Add claude 3 / anthropic with cost calculation + convenience fixes. gpt-engineer is coauthor

.env.template

@@ -1,4 +1,5 @@
 ### OpenAI Setup ###
 
 # OPENAI_API_KEY=Your personal OpenAI API key from https://platform.openai.com/account/api-keys
-OPENAI_API_KEY=$key
+OPENAI_API_KEY=...
+ANTHROPIC_API_KEY=...

gpt_engineer/applications/cli/cli_agent.py

@@ -4,9 +4,8 @@
 and process the code through various steps defined in the step bundle.
 """
 
-from typing import Callable, Optional, TypeVar
+from typing import Callable, Optional, TypeAlias
 
-# from gpt_engineer.core.default.git_version_manager import GitVersionManager
 from gpt_engineer.core.ai import AI
 from gpt_engineer.core.base_agent import BaseAgent
 from gpt_engineer.core.base_execution_env import BaseExecutionEnv
@@ -18,18 +17,16 @@
     execute_entrypoint,
     gen_code,
     gen_entrypoint,
-    improve,
+    improve_fn,
 )
 from gpt_engineer.core.files_dict import FilesDict
 from gpt_engineer.core.preprompts_holder import PrepromptsHolder
 
-CodeGenType = TypeVar("CodeGenType", bound=Callable[[AI, str, BaseMemory], FilesDict])
-CodeProcessor = TypeVar(
-    "CodeProcessor", bound=Callable[[AI, BaseExecutionEnv, FilesDict], FilesDict]
-)
-ImproveType = TypeVar(
-    "ImproveType", bound=Callable[[AI, str, FilesDict, BaseMemory], FilesDict]
-)
+# from gpt_engineer.core.default.git_version_manager import GitVersionManager
+
+CodeGenType: TypeAlias = Callable[[AI, str, BaseMemory], FilesDict]
+CodeProcessor: TypeAlias = Callable[[AI, BaseExecutionEnv, FilesDict], FilesDict]
+ImproveType: TypeAlias = Callable[[AI, str, FilesDict, BaseMemory], FilesDict]
 
 
 class CliAgent(BaseAgent):
@@ -86,7 +83,7 @@ def __init__(
         execution_env: BaseExecutionEnv,
         ai: AI = None,
         code_gen_fn: CodeGenType = gen_code,
-        improve_fn: ImproveType = improve,
+        improve_fn: ImproveType = improve_fn,
         process_code_fn: CodeProcessor = execute_entrypoint,
         preprompts_holder: PrepromptsHolder = None,
     ):
@@ -105,7 +102,7 @@ def with_default_config(
         execution_env: DiskExecutionEnv,
         ai: AI = None,
         code_gen_fn: CodeGenType = gen_code,
-        improve_fn: ImproveType = improve,
+        improve_fn: ImproveType = improve_fn,
         process_code_fn: CodeProcessor = execute_entrypoint,
         preprompts_holder: PrepromptsHolder = None,
     ):

gpt_engineer/applications/cli/collect.py

@@ -22,7 +22,7 @@
     Consent logic is in gpt_engineer/learning.py.
 """
 
-from typing import Tuple
+from typing import Any, Tuple
 
 from gpt_engineer.applications.cli.learning import (
     Learning,
@@ -49,7 +49,7 @@ def send_learning(learning: Learning):
     improving gpt-engineer, and letting it handle more use cases.
     Consent logic is in gpt_engineer/learning.py.
     """
-    import rudderstack.analytics as rudder_analytics
+    import rudderstack.analytics as rudder_analytics  # fmt: skip
 
     rudder_analytics.write_key = "2Re4kqwL61GDp7S8ewe6K5dbogG"
     rudder_analytics.dataPlaneUrl = "https://gptengineerezm.dataplane.rudderstack.com"
@@ -65,7 +65,7 @@ def collect_learnings(
     prompt: str,
     model: str,
     temperature: float,
-    config: any,
+    config: Any,
     memory: DiskMemory,
     review: Review,
 ):
@@ -99,7 +99,8 @@ def collect_learnings(
         # try to remove some parts of learning that might be too big
         # rudderstack max event size is 32kb
         max_size = 32 << 10  # 32KB in bytes
-        current_size = len(learnings.to_json().encode("utf-8"))  # get size in bytes
+        learnings_bytes = learnings.to_json().encode("utf-8")  # type: ignore
+        current_size = len(learnings_bytes)  # get size in bytes
 
