ProspectOS · Maps Scout

A small, personal-use prospect workspace. It sends one search at a time to the bundled gosom/google-maps-scraper worker, waits for its asynchronous job to finish, filters places already in the local catalogue, and presents the remaining places for human review.

The interface is split into Dashboard, Discover, Prospects, Runs, Logs, Teach AI, Promotions, and Settings views. It includes website health and email evidence, explainable scoring, domain ideas, suppression, CSV export, scheduled runs, rescans, and human review. It never sends outreach automatically. The Prospects explorer has an All high potential tab and category tabs populated from each discovery run, with every tab sorted from highest to lowest opportunity score. It also provides search, potential-score, website-health, public-email, and review-status filters; review status itself is changed inside the prospect drawer so list rows stay focused on evidence.

Optional AI can analyse a prospect and draft a subject/email from supplied evidence and your offer; you edit and approve the draft yourself. Drafts now also return the reasoning, stored evidence IDs used, facts that still need confirmation, and a follow-up review note so a polished email is not mistaken for verified information. The draft dialog also includes a revision chat: after generating a draft, ask for changes such as “make this warmer”, “shorten the opening”, or “use the selected promotion more naturally”. The chat sends the current editable subject/body and applies the returned revision in place; it never sends an email. Every revision is saved on the prospect and recorded in the AI/audit logs for review. Draft instructions explicitly ask the model to choose a prospect-specific angle, use one or two real facts, vary its opening and close, avoid stock greetings and marketing filler, and read naturally aloud. The strategy note and variation hint are private planning context rather than copy to paste, so each run can use a different natural phrasing without inventing claims. The Teach AI view stores the sender company's website, services, packages, prices, and writing guidance. Its bounded public-page reader captures a reviewable homepage text snapshot that is included in AI assessments and email drafts. The Promotions view stores dated, active/inactive offers; an active promotion can be selected in the email draft dialog and is passed to the AI with its exact description and terms. From a prospect's detail drawer, Generate modern mockup creates a shareable, mobile-first website concept using the prospect's public details and (when available) a fresh snapshot of its current homepage. The preview is a standalone HTML document (or a four-page HTML site) ready to place in a PHP/HTML hosting folder; it does not require PHP, JavaScript, forms, tracking, external fonts, or unapproved remote assets to render. If AI is configured it can produce a tailored design; when AI is unavailable the deterministic fallback still produces a polished preview. Each tokenised link is read-only, marked as a concept, sent with noindex, and can be included once in a human-reviewed email draft. It is not a production site and should be checked and edited before sending. The design prompt receives a small category-matched library of Unsplash stock images; generated pages may use only those supplied image URLs, and the fallback template uses the same curated set. Each saved concept also has an Edit template action. It opens the shareable site beside a chat-style editor where you can ask for copy, emphasis, palette, imagery, or layout changes. The request is sent to the configured AI with the prospect's public evidence and rendered through the same deterministic, sanitised template renderer. Every successful edit creates a new version and share token; earlier versions remain in the prospect drawer and are never overwritten. If AI is unavailable, safe visual hints such as “make it darker” still select one of the built-in palettes. The Logs view separates API calls, user actions, AI requests, searches, Browser Use/tool steps, and errors. AI request payloads and responses are truncated and credentials such as API keys, authorization headers, tokens, and passwords are redacted. Logs are retained up to LOG_RETENTION entries (20,000 by default). From a prospect's detail drawer, Assess with AI stores a contact probability, recommendation, and short evidence-grounded rationale for that specific company. The same drawer can optionally run a bounded website investigation to look for a likely official website when Maps did not list one. The investigator first opens public Bing/alternative result pages with headless Playwright and reads the visible result links and snippets directly from the DOM; it does not rely on unstable Browser Use element indexes. Search links are persisted immediately and then checked for reachability/title identity evidence. Browser Use remains as a fallback when no parseable result links are found. Candidate domains are shown with evidence and must be accepted by you before they replace the catalogue record.

