Make testgenerator output compatible with evaluate (#302)

* Changed context from str to List[str] so that it is consistent with
eval. Now output of TestDataset can be used for evaluation.
*  Changed typo in _generate_doc_nodes_map
* Changed TestDataset class to reflect the changes in test set
generation. Drawback is episode_done will be True in all cases as data
is changed at the level above.

Author: tinomaxthayil

src/ragas/testset/testset_generator.py

@@ -57,7 +57,7 @@
     "conditional": "_condition_question",
 }
 
-DataRow = namedtuple("DataRow", ["question", "context", "answer", "question_type"])
+DataRow = namedtuple("DataRow", ["question", "ground_truth_context", "ground_truth", "question_type", "episode_done"])
 
 
 @dataclass
@@ -71,21 +71,14 @@ class TestDataset:
     def to_pandas(self) -> pd.DataFrame:
         data_samples = []
         for data in self.test_data:
-            is_conv = len(data.context) > 1
-            question_type = data.question_type
-            data = [
-                {
-                    "question": qstn,
-                    "context": ctx,
-                    "answer": ans,
-                    "question_type": question_type,
-                    "episode_done": True,
-                }
-                for qstn, ctx, ans in zip(data.question, data.context, data.answer)
-            ]
-            if is_conv:
-                data[0].update({"episode_done": False})
-            data_samples.extend(data)
+            data = {
+                    "question": data.question,
+                    "ground_truth_context": data.ground_truth_context,
+                    "ground_truth": data.ground_truth,
+                    "question_type": data.question_type,
+                    "episode_done": data.episode_done,
+            }
+            data_samples.append(data)
 
         return pd.DataFrame.from_records(data_samples)
 
@@ -260,10 +253,10 @@ def _remove_nodes(
         return available_indices
 
     def _generate_doc_nodes_map(
-        self, documenet_nodes: t.List[BaseNode]
+        self, document_nodes: t.List[BaseNode]
     ) -> t.Dict[str, t.List[BaseNode]]:
         doc_nodes_map: t.Dict[str, t.List[BaseNode]] = defaultdict(list)
-        for node in documenet_nodes:
+        for node in document_nodes:
             if node.ref_doc_id:
                 doc_nodes_map[node.ref_doc_id].append(node)
 
@@ -398,10 +391,13 @@ def generate(
             is_valid_question = self._filter_question(question)
             if is_valid_question:
                 context = self._generate_context(question, text_chunk)
+                is_conv = len(context) > 1
                 answer = self._generate_answer(question, context)
-                samples.append(
-                    DataRow(question.split("\n"), context, answer, evolve_type)
-                )
+                for i, (qstn, ctx, ans) in enumerate(zip(question.split("\n"), context, answer)):
+                    episode_done = False if is_conv and i==0 else True
+                    samples.append(
+                            DataRow(qstn, [ctx], [ans], evolve_type, episode_done)
+                        )
                 count += 1
                 pbar.update(count)