# Context:
USER: make `get_ranked_tags_map` use binary search
ASSISTANT: To modify the `get_ranked_tags_map` function to use binary search, follow these steps:
1. Replace the for loop with a binary search implementation.
2. Update the loop to calculate the middle index and generate the tree with the middle index.
3. Check if the number of tokens is less than `max_map_tokens`. If it is, update the lower bound. Otherwise, update the upper bound.
4. Continue the binary search until the lower bound is greater than or equal to the upper bound.
Here's the updated `get_ranked_tags_map` function:
```python
aider/repomap.py
<<<<<<< ORIGINAL
def get_ranked_tags_map(self, fnames):
# 1/4 of gpt-4's context window
max_map_tokens = 2048
ranked_tags = self.get_ranked_tags(fnames)
num_tags = len(ranked_tags)
for i in range(num_tags, 0, -1):
tree = to_tree(ranked_tags[:i])
num_tokens = self.token_count(tree)
dump(i, num_tokens)
if num_tokens < max_map_tokens:
return tree
=======
def get_ranked_tags_map(self, fnames):
# 1/4 of gpt-4's context window
max_map_tokens = 2048
ranked_tags = self.get_ranked_tags(fnames)
num_tags = len(ranked_tags)
lower_bound = 0
upper_bound = num_tags
best_tree = None
while lower_bound <= upper_bound:
middle = (lower_bound + upper_bound) // 2
tree = to_tree(ranked_tags[:middle])
num_tokens = self.token_count(tree)
if num_tokens < max_map_tokens:
best_tree = tree
lower_bound = middle + 1
else:
upper_bound = middle - 1
return best_tree
>>>>>>> UPDATED
```
# Context:
USER: do the todo
ASSISTANT: I see a "todo" comment in the `aider/repomap.py` file. To complete the task, we need to calculate the sum of the weights of every inbound edge to each node in the graph. Here's how to do it:
```python
aider/repomap.py
<<<<<<< ORIGINAL
for node in G.nodes:
# todo: sum up the weight of every inbound edge to node
pass
=======
inbound_weights = {}
for node in G.nodes:
inbound_weights[node] = sum(data["weight"] for _, _, data in G.in_edges(node, data=True))
>>>>>>> UPDATED
```
This code calculates the sum of the weights of every inbound edge to each node and stores the result in the `inbound_weights` dictionary.
# Context:
USER: how can i move the patch to setUp so that it is active for all tests?
ASSISTANT: To move the patch to the `setUp` method and make it active for all tests, you can use the `patch` as a context manager in the `setUp` method and store the mock object as an instance variable. Then, in the `tearDown` method, you can stop the patch. Here's how to do it:
```python
tests/test_main.py
<<<<<<< ORIGINAL
def setUp(self):
os.environ["OPENAI_API_KEY"] = "deadbeef"
self.original_cwd = os.getcwd()
self.tempdir = tempfile.mkdtemp()
os.chdir(self.tempdir)
def tearDown(self):
os.chdir(self.original_cwd)
shutil.rmtree(self.tempdir)
=======
def setUp(self):
os.environ["OPENAI_API_KEY"] = "deadbeef"
self.original_cwd = os.getcwd()
self.tempdir = tempfile.mkdtemp()
os.chdir(self.tempdir)
self.patcher = patch("aider.main.Coder.check_model_availability")
self.mock_check = self.patcher.start()
self.mock_check.return_value = True
def tearDown(self):
os.chdir(self.original_cwd)
shutil.rmtree(self.tempdir)
self.patcher.stop()
>>>>>>> UPDATED
```
Now the patch is active for all tests, and you can remove the `with` statement from the `test_main_with_empty_dir_no_files_on_command` method:
```python
tests/test_main.py
<<<<<<< ORIGINAL
def test_main_with_empty_dir_no_files_on_command(self):
with patch("aider.main.Coder.check_model_availability") as mock_check:
mock_check.return_value = True
pipe_input = create_input(StringIO(""))
main([], input=pipe_input, output=DummyOutput())
pipe_input.close()
=======
def test_main_with_empty_dir_no_files_on_command(self):
pipe_input = create_input(StringIO(""))
main([], input=pipe_input, output=DummyOutput())
pipe_input.close()
>>>>>>> UPDATED
```
# Context:
USER: the patch in `setUp` is not correcting forcing a return of true
ASSISTANT: To ensure that the patch in `setUp` correctly forces a return of `True`, you need to modify the `setUp` method in the `TestMain` class in the `tests/test_main.py` file. Here's the change:
```python
tests/test_main.py
<<<<<<< ORIGINAL
def setUp(self):
os.environ["OPENAI_API_KEY"] = "deadbeef"
self.original_cwd = os.getcwd()
self.tempdir = tempfile.mkdtemp()
os.chdir(self.tempdir)
with patch("aider.main.Coder.check_model_availability") as self.mock_check:
self.mock_check.return_value = True
super().setUp()
=======
def setUp(self):
os.environ["OPENAI_API_KEY"] = "deadbeef"
self.original_cwd = os.getcwd()
self.tempdir = tempfile.mkdtemp()
os.chdir(self.tempdir)
self.mock_check = MagicMock(return_value=True)
with patch("aider.main.Coder.check_model_availability", new=self.mock_check):
super().setUp()
>>>>>>> UPDATED
```
This change ensures that the `check_model_availability` method is patched with a `MagicMock` object that always returns `True`.
