diff --git a/dummy-evaluation.py b/dummy-evaluation.py
index 318b80d..53ec812 100644
--- a/dummy-evaluation.py
+++ b/dummy-evaluation.py
@@ -3,7 +3,12 @@
 import plotly.graph_objects as go
 import plotly.io as pio
 
-metrics = {"answer_relevancy", "answer_correctness", "context_precision", "context_recall"}
+metrics = {
+    "answer_relevancy",
+    "answer_correctness",
+    "context_precision",
+    "context_recall",
+}
 dummy_data = {metric: np.random.rand(100) for metric in metrics}
 df = pd.DataFrame(dummy_data)
 
@@ -13,8 +18,20 @@
 
 pio.templates.default = "gridon"
 fig = go.Figure()
-metrics = [metric for metric in df.columns.to_list() if metric not in ["question", "ground_truth", "answer", "contexts"]]
+metrics = [
+    metric
+    for metric in df.columns.to_list()
+    if metric not in ["question", "ground_truth", "answer", "contexts"]
+]
 for metric in metrics:
-    fig.add_trace(go.Violin(y=df[metric], name=metric, points="all", box_visible=True, meanline_visible=True))
-fig.update_yaxes(range=[-0.02,1.02])
+    fig.add_trace(
+        go.Violin(
+            y=df[metric],
+            name=metric,
+            points="all",
+            box_visible=True,
+            meanline_visible=True,
+        )
+    )
+fig.update_yaxes(range=[-0.02, 1.02])
 fig.write_image("metrics.png")
diff --git a/notebooks/ragas_eval.ipynb b/notebooks/ragas_eval.ipynb
index 53d862b..56bcb43 100644
--- a/notebooks/ragas_eval.ipynb
+++ b/notebooks/ragas_eval.ipynb
@@ -54,7 +54,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "nest_asyncio.apply() # apply the event loop async fix"
+    "nest_asyncio.apply()  # apply the event loop async fix"
    ]
   },
   {
@@ -70,7 +70,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df = pd.read_csv(\"../data/evaluation-sets/eidc-eval-sample.csv\", converters={\"contexts\": pd.eval})\n",
+    "df = pd.read_csv(\n",
+    "    \"../data/evaluation-sets/eidc-eval-sample.csv\", converters={\"contexts\": pd.eval}\n",
+    ")\n",
     "eval_dataset = Dataset.from_pandas(df)"
    ]
   },
@@ -235,8 +237,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "llm = ChatOllama(model='mistral-nemo', num_ctx=16384)\n",
-    "embeddings = OllamaEmbeddings(model='mistral-nemo', num_ctx=16384)"
+    "llm = ChatOllama(model=\"mistral-nemo\", num_ctx=16384)\n",
+    "embeddings = OllamaEmbeddings(model=\"mistral-nemo\", num_ctx=16384)"
    ]
   },
   {
@@ -316,10 +318,22 @@
     "result_df = result.to_pandas()\n",
     "pio.templates.default = \"gridon\"\n",
     "fig = go.Figure()\n",
-    "metrics = [metric for metric in result_df.columns.to_list() if metric not in [\"question\", \"ground_truth\", \"answer\", \"contexts\"]]\n",
+    "metrics = [\n",
+    "    metric\n",
+    "    for metric in result_df.columns.to_list()\n",
+    "    if metric not in [\"question\", \"ground_truth\", \"answer\", \"contexts\"]\n",
+    "]\n",
     "for metric in metrics:\n",
-    "    fig.add_trace(go.Violin(y=result_df[metric], name=metric, points=\"all\", box_visible=True, meanline_visible=True))\n",
-    "fig.update_yaxes(range=[-0.02,1.02])\n",
+    "    fig.add_trace(\n",
+    "        go.Violin(\n",
+    "            y=result_df[metric],\n",
+    "            name=metric,\n",
+    "            points=\"all\",\n",
+    "            box_visible=True,\n",
