# 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: pass it to Coder as map_tokens instead of `use_ctags`
ASSISTANT: I will modify the `aider/main.py` file to pass `map_tokens` to the `Coder` class instead of `use_ctags`.
```python
aider/main.py
<<<<<<< ORIGINAL
coder = Coder(
io,
main_model=args.model,
fnames=args.files,
pretty=args.pretty,
show_diffs=args.show_diffs,
auto_commits=args.auto_commits,
dirty_commits=args.dirty_commits,
dry_run=args.dry_run,
use_ctags=args.ctags,
verbose=args.verbose,
openai_api_key=args.openai_api_key,
)
=======
coder = Coder(
io,
main_model=args.model,
fnames=args.files,
pretty=args.pretty,
show_diffs=args.show_diffs,
auto_commits=args.auto_commits,
dirty_commits=args.dirty_commits,
dry_run=args.dry_run,
map_tokens=args.map_tokens,
verbose=args.verbose,
openai_api_key=args.openai_api_key,
)
>>>>>>> UPDATED
```
Now, the `map_tokens` value is passed to the `Coder` class instead of `use_ctags`. Please make sure to update the `Coder` class in `aider/coder.py` to accept and use the `map_tokens` parameter.
# Context:
USER: change the --ctags switch into --map-tokens, which is an int that defaults to 1024
ASSISTANT: To make this change, I need to modify the `aider/main.py` file. Please make it *read-write* and let me know when it's done.
USER: I added these *read-write* files: aider/main.py
ASSISTANT: Great! I will now modify the `aider/main.py` file to change the `--ctags` switch into `--map-tokens`, which is an int that defaults to 1024.
```python
aider/main.py
<<<<<<< ORIGINAL
parser.add_argument(
"--ctags",
type=lambda x: (str(x).lower() == "true"),
nargs="?",
const=True,
default=None,
help=(
"Add ctags to the chat to help GPT understand the codebase (default: check for ctags"
" executable)"
),
)
=======
parser.add_argument(
"--map-tokens",
type=int,
default=1024,
help="Number of tokens to map for code understanding (default: 1024)",
)
>>>>>>> UPDATED
```
This change replaces the `--ctags` argument with the `--map-tokens` argument, which takes an integer value and defaults to 1024.
# Context:
USER: is there another persistent dictionary besides shelve?
ASSISTANT: Yes, there are several alternatives to `shelve` for creating persistent dictionaries in Python. Some popular options include:
1. `pickle`: A built-in Python module for object serialization and deserialization. You can use it to store dictionaries in binary format and load them back into memory when needed.
2. `json`: Another built-in Python module for working with JSON data. You can use it to store dictionaries in a human-readable format and load them back into memory when needed.
3. `sqlite3`: A built-in Python module for working with SQLite databases. You can use it to create a simple key-value store with SQL queries.
4. `TinyDB`: A lightweight, document-oriented database for Python
^C KeyboardInterrupt
USER: i want something which presents as a dict though
ASSISTANT: In that case, you can use the `sqlite3` module to create a custom class that behaves like a dictionary. Here's an example of how you can create a persistent dictionary using SQLite:
```python
import sqlite3
class
^C KeyboardInterrupt
USER: i don't want to build something. i want an existing package.
ASSISTANT: I apologize for the confusion. In that case, you can use the `diskcache` package, which provides a dictionary-like interface for disk-based storage. It is easy to use and has good performance.
To install `diskcache`, you can use pip:
```
pip install diskcache
```
Here's an example of how to use `diskcache`:
```python
from diskcache import Cache
cache = Cache('path/to/cache/directory')
# Set a key-value pair
cache['key'] = 'value'
# Get the value for a key
value = cache['key']
# Check if a key is in the cache
if 'key' in cache:
print('Key exists')
# Delete a key-value pair
del cache['key']
# Close the cache when done
cache.close()
```
This will create a persistent dictionary-like object using the `diskcache` package. The data will be stored on disk in the specified directory, and you can use the standard dictionary methods to interact with it.
USER: great. use that.
ASSISTANT: To use `diskcache` in the `aider/repomap.py` file, you'll need to replace the `shelve` usage with `diskcache`. Here are the changes you need to make:
1. Install `diskcache` using pip:
```
pip install diskcache
```
2. Modify the `aider/repomap.py` file:
```python
aider/repomap.py
<<<<<<< ORIGINAL
import colorsys
import json
import os
import random
import subprocess
import sys
import tempfile
from collections import Counter, defaultdict
# import shelve
=======
import colorsys
import json
import os
import random
import subprocess
import sys
import tempfile
from collections import Counter, defaultdict
from diskcache import Cache
>>>>>>> UPDATED
```
```python
aider/repomap.py
<<<<<<< ORIGINAL
IDENT_CACHE_FILE = ".aider.ident.cache"
TAGS_CACHE_FILE = ".aider.tags.cache"
=======
IDENT_CACHE_DIR = ".aider.ident.cache"
TAGS_CACHE_DIR = ".aider.tags.cache"
>>>>>>> UPDATED
```
```python
aider/repomap.py
<<<<<<< ORIGINAL
def load_tags_cache(self):
self.TAGS_CACHE = dict() # shelve.open(self.TAGS_CACHE_FILE)
def save_tags_cache(self):
# self.TAGS_CACHE.sync()
pass
def load_ident_cache(self):
self.IDENT_CACHE = dict() # shelve.open(self.IDENT_CACHE_FILE)
def save_ident_cache(self):
# self.IDENT_CACHE.sync()
pass
=======
def load_tags_cache(self):
self.TAGS_CACHE = Cache(self.TAGS_CACHE_DIR)
def save_tags_cache(self):
self.TAGS_CACHE.close()
def load_ident_cache(self):
self.IDENT_CACHE = Cache(self.IDENT_CACHE_DIR)
def save_ident_cache(self):
self.IDENT_CACHE.close()
>>>>>>> UPDATED
```
These changes will replace the usage of `shelve` with `diskcache` for the `IDENT_CACHE` and `TAGS_CACHE` dictionaries. Make sure to install the `diskcache` package before running the updated code.
