Trying.

.github/workflows/tests.yml

@@ -46,7 +46,7 @@ jobs:
     - name: install test dependencies
       run: |
         python3 -m pip install pytest pytest-asyncio pytest-forked hypothesis pytest-mock
-	python3 -m pip install -r test/requirements.txt
+        python3 -m pip install -r test/requirements.txt
         python3 -m pip install .
 
     - name: run tests

README.md

@@ -10,13 +10,16 @@ ChatDBG is an AI-based debugging assistant for C/C++/Python/Rust code that integ
 
 As far as we are aware, ChatDBG is the *first* debugger to automatically perform root cause analysis and to provide suggested fixes.
 
-> [!INFO]
-> For technical details and a complete evaluation, see our arXiv paper, [_ChatDBG: An AI-Powered Debugging Assistant_](https://arxiv.org/abs/2403.16354) ([PDF](https://github.com/plasma-umass/ChatDBG/blob/main/ChatDBG-arxiv-2403.16354.pdf)).
+For technical details and a complete evaluation, see our arXiv paper, [_ChatDBG: An AI-Powered Debugging Assistant_](https://arxiv.org/abs/2403.16354) ([PDF](https://github.com/plasma-umass/ChatDBG/blob/main/ChatDBG-arxiv-2403.16354.pdf)).
 
+> [!NOTE]
+>
+> ChatDBG for `pdb` and `lldb` are feature-complete; we are currently backporting features for these debuggers into the other debuggers.
+>
 
 ## Installation
 
-> [!NOTE]
+> [!IMPORTANT]
 >
 > ChatDBG currently needs to be connected to an [OpenAI account](https://openai.com/api/). _Your account will need to have a positive balance for this to work_ ([check your balance](https://platform.openai.com/account/usage)). If you have never purchased credits, you will need to purchase at least \$1 in credits (if your API account was created before August 13, 2023) or \$0.50 (if you have a newer API account) in order to have access to GPT-4, which ChatDBG uses. [Get a key here.](https://platform.openai.com/account/api-keys)
 >

src/chatdbg/pdb_util/locals.py

@@ -82,7 +82,7 @@ def _repr_if_defined(obj: Any) -> bool:
     return result
 
 
-def _format_limited(value: Any, limit: int = 10, depth: int = 3) -> str:
+def _format_limited(value: Union[int, np.ndarray], limit: int = 10, depth: int = 3) -> str:
     def format_tuple(t, depth):
         return tuple([helper(x, depth) for x in t])
 

src/chatdbg/util/config.py

@@ -17,8 +17,8 @@
 
 
 def _chatdbg_get_env(
-    option_name: str, default_value: Union[int, bool, str]
-) -> Union[int, bool, str]:
+    option_name: str, default_value: Union[bool, int, str]
+) -> Union[bool, int, str]:
     env_name = "CHATDBG_" + option_name.upper()
     v = os.getenv(env_name, str(default_value))
     if type(default_value) == int:

src/chatdbg/util/prompts.py

@@ -7,7 +7,7 @@
 
 
 def _wrap_it(
-    before: str, text: Optional[str], after: str = "", maxlen: int = 2048
+    before: str, text: str, after: str = "", maxlen: int = 2048
 ) -> str:
     if text:
         text = truncate_proportionally(text, maxlen, 0.5)

src/chatdbg/util/text.py

@@ -18,7 +18,7 @@ def strip_ansi(s: str) -> str:
 
 
 def truncate_proportionally(
-    text: str, maxlen: int = 32000, top_proportion: float = 0.5
+    text: str, maxlen: int = 32000, top_proportion: Union[float, int] = 0.5
 ) -> str:
     """Omit part of a string if needed to make it fit in a maximum length."""
     if len(text) > maxlen:

src/chatdbg/util/trim.py

@@ -62,10 +62,10 @@ def _chunkify(messages, model):
 
 
 def trim_messages(
-    messages: List[Dict],  # list of JSON objects encoded as dicts
+    messages: List[Dict[str, str]],  # list of JSON objects encoded as dicts
     model: str,
     trim_ratio: float = 0.75,
-) -> List[Dict]:
+) -> list:
     """
     Strategy:
     - chunk messages: