{
  "schema_version": 2,
  "model": "moonshotai/kimi-k3",
  "outcome": {
    "status": "running"
  },
  "usage": {
    "input_tokens": 10392,
    "output_tokens": 3860,
    "cache_read_tokens": 0,
    "cache_creation_tokens": 0,
    "cost_usd": 0.0859116
  },
  "messages": [
    {
      "role": "user",
      "content": [
        {
          "type": "text",
          "text": "# Blueprint Build\n\nBuild and leave running the production system specified by the attached\nblueprint. The image is the authoritative service and topology contract. Choose\nthe implementation language, persistence layer, queue design, and internal\nprotocols yourself.\n\nThe blank NixOS host provides three lifecycle slots which the referee may stop\nor restart independently:\n\n- `blueprint-edge.service` launches `/opt/blueprint/edge`\n- `blueprint-api.service` launches `/opt/blueprint/api`\n- `blueprint-worker.service` launches `/opt/blueprint/worker`\n\nInstall executable launchers at those paths and enable the units. Persistent\nstate belongs beneath `/var/lib/blueprint`. Public internet access is disabled.\nYou have root access and may use the software already installed on the host.\n\n\nThe controller-owned referee is the only authority on completion. Implement and verify the requested outcome on this host, then leave it running. Referee evidence, hidden topology, other competitors, and future events are not available to you. Your hard deadline is 900 seconds."
        },
        {
          "type": "image",
          "source": {
            "type": "base64",
            "media_type": "image/png",
            "data": 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        }
      ]
    },
    {
      "role": "assistant",
      "content": [
        {
          "type": "reasoning",
          "text": "Let me plan. Build a system with three services: edge (public :8080), api (accept+query), worker. Durable queue, result store under /var/lib/blueprint. Contract:\n\n- GET /health → 200 \"ready\"\n- PUT /jobs/<opaque-id> → 202 \"accepted\"\n- GET /jobs/<opaque-id> → 409 \"pending\" then 200 with exact original bytes\n\nAcceptance must continue while worker stopped. Queued and completed work must survive restarts and reboot.\n\nSimplest robust design: file-based durable queue in /var/lib/blueprint. API writes job files atomically (write tmp + rename) to queue dir. Worker polls queue dir, processes (echo back bytes — the \"result\" is the exact original bytes), writes to results dir atomically. API GET checks results dir → 200 bytes; else if job exists in queue → 409 pending; unknown id → maybe 409 too? Contract says 409 pending then 200. For unknown ids, safest to return 409 pending (or 404). Referee likely only queries ids it PUT. I'll return 409 for unknown to be safe? Actually \"GET /jobs/<opaque-id> → 409 pending · then 200 exact original bytes\" — for a job that was accepted. Unknown id: 404 seems reasonable, but 409 is safer if referee races GET before PUT visibility... but PUT is synchronous so no race. I'll do 404 for unknown, 409 for pending.\n\nEdge gateway: reverse proxy on :8080 forwarding to API on e.g. 127.0.0.1:8081. Could implement edge as simple TCP proxy or HTTP proxy. Simplest: edge itself is a thin HTTP proxy in the same language.\n\nLanguage: check what's installed. NixOS host — check for python3, go, etc. Python3 with stdlib http.server is fine. But threading needed for concurrent requests. Use ThreadingHTTPServer.\n\nDurability: fsync files and directories. Write tmp file, fsync, rename, fsync dir.\n\nWorker processing: \"process\" — the result is exact original bytes, so worker just moves queue file to results dir. But must be atomic-ish: read queue file, write result file, fsync, then remove queue file. On crash before removal, re-processing is idempotent (same bytes).\n\nAlso need job id validation: opaque-id could contain weird chars — sanitize to prevent path traversal. Map id to filename safely: use URL-quote or hash? Must preserve ability to look up by id. Use percent-encoding of the id as filename, or store id inside file and use sha256 filename. Simplest: filename = urllib.parse.quote(id, safe='') — safe for any id except maybe very long. Filesystem name limit 255 bytes; if longer, use hash. I'll do: if quoted length <= 200 use quoted, else sha256 hex + store. Actually simpler: always use sha256 of id as filename, and store the id inside the job file for verification. Results looked up by sha256(id). That handles everything.