diff --git a/README.md b/README.md
index f3a9707..df94af1 100644
--- a/README.md
+++ b/README.md
@@ -1,29 +1,18 @@
-
-🚧 This repo is under construction. Do not use. 🚧
-
-[INSERT YOUR LOGO IMAGE HERE (IF APPLICABLE)]
-
-
-
SLIM CLI Tool
-
Automate the application of best practices to your git repositories
-
-
-[INSERT YOUR BADGES HERE (SEE: https://shields.io)] [](https://nasa-ammos.github.io/slim/)
+[](https://nasa-ammos.github.io/slim/)
-[INSERT SCREENSHOT OF YOUR SOFTWARE, IF APPLICABLE]
-
+
SLIM CLI is a command-line tool designed to infuse SLIM best practices seamlessly with your development workflow. It fetches and applies structured SLIM best practices directly into your Git repositories. The tool leverages artificial intelligence capabilities to customize and tailor the application of SLIM best practices based on your repository's specifics.
@@ -31,10 +20,10 @@ SLIM CLI is a command-line tool designed to infuse SLIM best practices seamlessl
## Features
-- Command-line interface for applying SLIM best practices into Git development workflows
-- Fetches the latest SLIM best practices dynamically from SLIM's registry
-- Allows customization of best practices using advanced AI models before applying them to repositories
-- Deploys, or git adds, commits, and pushes changes to your repository's remote
+- Command-line interface for applying SLIM best practices into Git development workflows.
+- Fetches the latest SLIM best practices dynamically from SLIM's registry.
+- Allows customization of best practices using advanced AI models before applying them to repositories.
+- Deploys, or git adds, commits, and pushes changes to your repository's remote.
## Contents
@@ -94,7 +83,7 @@ This section provides detailed commands to interact with the SLIM CLI. Each comm
```
- To apply a best practice using AI customization:
```bash
- python slim_cli.py apply --best-practice-ids SLIM-3.1 --repo-urls https://github.com/your_org/your_repo.git --use-ai --model openai/gpt-4o
+ python slim-cli.py apply --best-practice-ids SLIM-123 --repo-urls https://github.com/your_org/your_repo.git --use-ai openai/gpt-4o
```
3. **Deploy a best practice**
@@ -127,7 +116,6 @@ This section provides detailed commands to interact with the SLIM CLI. Each comm
Each command can be modified with additional flags as needed for more specific tasks or environments.
-
## Changelog
See our [CHANGELOG.md](CHANGELOG.md) for a history of our changes.
diff --git a/requirements.txt b/requirements.txt
index c358ce7..6f6dfbc 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -3,4 +3,6 @@ tabulate
openai
python-dotenv
rich
-gitpython
\ No newline at end of file
+gitpython
+azure-identity
+ollama
\ No newline at end of file
diff --git a/slim-cli.py b/slim-cli.py
index 44fcd82..eea1f0c 100644
--- a/slim-cli.py
+++ b/slim-cli.py
@@ -18,11 +18,14 @@
import git
import urllib
+
+
# Constants
SLIM_REGISTRY_URI = "https://raw.githubusercontent.com/NASA-AMMOS/slim/issue-154/static/data/slim-registry.json"
SUPPORTED_MODELS = {
"openai": ["gpt-3.5-turbo", "gpt-4o"],
- "ollama": ["llama2", "mistral", "codellama"],
+ "ollama": ["llama3.1", "mistral", "codellama"],
+ "azure" : ["gpt-3.5-turbo", "gpt-4o"],
# Add more models as needed
}
GIT_BRANCH_NAME_FOR_MULTIPLE_COMMITS = 'slim-best-practices'
@@ -90,6 +93,9 @@ def create_slim_registry_dictionary(practices):
i += 1
return asset_mapping
+def get_ai_model_pairs(supported_models):
+ # return a list of "key/value" pairs
+ return [f"{key}/{model}" for key, models in supported_models.items() for model in models]
def use_ai(best_practice_id: str, repo_path: str, template_path: str, model: str = "openai/gpt-4o") -> Optional[str]:
"""
@@ -120,18 +126,23 @@ def use_ai(best_practice_id: str, repo_path: str, template_path: str, model: str