Prospect review status is changed inside the detail drawer (In review, Accepted, Rejected, or Contacted), keeping the explorer focused on discovery categories and opportunity scores. The AI draft dialog shows the prospect evidence, lets you choose a voice and call-to-action, and produces an editable subject and plain-text email using a stricter evidence-grounded prompt.

Start the stack

cp .env.example .env
docker compose up -d --build

Open http://SERVER:8000 for ProspectOS. The Maps worker is available on http://SERVER:8081 if you want to inspect its native Web UI.

How the worker connects

No Google Cloud API key is required. The bundled standard worker exposes a local REST API on the Docker network, and ProspectOS calls it directly.

The app uses /api/v1/jobs to queue a search, polls /api/v1/jobs/{id}, and downloads /api/v1/jobs/{id}/download when the job finishes. Jobs are deliberately asynchronous because a Maps scrape can take several minutes.

Only set GMAPS_API_MODE=saas and GMAPS_API_KEY=... if you deliberately replace the bundled worker with gosom's optional SaaS edition.

A run that loses its worker connection is shown as failed with a specific error rather than remaining stuck forever.

Configuration

Variable	Default	Purpose
HOST_PORT	8000	Host port for ProspectOS
PUBLIC_BASE_URL	empty	Public origin used for client-facing mockup share links; set it behind a reverse proxy if forwarded host headers are unavailable
GMAPS_HOST_PORT	8081	Host port for the Maps worker admin UI
GMAPS_API_MODE	standard	standard for the bundled worker; saas only for the optional SaaS API
GMAPS_API_KEY	empty	Not required in standard mode; only used in SaaS mode
GMAPS_REQUEST_TIMEOUT	900	Maximum wait for the Maps worker in seconds; raise it for very large searches
GMAPS_POLL_SECONDS	2	Poll interval while a job is running
OUTBOUND_USER_AGENT	ProspectOS/2.0 (+personal-use)	Identifies provider HTTP requests; avoids Python's default client fingerprint
DISCOVERY_BACKEND	gmaps when GMAPS_URL is set	Set to browser only for the bounded public-search fallback
BROWSER_USE_ENABLED	true	Enables the optional website-candidate investigator
BROWSER_USE_MAX_STEPS	10	Maximum Browser Use actions for one investigation (3–50); can be changed in Settings
BROWSER_USE_TIMEOUT_SECONDS	600	Hard timeout for one investigation (30–1800 seconds); can be changed in Settings
BROWSER_USE_LLM_TIMEOUT_SECONDS	90	Timeout for one Browser Use model call (10–300 seconds); can be changed in Settings
WEBSITE_SCAN_TIMEOUT	8	Per-page public website/email scan timeout (2–60 seconds); can be changed in Settings
ANONYMIZED_TELEMETRY	false	Keeps Browser Use telemetry disabled in this personal deployment
LOG_RETENTION	20000	Maximum operational log entries retained in SQLite
AI_PROVIDER	custom	Set to nous, deepseek, or custom for an OpenAI-compatible endpoint
AI_BASE_URL	empty	Optional OpenAI-compatible /chat/completions endpoint; DeepSeek uses https://api.deepseek.com/v1 automatically
AI_MODEL	empty	Model name; DeepSeek defaults to deepseek-chat
AI_API_KEY	empty	Optional provider key; keep server-side
AI_MOCKUP_TIMEOUT_SECONDS	45	Maximum AI wait for mockup copy before the deterministic premium renderer is used (20–300 seconds)

Nous Research Portal

Choose Nous Portal · free models in Settings, paste a Nous API key, select a free model, save, and use Test connection before drafting a message. The app uses https://inference-api.nousresearch.com/v1 automatically and tries the live /models catalog; if the catalog is unavailable it shows a stable fallback list of the free models currently published by Nous. Availability and model IDs can change, so refresh Settings periodically.

If a Nous request returns ai_cloudflare_1010, rebuild the app from the latest source so provider requests include the explicit ProspectOS/2.0 client identity. The old build used Python's default Python-urllib fingerprint, which can be rejected by the Portal's Cloudflare policy. This is not a Maps error and it cannot be fixed by changing the model name. If the rebuilt app still receives 1010, test the same key from the server with the provider's documented OpenAI-compatible endpoint and contact Nous support if the endpoint continues to block that client; do not try to evade the security challenge.