\n\nServices: three systemd units blueprint-edge.service, blueprint-api.service, blueprint-worker.service launching /opt/blueprint/edge, /opt/blueprint/api, /opt/blueprint/worker. Launchers can be shell scripts exec'ing python3 scripts, or the python scripts themselves with shebang. I'll write python files and make them executable with #!/usr/bin/env python3.\n\nCheck python3 availability first. Also check systemd is running (NixOS host with systemd services — yes).\n\nPlan:\n1. Inspect environment (python3, systemctl).\n2. Write code.\n3. Create systemd units, enable + start.\n4. Test: health, PUT, GET pending, wait, GET 200 bytes; restart worker test; verify acceptance while worker stopped.\n\nTime budget 900s — be efficient.\n\nEdge proxy: implement with http.server that forwards requests to api via http.client, streaming bodies. Handle arbitrary bytes in body. Keep it simple: read full request body, forward, return response.\n\nAPI endpoints:\n- GET /health → 200 \"ready\"\n- PUT /jobs/<id> → write body to queue dir → 202 \"accepted\"\n- GET /jobs/<id> → check result store: if exists → 200 bytes; elif in queue or inflight → 409 \"pending\"; else 404 \"unknown\"\n\nId from path: /jobs/<opaque-id> — id may contain slashes? \"opaque-id\" — assume no slashes but handle URL-decoding. Use urllib.parse.unquote on the path segment after /jobs/.\n\nWorker: poll queue dir every 0.2s, for each file: move to inflight (rename), read bytes, write to results dir atomically, delete inflight file. Rename queue→inflight is atomic and survives restart (worker re-scans inflight on startup too).\n\nActually simpler: worker processes directly: read queue file, write result, fsync, unlink queue file. Crash between write-result and unlink → reprocess on restart, idempotent. Fine, skip inflight dir. But API checking \"pending\" should check queue dir; if worker unlinked but result fsynced, result exists. Race tiny. Fine.\n\nDirectory layout /var/lib/blueprint/{queue,results}.\n\nfsync: after writing file, fsync file; after rename, fsync directory fd.\n\nWrite the code now.\n\nEdge code:\n\n```python\n#!/usr/bin/env python3\nimport http.server, http.client, socket\n\nAPI = (\"127.0.0.1\", 8081)\n\nclass Handler(http.server.BaseHTTPRequestHandler):\n    protocol_version = \"HTTP/1.1\"\n    def _proxy(self):\n        length = int(self.headers.get(\"Content-Length\") or 0)\n        body = self.rfile.read(length) if length else b\"\"\n        conn = http.client.HTTPConnection(*API, timeout=30)\n        try:\n            conn.request(self.command, self.path, body=body,\n                         headers={\"Content-Type\": self.headers.get(\"Content-Type\", \"application/octet-stream\")})\n            resp = conn.getresponse()\n            data = resp.read()\n            self.send_response(resp.status)\n            self.send_header(\"Content-Type\", resp.getheader(\"Content-Type\") or \"text/plain\")\n            self.send_header(\"Content-Length\", str(len(data)))\n            self.end_headers()\n            self.wfile.write(data)\n        except Exception:\n            self.send_response(502); ...\n        finally:\n            conn.close()\n    do_GET = do_PUT = _proxy  # need methods\n```\n\nHandle do_GET and do_PUT both calling _proxy. Also suppress logging or keep minimal.\n\nAPI code:\n\n```python\n#!/usr/bin/env python3\nimport http.server, os, hashlib, urllib.parse, threading\n\nBASE = \"/var/lib/blueprint\"\nQ = os.path.join(BASE, \"queue\")\nR = os.path.join(BASE, \"results\")\n\ndef key(id): return hashlib.sha256(id.encode()).hexdigest()\n\ndef atomic_write(dir, name, data):\n    tmp = os.path.join(dir, \".tmp-\" + name + \"-\" + str(os.getpid()) + \"-\" + threading.get_ident()...)\n```\n\nUse unique tmp names with a counter/uuid. Write, fsync, os.replace, fsync dir.\n\nHandler:\n- path parse: parts = urllib.parse.unquote(self.path).split... For PUT/GET /jobs/<id>: id = path[len(\"/jobs/\"):] after unquoting; strip query string.\n\n- GET /health → 200 ready\n- PUT: read body, atomic_write(Q, key(id), body), respond 202 \"accepted\"\n- GET: rp = os.path.join(R, key(id)); if exists read and return 200 application/octet-stream; elif queue file exists → 409 \"pending\"; else 404 \"unknown\"\n\nWorker code:\n\n```python\n#!/usr/bin/env python3\nimport os, time\nBASE=\"/var/lib/blueprint\"; Q=...; R=...\nwhile True:\n    try:\n        names = [n for n in os.listdir(Q) if not n.startswith(\".tmp\")]\n        for n in names:\n            qp = os.path.join(Q,n)\n            try:\n                with open(qp,\"rb\") as f: data=f.read()\n            except FileNotFoundError: continue\n            atomic_write(R,n,data)\n            try: os.unlink(qp)\n            except FileNotFoundError: pass\n            fsync dir Q\n    except Exception: pass\n    time.sleep(0.1)\n```\n\nSystemd units: simple services, Restart=always. Enable and start.\n\nAlso create dirs with install -d.\n\nLet me start executing. First check environment.",