# 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: 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.
# Context:
USER: switch both caches to use shelve instead of json
ASSISTANT: To switch both caches to use `shelve` instead of `json`, we need to modify the `aider/repomap.py` file. We will update the `load_tags_cache`, `save_tags_cache`, `load_ident_cache`, and `save_ident_cache` methods.
Here are the changes:
```python
aider/repomap.py
<<<<<<< ORIGINAL
import json
=======
import shelve
>>>>>>> UPDATED
```
```python
aider/repomap.py
<<<<<<< ORIGINAL
IDENT_CACHE_FILE = ".aider.ident.cache.json"
TAGS_CACHE_FILE = ".aider.tags.cache.json"
def load_tags_cache(self):
if os.path.exists(self.TAGS_CACHE_FILE):
with open(self.TAGS_CACHE_FILE, "r") as f:
self.TAGS_CACHE = json.load(f)
else:
self.TAGS_CACHE = dict()
def save_tags_cache(self):
with open(self.TAGS_CACHE_FILE, "w") as f:
json.dump(self.TAGS_CACHE, f)
=======
IDENT_CACHE_FILE = ".aider.ident.cache"
TAGS_CACHE_FILE = ".aider.tags.cache"
def load_tags_cache(self):
if os.path.exists(self.TAGS_CACHE_FILE):
with shelve.open(self.TAGS_CACHE_FILE) as db:
self.TAGS_CACHE = dict(db)
else:
self.TAGS_CACHE = dict()
def save_tags_cache(self):
with shelve.open(self.TAGS_CACHE_FILE) as db:
db.update(self.TAGS_CACHE)
>>>>>>> UPDATED
```
```python
aider/repomap.py
<<<<<<< ORIGINAL
def load_ident_cache(self):
if os.path.exists(self.IDENT_CACHE_FILE):
with open(self.IDENT_CACHE_FILE, "r") as f:
self.IDENT_CACHE = json.load(f)
else:
self.IDENT_CACHE = dict()
def save_ident_cache(self):
with open(self.IDENT_CACHE_FILE, "w") as f:
json.dump(self.IDENT_CACHE, f)
=======
def load_ident_cache(self):
if os.path.exists(self.IDENT_CACHE_FILE):
with shelve.open(self.IDENT_CACHE_FILE) as db:
self.IDENT_CACHE = dict(db)
else:
self.IDENT_CACHE = dict()
def save_ident_cache(self):
with shelve.open(self.IDENT_CACHE_FILE) as db:
db.update(self.IDENT_CACHE)
>>>>>>> UPDATED
```
These changes will replace the usage of `json` with `shelve` for both caches.
# Context:
USER: persist the tags cache to .aider.tags.cache
ASSISTANT: To persist the tags cache to `.aider.tags.cache`, you need to modify the `aider/repomap.py` file. Add two new methods `load_tags_cache` and `save_tags_cache` to the `RepoMap` class, and call them in the `__init__` method and `run_ctags` method, respectively.
Here are the changes you need to make:
```python
aider/repomap.py
<<<<<<< ORIGINAL
TAGS_CACHE_FILE = ".aider.tags.cache"
=======
TAGS_CACHE_FILE = ".aider.tags.cache"
def load_tags_cache(self):
if os.path.exists(self.TAGS_CACHE_FILE):
with open(self.TAGS_CACHE_FILE, "r") as f:
self.TAGS_CACHE = json.load(f)
else:
self.TAGS_CACHE = dict()
def save_tags_cache(self):
with open(self.TAGS_CACHE_FILE, "w") as f:
json.dump(self.TAGS_CACHE, f)
>>>>>>> UPDATED
```
```python
aider/repomap.py
<<<<<<< ORIGINAL
def __init__(self, use_ctags=None, root=None, main_model="gpt-4"):
=======
def __init__(self, use_ctags=None, root=None, main_model="gpt-4"):
self.load_tags_cache()
>>>>>>> UPDATED
```
```python
aider/repomap.py
<<<<<<< ORIGINAL
def run_ctags(self, filename):
# Check if the file is in the cache and if the modification time has not changed
file_mtime = os.path.getmtime(filename)
cache_key = filename
if cache_key in self.TAGS_CACHE and self.TAGS_CACHE[cache_key]["mtime"] == file_mtime:
return self.TAGS_CACHE[cache_key]["data"]
cmd = self.ctags_cmd + [filename]
output = subprocess.check_output(cmd).decode("utf-8")
output = output.splitlines()
data = [json.loads(line) for line in output]
# Update the cache
self.TAGS_CACHE[cache_key] = {"mtime": file_mtime, "data": data}
=======
def run_ctags(self, filename):
# Check if the file is in the cache and if the modification time has not changed
file_mtime = os.path.getmtime(filename)
cache_key = filename
if cache_key in self.TAGS_CACHE and self.TAGS_CACHE[cache_key]["mtime"] == file_mtime:
return self.TAGS_CACHE[cache_key]["data"]
cmd = self.ctags_cmd + [filename]
output = subprocess.check_output(cmd).decode("utf-8")
output = output.splitlines()
data = [json.loads(line) for line in output]
# Update the cache
self.TAGS_CACHE[cache_key] = {"mtime": file_mtime, "data": data}
self.save_tags_cache()
>>>>>>> UPDATED
```
These changes will load the tags cache from the `.aider.tags.cache` file when initializing the `RepoMap` class and save the updated cache to the file after running ctags.