# Fetch the code base for SLIM-3.1 readme (limited to specific file types)
if best_practice_id == 'SLIM-1.1': #governance
reference = fetch_readme(repo_path)
+ # Construct the prompt for the AI
+ prompt = construct_prompt(template_content, best_practice, reference)
elif best_practice_id == 'SLIM-3.1': #readme
reference = fetch_code_base(repo_path)
+ # Construct the prompt for the AI
+ prompt = construct_prompt(template_content, best_practice, reference)
else:
reference = fetch_readme(repo_path)
+ # Construct the prompt for the AI
+ prompt = construct_prompt(template_content, best_practice, reference)
if not reference:
return None
- # Construct the prompt for the AI
- prompt = construct_prompt(template_content, best_practice, reference)
- print("prompt: ")
- print(prompt)
+
# Generate the content using the specified model
+ print("model: ")
+ print(model)
new_content = generate_content(prompt, model)
#print("output: ")
#print(new_content)
@@ -162,11 +173,14 @@ def fetch_code_base(repo_path: str) -> Optional[str]:
def construct_prompt(template_content: str, best_practice: Dict[str, Any], reference: str) -> str:
return (
f"Fill out all blanks in the template below that start with INSERT. Return the result as Markdown code.\n\n"
- #f"Best Practice: {best_practice['title']}\n"
- #f"Description: {best_practice['description']}\n\n"
+ ##f"Best Practice: {best_practice['title']}\n"
+ ##f"Description: {best_practice['description']}\n\n"
f"Template and output format:\n{template_content}\n\n"
f"Use the info:\n{reference}...\n\n"
f"Show only the updated template output as markdown code."
+
+ #f"Use the info:\n{reference}...\n\n"
+ #f"Generate unit tests"
)
def generate_content(prompt: str, model: str) -> Optional[str]:
@@ -182,6 +196,16 @@ def generate_content(prompt: str, model: str) -> Optional[str]:
print("\nError occurred during generation.")
print() # Print a newline at the end
return ''.join(collected_response)
+ elif model_provider == "azure":
+ collected_response = []
+ for token in generate_with_azure(prompt, model_name):
+ if token is not None:
+ print(token, end='', flush=True)
+ collected_response.append(token)
+ else:
+ print("\nError occurred during generation.")
+ print() # Print a newline at the end
+ return ''.join(collected_response)
elif model_provider == "ollama":
return generate_with_ollama(prompt, model_name)
else:
@@ -197,14 +221,68 @@ def read_file_content(file_path: str) -> Optional[str]:
logging.error(f"Error reading file {file_path}: {e}")
return None
+def generate_with_azure(prompt: str, model_name: str) -> Optional[str]:
+ from azure.identity import ClientSecretCredential
+ from dotenv import load_dotenv
+
+ load_dotenv()
+
+ TENANT_ID = os.getenv("AZURE_TENANT_ID")
+ CLIENT_ID = os.getenv("AZURE_CLIENT_ID")
+ CLIENT_SECRET = os.getenv("AZURE_CLIENT_SECRET")
+ API_ENDPOINT = os.getenv("API_ENDPOINT")
+ DEPLOYMENT_ID = os.getenv("DEPLOYMENT_ID")
+
+ # Check if all required environment variables are set
+ if not all([TENANT_ID, CLIENT_ID, CLIENT_SECRET, API_ENDPOINT, DEPLOYMENT_ID]):
+ missing_vars = [var for var, value in [
+ ("AZURE_TENANT_ID", TENANT_ID),
+ ("AZURE_CLIENT_ID", CLIENT_ID),
+ ("AZURE_CLIENT_SECRET", CLIENT_SECRET),
+ ("API_ENDPOINT", API_ENDPOINT),
+ ("DEPLOYMENT_ID", DEPLOYMENT_ID),
+ ] if value is None]
+ raise ValueError(f"Missing environment variables: {', '.join(missing_vars)}")
+
+ authority = "https://login.microsoftonline.com"
+ credential = ClientSecretCredential(
+ tenant_id=TENANT_ID,
+ client_id=CLIENT_ID,
+ client_secret=CLIENT_SECRET,
+ authority=authority,
+ )
+
+ access_token = credential.get_token("https://cognitiveservices.azure.com/.default").token
+ headers = {
+ "Authorization": f"Bearer {access_token}",
+ "Content-Type": "application/json"
