Update app.py

app.py

@@ -5,6 +5,9 @@ import inspect
 import pandas as pd
 from smolagents import DuckDuckGoSearchTool,HfApiModel,load_tool, CodeAgent
 from smolagents import CodeAgent
+import hashlib
+import json
+
 
 # (Keep Constants as is)
 # --- Constants ---
@@ -12,7 +15,8 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
 # --- Basic Agent Definition ---
 # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
-
+import os
+os.makedirs("cache", exist_ok=True)
 
 web_search = DuckDuckGoSearchTool()
 
@@ -21,7 +25,28 @@ web_search = DuckDuckGoSearchTool()
 # If the agent does not answer, the model is overloaded, please use another model or the following Hugging Face Endpoint that also contains qwen2.5 coder:
 # model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud' 
 
-model = HfApiModel(model_id='meta-llama/Llama-3.3-70B-Instruct', max_tokens=1024)
+model = HfApiModel(model_id='mistralai/Mistral-7B-Instruct-v0.2', max_tokens=512)
+
+
+
+def get_cache_key(question: str) -> str:
+    return hashlib.sha256(question.encode()).hexdigest()
+
+def load_cached_answer(question: str) -> str | None:
+    key = get_cache_key(question)
+    path = f"cache/{key}.json"
+    if os.path.exists(path):
+        with open(path, "r") as f:
+            data = json.load(f)
+            return data.get("answer")
+    return None
+
+def cache_answer(question: str, answer: str):
+    key = get_cache_key(question)
+    path = f"cache/{key}.json"
+    with open(path, "w") as f:
+        json.dump({"question": question, "answer": answer}, f)
+
 
 
 class BasicAgent:
@@ -106,12 +131,20 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
             print(f"Skipping item with missing task_id or question: {item}")
             continue
         try:
-            submitted_answer = agent(question_text)
+            cached = load_cached_answer(question_text)
+            if cached:
+                submitted_answer = cached
+                print(f"Loaded cached answer for task {task_id}")
+            else:
+                submitted_answer = agent(question_text)
+                cache_answer(question_text, submitted_answer)
+                print(f"Generated and cached answer for task {task_id}")
+    
             answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
             results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
         except Exception as e:
-             print(f"Error running agent on task {task_id}: {e}")
-             results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": f"AGENT ERROR: {e}"})
+            print(f"Error running agent on task {task_id}: {e}")
+            results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": f"AGENT ERROR: {e}"})
 
     if not answers_payload:
         print("Agent did not produce any answers to submit.")