueries\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mqueries\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m     72\u001b[39m \u001b[43m    \u001b[49m\u001b[43mtop_k\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mtop_k\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m     73\u001b[39m \u001b[43m    \u001b[49m\u001b[43mtask_metadata\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mtask_metadata\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m     74\u001b[39m \u001b[43m    \u001b[49m\u001b[43mhf_split\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mhf_split\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m     75\u001b[39m \u001b[43m    \u001b[49m\u001b[43mhf_subset\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mhf_subset\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m     76\u001b[39m \u001b[43m    \u001b[49m\u001b[43mencode_kwargs\u001b[49m\u001b[43m=\u001b[49m\u001b[43mencode_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m     77\u001b[39m \u001b[43m    \u001b[49m\u001b[43mtop_ranked\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mtop_ranked\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m     78\u001b[39m \u001b[43m    \u001b[49m\u001b[43mnum_proc\u001b[49m\u001b[43m=\u001b[49m\u001b[43mnum_proc\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m     79\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/PycharmProjects/assistance-engine/.venv/lib/python3.11/site-packages/mteb/models/search_wrappers.py:183\u001b[39m, in \u001b[36mSearchEncoderWrapper.search\u001b[39m\u001b[34m(self, queries, task_metadata, hf_split, hf_subset, top_k, encode_kwargs, top_ranked, num_proc)\u001b[39m\n\u001b[32m    181\u001b[39m logger.info(\u001b[33m\"\u001b[39m\u001b[33mPerforming full corpus search...\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m    182\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m.index_backend \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m183\u001b[39m     result_heaps = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_full_corpus_search\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m    184\u001b[39m \u001b[43m        \u001b[49m\u001b[43mquery_idx_to_id\u001b[49m\u001b[43m=\u001b[49m\u001b[43mquery_idx_to_id\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    185\u001b[39m \u001b[43m        \u001b[49m\u001b[43mquery_embeddings\u001b[49m\u001b[43m=\u001b[49m\u001b[43mquery_embeddings\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    186\u001b[39m \u001b[43m        \u001b[49m\u001b[43mtask_metadata\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtask_metadata\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    187\u001b[39m \u001b[43m        \u001b[49m\u001b[43mhf_subset\u001b[49m\u001b[43m=\u001b[49m\u001b[43mhf_subset\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    188\u001b[39m \u001b[43m        \u001b[49m\u001b[43mhf_split\u001b[49m\u001b[43m=\u001b[49m\u001b[43mhf_split\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    189\u001b[39m \u001b[43m        \u001b[49m\u001b[43mtop_k\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtop_k\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    190\u001b[39m \u001b[43m        \u001b[49m\u001b[43mencode_kwargs\u001b[49m\u001b[43m=\u001b[49m\u001b[43mencode_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    191\u001b[39m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    192\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m    193\u001b[39m     cos_scores_top_k_values, cos_scores_top_k_idx = (\n\u001b[32m    194\u001b[39m         \u001b[38;5;28mself\u001b[39m.index_backend.search(\n\u001b[32m    195\u001b[39m             query_embeddings,\n\u001b[32m   (...)\u001b[39m\u001b[32m    200\u001b[39m         )\n\u001b[32m    201\u001b[39m     )\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/PycharmProjects/assistance-engine/.venv/lib/python3.11/site-packages/mteb/models/search_wrappers.py:253\u001b[39m, in \u001b[36mSearchEncoderWrapper._full_corpus_search\u001b[39m\u001b[34m(self, query_idx_to_id, query_embeddings, task_metadata, hf_subset, hf_split, top_k, encode_kwargs)\u001b[39m\n\u001b[32m    249\u001b[39m sub_corpus = \u001b[38;5;28mself\u001b[39m.task_corpus.select(\n\u001b[32m    250\u001b[39m     \u001b[38;5;28mrange\u001b[39m(corpus_start_idx, corpus_end_idx)\n\u001b[32m    251\u001b[39m )\n\u001b[32m    252\u001b[39m sub_corpus_ids = sub_corpus[\u001b[33m\"\u001b[39m\u001b[33mid\u001b[39m\u001b[33m\"\u001b[39m]\n\u001b[32m--> \u001b[39m\u001b[32m253\u001b[39m sub_corpus_embeddings = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m.