Support weak_model=False

aider/history.py

@@ -123,7 +123,7 @@ def main():
 
         assistant.append(line)
 
-    summarizer = ChatSummary(models.Model(models.DEFAULT_WEAK_MODEL_NAME))
+    summarizer = ChatSummary(models.Model(models.DEFAULT_WEAK_MODEL_NAME, weak_model=False))
     summary = summarizer.summarize(messages[-40:])
     dump(summary)
 

aider/models.py

@@ -139,7 +139,10 @@ class Model:
             self.max_chat_history_tokens = 2 * 1024
 
         self.configure_model_settings(model)
-        self.get_weak_model(weak_model, require_model_info)
+        if weak_model is False:
+            self.weak_model_name = None
+        else:
+            self.get_weak_model(weak_model, require_model_info)
 
     def configure_model_settings(self, model):
         for ms in MODEL_SETTINGS:
@@ -174,7 +177,7 @@ class Model:
 
         self.weak_model = Model(
             self.weak_model_name,
-            weak_model=self.weak_model_name,
+            weak_model=False,
             require_model_info=require_model_info,
         )
         return self.weak_model

aider/repo.py

@@ -25,7 +25,7 @@ class GitRepo:
             self.models = [
                 Model(
                     DEFAULT_WEAK_MODEL_NAME,
-                    weak_model=DEFAULT_WEAK_MODEL_NAME,
+                    weak_model=False,
                     require_model_info=False,
                 )
             ]

docs/connect.md

@@ -91,6 +91,11 @@ for more information on how to populate the above configuration values.
 If you can make an LLM accessible via an OpenAI compatible API,
 you can use `--openai-api-base` to connect to a different API endpoint.
 
+You might need to use `--no-require-model-info` to tell aider to
+work with an unknown model that has no metadata available like
+context size, token costs, etc.
+Some minor functionality will be limited when using such models.
+
 ## Other LLMs
 
 Aider uses the [litellm](https://docs.litellm.ai/docs/providers) package