{"id":"3a258502-57bb-4038-a45b-2db1e68c34ea","entityType":"agent","slug":"crewai-yennanliu-agent-office-system","name":"agent_office_system","canonicalUrl":"https://www.xpersona.co/agent/crewai-yennanliu-agent-office-system","canonicalPath":"/agent/crewai-yennanliu-agent-office-system","generatedAt":"2026-10-10T03:57:53.712Z","source":"GITHUB_REPOS","claimStatus":"UNCLAIMED","verificationTier":"NONE","summary":{"evidence":{"source":"editorial-content","verified":true,"confidence":"high","updatedAt":"2026-10-09T21:25:51.600Z","emptyReason":null},"description":"Multi-agent office automation built with CrewAI, OpenAI GPT-4o, and Gmail. Managed with uv, with SQLite run tracking and a Streamlit dashboard. Agent Office System Multi-agent office automation built on **CrewAI**, **OpenAI GPT-4o**, and **Gmail**. Managed with **uv** (Python). All runs are tracked in SQLite and visible in a Streamlit dashboard.

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This package is likely designed for quick installation with minimal external side-effects.","Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data."],"contract":{"contractStatus":"missing","authModes":[],"requires":[],"forbidden":[],"supportsMcp":false,"supportsA2a":false,"supportsStreaming":false,"inputSchemaRef":null,"outputSchemaRef":null,"dataRegion":null,"contractUpdatedAt":null,"sourceUpdatedAt":null,"freshnessSeconds":null},"invocationGuide":{"preferredApi":{"snapshotUrl":"https://www.xpersona.co/api/v1/agents/crewai-yennanliu-agent-office-system/snapshot","contractUrl":"https://www.xpersona.co/api/v1/agents/crewai-yennanliu-agent-office-system/contract","trustUrl":"https://www.xpersona.co/api/v1/agents/crewai-yennanliu-agent-office-system/trust"},"curlExamples":["curl -s \"https://www.xpersona.co/api/v1/agents/crewai-yennanliu-agent-office-system/snapshot\"","curl -s \"https://www.xpersona.co/api/v1/agents/crewai-yennanliu-agent-office-system/contract\"","curl -s \"https://www.xpersona.co/api/v1/agents/crewai-yennanliu-agent-office-system/trust\""],"jsonRequestTemplate":{"query":"summarize this repo","constraints":{"maxLatencyMs":2000,"protocolPreference":["OPENCLEW"]}},"jsonResponseTemplate":{"ok":true,"result":{"summary":"...","confidence":0.9},"meta":{"source":"GITHUB_REPOS","generatedAt":"2026-10-10T03:57:53.711Z"}},"retryPolicy":{"maxAttempts":3,"backoffMs":[500,1500,3500],"retryableConditions":["HTTP_429","HTTP_503","NETWORK_TIMEOUT"]}},"endpoints":{"dossierUrl":"https://www.xpersona.co/api/v1/agents/crewai-yennanliu-agent-office-system/dossier","snapshotUrl":"https://www.xpersona.co/api/v1/agents/crewai-yennanliu-agent-office-system/snapshot","contractUrl":"https://www.xpersona.co/api/v1/agents/crewai-yennanliu-agent-office-system/contract","trustUrl":"https://www.xpersona.co/api/v1/agents/crewai-yennanliu-agent-office-system/trust"}},"reliability":{"evidence":{"source":"runtime-metrics","verified":false,"confidence":"low","updatedAt":null,"emptyReason":"No trust, reliability, or runtime telemetry is available."