\u001b[49m\u001b[43mencode\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m    254\u001b[39m \u001b[43m    \u001b[49m\u001b[43mcreate_dataloader\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m    255\u001b[39m \u001b[43m        \u001b[49m\u001b[43msub_corpus\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    256\u001b[39m \u001b[43m        \u001b[49m\u001b[43mtask_metadata\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    257\u001b[39m \u001b[43m        \u001b[49m\u001b[43mprompt_type\u001b[49m\u001b[43m=\u001b[49m\u001b[43mPromptType\u001b[49m\u001b[43m.\u001b[49m\u001b[43mdocument\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    258\u001b[39m \u001b[43m        \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mencode_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    259\u001b[39m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    260\u001b[39m \u001b[43m    \u001b[49m\u001b[43mtask_metadata\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtask_metadata\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    261\u001b[39m \u001b[43m    \u001b[49m\u001b[43mhf_split\u001b[49m\u001b[43m=\u001b[49m\u001b[43mhf_split\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    262\u001b[39m \u001b[43m    \u001b[49m\u001b[43mhf_subset\u001b[49m\u001b[43m=\u001b[49m\u001b[43mhf_subset\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    263\u001b[39m \u001b[43m    \u001b[49m\u001b[43mprompt_type\u001b[49m\u001b[43m=\u001b[49m\u001b[43mPromptType\u001b[49m\u001b[43m.\u001b[49m\u001b[43mdocument\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    264\u001b[39m \u001b[43m    \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mencode_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    265\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    267\u001b[39m \u001b[38;5;66;03m# Compute similarities using either cosine-similarity or dot product\u001b[39;00m\n\u001b[32m    268\u001b[39m logger.info(\u001b[33m\"\u001b[39m\u001b[33mComputing Similarities...\u001b[39m\u001b[33m\"\u001b[39m)\n",
-      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[3]\u001b[39m\u001b[32m, line 64\u001b[39m, in \u001b[36mOllamaLangChainEncoder.encode\u001b[39m\u001b[34m(self, inputs, task_metadata, hf_split, hf_subset, prompt_type, **kwargs)\u001b[39m\n\u001b[32m     62\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m batch \u001b[38;5;129;01min\u001b[39;00m inputs:\n\u001b[32m     63\u001b[39m     texts = _to_text_list(batch)\n\u001b[32m---> \u001b[39m\u001b[32m64\u001b[39m     vecs = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mlc_embeddings\u001b[49m\u001b[43m.\u001b[49m\u001b[43membed_documents\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtexts\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m     65\u001b[39m     arr = np.asarray(vecs, dtype=np.float32)\n\u001b[32m     66\u001b[39m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m.normalize:\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/PycharmProjects/assistance-engine/.venv/lib/python3.11/site-packages/langchain_ollama/embeddings.py:301\u001b[39m, in \u001b[36mOllamaEmbeddings.embed_documents\u001b[39m\u001b[34m(self, texts)\u001b[39m\n\u001b[32m    296\u001b[39m     msg = (\n\u001b[32m    297\u001b[39m         \u001b[33m\"\u001b[39m\u001b[33mOllama client is not initialized. \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m    298\u001b[39m         \u001b[33m\"\u001b[39m\u001b[33mPlease ensure Ollama is running and the model is loaded.\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m    299\u001b[39m     )\n\u001b[32m    300\u001b[39m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(msg)\n\u001b[32m--> \u001b[39m\u001b[32m301\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_client\u001b[49m\u001b[43m.