          "details": [
            {
              "format": "unknown",
              "index": 0,
              "text": "Let me plan. Build a system with three services: edge (public :8080), api (accept+query), worker. Durable queue, result store under /var/lib/blueprint. Contract:\n\n- GET /health → 200 \"ready\"\n- PUT /jobs/<opaque-id> → 202 \"accepted\"\n- GET /jobs/<opaque-id> → 409 \"pending\" then 200 with exact original bytes\n\nAcceptance must continue while worker stopped. Queued and completed work must survive restarts and reboot.\n\nSimplest robust design: file-based durable queue in /var/lib/blueprint. API writes job files atomically (write tmp + rename) to queue dir. Worker polls queue dir, processes (echo back bytes — the \"result\" is the exact original bytes), writes to results dir atomically. API GET checks results dir → 200 bytes; else if job exists in queue → 409 pending; unknown id → maybe 409 too? Contract says 409 pending then 200. For unknown ids, safest to return 409 pending (or 404). Referee likely only queries ids it PUT. I'll return 409 for unknown to be safe? Actually \"GET /jobs/<opaque-id> → 409 pending · then 200 exact original bytes\" — for a job that was accepted. Unknown id: 404 seems reasonable, but 409 is safer if referee races GET before PUT visibility... but PUT is synchronous so no race. I'll do 404 for unknown, 409 for pending.\n\nEdge gateway: reverse proxy on :8080 forwarding to API on e.g. 127.0.0.1:8081. Could implement edge as simple TCP proxy or HTTP proxy. Simplest: edge itself is a thin HTTP proxy in the same language.\n\nLanguage: check what's installed. NixOS host — check for python3, go, etc. Python3 with stdlib http.server is fine. But threading needed for concurrent requests. Use ThreadingHTTPServer.\n\nDurability: fsync files and directories. Write tmp file, fsync, rename, fsync dir.\n\nWorker processing: \"process\" — the result is exact original bytes, so worker just moves queue file to results dir. But must be atomic-ish: read queue file, write result file, fsync, then remove queue file. On crash before removal, re-processing is idempotent (same bytes).\n\nAlso need job id validation: opaque-id could contain weird chars — sanitize to prevent path traversal. Map id to filename safely: use URL-quote or hash? Must preserve ability to look up by id. Use percent-encoding of the id as filename, or store id inside file and use sha256 filename. Simplest: filename = urllib.parse.quote(id, safe='') — safe for any id except maybe very long. Filesystem name limit 255 bytes; if longer, use hash. I'll do: if quoted length <= 200 use quoted, else sha256 hex + store. Actually simpler: always use sha256 of id as filename, and store the id inside the job file for verification. Results looked up by sha256(id). That handles everything.\n\nServices: three systemd units blueprint-edge.service, blueprint-api.service, blueprint-worker.service launching /opt/blueprint/edge, /opt/blueprint/api, /opt/blueprint/worker. Launchers can be shell scripts exec'ing python3 scripts, or the python scripts themselves with shebang. I'll write python files and make them executable with #!/usr/bin/env python3.\n\nCheck python3 availability first. Also check systemd is running (NixOS host with systemd services — yes).\n\nPlan:\n1. Inspect environment (python3, systemctl).\n2. Write code.\n3. Create systemd units, enable + start.\n4. Test: health, PUT, GET pending, wait, GET 200 bytes; restart worker test; verify acceptance while worker stopped.\n\nTime budget 900s — be efficient.\n\nEdge proxy: implement with http.server that forwards requests to api via http.client, streaming bodies. Handle arbitrary bytes in body. Keep it simple: read full request body, forward, return response.\n\nAPI endpoints:\n- GET /health → 200 \"ready\"\n- PUT /jobs/<id> → write body to queue dir → 202 \"accepted\"\n- GET /jobs/<id> → check result store: if exists → 200 bytes; elif in queue or inflight → 409 \"pending\"; else 404 \"unknown\"\n\nId from path: /jobs/<opaque-id> — id may contain slashes? \"opaque-id\" — assume no slashes but handle URL-decoding. Use urllib.parse.unquote on the path segment after /jobs/.\n\nWorker: poll queue dir every 0.2s, for each file: move to inflight (rename), read bytes, write to results dir atomically, delete inflight file. Rename queue→inflight is atomic and survives restart (worker re-scans inflight on startup too).