# Context:
USER: Hello there,
thanks for making this open source!
I have a request: due to being still on the free credits of OpenAI API, I run into timeouts.
fetch_starred_repos.py
Add these files to the chat? y
RateLimitError: You exceeded your current quota, please check your plan and billing details.
Retry in 1 seconds.
...
Is it possible for you to implement this library to omit that?
https://pypi.org/project/backoff/
Thanks in advance.
Greetings from Germany
ASSISTANT: Sure, I can help you implement the `backoff` library to handle the rate limit issue. First, please make the `aider/coder.py` file *read-write* so I can propose changes to it.
USER: I added these *read-write* files: aider/coder.py
ASSISTANT: Great! First, you need to install the `backoff` library. You can do this by running:
```
pip install backoff
```
Next, I will show you the changes needed in the `aider/coder.py` file to implement the `backoff` library for handling rate limit issues.
1. Import the `backoff` library at the beginning of the file.
2. Replace the `send_with_retries` method with a new method that uses the `backoff` library.
Here are the changes:
```python
aider/coder.py
<<<<<<< ORIGINAL
import os
import sys
import time
import traceback
=======
import os
import sys
import traceback
import backoff
>>>>>>> UPDATED
```
```python
aider/coder.py
<<<<<<< ORIGINAL
def send_with_retries(self, model, messages):
while True:
try:
return openai.ChatCompletion.create(
model=model,
messages=messages,
temperature=0,
stream=True,
)
except RateLimitError as err:
self.io.tool_error(f"RateLimitError: {err}")
except requests.exceptions.ConnectionError as err:
self.io.tool_error(f"ConnectionError: {err}")
retry_after = 1
self.io.tool_error(f"Retry in {retry_after} seconds.")
time.sleep(retry_after)
=======
@backoff.on_exception(
backoff.expo,
(RateLimitError, requests.exceptions.ConnectionError),
max_tries=5,
on_backoff=lambda details: self.io.tool_error(f"Retry in {details['wait']} seconds."),
)
def send_with_retries(self, model, messages):
return openai.ChatCompletion.create(
model=model,
messages=messages,
temperature=0,
stream=True,
)
>>>>>>> UPDATED
```
These changes will implement the `backoff` library to handle rate limit issues with exponential backoff and a maximum of 5 retries. If you want to adjust the number of retries, you can change the `max_tries` parameter in the `backoff.on_exception` decorator.
# Context:
USER: I added these *read-write* files: aider/coder.py
ASSISTANT: Great! Now I will modify the `aider/coder.py` file to accept and use the `map_tokens` parameter instead of `use_ctags`.
```python
aider/coder.py
<<<<<<< ORIGINAL
def __init__(
self,
io,
main_model="gpt-4",
fnames=None,
pretty=True,
show_diffs=False,
auto_commits=True,
dirty_commits=True,
dry_run=False,
use_ctags=False,
verbose=False,
openai_api_key=None,
):
...
self.repo_map = RepoMap(use_ctags, self.root, self.main_model, rm_io)
=======
def __init__(
self,
io,
main_model="gpt-4",
fnames=None,
pretty=True,
show_diffs=False,
auto_commits=True,
dirty_commits=True,
dry_run=False,
map_tokens=1024,
verbose=False,
openai_api_key=None,
):
...
self.repo_map = RepoMap(map_tokens, self.root, self.main_model, rm_io)
>>>>>>> UPDATED
```
This change updates the `Coder` class in `aider/coder.py` to accept the `map_tokens` parameter and pass it to the `RepoMap` class instead of `use_ctags`.
# Context:
USER: in init, call check the list of available openai models and make sure the `main_model` is in there. if not, print an err msg
ASSISTANT:
^C KeyboardInterrupt
USER: in init, call check the list of available openai models and make sure the `main_model` is in there. if not, print an err msg
ASSISTANT: To check the list of available OpenAI models and make sure the `main_model` is in there, you need to modify the `__init__` method in the `Coder` class. Here's how you can do it:
1. Add a new method `check_model_availability` to the `Coder` class that takes the `main_model` as an argument and checks if it's available in the list of OpenAI models.
2. Call this method in the `__init__` method of the `Coder` class.
Here are the changes you need to make:
```python
aider/coder.py
<<<<<<< ORIGINAL
class Coder:
abs_fnames = None
repo = None
last_aider_commit_hash = None
last_asked_for_commit_time = 0
def __init__(
=======
class Coder:
abs_fnames = None
repo = None
last_aider_commit_hash = None
last_asked_for_commit_time = 0
def check_model_availability(self, main_model):
available_models = openai.Model.list()
model_ids = [model.id for model in available_models['data']]
if main_model not in model_ids:
raise ValueError(f"Model {main_model} is not available. Please choose from the available models: {model_ids}")
def __init__(
>>>>>>> UPDATED
```
```python
aider/coder.py
<<<<<<< ORIGINAL
self.main_model = main_model
if main_model == "gpt-3.5-turbo":
self.io.tool_error(
f"aider doesn't work well with {main_model}, use gpt-4 for best results."
)
self.set_repo(fnames)
=======
self.check_model_availability(main_model)
self.main_model = main_model
if main_model == "gpt-3.5-turbo":
self.io.tool_error(
f"aider doesn't work well with {main_model}, use gpt-4 for best results."
)
self.set_repo(fnames)
>>>>>>> UPDATED
```
These changes will add a new method `check_model_availability` to the `Coder` class and call it in the `__init__` method to ensure the `main_model` is available in the list of OpenAI models. If not, it will raise a `ValueError` with an appropriate error message.