\u001b[49m\u001b[43membed\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m    302\u001b[39m \u001b[43m    \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtexts\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43moptions\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_default_params\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkeep_alive\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mkeep_alive\u001b[49m\n\u001b[32m    303\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m[\u001b[33m\"\u001b[39m\u001b[33membeddings\u001b[39m\u001b[33m\"\u001b[39m]\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/PycharmProjects/assistance-engine/.venv/lib/python3.11/site-packages/ollama/_client.py:393\u001b[39m, in \u001b[36mClient.embed\u001b[39m\u001b[34m(self, model, input, truncate, options, keep_alive, dimensions)\u001b[39m\n\u001b[32m    384\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34membed\u001b[39m(\n\u001b[32m    385\u001b[39m   \u001b[38;5;28mself\u001b[39m,\n\u001b[32m    386\u001b[39m   model: \u001b[38;5;28mstr\u001b[39m = \u001b[33m'\u001b[39m\u001b[33m'\u001b[39m,\n\u001b[32m   (...)\u001b[39m\u001b[32m    391\u001b[39m   dimensions: Optional[\u001b[38;5;28mint\u001b[39m] = \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[32m    392\u001b[39m ) -> EmbedResponse:\n\u001b[32m--> \u001b[39m\u001b[32m393\u001b[39m   \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m    394\u001b[39m \u001b[43m    \u001b[49m\u001b[43mEmbedResponse\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    395\u001b[39m \u001b[43m    \u001b[49m\u001b[33;43m'\u001b[39;49m\u001b[33;43mPOST\u001b[39;49m\u001b[33;43m'\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[32m    396\u001b[39m \u001b[43m    \u001b[49m\u001b[33;43m'\u001b[39;49m\u001b[33;43m/api/embed\u001b[39;49m\u001b[33;43m'\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[32m    397\u001b[39m \u001b[43m    \u001b[49m\u001b[43mjson\u001b[49m\u001b[43m=\u001b[49m\u001b[43mEmbedRequest\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m    398\u001b[39m \u001b[43m      \u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    399\u001b[39m \u001b[43m      \u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m=\u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[32m    400\u001b[39m \u001b[43m      \u001b[49m\u001b[43mtruncate\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtruncate\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    401\u001b[39m \u001b[43m      \u001b[49m\u001b[43moptions\u001b[49m\u001b[43m=\u001b[49m\u001b[43moptions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    402\u001b[39m \u001b[43m      \u001b[49m\u001b[43mkeep_alive\u001b[49m\u001b[43m=\u001b[49m\u001b[43mkeep_alive\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    403\u001b[39m \u001b[43m      \u001b[49m\u001b[43mdimensions\u001b[49m\u001b[43m=\u001b[49m\u001b[43mdimensions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    404\u001b[39m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\u001b[43m.\u001b[49m\u001b[43mmodel_dump\u001b[49m\u001b[43m(\u001b[49m\u001b[43mexclude_none\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    405\u001b[39m \u001b[43m  \u001b[49m\u001b[43m)\u001b[49m\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/PycharmProjects/assistance-engine/.venv/lib/python3.11/site-packages/ollama/_client.py:189\u001b[39m, in \u001b[36mClient._request\u001b[39m\u001b[34m(self, cls, stream, *args, **kwargs)\u001b[39m\n\u001b[32m    185\u001b[39m         \u001b[38;5;28;01myield\u001b[39;00m \u001b[38;5;28mcls\u001b[39m(**part)\n\u001b[32m    187\u001b[39m   \u001b[38;5;28;01mreturn\u001b[39;00m inner()\n\u001b[32m--> \u001b[39m\u001b[32m189\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mcls\u001b[39m(**\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_request_raw\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m.json())\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/PycharmProjects/assistance-engine/.venv/lib/python3.11/site-packages/ollama/_client.py:129\u001b[39m, in \u001b[36mClient._request_raw\u001b[39m\u001b[34m(self, *args, **kwargs)\u001b[39m\n\u001b[32m    127\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34m_request_raw\u001b[39m(\u001b[38;5;28mself\u001b[39m, *args, **kwargs):\n\u001b[32m    128\u001b[39m   \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m129\u001b[39m     r = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_client\u001b[49m\u001b[43m.