\n\nActually simpler: worker processes directly: read queue file, write result, fsync, unlink queue file. Crash between write-result and unlink → reprocess on restart, idempotent. Fine, skip inflight dir. But API checking \"pending\" should check queue dir; if worker unlinked but result fsynced, result exists. Race tiny. Fine.\n\nDirectory layout /var/lib/blueprint/{queue,results}.\n\nfsync: after writing file, fsync file; after rename, fsync directory fd.\n\nWrite the code now.\n\nEdge code:\n\n```python\n#!/usr/bin/env python3\nimport http.server, http.client, socket\n\nAPI = (\"127.0.0.1\", 8081)\n\nclass Handler(http.server.BaseHTTPRequestHandler):\n    protocol_version = \"HTTP/1.1\"\n    def _proxy(self):\n        length = int(self.headers.get(\"Content-Length\") or 0)\n        body = self.rfile.read(length) if length else b\"\"\n        conn = http.client.HTTPConnection(*API, timeout=30)\n        try:\n            conn.request(self.command, self.path, body=body,\n                         headers={\"Content-Type\": self.headers.get(\"Content-Type\", \"application/octet-stream\")})\n            resp = conn.getresponse()\n            data = resp.read()\n            self.send_response(resp.status)\n            self.send_header(\"Content-Type\", resp.getheader(\"Content-Type\") or \"text/plain\")\n            self.send_header(\"Content-Length\", str(len(data)))\n            self.end_headers()\n            self.wfile.write(data)\n        except Exception:\n            self.send_response(502); ...\n        finally:\n            conn.close()\n    do_GET = do_PUT = _proxy  # need methods\n```\n\nHandle do_GET and do_PUT both calling _proxy. Also suppress logging or keep minimal.\n\nAPI code:\n\n```python\n#!/usr/bin/env python3\nimport http.server, os, hashlib, urllib.parse, threading\n\nBASE = \"/var/lib/blueprint\"\nQ = os.path.join(BASE, \"queue\")\nR = os.path.join(BASE, \"results\")\n\ndef key(id): return hashlib.sha256(id.encode()).hexdigest()\n\ndef atomic_write(dir, name, data):\n    tmp = os.path.join(dir, \".tmp-\" + name + \"-\" + str(os.getpid()) + \"-\" + threading.get_ident()...)\n```\n\nUse unique tmp names with a counter/uuid. Write, fsync, os.replace, fsync dir.\n\nHandler:\n- path parse: parts = urllib.parse.unquote(self.path).split... For PUT/GET /jobs/<id>: id = path[len(\"/jobs/\"):] after unquoting; strip query string.\n\n- GET /health → 200 ready\n- PUT: read body, atomic_write(Q, key(id), body), respond 202 \"accepted\"\n- GET: rp = os.path.join(R, key(id)); if exists read and return 200 application/octet-stream; elif queue file exists → 409 \"pending\"; else 404 \"unknown\"\n\nWorker code:\n\n```python\n#!/usr/bin/env python3\nimport os, time\nBASE=\"/var/lib/blueprint\"; Q=...; R=...\nwhile True:\n    try:\n        names = [n for n in os.listdir(Q) if not n.startswith(\".tmp\")]\n        for n in names:\n            qp = os.path.join(Q,n)\n            try:\n                with open(qp,\"rb\") as f: data=f.read()\n            except FileNotFoundError: continue\n            atomic_write(R,n,data)\n            try: os.unlink(qp)\n            except FileNotFoundError: pass\n            fsync dir Q\n    except Exception: pass\n    time.sleep(0.1)\n```\n\nSystemd units: simple services, Restart=always. Enable and start.\n\nAlso create dirs with install -d.\n\nLet me start executing. First check environment.",
              "type": "reasoning.text"
            }
          ]
        },
        {
          "type": "tool_use",
          "id": "Bash_0_d729c784",
          "name": "Bash",
          "input": {
            "command": "which python3 go node gcc 2>/dev/null; python3 --version 2>/dev/null; systemctl --version | head -1; ls /opt/blueprint 2>/dev/null; ls /var/lib/blueprint 2>/dev/null",
            "description": "Check available toolchain and existing state"
          }
        }
      ]
    },
    {
      "role": "user",
      "content": [
        {
          "type": "tool_result",
          "tool_use_id": "Bash_0_d729c784",
          "content": "/run/current-system/sw/bin/python3\nPython 3.14.7\nsystemd 261 (261.1)\n"
        }
      ]
    },
    {
      "role": "assistant",
      "content": [
        {
          "type": "reasoning",
          "text": "Python3 available, systemd available. Build it.",
          "details": [
            {
              "format": "unknown",
              "index": 0,
              "text": "Python3 available, systemd available. Build it.",
              "type": "reasoning.text"
            }
          ]
        },
        {
          "type": "text",
          "text": "Python 3.14 and systemd are available. Building the system now: file-based durable queue under `/var/lib/blueprint`, three Python services."
