Chapter 1: Getting Started and Current Product Posture

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.

Learning Goals

• understand current repository and product posture
• choose hosted app, CLI, or self-hosting entry path
• run a first end-to-end issue workflow safely

Product Posture Checklist

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

Fast Start: GitHub App Workflow

1. install Sweep in your preferred surface from sweep.dev
2. open an issue prefixed with Sweep:
3. monitor generated PR and CI behavior
4. iterate using issue/PR comments starting with Sweep:

First-Run Guardrails

• start with small, concrete tasks
• include specific filenames in issue text
• keep one behavior change per issue whenever possible

Source References

• README
• Getting Started
• Sweep Website

Summary

You now have a realistic starting context and first execution path.

Next: Chapter 2: Issue to PR Workflow Architecture

Source Code Walkthrough

sweepai/cli.py

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.

sweepai/cli.py

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.

sweepai/cli.py

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.

sweepai/cli.py

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.

How These Components Connect

flowchart TD
    A[posthog_capture]
    B[load_config]
    C[fetch_issue_request]
    D[pascal_to_snake]
    A --> B
    B --> C
    C --> D