\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    130\u001b[39m     r.raise_for_status()\n\u001b[32m    131\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m r\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/PycharmProjects/assistance-engine/.venv/lib/python3.11/site-packages/httpx/_client.py:825\u001b[39m, in \u001b[36mClient.request\u001b[39m\u001b[34m(self, method, url, content, data, files, json, params, headers, cookies, auth, follow_redirects, timeout, extensions)\u001b[39m\n\u001b[32m    810\u001b[39m     warnings.warn(message, \u001b[38;5;167;01mDeprecationWarning\u001b[39;00m, stacklevel=\u001b[32m2\u001b[39m)\n\u001b[32m    812\u001b[39m request = \u001b[38;5;28mself\u001b[39m.build_request(\n\u001b[32m    813\u001b[39m     method=method,\n\u001b[32m    814\u001b[39m     url=url,\n\u001b[32m   (...)\u001b[39m\u001b[32m    823\u001b[39m     extensions=extensions,\n\u001b[32m    824\u001b[39m )\n\u001b[32m--> \u001b[39m\u001b[32m825\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43msend\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mauth\u001b[49m\u001b[43m=\u001b[49m\u001b[43mauth\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfollow_redirects\u001b[49m\u001b[43m=\u001b[49m\u001b[43mfollow_redirects\u001b[49m\u001b[43m)\u001b[49m\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/PycharmProjects/assistance-engine/.venv/lib/python3.11/site-packages/httpx/_client.py:914\u001b[39m, in \u001b[36mClient.send\u001b[39m\u001b[34m(self, request, stream, auth, follow_redirects)\u001b[39m\n\u001b[32m    910\u001b[39m \u001b[38;5;28mself\u001b[39m._set_timeout(request)\n\u001b[32m    912\u001b[39m auth = \u001b[38;5;28mself\u001b[39m._build_request_auth(request, auth)\n\u001b[32m--> \u001b[39m\u001b[32m914\u001b[39m response = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_send_handling_auth\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m    915\u001b[39m \u001b[43m    \u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    916\u001b[39m \u001b[43m    \u001b[49m\u001b[43mauth\u001b[49m\u001b[43m=\u001b[49m\u001b[43mauth\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    917\u001b[39m \u001b[43m    \u001b[49m\u001b[43mfollow_redirects\u001b[49m\u001b[43m=\u001b[49m\u001b[43mfollow_redirects\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    918\u001b[39m \u001b[43m    \u001b[49m\u001b[43mhistory\u001b[49m\u001b[43m=\u001b[49m\u001b[43m[\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    919\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    920\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m    921\u001b[39m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m stream:\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/PycharmProjects/assistance-engine/.venv/lib/python3.11/site-packages/httpx/_client.py:942\u001b[39m, in \u001b[36mClient._send_handling_auth\u001b[39m\u001b[34m(self, request, auth, follow_redirects, history)\u001b[39m\n\u001b[32m    939\u001b[39m request = \u001b[38;5;28mnext\u001b[39m(auth_flow)\n\u001b[32m    941\u001b[39m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m942\u001b[39m     response = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_send_handling_redirects\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m    943\u001b[39m \u001b[43m        \u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    944\u001b[39m \u001b[43m        \u001b[49m\u001b[43mfollow_redirects\u001b[49m\u001b[43m=\u001b[49m\u001b[43mfollow_redirects\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    945\u001b[39m \u001b[43m        \u001b[49m\u001b[43mhistory\u001b[49m\u001b[43m=\u001b[49m\u001b[43mhistory\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    946\u001b[39m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    947\u001b[39m     \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m    948\u001b[39m         \u001b[38;5;28;01mtry\u001b[39;00m:\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/PycharmProjects/assistance-engine/.venv/lib/python3.11/site-packages/httpx/_client.py:979\u001b[39m, in \u001b[36mClient._send_handling_redirects\u001b[39m\u001b[34m(self, request, follow_redirects, history)\u001b[39m\n\u001b[32m    976\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m hook \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m._event_hooks[\u001b[33m\"\u001b[39m\u001b[33mrequest\u001b[39m\u001b[33m\"\u001b[39m]:\n\u001b[32m    977\u001b[39m     hook(request)\n\u001b[32m--> \u001b[39m\u001b[32m979\u001b[39m response = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_send_single_request\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    980\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m    981\u001b[39m     \u001b[38;5;28;01mfor\u001b[39;00m hook \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m._event_hooks[\u001b[33m\"\u001b[39m\u001b[33mresponse\u001b[39m\u001b[33m\"\u001b[39m]:\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/PycharmProjects/assistance-engine/.venv/lib/python3.11/site-packages/httpx/_client.py:1014\u001b[39m, in \u001b[36mClient._send_single_request\u001b[39m\u001b[34m(self, request)\u001b[39m\n\u001b[32m   1009\u001b[39m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[32m   1010\u001b[39m         \u001b[33m\"\u001b[39m\u001b[33mAttempted to send an async request with a sync Client instance.\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m   1011\u001b[39m     )\n\u001b[32m   1013\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m request_context(request=request):\n\u001b[32m-> \u001b[39m\u001b[32m1014\u001b[39m     response = \u001b[43mtransport\u001b[49m\u001b[43m.\u001b[49m\u001b[43mhandle_request\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m   1016\u001b[39m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(response.stream, SyncByteStream)\n\u001b[32m   1018\u001b[39m response.request = request\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/PycharmProjects/assistance-engine/.venv/lib/python3.11/site-packages/httpx/_transports/default.py:250\u001b[39m, in \u001b[36mHTTPTransport.handle_request\u001b[39m\u001b[34m(self, request)\u001b[39m\n\u001b[32m    237\u001b[39m req = httpcore.Request(\n\u001b[32m    238\u001b[39m     method=request.method,\n\u001b[32m    239\u001b[39m     url=httpcore.URL(\n\u001b[32m   (...)\u001b[39m\u001b[32m    247\u001b[39m     extensions=request.extensions,\n\u001b[32m    248\u001b[39m )\n\u001b[32m    249\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m map_httpcore_exceptions():\n\u001b[32m--> \u001b[39m\u001b[32m250\u001b[39m     resp = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_pool\u001b[49m\u001b[43m.\u001b[49m\u001b[43mhandle_request\u001b[49m\u001b[43m(\u001b[49m\u001b[43mreq\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    252\u001b[39m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(resp.stream, typing.Iterable)\n\u001b[32m    254\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m Response(\n\u001b[32m    255\u001b[39m     status_code=resp.status,\n\u001b[32m    256\u001b[39m     headers=resp.headers,\n\u001b[32m    257\u001b[39m     stream=ResponseStream(resp.stream),\n\u001b[32m    258\u001b[39m     extensions=resp.extensions,\n\u001b[32m    259\u001b[39m )\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/PycharmProjects/assistance-engine/.venv/lib/python3.11/site-packages/httpcore/_sync/connection_pool.py:256\u001b[39m, in \u001b[36mConnectionPool.handle_request\u001b[39m\u001b[34m(self, request)\u001b[39m\n\u001b[32m    253\u001b[39m         closing = \u001b[38;5;28mself\u001b[39m._assign_requests_to_connections()\n\u001b[32m    255\u001b[39m     \u001b[38;5;28mself\u001b[39m._close_connections(closing)\n\u001b[32m--> \u001b[39m\u001b[32m256\u001b[39m     \u001b[38;5;28;01mraise\u001b[39;00m exc \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[32m    258\u001b[39m \u001b[38;5;66;03m# Return the response. Note that in this case we still have to manage\u001b[39;00m\n\u001b[32m    259\u001b[39m \u001b[38;5;66;03m# the point at which the response is closed.\u001b[39;00m\n\u001b[32m    260\u001b[39m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(response.stream, typing.Iterable)\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/PycharmProjects/assistance-engine/.venv/lib/python3.11/site-packages/httpcore/_sync/connection_pool.py:236\u001b[39m, in \u001b[36mConnectionPool.handle_request\u001b[39m\u001b[34m(self, request)\u001b[39m\n\u001b[32m    232\u001b[39m connection = pool_request.wait_for_connection(timeout=timeout)\n\u001b[32m    234\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m    235\u001b[39m     \u001b[38;5;66;03m# Send the request on the assigned connection.\u001b[39;00m\n\u001b[32m--> \u001b[39m\u001b[32m236\u001b[39m     response = \u001b[43mconnection\u001b[49m\u001b[43m.