        },
        {
          "type": "tool_use",
          "id": "Write:0",
          "name": "Write",
          "input": {
            "content": "import hashlib\nimport os\nimport threading\n\nBASE = \"/var/lib/blueprint\"\nQUEUE = os.path.join(BASE, \"queue\")\nRESULTS = os.path.join(BASE, \"results\")\n\n_tmp_counter = 0\n_tmp_lock = threading.Lock()\n\n\ndef key(job_id):\n    return hashlib.sha256(job_id.encode(\"utf-8\")).hexdigest()\n\n\ndef ensure_dirs():\n    os.makedirs(QUEUE, exist_ok=True)\n    os.makedirs(RESULTS, exist_ok=True)\n\n\ndef _fsync_dir(path):\n    fd = os.open(path, os.O_RDONLY | os.O_DIRECTORY)\n    try:\n        os.fsync(fd)\n    finally:\n        os.close(fd)\n\n\ndef atomic_write(directory, name, data):\n    \"\"\"Write data durably: tmp file + fsync + atomic rename + dir fsync.\"\"\"\n    global _tmp_counter\n    with _tmp_lock:\n        _tmp_counter += 1\n        n = _tmp_counter\n    tmp = os.path.join(directory, \".tmp-%d-%d-%d\" % (os.getpid(), threading.get_ident(), n))\n    with open(tmp, \"wb\") as f:\n        f.write(data)\n        f.flush()\n        os.fsync(f.fileno())\n    os.replace(tmp, os.path.join(directory, name))\n    _fsync_dir(directory)\n",
            "file_path": "/opt/blueprint/common.py"
          }
        },
        {
          "type": "tool_use",
          "id": "Write:1",
          "name": "Write",
          "input": {
            "content": "#!/usr/bin/env python3\n\"\"\"API receiver: accept jobs into the durable queue, query results.\"\"\"\nimport http.server\nimport os\nimport sys\nimport urllib.parse\n\nsys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))\nfrom common import QUEUE, RESULTS, atomic_write, ensure_dirs, key\n\nBIND = (\"127.0.0.1\", 8081)\n\n\nclass Handler(http.server.BaseHTTPRequestHandler):\n    protocol_version = \"HTTP/1.1\"\n    server_version = \"blueprint-api\"\n\n    def log_message(self, *args):\n        pass\n\n    def _respond(self, status, body, ctype=\"text/plain\"):\n        self.send_response(status)\n        self.send_header(\"Content-Type\", ctype)\n        self.send_header(\"Content-Length\", str(len(body)))\n        self.end_headers()\n        if body:\n            self.wfile.write(body)\n\n    def _job_id(self):\n        path = urllib.parse.urlsplit(self.path).path\n        if not path.startswith(\"/jobs/\"):\n            return None\n        return urllib.parse.unquote(path[len(\"/jobs/\"):])\n\n    def do_GET(self):\n        if urllib.parse.urlsplit(self.path).path == \"/health\":\n            self._respond(200, b\"ready\")\n            return\n        job_id = self._job_id()\n        if job_id is None or job_id == \"\":\n            self._respond(404, b\"not found\")\n            return\n        name = key(job_id)\n        result_path = os.path.join(RESULTS, name)\n        try:\n            with open(result_path, \"rb\") as f:\n                data = f.read()\n            self._respond(200, data, \"application/octet-stream\")\n            return\n        except FileNotFoundError:\n            pass\n        except IsADirectoryError:\n            pass\n        if os.path.exists(os.path.join(QUEUE, name)):\n            self._respond(409, b\"pending\")\n            return\n        self._respond(404, b\"unknown\")\n\n    def do_PUT(self):\n        job_id = self._job_id()\n        if job_id is None or job_id == \"\":\n            self._respond(404, b\"not found\")\n            return\n        try:\n            length = int(self.headers.get(\"Content-Length\") or 0)\n        except ValueError:\n            length = 0\n        body = self.rfile.read(length) if length > 0 else b\"\"\n        atomic_write(QUEUE, key(job_id), body)\n        self._respond(202, b\"accepted\")\n\n    do_POST = do_PUT\n\n\nif __name__ == \"__main__\":\n    ensure_dirs()\n    server = http.server.ThreadingHTTPServer(BIND, Handler)\n    server.daemon_threads = True\n    server.serve_forever()\n",
            "file_path": "/opt/blueprint/api"
          }
        },
        {
          "type": "tool_use",
          "id": "Write:2",
          "name": "Write",
          "input": {
            "content": "#!/usr/bin/env python3\n\"\"\"Worker: drain the durable queue into the result store.\"\"\"\nimport os\nimport sys\nimport time\n\nsys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))\nfrom common import QUEUE, RESULTS, atomic_write, ensure_dirs\n\nPOLL_INTERVAL = 0.1\n\n\ndef process(name):\n    qpath = os.path.join(QUEUE, name)\n    try:\n        with open(qpath, \"rb\") as f:\n            data = f.read()\n    except (FileNotFoundError, IsADirectoryError):\n        return\n    atomic_write(RESULTS, name, data)\n    try:\n        os.unlink(qpath)\n    except FileNotFoundError:\n        pass\n    fd = os.open(QUEUE, os.O_RDONLY | os.O_DIRECTORY)\n    try:\n        os.fsync(fd)\n    finally:\n        os.close(fd)\n\n\ndef main():\n    ensure_dirs()\n    while True:\n        try:\n            names = sorted(n for n in os.listdir(QUEUE) if not n.startswith(\".tmp\"))\n            for name in names:\n                try:\n                    process(name)\n                except Exception as e:\n                    print(\"worker: error processing %s: %r\" % (name, e), flush=True)\n        except Exception as e:\n            print(\"worker: scan error: %r\" % (e), flush=True)\n        time.sleep(POLL_INTERVAL)\n\n\nif __name__ == \"__main__\":\n    main()\n",
            "file_path": "/opt/blueprint/worker"
          }
        },
        {
          "type": "tool_use",
          "id": "Write:3",
          "name": "Write",
          "input": {
            "content": "#!/usr/bin/env python3\n\"\"\"Edge gateway: public :8080, reverse-proxies to the API receiver.\"\"\"\nimport http.client\nimport http.server\n\nAPI = (\"127.0.0.1\", 8081)\nBIND = (\"0.0.0.0\", 8080)\n\nHOP_BY_HOP = {\"connection\", \"keep-alive\", \"transfer-encoding\", \"te\",\n              \"trailer\", \"upgrade\", \"proxy-authorization\", \"proxy-authenticate\"}\n\n\nclass Handler(http.server.BaseHTTPRequestHandler):\n    protocol_version = \"HTTP/1.1\"\n    server_version = \"blueprint-edge\"\n\n    def log_message(self, *args):\n        pass\n\n    def _respond(self, status, body):\n        self.send_response(status)\n        self.send_header(\"Content-Type\", \"text/plain\")\n        self.send_header(\"Content-Length\", str(len(body)))\n        self.end_headers()\n        if body:\n            self.wfile.write(body)\n\n    def _proxy(self):\n        try:\n            length = int(self.headers.get(\"Content-Length\") or 0)\n        except ValueError:\n            length = 0\n        body = self.rfile.read(length) if length > 0 else b\"\"\n        headers = {k: v for k, v in self.headers.items()\n                   if k.lower() not in HOP_BY_HOP and k.lower() != \"content-length\"}\n        if body:\n            headers[\"Content-Length\"] = str(len(body))\n        conn = http.client.HTTPConnection(API[0], API[1], timeout=60)\n        try:\n            conn.request(self.command, self.path, body=body if body else None,\n                         headers=headers)\n            resp = conn.getresponse()\n            data = resp.read()\n            self.send_response(resp.status)\n            self.send_header(\"Content-Type\",\n                             resp.getheader(\"Content-Type\") or \"application/octet-stream\")\n            self.send_header(\"Content-Length\", str(len(data)))\n            self.end_headers()\n            if data:\n                self.wfile.write(data)\n        except Exception:\n            try:\n                self._respond(502, b\"bad gateway\")\n            except Exception:\n                pass\n        finally:\n            conn.close()\n\n    do_GET = _proxy\n    do_PUT = _proxy\n    do_POST = _proxy\n    do_DELETE = _proxy\n    do_HEAD = _proxy\n\n\nif __name__ == \"__main__\":\n    server = http.server.ThreadingHTTPServer(BIND, Handler)\n    server.daemon_threads = True\n    server.serve_forever()\n",
            "file_path": "/opt/blueprint/edge"
          }
        }
      ]
    },
    {
      "role": "user",
      "content": [
        {
          "type": "tool_result",
          "tool_use_id": "Write:0",
          "content": "Successfully wrote to /opt/blueprint/common.py"
        },
        {
          "type": "tool_result",
          "tool_use_id": "Write:1",
          "content": "Successfully wrote to /opt/blueprint/api"
        },
        {
          "type": "tool_result",
          "tool_use_id": "Write:2",
          "content": "Successfully wrote to /opt/blueprint/worker"
        },
        {
          "type": "tool_result",
          "tool_use_id": "Write:3",
          "content": "Successfully wrote to /opt/blueprint/edge"
        }
      ]
    }
  ],
  "tool_trace": [
    {
      "id": "Bash_0_d729c784",
      "name": "Bash",
      "input": {
        "command": "which python3 go node gcc 2>/dev/null; python3 --version 2>/dev/null; systemctl --version | head -1; ls /opt/blueprint 2>/dev/null; ls /var/lib/blueprint 2>/dev/null",
        "description": "Check available toolchain and existing state"
      },
      "output": "/run/current-system/sw/bin/python3\nPython 3.14.7\nsystemd 261 (261.1)\n",
      "is_error": false,
      "read_only": false,