+ }
+ data = {
+ "deploymentId": DEPLOYMENT_ID,
+ "messages": [{"role": "user", "content": prompt}],
+ "stream": True
+ }
+
+ try:
+ response = requests.post(API_ENDPOINT, headers=headers, json=data, stream=True)
+ response.raise_for_status()
+
+ for line in response.iter_lines():
+ if line:
+ chunk = line.decode("utf-8")
+ # Assuming the response format and extracting content accordingly
+ if 'delta' in chunk:
+ content = chunk.get("choices", [{}])[0].get("delta", {}).get("content")
+ if content:
+ yield content
+ except Exception as e:
+ print(f"An error occurred: {e}")
+ yield None
def generate_with_openai(prompt: str, model_name: str) -> Optional[str]:
from openai import OpenAI
client = OpenAI(api_key = os.getenv('OPENAI_API_KEY'))
- #if not openai.api_key:
- # logging.error("OpenAI API key is missing.")
- # return None
-
+
try:
response = client.chat.completions.create(
model=model_name,
@@ -221,13 +299,28 @@ def generate_with_openai(prompt: str, model_name: str) -> Optional[str]:
#return str(response.choices[0].message.content)
def generate_with_ollama(prompt: str, model_name: str) -> Optional[str]:
+ import ollama
+
try:
- response = subprocess.run(['ollama', 'run', model_name, prompt], capture_output=True, text=True, check=True)
- return response.stdout.strip()
- except subprocess.CalledProcessError as e:
+ response = ollama.chat(model=model_name, messages=[
+ {
+ 'role': 'user',
+ 'content': prompt,
+ },
+ ])
+ print(response['message']['content'])
+ return (response['message']['content'])
+ except Exception as e:
logging.error(f"Error running Ollama model: {e}")
return None
+ #try:
+ # response = subprocess.run(['ollama', 'run', model_name, prompt], capture_output=True, text=True, check=True)
+ # return response.stdout.strip()
+ #except subprocess.CalledProcessError as e:
+ # logging.error(f"Error running Ollama model: {e}")
+ # return None
+
def download_and_place_file(repo, url, filename, target_relative_path_in_repo=''):
# Create the full path where the file will be saved. By default write to root.
target_directory = os.path.join(repo.working_tree_dir, target_relative_path_in_repo)
@@ -259,7 +352,7 @@ def generate_git_branch_name(best_practice_ids):
else:
return None
-def apply_best_practices(best_practice_ids, use_ai_flag, repo_urls = None, existing_repo_dir = None, target_dir_to_clone_to = None):
+def apply_best_practices(best_practice_ids, use_ai_flag, model, repo_urls = None, existing_repo_dir = None, target_dir_to_clone_to = None):
for repo_url in repo_urls:
if len(best_practice_ids) > 1:
@@ -278,6 +371,7 @@ def apply_best_practices(best_practice_ids, use_ai_flag, repo_urls = None, exist
apply_best_practice(
best_practice_id=best_practice_id,
use_ai_flag=use_ai_flag,
+ model=model,
repo_url=repo_url,
target_dir_to_clone_to=target_dir_to_clone_to,
branch=GIT_BRANCH_NAME_FOR_MULTIPLE_COMMITS)
@@ -288,23 +382,25 @@ def apply_best_practices(best_practice_ids, use_ai_flag, repo_urls = None, exist
apply_best_practice(
best_practice_id=best_practice_id,
use_ai_flag=use_ai_flag,
+ model=model,
repo_url=repo_url,
target_dir_to_clone_to=repo_dir,
branch=GIT_BRANCH_NAME_FOR_MULTIPLE_COMMITS)
else:
for best_practice_id in best_practice_ids:
- apply_best_practice(best_practice_id=best_practice_id, use_ai_flag=use_ai_flag, existing_repo_dir=existing_repo_dir)
+ apply_best_practice(best_practice_id=best_practice_id, use_ai_flag=use_ai_flag, model=model, existing_repo_dir=existing_repo_dir)
elif len(best_practice_ids) == 1:
apply_best_practice(
best_practice_id=best_practice_ids[0],
use_ai_flag=use_ai_flag,
+ model=model,
repo_url=repo_url,
existing_repo_dir=existing_repo_dir,
target_dir_to_clone_to=target_dir_to_clone_to)
else:
logging.error(f"No best practice IDs specified.")