\u001b[49m\u001b[43mhandle_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m    237\u001b[39m \u001b[43m        \u001b[49m\u001b[43mpool_request\u001b[49m\u001b[43m.\u001b[49m\u001b[43mrequest\u001b[49m\n\u001b[32m    238\u001b[39m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    239\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m ConnectionNotAvailable:\n\u001b[32m    240\u001b[39m     \u001b[38;5;66;03m# In some cases a connection may initially be available to\u001b[39;00m\n\u001b[32m    241\u001b[39m     \u001b[38;5;66;03m# handle a request, but then become unavailable.\u001b[39;00m\n\u001b[32m    242\u001b[39m     \u001b[38;5;66;03m#\u001b[39;00m\n\u001b[32m    243\u001b[39m     \u001b[38;5;66;03m# In this case we clear the connection and try again.\u001b[39;00m\n\u001b[32m    244\u001b[39m     pool_request.clear_connection()\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/PycharmProjects/assistance-engine/.venv/lib/python3.11/site-packages/httpcore/_sync/connection.py:103\u001b[39m, in \u001b[36mHTTPConnection.handle_request\u001b[39m\u001b[34m(self, request)\u001b[39m\n\u001b[32m    100\u001b[39m     \u001b[38;5;28mself\u001b[39m._connect_failed = \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[32m    101\u001b[39m     \u001b[38;5;28;01mraise\u001b[39;00m exc\n\u001b[32m--> \u001b[39m\u001b[32m103\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_connection\u001b[49m\u001b[43m.\u001b[49m\u001b[43mhandle_request\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m)\u001b[49m\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/PycharmProjects/assistance-engine/.venv/lib/python3.11/site-packages/httpcore/_sync/http11.py:136\u001b[39m, in \u001b[36mHTTP11Connection.handle_request\u001b[39m\u001b[34m(self, request)\u001b[39m\n\u001b[32m    134\u001b[39m     \u001b[38;5;28;01mwith\u001b[39;00m Trace(\u001b[33m\"\u001b[39m\u001b[33mresponse_closed\u001b[39m\u001b[33m\"\u001b[39m, logger, request) \u001b[38;5;28;01mas\u001b[39;00m trace:\n\u001b[32m    135\u001b[39m         \u001b[38;5;28mself\u001b[39m._response_closed()\n\u001b[32m--> \u001b[39m\u001b[32m136\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m exc\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/PycharmProjects/assistance-engine/.venv/lib/python3.11/site-packages/httpcore/_sync/http11.py:106\u001b[39m, in \u001b[36mHTTP11Connection.handle_request\u001b[39m\u001b[34m(self, request)\u001b[39m\n\u001b[32m     95\u001b[39m     \u001b[38;5;28;01mpass\u001b[39;00m\n\u001b[32m     97\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m Trace(\n\u001b[32m     98\u001b[39m     \u001b[33m\"\u001b[39m\u001b[33mreceive_response_headers\u001b[39m\u001b[33m\"\u001b[39m, logger, request, kwargs\n\u001b[32m     99\u001b[39m ) \u001b[38;5;28;01mas\u001b[39;00m trace:\n\u001b[32m    100\u001b[39m     (\n\u001b[32m    101\u001b[39m         http_version,\n\u001b[32m    102\u001b[39m         status,\n\u001b[32m    103\u001b[39m         reason_phrase,\n\u001b[32m    104\u001b[39m         headers,\n\u001b[32m    105\u001b[39m         trailing_data,\n\u001b[32m--> \u001b[39m\u001b[32m106\u001b[39m     ) = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_receive_response_headers\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    107\u001b[39m     trace.return_value = (\n\u001b[32m    108\u001b[39m         http_version,\n\u001b[32m    109\u001b[39m         status,\n\u001b[32m    110\u001b[39m         reason_phrase,\n\u001b[32m    111\u001b[39m         headers,\n\u001b[32m    112\u001b[39m     )\n\u001b[32m    114\u001b[39m network_stream = \u001b[38;5;28mself\u001b[39m._network_stream\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/PycharmProjects/assistance-engine/.venv/lib/python3.11/site-packages/httpcore/_sync/http11.py:177\u001b[39m, in \u001b[36mHTTP11Connection._receive_response_headers\u001b[39m\u001b[34m(self, request)\u001b[39m\n\u001b[32m    174\u001b[39m timeout = timeouts.get(\u001b[33m\"\u001b[39m\u001b[33mread\u001b[39m\u001b[33m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[32m    176\u001b[39m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m177\u001b[39m     event = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_receive_event\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtimeout\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtimeout\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    