Merge branch 'main' into 562-updata-work-summary-to-output-in-a-templ…

…ated-format

.pre-commit-config.yaml

@@ -4,9 +4,3 @@ repos:
     hooks:
       - id: flake8
         args: [--config=.flake8]
-
-  - repo: https://github.com/psf/black
-    rev: 23.3.0
-    hooks:
-      - id: black
-        args: [--line-length=88]

cli/kaizen_cli/cli.py

@@ -2,7 +2,7 @@
 from .config.manager import load_config
 from .commands.config_commands import config
 from .commands.unit_test_commands import unit_test
-from .commands.reviewer_commands import reviewer
+from .commands.reviewer_commands import reviewer, generate_commit_msg
 from .hooks.setup import hooks
 from kaizen.generator.e2e_tests import E2ETestGenerator
 
@@ -25,6 +25,7 @@ def ui_tests(url):
 cli.add_command(unit_test)
 cli.add_command(reviewer)
 cli.add_command(hooks)
+cli.add_command(generate_commit_msg)
 
 if __name__ == "__main__":
     cli()

cli/kaizen_cli/commands/reviewer_commands.py

@@ -1,4 +1,7 @@
 import click
+from kaizen.generator.pr_description import PRDescriptionGenerator
+from kaizen.llms.provider import LLMProvider
+from ..config.manager import load_config
 
 
 @click.group()
@@ -14,3 +17,20 @@ def work(github_url, branch):
     """Run reviewer work"""
     click.echo(f"Reviewing {github_url} on branch {branch}")
     # Implement the reviewer work logic here
+
+
+@click.command()
+@click.argument("diff", type=str, required=True)
+def generate_commit_msg(diff):
+    """Generate a commit message based on the provided diff"""
+    model_config = load_config()["language_model"]["models"][0]["litellm_params"]
+    generator = PRDescriptionGenerator(LLMProvider(model_config=model_config))
+    desc = generator.generate_pull_request_desc(
+        diff_text=diff,
+        pull_request_title="",
+        pull_request_desc="",
+        pull_request_files=[],
+        user="",
+    )
+    msg, _, _ = generator.generate_pr_commit_message(desc)
+    click.echo(f'{msg["subject"]}\n\n{msg["body"]}')

cli/kaizen_cli/config/manager.py

@@ -24,7 +24,7 @@ def load_config():
 
     # Override with environment variables
     for key, value in os.environ.items():
-        if key.startswith("MYAPP_"):
+        if key.startswith("KAIZEN_"):
             config_key = key[6:].lower().split("__")
             try:
                 parsed_value = json.loads(value)

cli/kaizen_cli/hooks/prepare-commit-msg

@@ -1,8 +1,14 @@
 #!/bin/sh
 # hooks/prepare-commit-msg
 
+# Change to the repository root directory
+cd "$(git rev-parse --show-toplevel)" || exit 1
+
+# Get the staged changes
+staged_diff=$(git diff --cached)
+
 # Run your CLI command and capture the output
-commit_msg=$(kaizen-cli generate-commit-msg)
+commit_info=$(kaizen-cli generate-commit-msg "$staged_diff")
 
-# Overwrite the commit message file with the generated message
-echo "$commit_msg" > "$1"
+# Write the commit info to the commit message file
+echo "$commit_info" > "$1"

cli/kaizen_cli/hooks/setup.py

@@ -15,14 +15,17 @@ def hooks():
 @click.argument("hook_type", type=click.Choice(HOOK_TYPES))
 def install(hook_type):
     """Install a specific git hook"""
-    source = os.path.join(os.path.dirname(__file__), "hooks", hook_type)
+    source = os.path.join(os.path.dirname(__file__), hook_type)
+    print(source)
     destination = os.path.join(".git", "hooks", hook_type)
 
     if not os.path.exists(source):
         click.echo(f"Error: Hook script for {hook_type} not found.")
         return
 
     try:
+        # Create the destination directory if it doesn't exist
+        os.makedirs(os.path.dirname(destination), exist_ok=True)
         shutil.copy(source, destination)
         os.chmod(destination, 0o755)
         click.echo(f"{hook_type} hook installed successfully")

examples/code_review/main.py

@@ -12,8 +12,8 @@
 
 logging.basicConfig(level="DEBUG")
 