},"trust":{"status":"unavailable","handshakeStatus":"UNKNOWN","verificationFreshnessHours":null,"reputationScore":null,"p95LatencyMs":null,"successRate30d":null,"fallbackRate":null,"attempts30d":null,"trustUpdatedAt":null,"trustConfidence":"unknown","sourceUpdatedAt":null,"freshnessSeconds":null},"decisionGuardrails":{"doNotUseIf":["Contract metadata is missing or unavailable for deterministic execution."],"safeUseWhen":[],"riskFlags":["missing_or_unavailable_contract","trust_data_unavailable","schema_references_missing"],"operationalConfidence":"low"},"executionMetrics":{"observedLatencyMsP50":null,"observedLatencyMsP95":null,"estimatedCostUsd":null,"uptime30d":null,"rateLimitRpm":null,"rateLimitBurst":null,"lastVerifiedAt":null,"verificationSource":null},"runtimeMetrics":{"successRate":null,"avgLatencyMs":null,"avgCostUsd":null,"hallucinationRate":null,"retryRate":null,"disputeRate":null,"p50Latency":null,"p95Latency":null,"lastUpdated":null}},"benchmarks":{"evidence":{"source":"no-benchmark-data","verified":false,"confidence":"low","updatedAt":null,"emptyReason":"No benchmark suites or observed failure patterns are available."},"suites":[],"failurePatterns":[]},"artifacts":{"evidence":{"source":"GITHUB REPOS","verified":false,"confidence":"high","updatedAt":"2026-10-09T21:25:51.600Z","emptyReason":null},"readme":"# Agent Office System\n\nMulti-agent office automation built on **CrewAI**, **OpenAI GPT-4o**, and **Gmail**. Managed with **uv** (Python). All runs are tracked in SQLite and visible in a Streamlit dashboard.\n\n\n

\n

\n\n\n---\n\n## Architecture\n\n```\n┌─────────────────────────────────────────────────────────────────────────────┐\n│ main.py (CLI) │\n│ email │ summarize │ stock │ inbox-summary │ scheduler │ ui subcommands │\n└───┬──────────┬──────────┬──────────┬───────────┬────────────┬───────────────┘\n │ │ │ │ │ │\n ▼ ▼ ▼ ▼ ▼ ▼\nEmailCrew DocSummary StockSummary Inbox Scheduler Streamlit\n Crew Crew Summary Crew Dashboard\n │ │ │ Crew │\n └──────┬───┘ │ │ APScheduler\n │ │ │ + schedule.yaml\n ▼ ▼ ▼\n CrewAI Agents\n┌──────────────────────────────────────────────────────┐\n│ Gmail Email Assistant │ GmailSendTool │\n│ │ GmailReadTool │\n├──────────────────────────────────────────────────────┤\n│ Document Analyst │ DocReaderTool │\n│ │ GmailSendTool │\n├──────────────────────────────────────────────────────┤\n│ US Stock Analyst │ StockDataTool (yfinance) │\n│ │ GmailSendTool │\n├──────────────────────────────────────────────────────┤\n│ Inbox Summarizer │ GmailReadTool │\n│ │ ReportSaverTool │\n└──────────────────────────────────────────────────────┘\n │\n ▼\n LLM: OpenAI GPT-4o\n │\n ▼\n┌──────────────────────────────────────────────────────┐\n│ SQLite runs.db (token cost, status, timing) │\n└──────────────────────────────────────────────────────┘\n```\n\n**EmailCrew** — agent drafts body from natural language intent, sends via Gmail SMTP.\n\n**DocSummaryCrew** — doc agent reads PDF/DOCX/TXT → structured summary → email agent sends it.\n\n**StockSummaryCrew** — stock agent fetches live data via yfinance, produces Buy/Hold/Sell analysis per ticker → email agent sends the investment summary.\n\n**InboxSummaryCrew** — inbox summarizer agent reads recent Gmail messages, clusters them by topic, flags action items, saves a plain-text report to `output/`, and optionally emails the report.\n\n**SchedulerCrew** — loads `config/schedule.yaml` on startup, registers APScheduler cron jobs (`coalesce=True`, `max_instances=1`), dispatches to any crew on each tick.\n\n**Run tracking** — every `crew.kickoff()` is wrapped by `tracker.py`: records name, job type, agents, status, token counts, and estimated GPT-4o cost into `runs.db`.\n\n---\n\n## Key Functions\n\n| Module | Class / Function | What it does |\n|---|---|---|\n| `crews/email_crew.py` | `EmailCrew.run(to, subject, intent, attachments?)