The bundled fallback entries are LongCat 2.0, Solar Pro 4, Step 3.7 Flash, Laguna S 2.1, Laguna XS 2.1, Ling 3.0 Flash Fin, and Ling 3.0 Flash Sante (using the Portal's :free model suffix).

Hermes Agent has its own browser-based OAuth flow, but that flow stores a Hermes refresh token and is not a portable credential for this standalone Docker app. ProspectOS therefore uses a server-side Nous API key here. The key is never returned by the Settings API or sent to the browser after saving.

Browser Use website investigator

Browser Use is an optional local browser agent. The website finder first uses deterministic Playwright DOM extraction so a search result cannot be lost just because an AI click target became stale. It uses the AI provider only as a bounded fallback when no usable result link was extracted. Both paths are limited to unauthenticated public research: no proxy rotation, stealth fingerprints, CAPTCHA solving, login, or challenge bypass is configured. If a site blocks the browser, the action records the block and leaves any partial candidate links intact. Browser Use itself is open source, but fallback investigations still use your configured model/provider and may consume quota.

To use it:

1. Configure and test an AI provider in Settings (a Nous key plus a selected model also works).
2. Open a prospect that has no detected website and choose Find possible websites.
3. Review the returned domains and evidence. Choose Accept only when the domain is genuinely the business's official site; accepting runs the normal website health and public-email scan.

The API equivalents are POST /api/prospects/{id}/website-candidates, GET /api/prospects/{id}/website-candidates, and PATCH /api/prospects/{id}/website-candidates/{candidate_id} with {"status":"accepted"} or {"status":"rejected"}.

Runtime settings

Open Settings → Browser and discovery timing to change Browser Use's enabled state, total investigation timeout, maximum agent steps, and per-call AI timeout. The same panel controls the Maps worker wait timeout/poll interval, search depth, website health/email scan timeout, and the maximum wait for AI-written mockup copy. Values are stored in the local SQLite database, survive container restarts, and override .env defaults for new runs. The safe UI ranges prevent a malformed value from creating an unbounded worker; a slow mockup provider automatically falls back to the complete local renderer.

The app stores its catalogue in the prospect_data Docker volume. The worker stores its own job data in gmaps_data; keep both volumes if you want to retain history. To inspect status:

docker compose ps
docker compose logs --tail=100 app
docker compose logs --tail=100 gmaps

Local fallback mode

For a quick local smoke test without the Maps worker:

DISCOVERY_BACKEND=browser GMAPS_URL= docker compose up -d --build

This uses Playwright against public search engines, keeps the same catalogue and review UI, and does not bypass CAPTCHAs or other access controls.

Data and review behavior

Each saved place includes its name, Maps link, website (when present), root domain, address, phone, category, rating, review count, public emails returned by the worker when available, source ID, and raw result JSON. A place with no website is still retained using a stable maps:<place_id> catalogue key, so it can be reviewed as a potential website opportunity. Existing websites are deduplicated by root domain.

Email extraction is always enabled. The worker may visit each public business website found by Maps; expect longer runs and review the resulting provenance before using any contact information. It does not invent email addresses when none are published.

Website scans are bounded and SSRF-safe. A scan records HTTP status, final URL, latency, HTTPS/TLS, title, technology hints, contact-page emails, and errors. Use /api/prospects/{id}/scan for a manual rescan. The explorer's “Draft AI email” action calls /api/prospects/{id}/message, and Assess with AI calls /api/prospects/{id}/assess; both require the optional AI variables above and accepts your exact offer/instructions (for example, the Gold Plus R119/month plan and a free rebuild). Suppressions are enforced before new records are saved and can be managed through /api/suppressions.

