file is a simple, text-based file format for storing tabular data.[3] Records are separated by newlines, and values within a record are separated by tab characters.UnstructuredTSVLoader‚ÄãYou can also load the table using the UnstructuredTSVLoader. One advantage of using UnstructuredTSVLoader is that if you use it in "elements" mode, an HTML representation of the table will be available in the metadata.from langchain.document_loaders.tsv import UnstructuredTSVLoaderloader = UnstructuredTSVLoader(    file_path="example_data/mlb_teams_2012.csv", mode="elements")docs = loader.load()print(docs[0].metadata["text_as_html"])    <table border="1" class="dataframe">      <tbody>        <tr>          <td>Nationals,     81.34, 98</td>        </tr>        <tr>          <td>Reds,          82.20, 97</td>        </tr>        <tr>          <td>Yankees,      197.96, 95</td>        </tr>        <tr>          <td>Giants,       117.62, 94</td>        </tr>        <tr>          <td>Braves,        83.31, 94</td>        </tr>        <tr>          <td>Athletics,     55.37, 94</td>        </tr>        <tr>          <td>Rangers,      120.51, 93</td>        </tr>        <tr>          <td>Orioles,       81.43, 93</td>        </tr>        <tr>          <td>Rays,          64.17, 90</td>        </tr>        <tr>          <td>Angels,       154.49, 89</td>        </tr>        <tr>          <td>Tigers,       132.30, 88</td>        </tr>        <tr>          <td>Cardinals,    110.30, 88</td>        </tr>        <tr>          <td>Dodgers,       95.14, 86</td>        </tr>        <tr>          <td>White Sox,     96.92, 85</td>        </tr>        <tr>          <td>Brewers,       97.65, 83</td>        </tr>        <tr>          <td>Phillies,     174.54, 81</td>        </tr>        <tr>          <td>Diamondbacks,  74.28, 81</td>        </tr>        <tr>          <td>Pirates,       63.43, 79</td>        </tr>        <tr>          <td>Padres,        55.24, 76</td>        </tr>        <tr>
A tab-separated values (TSV) file is a simple, text-based file format for storing tabular data.[3] Records are separated by newlines, and values within a record are separated by tab characters.
A tab-separated values (TSV) file is a simple, text-based file format for storing tabular data.[3] Records are separated by newlines, and values within a record are separated by tab characters. ->: file is a simple, text-based file format for storing tabular data.[3] Records are separated by newlines, and values within a record are separated by tab characters.UnstructuredTSVLoader‚ÄãYou can also load the table using the UnstructuredTSVLoader. One advantage of using UnstructuredTSVLoader is that if you use it in "elements" mode, an HTML representation of the table will be available in the metadata.from langchain.document_loaders.tsv import UnstructuredTSVLoaderloader = UnstructuredTSVLoader(    file_path="example_data/mlb_teams_2012.csv", mode="elements")docs = loader.load()print(docs[0].metadata["text_as_html"])    <table border="1" class="dataframe">      <tbody>        <tr>          <td>Nationals,     81.34, 98</td>        </tr>        <tr>          <td>Reds,          82.20, 97</td>        </tr>        <tr>          <td>Yankees,      197.96, 95</td>        </tr>        <tr>          <td>Giants,       117.62, 94</td>        </tr>        <tr>          <td>Braves,        83.31, 94</td>        </tr>        <tr>          <td>Athletics,     55.37, 94</td>        </tr>        <tr>          <td>Rangers,      120.51, 93</td>        </tr>        <tr>          <td>Orioles,       81.43, 93</td>        </tr>        <tr>          <td>Rays,          64.17, 90</td>        </tr>        <tr>          <td>Angels,       154.49, 89</td>        </tr>        <tr>          <td>Tigers,       132.30, 88</td>        </tr>        <tr>          <td>Cardinals,    110.30, 88</td>        </tr>        <tr>          <td>Dodgers,       95.14, 86</td>        </tr>        <tr>          <td>White Sox,     96.92, 85</td>        </tr>        <tr>          <td>Brewers,       97.65, 83</td>        </tr>        <tr>          <td>Phillies,     174.54, 81</td>        </tr>        <tr>          <td>Diamondbacks,  74.28, 81</td>        </tr>        <tr>          <td>Pirates,       63.43, 79</td>        </tr>        <tr>          <td>Padres,        55.24, 76</td>        </tr>        <tr>