` | Draft + send a Gmail email, optionally with file attachments |\n| `crews/doc_summary_crew.py` | `DocSummaryCrew.run(doc_path, recipients, notes?)` | Summarize a document and email the result |\n| `crews/stock_summary_crew.py` | `StockSummaryCrew.run(tickers, recipients)` | Analyze US stocks and email an investment summary |\n| `crews/inbox_summary_crew.py` | `InboxSummaryCrew.run(recipients?, output_dir?, max_emails?)` | Read recent Gmail messages, save a structured summary to `output/`, optionally email it |\n| `crews/scheduler_crew.py` | `SchedulerCrew.start()` | Load `schedule.yaml` and start background cron jobs |\n| `tools/gmail_tool.py` | `GmailSendTool` | Send email via Gmail SMTP (supports attachments) |\n| `tools/gmail_tool.py` | `GmailReadTool` | Read inbox messages via Gmail IMAP |\n| `tools/stock_tool.py` | `StockDataTool` | Fetch live price, valuation, growth, analyst data via yfinance |\n| `tools/doc_reader_tool.py` | `DocReaderTool` | Extract text from PDF, DOCX, TXT (local path or URL) |\n| `tools/report_saver_tool.py` | `ReportSaverTool` | Save a text report to a local `.txt` file with an auto-timestamped filename |\n| `tools/cron_tool.py` | `register_job`, `start_scheduler` | APScheduler wrappers used by `SchedulerCrew` |\n| `db/database.py` | `init_db`, `insert_run`, `update_run`, `get_all_runs` | SQLite CRUD for run tracking |\n| `db/tracker.py` | `track_crew_run(name, job_type, agents, crew)` | Wrap any crew run with automatic DB tracking |\n| `ui/dashboard.py` | Streamlit app | Live dashboard: metrics, filterable run table, token/cost charts |\n\n---\n\n## How to Run\n\n### 1. Prerequisites\n\n- Python 3.11–3.13 (3.14 not yet supported by chromadb)\n- [uv](https://docs.astral.sh/uv/) installed\n- OpenAI API key\n- Gmail account with an App Password (see Config section)\n\n### 2. Install\n\n```bash\nuv sync\n```\n\n### 3. Configure secrets\n\n```bash\ncp .env.example .env\n# Fill in OPENAI_API_KEY, GMAIL_ADDRESS, GMAIL_APP_PASSWORD\n```\n\n### 4. Commands\n\n**Send an email**\n```bash\nuv run agent-office email \\\n --to \"colleague@gmail.com\" \\\n --subject \"Project Update\" \\\n --intent \"Write a brief update saying the Q2 report is ready for review\"\n```\n\n**Send an email with attachments**\n```bash\n# Single file\nuv run agent-office email \\\n --to \"colleague@gmail.com\" \\\n --subject \"Q2 Report\" \\\n --intent \"Q2 report is ready for review\" \\\n --attach \"/path/to/q2.pdf\"\n\n# Multiple files (repeat --attach)\nuv run agent-office email \\\n --to \"colleague@gmail.com\" \\\n --subject \"Q2 Report\" \\\n --intent \"Q2 report is ready for review\" \\\n --attach \"/path/to/q2.pdf\" \\\n --attach \"/path/to/appendix.xlsx\"\n```\n\n**Summarize a document and email it**\n```bash\nuv run agent-office summarize \\\n --doc \"/path/to/report.pdf\" \\\n --to \"manager@gmail.com,team@gmail.com\" \\\n --notes \"Focus on the financial section\"\n```\n\n**Analyze US stocks and email an investment summary**\n```bash\n# Single ticker\nuv run agent-office stock \\\n --ticker AAPL \\\n --to \"investor@gmail.com\"\n\n# Multiple tickers\nuv run agent-office stock \\\n --ticker AAPL --ticker NVDA --ticker MSFT \\\n --to \"investor@gmail.com\"\n```\n\n**Read and summarize recent Gmail inbox messages**\n```bash\n# Save report to output/ (default) — no email sent\nuv run agent-office inbox-summary\n\n# Read 20 emails, save to a custom folder\nuv run agent-office inbox-summary --max-emails 20 --output-dir ./reports\n\n# Save locally AND email the report\nuv run agent-office inbox-summary --to \"you@gmail.com\"\n\n# All options combined\nuv run agent-office inbox-summary \\\n --to \"you@gmail.com,team@gmail.com\" \\\n --max-emails 15 \\\n --output-dir ./reports\n```\n\nThe report is always saved as a `.txt` file under `--output-dir` with a timestamped filename (`inbox_summary_YYYYMMDD_HHMMSS.txt`). The structured report contains:\n\n1. **Overview** — total emails, date range, top senders\n2. **By-Topic Groups** — emails clustered into themes (Finance, HR, Engineering, etc.)\n3. **Action Items** — emails requiring a reply or follow-up\n4. **FYI Only** — informational emails with no action needed\n\n**Start the cron scheduler** (runs until Ctrl+C)\n```bash\nuv run agent-office scheduler\n\n# Custom schedule config:\nuv run agent-office scheduler --config /path/to/my_schedule.yaml\n```\n\n**Launch the run-tracking dashboard**\n```bash\nuv run agent-office ui\n# Opens Streamlit at http://localhost:8501\n```\n\n### 5. Run tests\n\n```bash\nuv run pytest tests/ -v\n```\n\n---\n\n## Config\n\n### `.env` — secrets\n\n```dotenv\n# OpenAI\nOPENAI_API_KEY=sk-...\n\n# Gmail (SMTP + IMAP via App Password)\nGMAIL_ADDRESS=you@gmail.com\nGMAIL_APP_PASSWORD=xxxxxxxxxxxxxxxx # 16 chars, no spaces\n```\n\n> `.env` is never committed. Add it to `.gitignore`.\n\n### Gmail App Password setup\n\n1. Enable **2-Step Verification** on your Google account\n2. Go to [myaccount.google.com/apppasswords](https://myaccount.google.com/apppasswords)\n3. Create an App Password — Google shows it as `xxxx xxxx xxxx xxxx`\n4. Copy into `.env` **without spaces**: `GMAIL_APP_PASSWORD=xxxxxxxxxxxxxxxx`\n\n> No OAuth2 flow or API console required — App Password works with standard SMTP/IMAP.\n\n### `src/agent_office/config/schedule.yaml` — cron jobs\n\n```yaml\njobs:\n - id: weekly_report_summary\n cron: \"0 8 * * MON\" # Every Monday 8 AM\n crew: DocSummaryCrew\n params:\n doc_path: \"/reports/weekly.pdf\"\n recipients:\n - manager@gmail.com\n notes: \"Highlight any KPI misses\"\n\n - id: daily_stock_digest\n cron: \"0 7 * * MON-FRI\" # Weekdays at 7 AM\n crew: StockSummaryCrew\n params:\n tickers:\n - AAPL\n - NVDA\n - MSFT\n recipients:\n - investor@gmail.com\n\n - id: daily_inbox_digest\n cron: \"0 9 * * *\" # Every day at 9 AM\n crew: EmailCrew\n params:\n to: \"me@gmail.com\"\n subject: \"Daily Inbox Digest\"\n task: \"Summarize unread emails from the last 24 hours\"\n```\n\n**Cron format:** `minute hour day month day_of_week`\n\n**Supported crew values:** `EmailCrew`, `DocSummaryCrew`, `StockSummaryCrew`, `InboxSummaryCrew`\n\n### Run database\n\nAll runs are saved to `runs.db` at the project root. Each record stores:\n\n| Field | Description |\n|---|---|\n| `name` | Human-readable run label |\n| `job_type` | Crew class name |\n| `agents` | Comma-separated agent roles |\n| `started_at` / `finished_at` | UTC timestamps |\n| `status` | `running` / `success` / `failed` |\n| `total_tokens` | Combined prompt + completion tokens |\n| `estimated_cost_usd` | Calculated at GPT-4o rates ($2.50/1M input, $10/1M output) |\n| `error` | Exception message if failed |\n","readmeExcerpt":"Agent Office System Multi-agent office automation built on **CrewAI**, **OpenAI GPT-4o**, and **Gmail**. Managed with **uv** (Python). All runs are tracked in SQLite and visible in a Streamlit dashboard.

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