+    "            meanline_visible=True,\n",
+    "        )\n",
+    "    )\n",
+    "fig.update_yaxes(range=[-0.02, 1.02])\n",
     "with open(\"eval.png\", \"wb\") as f:\n",
     "    f.write(fig.to_image(format=\"png\"))"
    ]
@@ -331,6 +345,7 @@
    "outputs": [],
    "source": [
     "import json\n",
+    "\n",
     "with open(\"metrics.json\", \"w\") as f:\n",
     "    json.dump(result, f)"
    ]
diff --git a/notebooks/ragas_synth.ipynb b/notebooks/ragas_synth.ipynb
index b0c4371..cf39b04 100644
--- a/notebooks/ragas_synth.ipynb
+++ b/notebooks/ragas_synth.ipynb
@@ -19,8 +19,6 @@
     "from ragas.testset.generator import TestsetGenerator\n",
     "from ragas.testset.evolutions import simple, reasoning, multi_context\n",
     "from ragas.run_config import RunConfig\n",
-    "from langchain.docstore.document import Document\n",
-    "import pandas as pd\n",
     "import nest_asyncio"
    ]
   },
@@ -30,7 +28,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "nest_asyncio.apply() # apply the event loop async fix"
+    "nest_asyncio.apply()  # apply the event loop async fix"
    ]
   },
   {
@@ -46,9 +44,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "llm = ChatOllama(model='mistral-nemo', num_ctx=16384)\n",
-    "embeddings = OllamaEmbeddings(model='mistral-nemo', num_ctx=16384)\n",
-    "gen = TestsetGenerator.from_langchain(llm, llm, embeddings, run_config=RunConfig(max_workers=1, max_retries=1))\n",
+    "llm = ChatOllama(model=\"mistral-nemo\", num_ctx=16384)\n",
+    "embeddings = OllamaEmbeddings(model=\"mistral-nemo\", num_ctx=16384)\n",
+    "gen = TestsetGenerator.from_langchain(\n",
+    "    llm, llm, embeddings, run_config=RunConfig(max_workers=1, max_retries=1)\n",
+    ")\n",
     "dist = {simple: 0.6, multi_context: 0.2, reasoning: 0.2}"
    ]
   },
@@ -65,7 +65,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "docs = [] # load a set of langchain documents to base the synthetic test set generation on"
+    "docs = []  # load a set of langchain documents to base the synthetic test set generation on"
    ]
   },
   {
@@ -81,7 +81,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "\n",
     "testset = gen.generate_with_langchain_docs(docs, 5, dist, is_async=False)"
    ]
   },
diff --git a/notebooks/vllm_test.ipynb b/notebooks/vllm_test.ipynb
index 755c34c..86701c7 100644
--- a/notebooks/vllm_test.ipynb
+++ b/notebooks/vllm_test.ipynb
@@ -15,9 +15,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "prompts = [\n",
-    "    \"Tell me a joke.\"\n",
-    "]\n",
+    "prompts = [\"Tell me a joke.\"]\n",
     "params = SamplingParams(temperature=0.8, top_p=0.95, max_tokens=1024)"
    ]
   },
@@ -26,9 +24,7 @@
    "execution_count": 3,
    "metadata": {},
    "outputs": [],
-   "source": [
-    "import os"
-   ]
+   "source": []
   },
   {
    "cell_type": "code",
@@ -87,7 +83,12 @@
     }
    ],
    "source": [
-    "llm = LLM(model=\"unsloth/Mistral-Nemo-Instruct-2407-bnb-4bit\", quantization=\"bitsandbytes\", load_format=\"bitsandbytes\", max_model_len=4096)"
+    "llm = LLM(\n",
+    "    model=\"unsloth/Mistral-Nemo-Instruct-2407-bnb-4bit\",\n",
+    "    quantization=\"bitsandbytes\",\n",
+    "    load_format=\"bitsandbytes\",\n",
+    "    max_model_len=4096,\n",
+    ")"
    ]
   },
   {