The Teach AI page saves a company_profile object through POST /api/settings. Its Read website now action calls POST /api/company-profile/learn and stores a bounded, reviewable public homepage snapshot. Promotions are managed with GET/POST /api/promotions, PATCH /api/promotions/{id}, and DELETE /api/promotions/{id}. An active promotion selected in the draft dialog is sent as promotion_id and retained on that prospect's draft. The initial email draft is generated with POST /api/prospects/{id}/message. The revision chat calls POST /api/prospects/{id}/message/edit with the current subject, message, and a bounded wording instruction. The endpoint reuses the same evidence and offer boundary, preserves a selected mockup preview URL, and persists the revised subject, body, rationale, unknowns, and evidence IDs. Mockups are created with POST /api/prospects/{id}/mockup, listed with GET /api/prospects/{id}/mockups, and opened by their public /mockups/{token} share URL. Choose mode=onepage for a single scrollable landing page or mode=multipage for real Home, Services, About, and Contact routes. Both modes use the same deterministic premium renderer: responsive sticky navigation, layered hero imagery, editorial service cards, accessible contact calls-to-action, a dark structured footer, hover states, and CSS-only entrance/ambient animations with reduced-motion support. AI is asked only for bounded copy and curated image choices; malformed, truncated, unavailable, or slow AI responses fall back to the same complete renderer instead of failing the request. Set PUBLIC_BASE_URL when the reverse proxy does not forward the public host; otherwise the link is built from the request's forwarded host or Host header. Use GET /api/mockups/{id} to load editor metadata and POST /api/mockups/{id}/edit with {"instruction":"...","page":"all"} to create the next version. The edit endpoint requires reviewer access, limits instructions to 3,000 characters, and accepts all, home, services, about, or contact as the page scope.

Tests

python3 -m py_compile api/server.py
node --check web/app.js
python3 -m unittest discover -s tests -q

This project is packaged for personal research. Public availability does not override a website's terms, robots controls, or applicable privacy law; keep searches small, use the worker only on data you are permitted to collect, and do not turn the review screen into unattended outreach.

Workspace accounts and operational controls

Authentication is enabled by default. On a fresh database, open the app and complete the first-run owner setup. For unattended deployments, set OWNER_EMAIL, OWNER_PASSWORD (8+ characters), OWNER_NAME, and WORKSPACE_NAME in .env; the owner is created automatically only when no user exists. Sessions are server-side, cookies are HTTP-only, and mutating browser requests require a per-session CSRF token. Failed sign-ins are temporarily rate-limited after five consecutive failures.

Roles are deliberately small:

Role	Capabilities
Viewer	Read catalogue and runs
Reviewer	Viewer + review status, notes, and follow-up tasks
Researcher	Reviewer + discovery runs, retries, cancellation, and assignments
Admin	Researcher + users, workspace name, backups, and audit trail
Owner	Admin, and cannot be removed as the last active owner

The Users page manages workspace members. A prospect drawer contains its assignee, notes, tasks, review status, and score/AI assessment history. Every workspace-scoped API query checks the signed-in organisation before returning data.

Backups and recovery

The app keeps the existing SQLite catalogue and performs additive schema migrations; it does not delete or rewrite existing prospects. Use Users → Verified backups → Create backup or run this inside the app container:

python scripts/backup_sqlite.py

Backups use SQLite's online backup API, run PRAGMA integrity_check, and keep the newest BACKUP_RETENTION files in BACKUP_DIR (default /data/backups). The background scheduler creates one automatically every BACKUP_INTERVAL_HOURS (default 24; set it to 0 to disable automatic creation). Include the prospect_data volume in server backups. A scheduled or interrupted run is marked recovery_required after 30 minutes without a heartbeat. The Runs page can show its persisted event timeline and retry a failed/recoverable run as a new attempt, preserving the original run. Active jobs can be cancelled and the worker records the cancellation in the event stream.

The audit trail records sign-ins, user and workspace changes, assignments, review decisions, notes, tasks, AI assessments, message generation, run retries/cancellations, settings, suppressions, and backup actions. Operational logs remain available under Logs; credentials and authorization values are redacted and retention is bounded by LOG_RETENTION.

This release intentionally keeps SQLite for safety. PostgreSQL migration can be added later as a separate, tested data-migration project once the current workspace and backup workflow is stable.