text: Title: OpenAI should automatically switch to the model with more context
  Body: ### 🚀 The feature
  
  Currently, when users encounter errors due to a context window that exceeds the model's capacity, they need to manually adjust their model choice to a larger version, which can be cumbersome and may disrupt the workflow. This feature would automate the process, ensuring that users get the best possible performance without the need for manual intervention.
  
  ## Proposed Solution
  
  The proposed solution is to implement an automatic context model switching mechanism that checks the context window size and switches to a larger model if needed. Here's how it could work:
  
  1. When a user sends a request with a specific model (e.g., "gpt-4"), the system checks the context window size.
  
  2. If the context window size exceeds the capacity of the selected model (e.g., "gpt-4"), the system automatically switches to the corresponding larger model (e.g., "gpt-4-32k").
  
  3. The system processes the request using the larger model to ensure the context fits within its capacity.
  
  4. The user receives the response seamlessly, without having to manually change the model selection.
  
  ## Implementation Considerations
  
  To implement this feature, OpenAI may need to develop a mechanism for context size detection and automatic model switching within the API infrastructure.
  
  ## Example Scenario
  
  A user sends a request to the API using "gpt-4" but accidentally provides a very long context that exceeds the model's capacity. Instead of receiving an error, the system automatically switches to "gpt-4-32k" to accommodate the larger context, and the user receives a timely and accurate response.
  
  ### Motivation, pitch
  
  1. Improved user experience: Users won't have to manually switch models when encountering context-related errors, making the interaction with OpenAI models more seamless.
  
  2. Error prevention: Automatic context model switching can help prevent errors caused by users inadvertently exceeding the context window of their selected model.
  
  3. Efficient use of resources: By automatically selecting the appropriate model based on context size, the system can make efficient use of computational resources.
  
  ### Alternatives
  
  _No response_
  
  ### Additional context
  
  This feature could be particularly useful for applications that involve dynamic and variable-length input contexts, such as chatbots, language translation, and content generation.