Update retriever.py

retriever.py

@@ -1,19 +1,11 @@
-from typing import List
+import json
 
-# Dummy in-memory document store for simplicity
-document_store = {
-    "task_id_1": "The Titanic was used in the film The Last Voyage.",
-    "task_id_2": "The fruits in the 2008 painting were apples, grapes, and pears.",
-    # Add more if needed
-}
+# Load the context from context.json once at startup
+with open("context.json", "r") as f:
+    context_data = json.load(f)
 
-def retrieve_context(task_id: str, question: str) -> List[str]:
+def retrieve_relevant_context(task_id: str) -> str:
     """
-    Simulated retrieval logic. Replace with RAG/FAISS/LLM Search for real usage.
+    Retrieves the relevant context for a given task_id using preloaded context.json.
     """
-    if task_id in document_store:
-        return [document_store[task_id]]
-    elif "Titanic" in question:
-        return ["Titanic was featured in The Last Voyage."]
-    else:
-        return ["Context not found. Please refer to web or document tools."]
+    return context_data.get(task_id, "")