         overflow = current_size - max_size
 

gpt_engineer/applications/cli/file_selector.py

@@ -22,7 +22,7 @@
 import subprocess
 
 from pathlib import Path
-from typing import Any, Dict, List, Union
+from typing import Any, Dict, Generator, List, Union
 
 import toml
 
@@ -288,14 +288,22 @@ def get_files_from_toml(
         print(f"\nYou have selected the following files:\n{input_path}")
 
         project_path = Path(input_path).resolve()
-        all_paths = set(
+        selected_paths = set(
             project_path.joinpath(file).resolve(strict=False) for file in selected_files
         )
 
+        for displayable_path in DisplayablePath.make_tree(project_path):
+            if displayable_path.path in selected_paths:
+                p = displayable_path
+                while p.parent and p.parent.path not in selected_paths:
+                    selected_paths.add(p.parent.path)
+                    p = p.parent
+
         try:
             for displayable_path in DisplayablePath.make_tree(project_path):
-                if displayable_path.path in all_paths:
+                if displayable_path.path in selected_paths:
                     print(displayable_path.displayable())
+
         except FileNotFoundError:
             print("Specified path does not exist: ", project_path)
         except Exception as e:
@@ -378,24 +386,6 @@ def get_current_files(self, project_path: Union[str, Path]) -> List[str]:
 
         return all_files
 
-    def is_in_ignoring_extensions(self, path: Path) -> bool:
-        """
-        Checks if a file path should be ignored based on predefined criteria.
-
-        Parameters
-        ----------
-        path : Path
-            The path to the file to be checked.
-
-        Returns
-        -------
-        bool
-            True if the file should not be ignored, False otherwise.
-        """
-        is_hidden = not path.name.startswith(".")
-        is_pycache = "__pycache__" not in path.name
-        return is_hidden and is_pycache
-
 
 class DisplayablePath(object):
     """
@@ -444,7 +434,7 @@ def display_name(self) -> str:
     @classmethod
     def make_tree(
         cls, root: Union[str, Path], parent=None, is_last=False, criteria=None
-    ):
+    ) -> Generator["DisplayablePath", None, None]:
         """
         Creates a tree of DisplayablePath objects from a root directory.
 

gpt_engineer/applications/cli/learning.py

@@ -117,8 +117,6 @@ class Learning:
     + "(ncertain): "
 )
 
-VALID_INPUTS = ("y", "n", "u")
-
 
 def human_review_input() -> Optional[Review]:
     """
@@ -141,17 +139,17 @@ def human_review_input() -> Optional[Review]:
     print()
 
     ran = input("Did the generated code run at all? " + TERM_CHOICES)
-    ran = ask_for_valid_input(ran, VALID_INPUTS)
+    ran = ask_for_valid_input(ran)
 
     if ran == "y":
         perfect = input(
             "Did the generated code do everything you wanted? " + TERM_CHOICES
         )
-        perfect = ask_for_valid_input(perfect, VALID_INPUTS)
+        perfect = ask_for_valid_input(perfect)
 
         if perfect != "y":
             useful = input("Did the generated code do anything useful? " + TERM_CHOICES)
-            useful = ask_for_valid_input(useful, VALID_INPUTS)
+            useful = ask_for_valid_input(useful)
         else:
             useful = ""
     else:
@@ -175,8 +173,8 @@ def human_review_input() -> Optional[Review]:
     )
 
 
-def ask_for_valid_input(ran, valid_inputs):
-    while ran not in valid_inputs:
+def ask_for_valid_input(ran):
+    while ran not in ("y", "n", "u"):
         ran = input("Invalid input. Please enter y, n, or u: ")
     return ran