43 lines
3.1 KiB
Markdown
43 lines
3.1 KiB
Markdown
# Deployment Plan — Athena MVP
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## Prerequisites
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- Docker installed on the target host
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- Network access to the 6 source APIs/feeds (arxiv, github, huggingface, hackernews, reddit, rss_feeds)
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- `GITHUB_TOKEN` available as an environment variable (optional, but raises the GitHub rate limit from 60/hr to 5000/hr)
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- `HUGGINGFACE_TOKEN` available as an environment variable
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- A local Ollama instance running `llama3.2:1b`, or an alternate reachable inference backend if swapping — per the model-agnostic `summarize(text) -> (summary, model)` contract
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- Hermes cron infrastructure available and able to invoke `oracle-pipeline.sh`
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## Setup
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1. Clone `main` (not a milestone branch) onto the target host
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2. `pip install -r requirements.txt` if present; otherwise confirm stdlib + `requests` are available
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3. Run `schema.sql` against a fresh `oracle.db` — this file is git-ignored and created locally, never committed
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4. Export required environment variables (`GITHUB_TOKEN`, `HUGGINGFACE_TOKEN`) — never hardcode these
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5. Build and run inside Docker with the 150MB memory cap and non-root user enforced, per the PRD platform requirements
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6. Manual smoke test: run `python3 pipeline.py` once and confirm ingest → store → summarize → score completes without errors before handing off to cron
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## Cron / Scheduling
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1. Confirm `oracle-pipeline.sh` is the entry point Hermes cron calls
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2. Schedule for 13:00 UTC daily
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3. Add a lock file or PID check so overlapping runs can't happen if a prior run is still in progress
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4. Confirm the cron environment actually carries the exported tokens — cron environments are frequently minimal and won't inherit an interactive shell's exports
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## Hermes Integration
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1. Confirm the wrapper script's exit codes are meaningful (0 = success, non-zero = failure) so Hermes can act on them
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2. Define where Hermes should look for pipeline output/logs
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3. Decide on a failure-notification path (Hermes alert, log flag, etc.) — **not yet specified, needs a decision**
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## Monitoring
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1. Aggregate logs from each pipeline stage (ingest, store, summarize, score)
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2. Track theme-scan new-arrival counts per cycle per theme — this is the core signal the falsification logic depends on, so it deserves visibility beyond raw logs
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3. Add a heartbeat/dead-man's-switch alert if a scheduled run doesn't fire, rather than relying on someone noticing missing data days later
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4. Watch memory usage against the 150MB cap under real production load, not just dev conditions
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## Rollback
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1. Back up `oracle.db` before any schema change — it's git-ignored and not recoverable from the repo itself
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2. If a bad deploy breaks the pipeline, revert to the last known-good commit on `main` and redeploy the Docker image
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3. Check falsification state (new-arrivals counters) after any rollback — rolling back mid-window could distort the 7-day dead-thesis calculation if not handled carefully
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---
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*Draft prepared by Claude from the README, whitepaper falsification logic, and MVP-PRD platform requirements on `main`. The Hermes failure-notification path is the one open decision blocking this from being final.*
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