178\u001b[39m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(event, h11.Response):\n\u001b[32m    179\u001b[39m         \u001b[38;5;28;01mbreak\u001b[39;00m\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/PycharmProjects/assistance-engine/.venv/lib/python3.11/site-packages/httpcore/_sync/http11.py:217\u001b[39m, in \u001b[36mHTTP11Connection._receive_event\u001b[39m\u001b[34m(self, timeout)\u001b[39m\n\u001b[32m    214\u001b[39m     event = \u001b[38;5;28mself\u001b[39m._h11_state.next_event()\n\u001b[32m    216\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m event \u001b[38;5;129;01mis\u001b[39;00m h11.NEED_DATA:\n\u001b[32m--> \u001b[39m\u001b[32m217\u001b[39m     data = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_network_stream\u001b[49m\u001b[43m.\u001b[49m\u001b[43mread\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m    218\u001b[39m \u001b[43m        \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mREAD_NUM_BYTES\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtimeout\u001b[49m\n\u001b[32m    219\u001b[39m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    221\u001b[39m     \u001b[38;5;66;03m# If we feed this case through h11 we'll raise an exception like:\u001b[39;00m\n\u001b[32m    222\u001b[39m     \u001b[38;5;66;03m#\u001b[39;00m\n\u001b[32m    223\u001b[39m     \u001b[38;5;66;03m#     httpcore.RemoteProtocolError: can't handle event type\u001b[39;00m\n\u001b[32m   (...)\u001b[39m\u001b[32m    227\u001b[39m     \u001b[38;5;66;03m# perspective. Instead we handle this case distinctly and treat\u001b[39;00m\n\u001b[32m    228\u001b[39m     \u001b[38;5;66;03m# it as a ConnectError.\u001b[39;00m\n\u001b[32m    229\u001b[39m     \u001b[38;5;28;01mif\u001b[39;00m data == \u001b[33mb\u001b[39m\u001b[33m\"\u001b[39m\u001b[33m\"\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m._h11_state.their_state == h11.SEND_RESPONSE:\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/PycharmProjects/assistance-engine/.venv/lib/python3.11/site-packages/httpcore/_backends/sync.py:128\u001b[39m, in \u001b[36mSyncStream.read\u001b[39m\u001b[34m(self, max_bytes, timeout)\u001b[39m\n\u001b[32m    126\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m map_exceptions(exc_map):\n\u001b[32m    127\u001b[39m     \u001b[38;5;28mself\u001b[39m._sock.settimeout(timeout)\n\u001b[32m--> \u001b[39m\u001b[32m128\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_sock\u001b[49m\u001b[43m.\u001b[49m\u001b[43mrecv\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmax_bytes\u001b[49m\u001b[43m)\u001b[49m\n",
-      "\u001b[31mKeyboardInterrupt\u001b[39m: "
-     ]
-    }
-   ],
-   "source": [
-    "encoder = OllamaLangChainEncoder(lc_embeddings=embeddings, normalize=True)\n",
-    "search_model = SearchEncoderWrapper(encoder)\n",
-    "\n",
-    "tasks = mteb.get_tasks([\n",
-    "    \"CodeSearchNetRetrieval\",\n",
-    "    \"CodeSearchNetCCRetrieval\",\n",
-    "    \"AppsRetrieval\",\n",
-    "    \"StackOverflowDupQuestions\",\n",
-    "])\n",
-    "results = mteb.evaluate(\n",
-    "    model=search_model,\n",
-    "    tasks=tasks,\n",
-    "    encode_kwargs={\"batch_size\": 32, \"show_progress_bar\": True}\n",
-    ")\n",
-    "\n",
-    "print(results)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "b2c5d9f6",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "ModelResult(model_name=no_model_name/available, model_revision=no_revision_available, task_results=[...](#1))"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "results"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "id": "7364562f",
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "AttributeError",
-     "evalue": "'list' object has no attribute 'scores'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
-      "\u001b[31mAttributeError\u001b[39m                            Traceback (most recent call last)",
-      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[10]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m \u001b[43mresults\u001b[49m\u001b[43m.\u001b[49m\u001b[43mtask_results\u001b[49m\u001b[43m.\u001b[49m\u001b[43mscores\u001b[49m\n",
-      "\u001b[31mAttributeError\u001b[39m: 'list' object has no attribute 'scores'"
-     ]
-    }
-   ],
-   "source": [
-    "results.task_results.scores"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a657676e",
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {