store feedback quickly

athena/athena/endpoints.py

@@ -235,7 +235,7 @@ def feedback_consumer(func: Union[
     feedback_type = inspect.signature(func).parameters["feedbacks"].annotation.__args__[0]
     module_config_type = inspect.signature(func).parameters["module_config"].annotation if "module_config" in inspect.signature(func).parameters else None
 
-    @app.post("/feed_feedbacks", responses=module_responses)
+    @app.post("/feedbacks", responses=module_responses)
     @authenticated
     @with_meta
     async def wrapper(

modules/text/module_text_llm/indices.json

@@ -0,0 +1,47 @@
+{
+    "0": {
+        "exercise_id": 3002,
+        "submission_id": 787782,
+        "feedbacks": [
+            {
+                "id": 6620,
+                "title": "Assessment of the Difference between Coupling/Cohesion",
+                "description": "You correctly explained the difference between coupling and cohesion, well done!",
+                "credits": 1.0,
+                "structured_grading_instruction_id": 6053,
+                "is_graded": null,
+                "meta": {},
+                "exercise_id": 3002,
+                "submission_id": 787782,
+                "index_start": 0,
+                "index_end": 722
+            },
+            {
+                "id": 6621,
+                "title": "Assessment of the Example",
+                "description": "Great example, well done!",
+                "credits": 1.0,
+                "structured_grading_instruction_id": 6058,
+                "is_graded": null,
+                "meta": {},
+                "exercise_id": 3002,
+                "submission_id": 787782,
+                "index_start": 909,
+                "index_end": 1299
+            },
+            {
+                "id": 6622,
+                "title": "Assessment of the Explanation why Coupling/Cohesion are important",
+                "description": "You correctly explained why coupling and cohesion are important, well done!",
+                "credits": 1.0,
+                "structured_grading_instruction_id": 6056,
+                "is_graded": null,
+                "meta": {},
+                "exercise_id": 3002,
+                "submission_id": 787782,
+                "index_start": null,
+                "index_end": null
+            }
+        ]
+    }
+}

modules/text/module_text_llm/module_text_llm/__main__.py

@@ -32,7 +32,7 @@ def process_incoming_feedback(exercise: Exercise, submission: Submission, feedba
     submission_id = submission.id
     exercise_id = exercise.id
     embedded_submission = embed_text(submission.text)
-    store_embedding_index(exercise_id, submission_id)
+    store_embedding_index(exercise_id, submission_id, feedbacks)
     save_embedding(embedded_submission)
 
 @feedback_provider

modules/text/module_text_llm/module_text_llm/icl_rag_approach/generate_suggestions.py

@@ -11,7 +11,7 @@
 from llm_core.utils.predict_and_parse import predict_and_parse
 from module_text_llm.helpers.utils import add_sentence_numbers, get_index_range_from_line_range, format_grading_instructions
 from module_text_llm.icl_rag_approach.prompt_generate_suggestions import AssessmentModel
-from module_text_llm.index_storage import retrieve_embedding_index
+from module_text_llm.index_storage import retrieve_embedding_index, retrieve_feedbacks
 from module_text_llm.storage_embeddings import query_embedding
 from module_text_llm.generate_embeddings import embed_text
 from athena.text import get_stored_feedback
@@ -47,10 +47,12 @@ async def generate_suggestions(exercise: Exercise, submission: Submission, confi
         for index in list_of_indices[0]:
             if index != -1:
                 exercise_id, submission_id = retrieve_embedding_index(list_of_indices)
-                stored_feedback = list(get_stored_feedback(exercise_id, submission_id))
+                stored_feedback = retrieve_feedbacks(index) # -> List[Feedback]
+                # stored_feedback = list(get_stored_feedback(exercise_id, submission_id))
                 logger.info("Stored feedback:")
-                for feedback_item in stored_feedback:
-                    logger.info("- %s", feedback_item) 
+                if stored_feedback is not None:
+                    for feedback_item in stored_feedback:
+                        logger.info("- %s", feedback_item) 
 
                 logger.info("Stored submission:")
                 rag_context.append({"submission": submission.text, "feedback": stored_feedback})

modules/text/module_text_llm/module_text_llm/index_storage.py

@@ -1,6 +1,5 @@
 import json
 import os
-
 INDEX_FILE = "indices.json"
 
 def load_indices():
@@ -10,15 +9,15 @@ def load_indices():
             return json.load(f)
     else:
         return {}
-
-def store_embedding_index(exercise_id, submission_id):
+    
+def store_embedding_index(exercise_id, submission_id,feedbacks):
     """ Store a new submission and exercise ID with an auto-incrementing index. """
     indices = load_indices()
     next_index = len(indices)
-
     indices[next_index] = {
         "exercise_id": exercise_id,
-        "submission_id": submission_id
+        "submission_id": submission_id,
+        "feedbacks": [feedback.dict() for feedback in feedbacks]
     }
 
     with open(INDEX_FILE, 'w', encoding="utf-8") as f:
@@ -34,3 +33,12 @@ def retrieve_embedding_index(index):
         return indices[index]["exercise_id"], indices[index]["submission_id"]
 
     return None, None
+
+def retrieve_feedbacks(index):
+    index = str(index)
+    indices = load_indices()
+
+    if index in indices:
+        return indices[index]["feedbacks"]
+
+    return None