Emo-Social Insta DM Agent

Project for the Emo-Social Instagram DM agent for @socialmediatorr (distinct from the existing Sergio RAG DB agent).

Includes:

• Meta Graph API exporter (full DM history)
• Instagram “Download your information” importer
• DM analysis pipeline (bot-vs-human, conversions, objections, rescue logic, product eras)
• Helpers for device login + page subscription + sending replies

Where this runs

Build/run the Docker image in pct 250 (ai-dev) and keep production (pct 220) clean.

Credentials

Source of truth creds file (host):

• /root/tmp/emo-social-meta-app-creds.txt

Inside pct 250, place the same file at the same path:

• /root/tmp/emo-social-meta-app-creds.txt

Required for export:

• META_PAGE_ID
• META_PAGE_ACCESS_TOKEN

Build (pct 250)

• docker build -t emo-social-insta-dm-agent:dev /root/ai-workspace/emo-social-insta-dm-agent

Note: in this LXC, docker run / podman run can fail due to AppArmor confinement. Use the direct Python commands below unless you change the LXC config to be AppArmor-unconfined.

Obtain tokens (pct 250)

meta_device_login requires META_CLIENT_TOKEN (from Meta app dashboard → Settings → Advanced → Client token). Alternatively, set META_CLIENT_ACCESS_TOKEN as APP_ID|CLIENT_TOKEN to override META_APP_ID for device-login only.

If meta_device_login start returns OAuth error (#3) enable "Login from Devices", enable it in the same app id the script prints:

• https://developers.facebook.com/apps/<APP_ID>/fb-login/settings/ → set Login from Devices = Yes

Start device login (prints a URL + code to enter; no tokens are printed):

• cd /root/ai-workspace/emo-social-insta-dm-agent && python3 -m sergio_instagram_messaging.meta_device_login start

After authorizing in the browser, poll and write META_PAGE_ID + META_PAGE_ACCESS_TOKEN into /root/tmp/emo-social-meta-app-creds.txt:

• cd /root/ai-workspace/emo-social-insta-dm-agent && python3 -m sergio_instagram_messaging.meta_device_login poll --write-page-token --target-ig-user-id 17841466913731557

Fallback: Graph API Explorer → user token → page token

If device-login is blocked, get a Facebook User access token via Graph API Explorer and derive the Page token:

• Open: https://developers.facebook.com/tools/explorer/
• Select the correct app, then generate a user token with:
  • pages_show_list,pages_read_engagement,instagram_manage_messages
• Save the user token to (keep mode 600):
  • /root/tmp/meta-user-access-token.txt
• Then write META_PAGE_ID + META_PAGE_ACCESS_TOKEN into /root/tmp/emo-social-meta-app-creds.txt (no token values printed):
• cd /root/ai-workspace/emo-social-insta-dm-agent && python3 -m sergio_instagram_messaging.meta_page_token_from_user_token --target-ig-user-id 17841466913731557

Export history (pct 250)

Quick token sanity check (does not print token values):

• cd /root/ai-workspace/emo-social-insta-dm-agent && python3 -m sergio_instagram_messaging.meta_token_doctor

Export to a mounted directory so results persist on disk:

• docker run --rm -v /root/tmp:/root/tmp emo-social-insta-dm-agent:dev python -m sergio_instagram_messaging.export_meta_ig_history --out /root/tmp/emo-social-insta-dm-history
  • (Direct) cd /root/ai-workspace/emo-social-insta-dm-agent && python3 -m sergio_instagram_messaging.export_meta_ig_history --out /root/tmp/emo-social-insta-dm-history

Workaround: fetch a single thread by user_id

If /conversations listing times out, you can still fetch a single thread if you know the sender’s user_id (from webhook sender.id):

• cd /root/ai-workspace/emo-social-insta-dm-agent && python3 -m sergio_instagram_messaging.fetch_thread_messages --user-id <SENDER_ID> --max-pages 2 --out /root/tmp/thread.jsonl

Small test run:

