Create a sample per seed example for skills

The full skills pipelines expect a single seed question and response
in each sample in the dataset. Change the simple skills pipelines to
match and update the code to generate the samples in the expected
format.

Closes #55 (the short term needs at least)

Signed-off-by: Russell Bryant <[email protected]>

src/instructlab/sdg/configs/skills/simple_generate_qa_freeform.yaml

@@ -15,16 +15,10 @@ Here are the requirements:
 examples: |
   The task is {task_description}.
 
-  Here are some examples to help you understand the type of questions that are asked for:
+  Here is an example to help you understand the type of questions that are asked for:
 
-  {icl_query_1}
-  {icl_response_1}
-
-  {icl_query_2}
-  {icl_response_2}
-
-  {icl_query_3}
-  {icl_response_3}
+  {seed_question}
+  {seed_response}
 
 generation: |
   Provide a single question and answer pair based on the examples.

src/instructlab/sdg/configs/skills/simple_generate_qa_grounded.yaml

@@ -15,23 +15,17 @@ Here are the requirements:
 examples: |
   The task is {task_description}.
 
-  Here is some context for the example questions:
+  Here is some context for the example question:
 
-  {context}
+  {seed_context}
 
-  Here are some examples to help you understand the type of questions that are asked for:
+  Here is an example to help you understand the type of questions that are asked for:
 
-  {icl_query_1}
-  {icl_response_1}
-
-  {icl_query_2}
-  {icl_response_2}
-
-  {icl_query_3}
-  {icl_response_3}
+  {seed_question}
+  {seed_response}
 
 generation: |
-  Provide a single question and answer pair based on the examples.
+  Provide a single question and answer pair based on the example.
 
 start_tags: [""]
 end_tags: [""]

src/instructlab/sdg/utils/taxonomy.py

@@ -472,43 +472,24 @@ def _knowledge_leaf_node_to_samples(leaf_node, server_ctx_size, chunk_word_count
 
 
 def _skill_leaf_node_to_samples(leaf_node):
-    samples = [{}]
+    samples = []
 
     # pylint: disable=consider-using-enumerate
     for i in range(len(leaf_node)):
-        samples[-1].setdefault("task_description", leaf_node[i]["task_description"])
+        samples.append({})
+        samples[-1]["task_description"] = leaf_node[i]["task_description"]
         if leaf_node[i].get("input"):
-            samples[-1].setdefault("context", leaf_node[i]["input"])
-        if "icl_query_3" in samples[-1]:
-            samples.append({})
-        if "icl_query_1" not in samples[-1]:
-            samples[-1]["icl_query_1"] = leaf_node[i]["instruction"]
-            samples[-1]["icl_response_1"] = leaf_node[i]["output"]
-        elif "icl_query_2" not in samples[-1]:
-            samples[-1]["icl_query_2"] = leaf_node[i]["instruction"]
-            samples[-1]["icl_response_2"] = leaf_node[i]["output"]
-        else:
-            samples[-1]["icl_query_3"] = leaf_node[i]["instruction"]
-            samples[-1]["icl_response_3"] = leaf_node[i]["output"]
-
-    # wrap back around to the beginning if the number of examples was not
-    # evenly divisble by 3
-    if "icl_query_2" not in samples[-1]:
-        samples[-1]["icl_query_2"] = leaf_node[0]["instruction"]
-        samples[-1]["icl_response_2"] = leaf_node[0]["output"]
-    if "icl_query_3" not in samples[-1]:
-        samples[-1]["icl_query_3"] = leaf_node[1 if len(leaf_node) > 1 else 0][
-            "instruction"
-        ]
-        samples[-1]["icl_response_3"] = leaf_node[1 if len(leaf_node) > 1 else 0]["output"]
+            samples[-1]["seed_context"] = leaf_node[i]["input"]
+        samples[-1]["seed_question"] = leaf_node[i]["instruction"]
+        samples[-1]["seed_response"] = leaf_node[i]["output"]
 
     return samples
 
 
 def leaf_node_to_samples(leaf_node, server_ctx_size, chunk_word_count):
     if not leaf_node:
         return []
-    if "document" in leaf_node[0]:
+    if leaf_node[0].get("document"):
         return _knowledge_leaf_node_to_samples(
             leaf_node, server_ctx_size, chunk_word_count
         )