| layout | default |
|---|---|
| title | Chapter 1: Getting Started and Current Product Posture |
| nav_order | 1 |
| parent | Sweep Tutorial |
Welcome to Chapter 1: Getting Started and Current Product Posture. In this part of Sweep Tutorial: Issue-to-PR AI Coding Workflows on GitHub, you will build an intuitive mental model first, then move into concrete implementation details and practical production tradeoffs.
This chapter establishes where Sweep stands today and how to choose a practical adoption entry point.
- understand current repository and product posture
- choose hosted app, CLI, or self-hosting entry path
- run a first end-to-end issue workflow safely
| Signal | Interpretation |
|---|---|
| README points to JetBrains plugin | current primary product surface has shifted |
| docs still cover GitHub app and CLI | legacy workflows remain useful for study and operations |
| repo activity continues | ecosystem and operational knowledge still evolving |
- install Sweep in your preferred surface from sweep.dev
- open an issue prefixed with
Sweep: - monitor generated PR and CI behavior
- iterate using issue/PR comments starting with
Sweep:
- start with small, concrete tasks
- include specific filenames in issue text
- keep one behavior change per issue whenever possible
You now have a realistic starting context and first execution path.
Next: Chapter 2: Issue to PR Workflow Architecture
The posthog_capture function in sweepai/cli.py handles a key part of this chapter's functionality:
def posthog_capture(event_name, properties, *args, **kwargs):
POSTHOG_DISTINCT_ID = os.environ.get("POSTHOG_DISTINCT_ID")
if POSTHOG_DISTINCT_ID:
posthog.capture(POSTHOG_DISTINCT_ID, event_name, properties, *args, **kwargs)
def load_config():
if os.path.exists(config_path):
cprint(f"\nLoading configuration from {config_path}", style="yellow")
with open(config_path, "r") as f:
config = json.load(f)
for key, value in config.items():
try:
os.environ[key] = value
except Exception as e:
cprint(f"Error loading config: {e}, skipping.", style="yellow")
os.environ["POSTHOG_DISTINCT_ID"] = str(os.environ.get("POSTHOG_DISTINCT_ID", ""))
# Should contain:
# GITHUB_PAT
# OPENAI_API_KEY
# ANTHROPIC_API_KEY
# VOYAGE_API_KEY
# POSTHOG_DISTINCT_ID
def fetch_issue_request(issue_url: str, __version__: str = "0"):
(
protocol_name,
_,
_base_url,This function is important because it defines how Sweep Tutorial: Issue-to-PR AI Coding Workflows on GitHub implements the patterns covered in this chapter.
The load_config function in sweepai/cli.py handles a key part of this chapter's functionality:
def load_config():
if os.path.exists(config_path):
cprint(f"\nLoading configuration from {config_path}", style="yellow")
with open(config_path, "r") as f:
config = json.load(f)
for key, value in config.items():
try:
os.environ[key] = value
except Exception as e:
cprint(f"Error loading config: {e}, skipping.", style="yellow")
os.environ["POSTHOG_DISTINCT_ID"] = str(os.environ.get("POSTHOG_DISTINCT_ID", ""))
# Should contain:
# GITHUB_PAT
# OPENAI_API_KEY
# ANTHROPIC_API_KEY
# VOYAGE_API_KEY
# POSTHOG_DISTINCT_ID
def fetch_issue_request(issue_url: str, __version__: str = "0"):
(
protocol_name,
_,
_base_url,
org_name,
repo_name,
_issues,
issue_number,
) = issue_url.split("/")
cprint("Fetching installation ID...")This function is important because it defines how Sweep Tutorial: Issue-to-PR AI Coding Workflows on GitHub implements the patterns covered in this chapter.
The fetch_issue_request function in sweepai/cli.py handles a key part of this chapter's functionality:
def fetch_issue_request(issue_url: str, __version__: str = "0"):
(
protocol_name,
_,
_base_url,
org_name,
repo_name,
_issues,
issue_number,
) = issue_url.split("/")
cprint("Fetching installation ID...")
installation_id = -1
cprint("Fetching access token...")
_token, g = get_github_client(installation_id)
g: Github = g
cprint("Fetching repo...")
issue = g.get_repo(f"{org_name}/{repo_name}").get_issue(int(issue_number))
issue_request = IssueRequest(
action="labeled",
issue=IssueRequest.Issue(
title=issue.title,
number=int(issue_number),
html_url=issue_url,
user=IssueRequest.Issue.User(
login=issue.user.login,
type="User",
),
body=issue.body,
labels=[This function is important because it defines how Sweep Tutorial: Issue-to-PR AI Coding Workflows on GitHub implements the patterns covered in this chapter.
The pascal_to_snake function in sweepai/cli.py handles a key part of this chapter's functionality:
def pascal_to_snake(name):
return "".join(["_" + i.lower() if i.isupper() else i for i in name]).lstrip("_")
def get_event_type(event: Event | IssueEvent):
if isinstance(event, IssueEvent):
return "issues"
else:
return pascal_to_snake(event.type)[: -len("_event")]
@app.command()
def test():
cprint("Sweep AI is installed correctly and ready to go!", style="yellow")
@app.command()
def watch(
repo_name: str,
debug: bool = False,
record_events: bool = False,
max_events: int = 30,
):
if not os.path.exists(config_path):
cprint(
f"\nConfiguration not found at {config_path}. Please run [green]'sweep init'[/green] to initialize the CLI.\n",
style="yellow",
)
raise ValueError(
"Configuration not found, please run 'sweep init' to initialize the CLI."
)
posthog_capture(This function is important because it defines how Sweep Tutorial: Issue-to-PR AI Coding Workflows on GitHub implements the patterns covered in this chapter.
flowchart TD
A[posthog_capture]
B[load_config]
C[fetch_issue_request]
D[pascal_to_snake]
A --> B
B --> C
C --> D