# Aider chat conversation:
USER: add a main func so i can run this script with a model name on the cmd line and print the results
ASSISTANT: Here are the changes to add a `main` function that allows running the script with a model name from the command line and printing the results:
aider/models.py
```python
<<<<<<< SEARCH
=======
import sys
def main():
if len(sys.argv) != 2:
print("Usage: python models.py <model_name>")
sys.exit(1)
model_name = sys.argv[1]
matching_models = fuzzy_match_models(model_name)
if matching_models:
print(f"Matching models for '{model_name}':")
for model in matching_models:
print(model)
else:
print(f"No matching models found for '{model_name}'.")
if __name__ == "__main__":
main()
>>>>>>> REPLACE
```
The `main` function does the following:
1. It checks if the script is called with exactly one command-line argument (the model name). If not, it prints the usage instructions and exits with an error code.
2. It retrieves the model name from the command-line argument using `sys.argv[1]`.
3. It calls the `fuzzy_match_models` function with the provided model name to get the list of matching models.
4. If matching models are found, it prints a message indicating the matching models for the given model name and then prints each matching model on a separate line.
5. If no matching models are found, it prints a message indicating that no matching models were found for the given model name.
The `if __name__ == "__main__":` block ensures that the `main` function is only executed when the script is run directly, not when it is imported as a module.
With these changes, you can run the script from the command line by providing a model name as an argument, and it will print the matching models or a message if no matches are found.
# Aider chat conversation:
USER: implemenet the `fuzzy_match_models` function. takes the name of a LLM like "gpt-3.5" and searches the list of `models` to find models which contain the name or contain a slight misspelling of the name
ASSISTANT: Here is an implementation of the `fuzzy_match_models` function that searches for models containing the given name or a slight misspelling:
aider/models.py
```python
<<<<<<< SEARCH
def fuzzy_match_models(name):
models = litellm.most_cost.keys()
=======
import difflib
def fuzzy_match_models(name):
models = litellm.most_cost.keys()
# Check for exact match first
if name in models:
return [name]
# Check for models containing the name
matching_models = [model for model in models if name in model]
# If no matches found, check for slight misspellings
if not matching_models:
matching_models = difflib.get_close_matches(name, models, n=3, cutoff=0.8)
return matching_models
>>>>>>> REPLACE
```
This implementation does the following:
1. It first checks if the given `name` exactly matches any model in the `models` list. If an exact match is found, it returns a list containing only that model name.
2. If no exact match is found, it searches for models that contain the given `name` as a substring. It uses a list comprehension to filter the `models` list and find models that include `name`.
3. If still no matches are found, it uses the `difflib.get_close_matches()` function to find models that are close matches to the given `name`. It searches for up to 3 close matches with a similarity ratio of at least 0.8 (80%).
4. Finally, it returns the list of matching models found either by exact match, substring match, or close match.
This implementation allows for fuzzy matching of model names, considering both exact matches and slight misspellings.