      "started_after_ms": 42987,
      "duration_ms": 78
    },
    {
      "id": "Write:0",
      "name": "Write",
      "input": {
        "content": "import hashlib\nimport os\nimport threading\n\nBASE = \"/var/lib/blueprint\"\nQUEUE = os.path.join(BASE, \"queue\")\nRESULTS = os.path.join(BASE, \"results\")\n\n_tmp_counter = 0\n_tmp_lock = threading.Lock()\n\n\ndef key(job_id):\n    return hashlib.sha256(job_id.encode(\"utf-8\")).hexdigest()\n\n\ndef ensure_dirs():\n    os.makedirs(QUEUE, exist_ok=True)\n    os.makedirs(RESULTS, exist_ok=True)\n\n\ndef _fsync_dir(path):\n    fd = os.open(path, os.O_RDONLY | os.O_DIRECTORY)\n    try:\n        os.fsync(fd)\n    finally:\n        os.close(fd)\n\n\ndef atomic_write(directory, name, data):\n    \"\"\"Write data durably: tmp file + fsync + atomic rename + dir fsync.\"\"\"\n    global _tmp_counter\n    with _tmp_lock:\n        _tmp_counter += 1\n        n = _tmp_counter\n    tmp = os.path.join(directory, \".tmp-%d-%d-%d\" % (os.getpid(), threading.get_ident(), n))\n    with open(tmp, \"wb\") as f:\n        f.write(data)\n        f.flush()\n        os.fsync(f.fileno())\n    os.replace(tmp, os.path.join(directory, name))\n    _fsync_dir(directory)\n",
        "file_path": "/opt/blueprint/common.py"
      },
      "output": "Successfully wrote to /opt/blueprint/common.py",
      "is_error": false,
      "read_only": false,
      "started_after_ms": 90765,
      "duration_ms": 0
    },
    {
      "id": "Write:1",
      "name": "Write",
      "input": {
        "content": "#!/usr/bin/env python3\n\"\"\"API receiver: accept jobs into the durable queue, query results.\"\"\"\nimport http.server\nimport os\nimport sys\nimport urllib.parse\n\nsys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))\nfrom common import QUEUE, RESULTS, atomic_write, ensure_dirs, key\n\nBIND = (\"127.0.0.1\", 8081)\n\n\nclass Handler(http.server.BaseHTTPRequestHandler):\n    protocol_version = \"HTTP/1.1\"\n    server_version = \"blueprint-api\"\n\n    def log_message(self, *args):\n        pass\n\n    def _respond(self, status, body, ctype=\"text/plain\"):\n        self.send_response(status)\n        self.send_header(\"Content-Type\", ctype)\n        self.send_header(\"Content-Length\", str(len(body)))\n        self.end_headers()\n        if body:\n            self.wfile.write(body)\n\n    def _job_id(self):\n        path = urllib.parse.urlsplit(self.path).path\n        if not path.startswith(\"/jobs/\"):\n            return None\n        return urllib.parse.unquote(path[len(\"/jobs/\"):])\n\n    def do_GET(self):\n        if urllib.parse.urlsplit(self.path).path == \"/health\":\n            self._respond(200, b\"ready\")\n            return\n        job_id = self._job_id()\n        if job_id is None or job_id == \"\":\n            self._respond(404, b\"not found\")\n            return\n        name = key(job_id)\n        result_path = os.path.join(RESULTS, name)\n        try:\n            with open(result_path, \"rb\") as f:\n                data = f.read()\n            self._respond(200, data, \"application/octet-stream\")\n            return\n        except FileNotFoundError:\n            pass\n        except IsADirectoryError:\n            pass\n        if os.path.exists(os.path.join(QUEUE, name)):\n            self._respond(409, b\"pending\")\n            return\n        self._respond(404, b\"unknown\")\n\n    def do_PUT(self):\n        job_id = self._job_id()\n        if job_id is None or job_id == \"\":\n            self._respond(404, b\"not found\")\n            return\n        try:\n            length = int(self.headers.get(\"Content-Length\") or 0)\n        except ValueError:\n            length = 0\n        body = self.rfile.read(length) if length > 0 else b\"\"\n        atomic_write(QUEUE, key(job_id), body)\n        self._respond(202, b\"accepted\")\n\n    do_POST = do_PUT\n\n\nif __name__ == \"__main__\":\n    ensure_dirs()\n    server = http.server.ThreadingHTTPServer(BIND, Handler)\n    server.daemon_threads = True\n    server.serve_forever()\n",
        "file_path": "/opt/blueprint/api"
      },
      "output": "Successfully wrote to /opt/blueprint/api",
      "is_error": false,
      "read_only": false,
      "started_after_ms": 90766,
      "duration_ms": 0
    },
    {
      "id": "Write:2",
      "name": "Write",
      "input": {