-def apply_best_practice(best_practice_id, use_ai_flag, repo_url = None, existing_repo_dir = None, target_dir_to_clone_to = None, branch = None):
+def apply_best_practice(best_practice_id, use_ai_flag, model, repo_url = None, existing_repo_dir = None, target_dir_to_clone_to = None, branch = None):
applied_file_path = None # default return value is invalid applied best practice
logging.debug(f"AI features {'enabled' if use_ai_flag else 'disabled'} for applying best practices")
@@ -394,12 +490,12 @@ def apply_best_practice(best_practice_id, use_ai_flag, repo_url = None, existing
# Process best practice by ID
if best_practice_id == 'SLIM-1.1':
applied_file_path = download_and_place_file(git_repo, uri, 'GOVERNANCE.md')
- if use_ai_flag:
+ if use_ai_flag and model:
#logging.warning(f"AI apply features unsupported for best practice {best_practice_id} currently")
# Custom AI processing code to go here using and modifying applied_file_path content
- ai_content = use_ai(best_practice_id, git_repo.working_tree_dir, applied_file_path) #template file path
+ ai_content = use_ai(best_practice_id, git_repo.working_tree_dir, applied_file_path, model) #template file path
if ai_content:
with open(applied_file_path, 'w') as f:
f.write(ai_content)
@@ -408,11 +504,11 @@ def apply_best_practice(best_practice_id, use_ai_flag, repo_url = None, existing
logging.warning(f"AI generation failed for best practice {best_practice_id}")
elif best_practice_id == 'SLIM-1.2':
applied_file_path = download_and_place_file(git_repo, uri, 'GOVERNANCE.md')
- if use_ai_flag:
+ if use_ai_flag and model:
#logging.warning(f"AI apply features unsupported for best practice {best_practice_id} currently")
# Custom AI processing code to go here using and modifying applied_file_path content
- ai_content = use_ai(best_practice_id, git_repo.working_tree_dir, applied_file_path)
+ ai_content = use_ai(best_practice_id, git_repo.working_tree_dir, applied_file_path, model)
if ai_content:
with open(applied_file_path, 'w') as f:
f.write(ai_content)
@@ -421,11 +517,11 @@ def apply_best_practice(best_practice_id, use_ai_flag, repo_url = None, existing
logging.warning(f"AI generation failed for best practice {best_practice_id}")
elif best_practice_id == 'SLIM-3.1':
applied_file_path = download_and_place_file(git_repo, uri, 'README.md')
- if use_ai_flag:
+ if use_ai_flag and model:
#logging.warning(f"AI apply features unsupported for best practice {best_practice_id} currently")
# Custom AI processing code to go here using and modifying applied_file_path content
- ai_content = use_ai(best_practice_id, git_repo.working_tree_dir, applied_file_path)
+ ai_content = use_ai(best_practice_id, git_repo.working_tree_dir, applied_file_path, model)
if ai_content:
with open(applied_file_path, 'w') as f:
f.write(ai_content)
@@ -434,11 +530,11 @@ def apply_best_practice(best_practice_id, use_ai_flag, repo_url = None, existing
logging.warning(f"AI generation failed for best practice {best_practice_id}")
elif best_practice_id == 'SLIM-4.1':
applied_file_path = download_and_place_file(git_repo, uri, '.github/ISSUE_TEMPLATE/bug_report.md')
- if use_ai_flag:
+ if use_ai_flag and model:
