the test results tracing UI below by clicking the URL in the output above or navigating to the "Testing & Datasets" page in LangSmith  "agent-qa-{unique_id}" dataset. This will show the new runs and the feedback logged from the selected evaluators. You can also explore a summary of the results in tabular format below.chain_results.to_dataframe()<div><style scoped>    .dataframe tbody tr th:only-of-type {        vertical-align: middle;    }    .dataframe tbody tr th {        vertical-align: top;    }    .dataframe thead th {        text-align: right;    }</style><table border="1" class="dataframe">  <thead>    <tr style="text-align: right;">      <th></th>      <th>embedding_cosine_distance</th>      <th>correctness</th>      <th>score_string:accuracy</th>      <th>helpfulness</th>      <th>input</th>      <th>output</th>      <th>reference</th>    </tr>  </thead>  <tbody>    <tr>      <th>42b639a2-17c4-4031-88a9-0ce2c45781ce</th>      <td>0.317938</td>      <td>0.0</td>      <td>1.0</td>      <td>1.0</td>      <td>{'input': 'What is the langsmith cookbook?'}</td>      <td>{'input': 'What is the langsmith cookbook?', '...</td>      <td>{'output': 'September 5, 2023'}</td>    </tr>    <tr>      <th>54b4fce8-4492-409d-94af-708f51698b39</th>      <td>NaN</td>      <td>NaN</td>      <td>NaN</td>      <td>NaN</td>      <td>{'input': 'Who trained Llama-v2?'}</td>      <td>{'Error': 'TypeError("DuckDuckGoSearchResults....</td>      <td>{'output': 'The langsmith cookbook is a github...</td>    </tr>    <tr>      <th>8ae5104e-bbb4-42cc-a84e-f9b8cfc92b8e</th>      <td>0.138916</td>      <td>1.0</td>      <td>1.0</td>      <td>1.0</td>      <td>{'input': 'When was Llama-v2 released?'}</td>      <td>{'input': 'When was Llama-v2 released?', 'outp...</td>      <td>{'output': 'July 18, 2023'}</td>    </tr>    <tr>      <th>678c0363-3ed1-410a-811f-ebadef2e783a</th>      <td>0.050158</td>      <td>1.0</td>      <td>1.0</td>      <td>1.0</td>      <td>{'input': 'What's
Open In Colab
Open In Colab ->: the test results tracing UI below by clicking the URL in the output above or navigating to the "Testing & Datasets" page in LangSmith  "agent-qa-{unique_id}" dataset. This will show the new runs and the feedback logged from the selected evaluators. You can also explore a summary of the results in tabular format below.chain_results.to_dataframe()<div><style scoped>    .dataframe tbody tr th:only-of-type {        vertical-align: middle;    }    .dataframe tbody tr th {        vertical-align: top;    }    .dataframe thead th {        text-align: right;    }</style><table border="1" class="dataframe">  <thead>    <tr style="text-align: right;">      <th></th>      <th>embedding_cosine_distance</th>      <th>correctness</th>      <th>score_string:accuracy</th>      <th>helpfulness</th>      <th>input</th>      <th>output</th>      <th>reference</th>    </tr>  </thead>  <tbody>    <tr>      <th>42b639a2-17c4-4031-88a9-0ce2c45781ce</th>      <td>0.317938</td>      <td>0.0</td>      <td>1.0</td>      <td>1.0</td>      <td>{'input': 'What is the langsmith cookbook?'}</td>      <td>{'input': 'What is the langsmith cookbook?', '...</td>      <td>{'output': 'September 5, 2023'}</td>    </tr>    <tr>      <th>54b4fce8-4492-409d-94af-708f51698b39</th>      <td>NaN</td>      <td>NaN</td>      <td>NaN</td>      <td>NaN</td>      <td>{'input': 'Who trained Llama-v2?'}</td>      <td>{'Error': 'TypeError("DuckDuckGoSearchResults....</td>      <td>{'output': 'The langsmith cookbook is a github...</td>    </tr>    <tr>      <th>8ae5104e-bbb4-42cc-a84e-f9b8cfc92b8e</th>      <td>0.138916</td>      <td>1.0</td>      <td>1.0</td>      <td>1.0</td>      <td>{'input': 'When was Llama-v2 released?'}</td>      <td>{'input': 'When was Llama-v2 released?', 'outp...</td>      <td>{'output': 'July 18, 2023'}</td>    </tr>    <tr>      <th>678c0363-3ed1-410a-811f-ebadef2e783a</th>      <td>0.050158</td>      <td>1.0</td>      <td>1.0</td>      <td>1.0</td>      <td>{'input': 'What's