Include LLM into the API docs

docs/requirements.txt

@@ -4,4 +4,5 @@ sphinx_rtd_theme
 ipython
 pandas
 Pillow
+openai
 -r ../requirements.txt

docs/source/autodocs/index.rst

@@ -16,6 +16,7 @@ API documentation is auto-generated.
    ./lightgbm
    ./catboost
    ./permutation_importance
+   ./llm
    ./keras
    ./base
 

docs/source/autodocs/llm.rst

@@ -0,0 +1,5 @@
+eli5.llm
+========
+
+.. automodule:: eli5.llm.explain_prediction
+    :members:

docs/source/tutorials/index.rst

@@ -10,4 +10,5 @@ Tutorials
    ./black-box-text-classifiers
    ./xgboost-titanic
    ./sklearn_crfsuite
-   ./keras-image-classifiers
+   ./explain_llm_logprobs
+   ./keras-image-classifiers

tests/conftest.py

@@ -1,4 +1,3 @@
-# -*- coding: utf-8 -*-
 from os.path import dirname
 from os.path import join
 import csv
@@ -27,7 +26,7 @@ def _get_newsgroups(binary=False, remove_chrome=False, test=False, size=SIZE):
     subset = 'test' if test else 'train'
     data = fetch_20newsgroups(subset=subset, categories=categories,
                               shuffle=True, random_state=42,
-                              remove=remove)
+                              remove=remove, n_retries=5, delay=5.0)
     assert data.target_names == categories
     return data.data[:size], data.target[:size], data.target_names
 
@@ -51,6 +50,7 @@ def newsgroups_train_big():
 def newsgroups_train_binary_big():
     return _get_newsgroups(binary=True, remove_chrome=True, size=1000)
 
+
 class Bunch(dict):
     """Container object for datasets: dictionary-like object that
        exposes its keys as attributes."""