#logging.warning(f"AI apply features unsupported for best practice {best_practice_id} currently")
# Custom AI processing code to go here using and modifying applied_file_path content
- ai_content = use_ai(best_practice_id, git_repo.working_tree_dir, applied_file_path)
+ ai_content = use_ai(best_practice_id, git_repo.working_tree_dir, applied_file_path, model)
if ai_content:
with open(applied_file_path, 'w') as f:
f.write(ai_content)
@@ -447,11 +543,11 @@ def apply_best_practice(best_practice_id, use_ai_flag, repo_url = None, existing
logging.warning(f"AI generation failed for best practice {best_practice_id}")
elif best_practice_id == 'SLIM-4.2':
applied_file_path = download_and_place_file(git_repo, uri, '.github/ISSUE_TEMPLATE/bug_report.yml')
- if use_ai_flag:
+ if use_ai_flag and model:
#logging.warning(f"AI apply features unsupported for best practice {best_practice_id} currently")
# Custom AI processing code to go here using and modifying applied_file_path content
- ai_content = use_ai(best_practice_id, git_repo.working_tree_dir, applied_file_path)
+ ai_content = use_ai(best_practice_id, git_repo.working_tree_dir, applied_file_path, model)
if ai_content:
with open(applied_file_path, 'w') as f:
f.write(ai_content)
@@ -460,11 +556,11 @@ def apply_best_practice(best_practice_id, use_ai_flag, repo_url = None, existing
logging.warning(f"AI generation failed for best practice {best_practice_id}")
elif best_practice_id == 'SLIM-4.3':
applied_file_path = download_and_place_file(git_repo, uri, '.github/ISSUE_TEMPLATE/new_feature.md')
- if use_ai_flag:
+ if use_ai_flag and model:
#logging.warning(f"AI apply features unsupported for best practice {best_practice_id} currently")
# Custom AI processing code to go here using and modifying applied_file_path content
- ai_content = use_ai(best_practice_id, git_repo.working_tree_dir, applied_file_path)
+ ai_content = use_ai(best_practice_id, git_repo.working_tree_dir, applied_file_path, model)
if ai_content:
with open(applied_file_path, 'w') as f:
f.write(ai_content)
@@ -473,11 +569,11 @@ def apply_best_practice(best_practice_id, use_ai_flag, repo_url = None, existing
logging.warning(f"AI generation failed for best practice {best_practice_id}")
elif best_practice_id == 'SLIM-4.4':
applied_file_path = download_and_place_file(git_repo, uri, '.github/ISSUE_TEMPLATE/new_feature.yml')
- if use_ai_flag:
+ if use_ai_flag and model:
#logging.warning(f"AI apply features unsupported for best practice {best_practice_id} currently")
# Custom AI processing code to go here using and modifying applied_file_path content
- ai_content = use_ai(best_practice_id, git_repo.working_tree_dir, applied_file_path)
+ ai_content = use_ai(best_practice_id, git_repo.working_tree_dir, applied_file_path, model)
if ai_content:
with open(applied_file_path, 'w') as f:
f.write(ai_content)
@@ -486,8 +582,8 @@ def apply_best_practice(best_practice_id, use_ai_flag, repo_url = None, existing
logging.warning(f"AI generation failed for best practice {best_practice_id}")
elif best_practice_id == 'SLIM-5.1':
applied_file_path = download_and_place_file(git_repo, uri, 'CHANGELOG.md')
- if use_ai_flag:
- ai_content = use_ai(best_practice_id, git_repo.working_tree_dir, applied_file_path)