-pr_diff = "https://github.com/Cloud-Code-AI/kaizen/pull/335.patch"
-pr_files = "https://api.github.com/repos/Cloud-Code-AI/kaizen/pulls/335/files"
+pr_diff = "https://github.com/Cloud-Code-AI/kaizen/pull/559.patch"
+pr_files = "https://api.github.com/repos/Cloud-Code-AI/kaizen/pulls/559/files"
 pr_title = "feat: updated the prompt to provide solution"
 
 diff_text = get_diff_text(pr_diff, "")
@@ -31,7 +31,7 @@
     reeval_response=False,
 )
 
-topics = clean_keys(review_data.topics, "important")
+topics = clean_keys(review_data.topics, "high")
 review_desc = create_pr_review_text(
     review_data.issues, code_quality=review_data.code_quality
 )
@@ -54,3 +54,4 @@
 print(desc_data)
 
 comit_message = pr_desc.generate_pr_commit_message(desc_data.desc)
+print(comit_message)

github_app/github_helper/pull_requests.py

@@ -19,8 +19,8 @@
 
 confidence_mapping = {
     "critical": 5,
-    "important": 4,
-    "moderate": 3,
+    "high": 4,
+    "medium": 3,
     "low": 2,
     "trivial": 1,
 }

kaizen/generator/pr_description.py

@@ -181,4 +181,4 @@ def generate_pr_commit_message(
             DESC=desc,
         )
         resp, usage = self.provider.chat_completion_with_json(prompt, user=user)
-        return resp, usage
+        return resp, usage, self.provider.model

kaizen/llms/provider.py

@@ -9,7 +9,7 @@
 import logging
 from collections import defaultdict
 
-DEFAULT_MAX_TOKENS = 8000
+DEFAULT_MAX_TOKENS = 4000
 
 
 def set_all_loggers_to_ERROR():
@@ -36,7 +36,7 @@ def set_all_loggers_to_ERROR():
 
 
 class LLMProvider:
-    DEFAULT_MODEL = "gpt-3.5-turbo-1106"
+    DEFAULT_MODEL = "gpt-4o-mini"
     DEFAULT_MAX_TOKENS = 4000
     DEFAULT_TEMPERATURE = 0
     DEFAULT_MODEL_CONFIG = {"model": DEFAULT_MODEL}
@@ -233,7 +233,12 @@ def is_inside_token_limit(self, PROMPT: str, percentage: float = 0.8) -> bool:
             {"role": "user", "content": PROMPT},
         ]
         token_count = litellm.token_counter(model=self.model, messages=messages)
-        max_tokens = litellm.get_max_tokens(self.model)
+        if token_count is None:
+            token_count = litellm.token_counter(model=self.DEFAULT_MODEL, text=PROMPT)
+        try:
+            max_tokens = litellm.get_max_tokens(self.model)
+        except Exception:
+            max_tokens = DEFAULT_MAX_TOKENS
         if not max_tokens:
             max_tokens = DEFAULT_MAX_TOKENS
         return token_count <= max_tokens * percentage
@@ -243,7 +248,10 @@ def available_tokens(
     ) -> int:
         if not model:
             model = self.model
-        max_tokens = litellm.get_max_tokens(model)
+        try:
+            max_tokens = litellm.get_max_tokens(model)
+        except Exception:
+            max_tokens = DEFAULT_MAX_TOKENS
         used_tokens = litellm.token_counter(model=model, text=message)
         if max_tokens:
             return int(max_tokens * percentage) - used_tokens