Address sporadic hanging of evals on certain samples (#1482)

As has been brought up before (#1384, #1292,
#270), evals suffer from a hanging
issue, where an evaluation run will hang for a very long time (if not
indefinitely) at the end of a run (say, on the 99th sample of out 100).

This PR addresses this issue, by replacing a seemingly redundant
single-threaded thread creation that was happening when making requests,
nested inside the already multi-threaded eval loop. My impression is
that this nested multithreading was causing overhead that resulted in
the hanging experienced.

I had also noticed this hanging issue in `EVALS_SEQUENTIAL=1` mode
(where it no longer occurs at the end, but instead randomly in the
middle of the run).

I was able to identify the source of this issue though debugging print
statements that ultimately pointed to the `request_with_timeout`
function as the culprit.

We have tested the new `request_with_timeout` code on a fork where we
have run multiple new and pre-existing evals, including with 3rd party
solvers, and found no change in behaviour or errors, and a clear
improvement on the hanging issue.

evals/utils/api_utils.py

@@ -1,7 +1,6 @@
 """
 This file defines various helper functions for interacting with the OpenAI API.
 """
-import concurrent
 import logging
 import os
 
@@ -38,16 +37,14 @@ def openai_completion_create_retrying(client: OpenAI, *args, **kwargs):
 
 def request_with_timeout(func, *args, timeout=EVALS_THREAD_TIMEOUT, **kwargs):
     """
-    Worker thread for making a single request within allotted time.
+    Function for making a single request within allotted time.
     """
     while True:
-        with concurrent.futures.ThreadPoolExecutor(max_workers=1) as executor:
-            future = executor.submit(func, *args, **kwargs)
-            try:
-                result = future.result(timeout=timeout)
-                return result
-            except concurrent.futures.TimeoutError:
-                continue
+        try:
+            result = func(*args, timeout=timeout, **kwargs)
+            return result
+        except openai.APITimeoutError as e:
+            continue
 
 
 @backoff.on_exception(