+ if use_ai_flag and model:
+ ai_content = use_ai(best_practice_id, git_repo.working_tree_dir, applied_file_path, model)
if ai_content:
with open(applied_file_path, 'w') as f:
f.write(ai_content)
@@ -496,8 +592,8 @@ def apply_best_practice(best_practice_id, use_ai_flag, repo_url = None, existing
logging.warning(f"AI generation failed for best practice {best_practice_id}")
elif best_practice_id == 'SLIM-7.1':
applied_file_path = download_and_place_file(git_repo, uri, '.github/PULL_REQUEST_TEMPLATE.md')
- if use_ai_flag:
- ai_content = use_ai(best_practice_id, git_repo.working_tree_dir, applied_file_path)
+ if use_ai_flag and model:
+ ai_content = use_ai(best_practice_id, git_repo.working_tree_dir, applied_file_path, model)
if ai_content:
with open(applied_file_path, 'w') as f:
f.write(ai_content)
@@ -506,11 +602,11 @@ def apply_best_practice(best_practice_id, use_ai_flag, repo_url = None, existing
logging.warning(f"AI generation failed for best practice {best_practice_id}")
elif best_practice_id == 'SLIM-8.1':
applied_file_path = download_and_place_file(git_repo, uri, 'CODE_OF_CONDUCT.md')
- if use_ai_flag:
+ if use_ai_flag and model:
#logging.warning(f"AI apply features unsupported for best practice {best_practice_id} currently")
# Custom AI processing code to go here using and modifying applied_file_path content
- ai_content = use_ai(best_practice_id, git_repo.working_tree_dir, applied_file_path)
+ ai_content = use_ai(best_practice_id, git_repo.working_tree_dir, applied_file_path, model)
if ai_content:
with open(applied_file_path, 'w') as f:
f.write(ai_content)
@@ -519,8 +615,8 @@ def apply_best_practice(best_practice_id, use_ai_flag, repo_url = None, existing
logging.warning(f"AI generation failed for best practice {best_practice_id}")
elif best_practice_id == 'SLIM-9.1':
applied_file_path = download_and_place_file(git_repo, uri, 'CONTRIBUTING.md')
- if use_ai_flag:
- ai_content = use_ai(best_practice_id, git_repo.working_tree_dir, applied_file_path)
+ if use_ai_flag and model:
+ ai_content = use_ai(best_practice_id, git_repo.working_tree_dir, applied_file_path, model)
if ai_content:
with open(applied_file_path, 'w') as f:
f.write(ai_content)
@@ -529,14 +625,14 @@ def apply_best_practice(best_practice_id, use_ai_flag, repo_url = None, existing
logging.warning(f"AI generation failed for best practice {best_practice_id}")
elif best_practice_id == 'SLIM-13.1':
applied_file_path = download_and_place_file(git_repo, uri, 'TESTING.md')
- if use_ai_flag:
- ai_content = use_ai(best_practice_id, git_repo.working_tree_dir, applied_file_path)
+ if use_ai_flag and model:
+ ai_content = use_ai(best_practice_id, git_repo.working_tree_dir, applied_file_path, model)
if ai_content:
with open(applied_file_path, 'w') as f:
f.write(ai_content)
logging.info(f"Applied AI-generated content to {applied_file_path}")
else:
- logging.warning(f"AI generation failed for best practice {best_practice_id}")
+ logging.warning(f"AI generation failed for best practice {best_practice_id}")
else:
applied_file_path = None # nothing was modified
logging.warning(f"SLIM best practice {best_practice_id} not supported.")
