diff --git a/aider/coders/base_coder.py b/aider/coders/base_coder.py
index b9d48cd62..89a9017bf 100755
--- a/aider/coders/base_coder.py
+++ b/aider/coders/base_coder.py
@@ -9,12 +9,9 @@ import traceback
 from json.decoder import JSONDecodeError
 from pathlib import Path, PurePosixPath
 
-import backoff
 import git
 import openai
-import requests
 from jsonschema import Draft7Validator
-from openai.error import APIError, RateLimitError, ServiceUnavailableError, Timeout
 from rich.console import Console, Text
 from rich.live import Live
 from rich.markdown import Markdown
@@ -22,6 +19,7 @@ from rich.markdown import Markdown
 from aider import models, prompts, utils
 from aider.commands import Commands
 from aider.repomap import RepoMap
+from aider.sendchat import send_with_retries
 
 from ..dump import dump  # noqa: F401
 
@@ -555,43 +553,6 @@ class Coder:
 
         return prompts.added_files.format(fnames=", ".join(mentioned_rel_fnames))
 
-    @backoff.on_exception(
-        backoff.expo,
-        (
-            Timeout,
-            APIError,
-            ServiceUnavailableError,
-            RateLimitError,
-            requests.exceptions.ConnectionError,
-        ),
-        max_tries=10,
-        on_backoff=lambda details: print(
-            f"{details.get('exception','Exception')}\nRetry in {details['wait']:.1f} seconds."
-        ),
-    )
-    def send_with_retries(self, model, messages, functions):
-        kwargs = dict(
-            model=model,
-            messages=messages,
-            temperature=0,
-            stream=self.stream,
-        )
-        if functions is not None:
-            kwargs["functions"] = self.functions
-
-        # we are abusing the openai object to stash these values
-        if hasattr(openai, "api_deployment_id"):
-            kwargs["deployment_id"] = openai.api_deployment_id
-        if hasattr(openai, "api_engine"):
-            kwargs["engine"] = openai.api_engine
-
-        # Generate SHA1 hash of kwargs and append it to chat_completion_call_hashes
-        hash_object = hashlib.sha1(json.dumps(kwargs, sort_keys=True).encode())
-        self.chat_completion_call_hashes.append(hash_object.hexdigest())
-
-        res = openai.ChatCompletion.create(**kwargs)
-        return res
-
     def send(self, messages, model=None, silent=False, functions=None):
         if not model:
             model = self.main_model.name
@@ -601,7 +562,9 @@ class Coder:
 
         interrupted = False
         try:
-            completion = self.send_with_retries(model, messages, functions)
+            hash_object, completion = send_with_retries(model, messages, functions, self.stream)
+            self.chat_completion_call_hashes.append(hash_object.hexdigest())
+
             if self.stream:
                 self.show_send_output_stream(completion, silent)
             else:
diff --git a/aider/sendchat.py b/aider/sendchat.py
new file mode 100644
index 000000000..9a4414230
--- /dev/null
+++ b/aider/sendchat.py
@@ -0,0 +1,44 @@
+import hashlib
+import json
+
+import backoff
+import openai
+import requests
+from openai.error import APIError, RateLimitError, ServiceUnavailableError, Timeout
+
+
+@backoff.on_exception(
+    backoff.expo,
+    (
+        Timeout,
+        APIError,
+        ServiceUnavailableError,
+        RateLimitError,
+        requests.exceptions.ConnectionError,
+    ),
+    max_tries=10,
+    on_backoff=lambda details: print(
+        f"{details.get('exception','Exception')}\nRetry in {details['wait']:.1f} seconds."
+    ),
+)
+def send_with_retries(model, messages, functions, stream):
+    kwargs = dict(
+        model=model,
+        messages=messages,
+        temperature=0,
+        stream=stream,
+    )
+    if functions is not None:
+        kwargs["functions"] = functions
+
+    # we are abusing the openai object to stash these values
+    if hasattr(openai, "api_deployment_id"):
+        kwargs["deployment_id"] = openai.api_deployment_id
+    if hasattr(openai, "api_engine"):
+        kwargs["engine"] = openai.api_engine
+
+    # Generate SHA1 hash of kwargs and append it to chat_completion_call_hashes
+    hash_object = hashlib.sha1(json.dumps(kwargs, sort_keys=True).encode())
+
+    res = openai.ChatCompletion.create(**kwargs)
+    return hash_object, res