Update app.py

app.py

@@ -8,9 +8,11 @@ Updates:
 ✅ Prints all questions and corresponding results at the end
 ✅ Maintains modular design and existing architecture
 """
+import os
+os.environ["LLAMA_BLAS"] = "1"
+os.environ["LLAMA_BLAS_VENDOR"] = "OpenBLAS"
 from langchain_community.llms import LlamaCpp
 from llama_cpp import Llama
-import os
 import re
 import json
 import requests
@@ -25,7 +27,6 @@ from langchain_core.prompts import PromptTemplate
 from langchain.agents import create_react_agent, AgentExecutor
 from datasets import load_dataset
 from huggingface_hub import login
-import os
 import threading
 import logging
 logging.getLogger("httpx").setLevel(logging.WARNING)
@@ -40,11 +41,11 @@ model_path = hf_hub_download(
 llm = LlamaCpp(
     model_path=model_path,
     n_ctx=10000,
-    n_threads=8,
+    n_threads=4,
     n_gpu_layers=0,
     temperature=0.65,
     top_p=0.9,
-    max_tokens=200,
+    max_tokens=100,
     n_batch=64,
     verbose=False
     )
@@ -356,19 +357,27 @@ class GaiaRunner:
         answers = []
         results_log = []
 
-        with ThreadPoolExecutor(max_workers=1) as executor:
-          futures = {}
-          for q in questions_data:
-            task_id = q.get("task_id")
-            qtext = q.get("question")
-            attach = q.get("file_name")
-            file_path = None
-            if attach and attach.strip():  # تأكد أن الحقل غير فارغ
-                file_path = self.download_gaia_attachment(q)
-            else:
-                file_path = None
-            futures[executor.submit(self.run_on_question, qtext, file_path)] = (task_id, qtext)
+        futures = []  # لتخزين النتائج النهائية
+
+        for q in questions_data:
+         task_id = q.get("task_id")
+         qtext = q.get("question")
+         attach = q.get("file_name")
+
+         # تحميل المرفق فقط إذا كان موجودًا فعلاً
+         if attach and attach.strip():
+             file_path = self.download_gaia_attachment(q)
+         else:
+             file_path = None
+
+         # تنفيذ الدالة مباشرة (تسلسليًا)
+         print(f"🔹 Running question {task_id}: {qtext[:60]}...")
+         futures = self.run_on_question(qtext, file_path)
+
+         # حفظ النتيجة بشكل مشابه لاستخدام futures سابقًا
+         futures.append((task_id, qtext, result))
 
+         print("✅ All questions processed.")
         for fut in as_completed(futures):
             task_id, qtext = futures[fut]
             ans = fut.result()