@@ -615,7 +711,7 @@ def deploy_best_practice(best_practice_id, repo_dir, remote_name='origin', commi
return False
-def apply_and_deploy_best_practices(best_practice_ids, use_ai_flag, remote_name = GIT_DEFAULT_REMOTE_NAME, commit_message = GIT_DEFAULT_COMMIT_MESSAGE, repo_urls=None, existing_repo_dir=None, target_dir_to_clone_to=None):
+def apply_and_deploy_best_practices(best_practice_ids, use_ai_flag, model, remote_name = GIT_DEFAULT_REMOTE_NAME, commit_message = GIT_DEFAULT_COMMIT_MESSAGE, repo_urls=None, existing_repo_dir=None, target_dir_to_clone_to=None):
branch_name = generate_git_branch_name(best_practice_ids)
for repo_url in repo_urls:
@@ -629,6 +725,7 @@ def apply_and_deploy_best_practices(best_practice_ids, use_ai_flag, remote_name
git_repo = apply_best_practice(
best_practice_id=best_practice_id,
use_ai_flag=use_ai_flag,
+ model=model,
repo_url=repo_url,
target_dir_to_clone_to=target_dir_to_clone_to,
branch=branch_name)
@@ -650,6 +747,7 @@ def apply_and_deploy_best_practices(best_practice_ids, use_ai_flag, remote_name
git_repo = apply_best_practice(
best_practice_id=best_practice_id,
use_ai_flag=use_ai_flag,
+ model=model,
repo_url=repo_url,
target_dir_to_clone_to=repo_dir,
branch=branch_name)
@@ -666,7 +764,7 @@ def apply_and_deploy_best_practices(best_practice_ids, use_ai_flag, remote_name
logging.error(f"Unable to deploy best practice '{best_practice_id}' because apply failed.")
else:
for best_practice_id in best_practice_ids:
- git_repo = apply_best_practice(best_practice_id=best_practice_id, use_ai_flag=use_ai_flag, existing_repo_dir=existing_repo_dir)
+ git_repo = apply_best_practice(best_practice_id=best_practice_id, use_ai_flag=use_ai_flag, model=model, existing_repo_dir=existing_repo_dir)
# deploy just the last best practice, which deploys others as well
if git_repo:
@@ -682,6 +780,7 @@ def apply_and_deploy_best_practices(best_practice_ids, use_ai_flag, remote_name
git_repo = apply_best_practice(
best_practice_id=best_practice_ids[0],
use_ai_flag=use_ai_flag,
+ model=model,
repo_url=repo_url,
existing_repo_dir=existing_repo_dir,
target_dir_to_clone_to=branch_name)
@@ -689,7 +788,7 @@ def apply_and_deploy_best_practices(best_practice_ids, use_ai_flag, remote_name
# deploy just the last best practice, which deploys others as well
if git_repo:
deploy_best_practice(
- best_practice_id=best_practice_id,
+ best_practice_id=best_practice_ids[0],
repo_dir=git_repo.working_tree_dir,
remote_name=remote_name,
commit_message=commit_message,
@@ -699,25 +798,26 @@ def apply_and_deploy_best_practices(best_practice_ids, use_ai_flag, remote_name
else:
logging.error(f"No best practice IDs specified.")
- # for best_practice_id in best_practice_ids:
- # result = apply_and_deploy_best_practice(
- # best_practice_id,
- # use_ai_flag,
- # remote_name,
- # commit_message,
- # repo_url,
- # existing_repo_dir,
- # target_dir_to_clone_to,
- # branch=branch_name)
- # if not result:
- # logging.error(f"Failed to apply and deploy best practice ID: {best_practice_id}")
-
-def apply_and_deploy_best_practice(best_practice_id, use_ai_flag, remote_name=GIT_DEFAULT_REMOTE_NAME, commit_message=GIT_DEFAULT_COMMIT_MESSAGE, repo_url = None, existing_repo_dir = None, target_dir_to_clone_to = None, branch = None):
+ for best_practice_id in best_practice_ids:
+ result = apply_and_deploy_best_practice(
+ best_practice_id,
+ use_ai_flag,
+ model,
+ remote_name,
+ commit_message,
+ repo_url,
+ existing_repo_dir,
+ target_dir_to_clone_to,
+ branch=branch_name)
+ if not result:
+ logging.error(f"Failed to apply and deploy best practice ID: {best_practice_id}")
+
+def apply_and_deploy_best_practice(best_practice_id, use_ai_flag, model, remote_name=GIT_DEFAULT_REMOTE_NAME, commit_message=GIT_DEFAULT_COMMIT_MESSAGE, repo_url = None, existing_repo_dir = None, target_dir_to_clone_to = None, branch = None):
