From ace0fb59134beb2ffa16942cc58f21cd7394cbf8 Mon Sep 17 00:00:00 2001
From: Soumik Rakshit <19soumik.rakshit96@gmail.com>
Date: Mon, 19 Aug 2024 03:03:44 +0000
Subject: [PATCH] fix: lint

---
 docs/notebooks/parse_arxiv_papers.ipynb | 26 +++++++++++++++----------
 1 file changed, 16 insertions(+), 10 deletions(-)

diff --git a/docs/notebooks/parse_arxiv_papers.ipynb b/docs/notebooks/parse_arxiv_papers.ipynb
index 310b2880352..e7192abcf44 100644
--- a/docs/notebooks/parse_arxiv_papers.ipynb
+++ b/docs/notebooks/parse_arxiv_papers.ipynb
@@ -110,9 +110,10 @@
    },
    "outputs": [],
    "source": [
-    "from pydantic import BaseModel\n",
     "from typing import List, Optional\n",
     "\n",
+    "from pydantic import BaseModel\n",
+    "\n",
     "\n",
     "class Finding(BaseModel):\n",
     "    finding_name: str\n",
@@ -133,14 +134,20 @@
     "\n",
     "\n",
     "class PaperInfo(BaseModel):\n",
-    "    main_findings: List[Finding] # The main findings of the paper\n",
+    "    main_findings: List[Finding]  # The main findings of the paper\n",
     "    novel_methods: List[Method]  # The novel methods proposed in the paper\n",
-    "    existing_methods: List[Method] # The existing methods used in the paper\n",
-    "    machine_learning_techniques: List[Method] # The machine learning techniques used in the paper\n",
-    "    metrics: List[Evaluation] # The evaluation metrics used in the paper\n",
-    "    github_repository: str # The link to the GitHub repository of the paper (if there is any)\n",
-    "    hardware: str # The hardware or accelerator setup used in the paper\n",
-    "    further_research: List[str] # The further research directions suggested in the paper"
+    "    existing_methods: List[Method]  # The existing methods used in the paper\n",
+    "    machine_learning_techniques: List[\n",
+    "        Method\n",
+    "    ]  # The machine learning techniques used in the paper\n",
+    "    metrics: List[Evaluation]  # The evaluation metrics used in the paper\n",
+    "    github_repository: (\n",
+    "        str  # The link to the GitHub repository of the paper (if there is any)\n",
+    "    )\n",
+    "    hardware: str  # The hardware or accelerator setup used in the paper\n",
+    "    further_research: List[\n",
+    "        str\n",
+    "    ]  # The further research directions suggested in the paper"
    ]
   },
   {
@@ -204,7 +211,6 @@
     "import instructor\n",
     "from openai import OpenAI\n",
     "\n",
-    "\n",
     "openai_client = OpenAI()\n",
     "structured_client = instructor.from_openai(openai_client)"
    ]
@@ -224,11 +230,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import requests\n",
     "from io import BytesIO\n",
     "\n",
     "import pymupdf\n",
     "import pymupdf4llm\n",
+    "import requests\n",
     "\n",
     "\n",
     "class ArxivModel(weave.Model):\n",