correct input value names

chains/distractors/runner.py

@@ -30,7 +30,7 @@ async def run_distractors(
     # Fetch the DistractorsChain configuration.
     config = chain_configs["distractors"]
 
-    # 1) Standardize the user query exactly once
+    # 1) Standardize the user query once for all tracks
     standardized_exercise = await standardize_exercise(
         user_query,
         exercise_format_distractors,

chains/exercises/fluster_writing_chain.py

@@ -15,7 +15,7 @@ class FlusterWritingChain(BaseModel):
     default_llm_a: Any
     default_llm_b: Any
 
-    template_refine_distractors: ChatPromptTemplate
+    template_refine_fluster: ChatPromptTemplate
     llm_refine: Any
 
     template_sanitize_fluster: ChatPromptTemplate

chains/exercises/runner.py

@@ -27,7 +27,7 @@ async def run_fluster(
     llm_a = llms.get(model_choice_1, config["default_llm_a"])
     llm_b = llms.get(model_choice_2, config["default_llm_b"])
 
-    template_refine = config["template_refine_distractors"]
+    template_refine = config["template_refine_fluster"]
     llm_refine = config["llm_refine"]
 
     template_sanitize = config["template_sanitize"]
@@ -60,17 +60,17 @@ async def run_fluster(
             gen_llm = llm_b
 
         # 1) Generate
-        gen_msg = await gen_template.aformat_prompt(user_input=user_input_text)
+        gen_msg = await gen_template.aformat_prompt(learning_objective=user_input_text)
         gen_resp = await gen_llm.ainvoke(gen_msg.to_messages())
         write_fluster_result = getattr(gen_resp, "content", gen_resp)
 
         # 2) Refine distractors
-        refine_msg = await template_refine.aformat_prompt(raw_exercise=write_fluster_result)
+        refine_msg = await template_refine.aformat_prompt(write_fluster_result=write_fluster_result)
         refine_resp = await llm_refine.ainvoke(refine_msg.to_messages())
         refined_output = getattr(refine_resp, "content", refine_resp)
 
         # 3) Sanitize
-        sanitize_msg = await template_sanitize.aformat_prompt(raw_output=refined_output)
+        sanitize_msg = await template_sanitize.aformat_prompt(refinement_result=refined_output)
         sanitize_resp = await llm_sanitize.ainvoke(sanitize_msg.to_messages())
         sanitized_output = getattr(sanitize_resp, "content", sanitize_resp)
 

config/chain_configs.py

@@ -15,7 +15,7 @@ from config.templates import (
     template_sanitize_learning_objectives,
     template_write_fluster_a,
     template_write_fluster_b,
-    template_refine_distractors,
+    template_refine_fluster,
     template_sanitize_fluster,
 )
 from chains.diagnoser.diagnoser_chain import DiagnoserChain
@@ -72,7 +72,7 @@ chain_configs = {
         "default_llm_a": llms["o1 (high reasoning_effort)"],
         "default_llm_b": llms["o3-mini (high reasoning_effort)"],
         # Prompt & LLM for the refine-distractors step
-        "template_refine_distractors": template_refine_distractors,
+        "template_refine_fluster": template_refine_fluster,
         "llm_refine": llms["o1 (high reasoning_effort)"],
         "template_sanitize": template_sanitize_fluster,
         "llm_sanitize": "GPT-4o-mini (zero temp)",

config/system_prompt_texts.py

@@ -775,7 +775,7 @@ Be precise. Shun absolute terms like 'never' or 'always', as they imply complete
 """
 
 
-template_refine_distractors_text = """
+template_refine_fluster_text = """
 Given some source data containing exercises, critically analyze this with the goal of refining and improving the exercises. 
 Play devil's advocate here: in what ways is this version of the exercises not perfect? Do some reasoning about this, and then give the improved exercises. If you didn't find anything to improve, just return the exercises as they are.
 """

config/templates.py

@@ -17,7 +17,7 @@ from config.system_prompt_texts import (
     template_sanitize_learning_objectives_text,
     template_write_fluster_a_text,
     template_write_fluster_b_text,
-    template_refine_distractors_text,
+    template_refine_fluster_text,
     template_sanitize_fluster_text,
 )
 
@@ -230,9 +230,9 @@ template_write_fluster_b = ChatPromptTemplate(
 )
 
 
-template_refine_distractors = ChatPromptTemplate(
+template_refine_fluster = ChatPromptTemplate(
     messages=[
-        ("system", template_refine_distractors_text),
+        ("system", template_refine_fluster_text),
         ("human", "Here's the source data:\n"
                   "{write_fluster_result}")
     ],