logging.debug("AI customization enabled for applying and deploying best practices" if use_ai_flag else "AI customization disabled")
logging.debug(f"Applying and deploying best practice ID: {best_practice_id}")
# Apply the best practice
- git_repo = apply_best_practice(best_practice_id=best_practice_id, use_ai_flag=use_ai_flag, repo_url=repo_url, existing_repo_dir=existing_repo_dir, target_dir_to_clone_to=target_dir_to_clone_to, branch=branch)
+ git_repo = apply_best_practice(best_practice_id=best_practice_id, use_ai_flag=use_ai_flag, model=model, repo_url=repo_url, existing_repo_dir=existing_repo_dir, target_dir_to_clone_to=target_dir_to_clone_to, branch=branch)
# Deploy the best practice if applied successfully
if git_repo:
@@ -747,10 +847,13 @@ def create_parser():
parser_apply.add_argument('--repo-urls', nargs='+', required=False, help='Repository URLs to apply to. Do not use if --repo-dir specified')
parser_apply.add_argument('--repo-dir', required=False, help='Repository directory location on local machine. Only one repository supported')
parser_apply.add_argument('--clone-to_dir', required=False, help='Local path to clone repository to. Compatible with --repo-urls')
- parser_apply.add_argument('--use-ai', action='store_true', help='Automatically customize the application of the best practice')
+ #parser_apply.add_argument('--use-ai', action='store_true', help='Automatically customize the application of the best practice')
+ parser_apply.add_argument('--use-ai', metavar='MODEL', help=f"Automatically customize the application of the best practice with an AI model. Support for: {get_ai_model_pairs(SUPPORTED_MODELS)}")
+ #parser_apply.add_argument('--model', required=False, help='Model name (openai/gpt-4o) for using ai')
parser_apply.set_defaults(func=lambda args: apply_best_practices(
best_practice_ids=args.best_practice_ids,
- use_ai_flag=args.use_ai,
+ use_ai_flag=bool(args.use_ai),
+ model=args.use_ai if args.use_ai else None,
repo_urls=args.repo_urls,
existing_repo_dir=args.repo_dir,
target_dir_to_clone_to=args.clone_to_dir
@@ -775,12 +878,15 @@ def create_parser():
parser_apply_deploy.add_argument('--repo-urls', nargs='+', required=False, help='Repository URLs to apply to. Do not use if --repo-dir specified')
parser_apply_deploy.add_argument('--repo-dir', required=False, help='Repository directory location on local machine. Only one repository supported')
parser_apply_deploy.add_argument('--clone-to-dir', required=False, help='Local path to clone repository to. Compatible with --repo-urls')
- parser_apply_deploy.add_argument('--use-ai', action='store_true', help='Automatically customize the application of the best practice')
+ parser_apply_deploy.add_argument('--use-ai', metavar='MODEL', help='Automatically customize the application of the best practice with the specified AI model. Support for: {get_ai_model_pairs(SUPPORTED_MODELS)}')
+ #parser_apply_deploy.add_argument('--use-ai', action='store_true', help='Automatically customize the application of the best practice')
+ #parser_apply_deploy.add_argument('--model', required=False, help='Model name (ollama/gpt-4o) for using ai')
parser_apply_deploy.add_argument('--remote-name', required=False, default=GIT_DEFAULT_REMOTE_NAME, help=f"Name of the remote to push changes to. Default: '{GIT_DEFAULT_REMOTE_NAME}")
parser_apply_deploy.add_argument('--commit-message', required=False, default=GIT_DEFAULT_COMMIT_MESSAGE, help=f"Commit message to use for the deployment. Default '{GIT_DEFAULT_COMMIT_MESSAGE}")
parser_apply_deploy.set_defaults(func=lambda args: apply_and_deploy_best_practices(
best_practice_ids=args.best_practice_ids,
- use_ai_flag=args.use_ai,
+ use_ai_flag=bool(args.use_ai),
+ model=args.use_ai if args.use_ai else None,
remote_name=args.remote_name,
commit_message=args.commit_message,
repo_urls=args.repo_urls,