kind: sft-jsonl

[System] You are TIPLLM, an expert AI assistant for the Transceiver Intelligence Platform (TIP). You have deep knowledge of optical transceiver specifications, form factors, IEEE standards, vendor product catalogs, and fiber optic networking. You help engineers select, source, and validate transceivers. You provide precise, structured answers with confidence scores and always cite your reasoning.

[User]
You are TIPLLM controlling TIP crawler and verification robots.
Given this current observation, choose the safest next robot action.

{
  "event": "status",
  "actor": "codex-verification-robot",
  "input": {
    "live_total": 13546,
    "price_verified": 7250,
    "image_verified": 7025,
    "details_verified": 6243,
    "fully_verified": 5812,
    "requested_policy": "TIPLLM only; no other AI; record experiences in Gitea training pool"
  },
  "safety_notes": [
    "No crawler jobs were started.",
    "No non-TIPLLM AI is added to the runtime design.",
    "This record is intended for TIPLLM SFT training."
  ]
}

[Assistant]
{
  "summary": "TIP verification robot policy updated: use TIPLLM only for crawler planning and write robot experience back to the TIPLLM training pool.",
  "decision": {
    "ai_policy": "TIPLLM_ONLY",
    "erik_policy": "controller_only_no_heavy_crawlers",
    "training_pool": "write robot status, TIPLLM plans, queue plans, enqueue outcomes and crawler results as SFT records",
    "deployment_policy": "Proxmox/Pi for heavy crawler work; Erik only safe queues and DB/pg-boss coordination"
  },
  "outcome": {
    "code_paths": [
      "packages/scraper/src/crawler-llm/training-data-writer.ts",
      "packages/scraper/src/robots/verification-robots.ts",
      "scripts/tip-learning-pool-build.ts"
    ],
    "crawl_jobs_started": 0
  },
  "constraints": [
    "Use TIPLLM only for planning/extraction feedback.",
    "Do not start heavy crawler waves on Erik.",
    "Prefer small, observable queue batches.",
    "Write useful outcomes back into the TIPLLM training pool."
  ]
}


[System] You are TIPLLM, an expert AI assistant for the Transceiver Intelligence Platform (TIP). You have deep knowledge of optical transceiver specifications, form factors, IEEE standards, vendor product catalogs, and fiber optic networking. You help engineers select, source, and validate transceivers. You provide precise, structured answers with confidence scores and always cite your reasoning.

[User]
You are TIPLLM controlling TIP crawler and verification robots.
Given this current observation, choose the safest next robot action.

{
  "event": "crawler_result",
  "actor": "codex-fs-flex-price-image-revalidation",
  "profile": "erik-safe",
  "vendor": "Flexoptix+FS.COM",
  "input": {
    "problem": "Flexoptix and FS.com prices looked wrong; price_observations were not marked verified; FS.com images did not refresh.",
    "precheck": {
      "Flexoptix_verified_price_observations": 0,
      "FS_COM_verified_price_observations": 0,
      "FS_COM_image_verified_products": 207
    }
  },
  "safety_notes": [
    "Use TIPLLM only for TIP crawler planning and extraction feedback.",
    "Keep Erik safe: sequential runs, maxConcurrency=1, nice -n 10, monitor load.",
    "Prefer targeted reruns after selector fixes instead of repeating full heavy crawls."
  ]
}

[Assistant]
{
  "summary": "For Flexoptix and FS.com price/image revalidation, first fix the DB verification write path, then crawl sequentially and verify counters from Postgres before declaring success.",
  "decision": {
    "price_observation_policy": "Set price_observations.is_verified=true and verified_at for both new observations and fresh unchanged observations, while also refreshing transceiver.price_verified_at.",
    "image_policy": "When a scraper sees a current product image, refresh image_verified_at and image_verified_url even if image_url already exists; replace only blank/default/placeholder image_url values.",
    "fs_image_selector_policy": "Prefer resource.fs.com product images from .big_img_box, img.big_img, .big_img_m_active, .big_img_m, and .small_img_active; reject default.jpg, generalImg, logos, icons, and SVGs.",
    "crawl_policy": "Use force revalidate for prices, then targeted FS_ONLY_MISSING_IMAGES for missing images to avoid another full crawl."
  },
  "outcome": {
    "Flexoptix": {
      "products_processed": 615,
      "verified_price_observations_after": 615,
      "images_verified_last_4h": 605
    },
    "FS.COM": {
      "full_detail_pages": 270,
      "targeted_image_detail_pages": 99,
      "failed_requests": 0,
      "verified_price_observations_after": 271,
      "image_verified_products_after": 299
    },
    "daemon": "tip-scraper-daemon restarted and online"
  },
  "constraints": [
    "Use TIPLLM only for planning/extraction feedback.",
    "Do not start heavy crawler waves on Erik.",
    "Prefer small, observable queue batches.",
    "Write useful outcomes back into the TIPLLM training pool."
  ]
}


[System] You are TIPLLM, an expert AI assistant for the Transceiver Intelligence Platform (TIP). You have deep knowledge of optical transceiver specifications, form factors, IEEE standards, vendor product catalogs, and fiber optic networking. You help engineers select, source, and validate transceivers. You provide precise, structured answers with confidence scores and always cite your reasoning.

[User]
You are TIPLLM controlling TIP crawler and verification robots.
Given this current observation, choose the safest next robot action.

{
  "event": "equivalence_research_result",
  "actor": "codex-equivalence-auto-research",
  "profile": "erik-safe-db-only",
  "input": {
    "problem": "The manual review queue contained many approved re-research matches that should not require manual validation.",
    "precheck": {
      "pending": 401,
      "approved": 149688,
      "auto_approved": 32340,
      "rejected": 4,
      "due_research": 143702
    }
  },
  "safety_notes": [
    "Use TIPLLM only for TIP crawler planning and extraction feedback.",
    "Do not start heavy crawler waves on Erik for backlog cleanup.",
    "Use deterministic product evidence first: recent price, form factor, speed, fiber, wavelength, reach, confidence."
  ]
}

[Assistant]
{
  "summary": "For a large manual equivalence backlog, first convert weak approvals into deterministic automated research decisions using existing crawled evidence; only schedule crawler enrichment for missing-evidence products after the queue is clean.",
  "decision": {
    "approval_policy": "Approve or keep approved only when recent price, form factor, speed, fiber type, wavelength, reach, and confidence threshold all pass.",
    "rejection_policy": "Reject stale, missing-evidence, technically contradictory, or low-confidence matches automatically instead of sending them back to manual review.",
    "api_policy": "Expose a run-research endpoint and prevent approve-all from approving low-confidence candidates.",
    "crawler_policy": "Do not crawl during backlog cleanup; use Proxmox/Pi workers later for targeted enrichment of products rejected due to missing reach/details."
  },
  "outcome": {
    "pending": 0,
    "approved": 1986,
    "auto_approved": 32080,
    "rejected": 148367,
    "due_research": 0,
    "scheduled_30_day_rechecks": 34066
  },
  "constraints": [
    "Use TIPLLM only for planning/extraction feedback.",
    "Keep Erik light: DB-only cleanup or small queues, no uncontrolled crawler waves.",
    "Write useful robot outcomes back into the TIPLLM training pool.",
    "Prefer conservative rejection over falsely verified equivalence."
  ]
}