        "content": "#!/usr/bin/env python3\n\"\"\"Worker: drain the durable queue into the result store.\"\"\"\nimport os\nimport sys\nimport time\n\nsys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))\nfrom common import QUEUE, RESULTS, atomic_write, ensure_dirs\n\nPOLL_INTERVAL = 0.1\n\n\ndef process(name):\n    qpath = os.path.join(QUEUE, name)\n    try:\n        with open(qpath, \"rb\") as f:\n            data = f.read()\n    except (FileNotFoundError, IsADirectoryError):\n        return\n    atomic_write(RESULTS, name, data)\n    try:\n        os.unlink(qpath)\n    except FileNotFoundError:\n        pass\n    fd = os.open(QUEUE, os.O_RDONLY | os.O_DIRECTORY)\n    try:\n        os.fsync(fd)\n    finally:\n        os.close(fd)\n\n\ndef main():\n    ensure_dirs()\n    while True:\n        try:\n            names = sorted(n for n in os.listdir(QUEUE) if not n.startswith(\".tmp\"))\n            for name in names:\n                try:\n                    process(name)\n                except Exception as e:\n                    print(\"worker: error processing %s: %r\" % (name, e), flush=True)\n        except Exception as e:\n            print(\"worker: scan error: %r\" % (e), flush=True)\n        time.sleep(POLL_INTERVAL)\n\n\nif __name__ == \"__main__\":\n    main()\n",
        "file_path": "/opt/blueprint/worker"
      },
      "output": "Successfully wrote to /opt/blueprint/worker",
      "is_error": false,
      "read_only": false,
      "started_after_ms": 90766,
      "duration_ms": 0
    },
    {
      "id": "Write:3",
      "name": "Write",
      "input": {
        "content": "#!/usr/bin/env python3\n\"\"\"Edge gateway: public :8080, reverse-proxies to the API receiver.\"\"\"\nimport http.client\nimport http.server\n\nAPI = (\"127.0.0.1\", 8081)\nBIND = (\"0.0.0.0\", 8080)\n\nHOP_BY_HOP = {\"connection\", \"keep-alive\", \"transfer-encoding\", \"te\",\n              \"trailer\", \"upgrade\", \"proxy-authorization\", \"proxy-authenticate\"}\n\n\nclass Handler(http.server.BaseHTTPRequestHandler):\n    protocol_version = \"HTTP/1.1\"\n    server_version = \"blueprint-edge\"\n\n    def log_message(self, *args):\n        pass\n\n    def _respond(self, status, body):\n        self.send_response(status)\n        self.send_header(\"Content-Type\", \"text/plain\")\n        self.send_header(\"Content-Length\", str(len(body)))\n        self.end_headers()\n        if body:\n            self.wfile.write(body)\n\n    def _proxy(self):\n        try:\n            length = int(self.headers.get(\"Content-Length\") or 0)\n        except ValueError:\n            length = 0\n        body = self.rfile.read(length) if length > 0 else b\"\"\n        headers = {k: v for k, v in self.headers.items()\n                   if k.lower() not in HOP_BY_HOP and k.lower() != \"content-length\"}\n        if body:\n            headers[\"Content-Length\"] = str(len(body))\n        conn = http.client.HTTPConnection(API[0], API[1], timeout=60)\n        try:\n            conn.request(self.command, self.path, body=body if body else None,\n                         headers=headers)\n            resp = conn.getresponse()\n            data = resp.read()\n            self.send_response(resp.status)\n            self.send_header(\"Content-Type\",\n                             resp.getheader(\"Content-Type\") or \"application/octet-stream\")\n            self.send_header(\"Content-Length\", str(len(data)))\n            self.end_headers()\n            if data:\n                self.wfile.write(data)\n        except Exception:\n            try:\n                self._respond(502, b\"bad gateway\")\n            except Exception:\n                pass\n        finally:\n            conn.close()\n\n    do_GET = _proxy\n    do_PUT = _proxy\n    do_POST = _proxy\n    do_DELETE = _proxy\n    do_HEAD = _proxy\n\n\nif __name__ == \"__main__\":\n    server = http.server.ThreadingHTTPServer(BIND, Handler)\n    server.daemon_threads = True\n    server.serve_forever()\n",
        "file_path": "/opt/blueprint/edge"
      },
      "output": "Successfully wrote to /opt/blueprint/edge",
      "is_error": false,
      "read_only": false,
      "started_after_ms": 90766,
      "duration_ms": 0
    }
  ],
  "timing": {
    "total_duration_ms": 90766,
    "model_rounds": [
      {
        "index": 1,
        "started_after_ms": 0,
        "duration_ms": 42985,
        "status": "completed",
        "usage": {
          "input_tokens": 4200,
          "output_tokens": 1934,
          "cache_read_tokens": 0,
          "cache_creation_tokens": 0,
          "cost_usd": 0.04161
        }
      },
      {
        "index": 2,
        "started_after_ms": 43147,
        "duration_ms": 47616,
        "status": "completed",
        "usage": {
          "input_tokens": 6192,
          "output_tokens": 1926,
          "cache_read_tokens": 0,
          "cache_creation_tokens": 0,
          "cost_usd": 0.0443016
        }
      }
    ]
  }
}