• docker run --rm -v /root/tmp:/root/tmp emo-social-insta-dm-agent:dev python -m sergio_instagram_messaging.export_meta_ig_history --out /root/tmp/emo-social-insta-dm-history --max-conversations 3 --max-pages 2
  • (Direct) cd /root/ai-workspace/emo-social-insta-dm-agent && python3 -m sergio_instagram_messaging.export_meta_ig_history --out /root/tmp/emo-social-insta-dm-history --max-conversations 3 --max-pages 2

Full history fallback (Instagram export)

If Meta app review blocks Graph API DM access, export Sergio’s IG data via Instagram “Download your information” and import it:

• cd /root/ai-workspace/emo-social-insta-dm-agent && python3 -m sergio_instagram_messaging.import_instagram_export --input /path/to/instagram-export.zip --out /root/tmp/emo-social-insta-dm-export-history

Analyze DM history (Behavioral Cloning / “Biographical Sales”)

This produces the “Sergio persona” artifacts needed for the DM agent:

• Separates frequent [BOT] templates vs rare [MANUAL] replies (plus [HYBRID]).
• Builds bot fatigue + script editorial timeline charts.
• Extracts training pairs (user → Sergio manual reply) from converted threads.
• Generates rescue playbook (human saves after silence/negative sentiment).
• Generates objection handlers (price/time/trust/stop → best replies).
• Builds a quarterly eras CSV (offers/pricing + vocabulary drift).

Outputs are written with mode 600 and may contain sensitive DM content. Keep them out of git.

Analyze a raw Instagram export folder (recommended)

Optional: index first (lets you filter recency without scanning every thread):

• python3 -m sergio_instagram_messaging.index_instagram_export --input /path/to/your_instagram_activity --out /root/tmp/socialmediatorr-ig-index.jsonl

Then analyze:

• python3 -m sergio_instagram_messaging.analyze_instagram_export --input /path/to/your_instagram_activity --out /root/tmp/socialmediatorr-agent-analysis --owner-name "Sergio de Vocht" --index /root/tmp/socialmediatorr-ig-index.jsonl --since-days 180

Analyze an imported history dir (messages/*.jsonl)

If you already ran import_instagram_export (or have a partial import output), point the analyzer at that directory:

• python3 -m sergio_instagram_messaging.analyze_instagram_export --input /root/tmp/socialmediatorr-ig-export-history --out /root/tmp/socialmediatorr-agent-analysis --owner-name "Sergio de Vocht"

Two-stage workflow (verify templates before full run)

Pass 1 generates top_outgoing_templates.json + template_counts.jsonl:

• python3 -m sergio_instagram_messaging.analyze_instagram_export --input /path/to/your_instagram_activity --out /root/tmp/socialmediatorr-agent-analysis --stage pass1

Pass 2 reuses the cache and writes the full deliverables:

• python3 -m sergio_instagram_messaging.analyze_instagram_export --input /path/to/your_instagram_activity --out /root/tmp/socialmediatorr-agent-analysis --stage pass2 --templates-cache /root/tmp/socialmediatorr-agent-analysis/top_outgoing_templates.json

Human-readable report (English)

After analysis, generate a single Markdown report:

• python3 -m sergio_instagram_messaging.generate_dm_report --analysis-dir /root/tmp/socialmediatorr-agent-analysis

Webhooks (new messages → auto-reply)

Meta webhooks are two steps:

1. App subscription (/{app_id}/subscriptions) — sets callback URL + verify token + fields.
2. Page subscription (/{page_id}/subscribed_apps) — attaches the Page/IG inbox to the app.

The production webhook endpoint exists at:

• https://emo-social.infrafabric.io/meta/webhook

Subscribe the Page to the app (required for message delivery)

This requires a Page access token that includes pages_manage_metadata.

Device login with that scope:

• cd /root/ai-workspace/emo-social-insta-dm-agent && python3 -m sergio_instagram_messaging.meta_device_login start --scope pages_show_list,pages_read_engagement,instagram_manage_messages,pages_manage_metadata
• After authorizing in the browser, poll and write tokens:
  • cd /root/ai-workspace/emo-social-insta-dm-agent && python3 -m sergio_instagram_messaging.meta_device_login poll --write-page-token --target-ig-user-id 17841466913731557

Then subscribe the Page:

• cd /root/ai-workspace/emo-social-insta-dm-agent && python3 -m sergio_instagram_messaging.meta_subscribe_page subscribe --fields messages