# Context:
USER: the patch in `setUp` is not correcting forcing a return of true
ASSISTANT: To fix the patch in `setUp`, you need to start the patch and set the return value to `True`. Here's the change you need to make in the `tests/test_main.py` file:
```python
tests/test_main.py
<<<<<<< ORIGINAL
self.mock_check = patch("aider.main.Coder.check_model_availability")
self.mock_check.return_value = True
=======
with patch("aider.main.Coder.check_model_availability") as self.mock_check:
self.mock_check.return_value = True
super().setUp()
>>>>>>> UPDATED
```
This change will ensure that the `check_model_availability` method returns `True` during the test setup.
# Context:
USER: E AttributeError: <class 'aider.coder.Coder'> does not have the attribute 'check_for_model_availability'
ASSISTANT: It seems like you are trying to access the `check_for_model_availability` method of the `Coder` class, but it is not defined as an instance method. To fix this issue, you need to move the `check_model_availability` method inside the `Coder` class and update the tests accordingly.
Here are the changes you need to make:
1. Move the `
^C KeyboardInterrupt
USER: fix the `setUp`
ASSISTANT: To fix the `setUp` method in the `TestMain` class, you need to update the way you are mocking the `check_for_model_availability` method. Here are the changes you need to make:
1. Modify the `setUp` method in the `TestMain` class to correctly mock the `check_for_model_availability` method of the `Coder` class.
```python
tests/test_main.py
<<<<<<< ORIGINAL
with patch("aider.coder.Coder.check_for_model_availability") as mock_check:
mock_check.return_value = True
self.mock_check = mock_check
=======
with patch("aider.coder.Coder.check_model_availability") as mock_check:
mock_check.return_value = True
self.mock_check = mock_check
>>>>>>> UPDATED
```
This change will ensure that the `check_for_model_availability` method is correctly mocked during the tests.
# Context:
USER: in setup, patch coder.check_for_model_availability to return true
ASSISTANT: To patch the `check_for_model_availability` method in the `setUp` method of the `TestMain` class, you can use the `unittest.mock.patch` context manager. Here's the change you need to make in the `tests/test_main.py` file:
```python
tests/test_main.py
<<<<<<< ORIGINAL
def setUp(self):
os.environ["OPENAI_API_KEY"] = "deadbeef"
self.original_cwd = os.getcwd()
self.tempdir = tempfile.mkdtemp()
os.chdir(self.tempdir)
=======
from unittest.mock import MagicMock
def setUp(self):
os.environ["OPENAI_API_KEY"] = "deadbeef"
self.original_cwd = os.getcwd()
self.tempdir = tempfile.mkdtemp()
os.chdir(self.tempdir)
with patch("aider.coder.Coder.check_for_model_availability") as mock_check:
mock_check.return_value = True
self.mock_check = mock_check
>>>>>>> UPDATED
```
This will patch the `check_for_model_availability` method to always return `True` during the `setUp` method execution.
# 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.
