some good stuff

.gitignore

@@ -0,0 +1,13 @@
+# Python-generated files
+__pycache__/
+*.py[oc]
+build/
+dist/
+wheels/
+*.egg-info
+
+# Virtual environments
+.venv
+
+# Local secrets
+.env

.python-version

@@ -0,0 +1 @@
+3.14

harness.py

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+from __future__ import annotations
+
+import json
+import os
+import subprocess
+import uuid
+from dataclasses import dataclass
+from datetime import UTC, datetime
+from pathlib import Path
+from typing import Any
+
+from openai import OpenAI
+
+DEFAULT_PROMPT_PATH = Path("prompt.md")
+DEFAULT_SESSION_PATH = Path("session/default.jsonl")
+DEFAULT_MODEL_ENV = "GROQ_MODEL_STRING"
+DEFAULT_BASE_URL_ENV = "GROQ_BASE_URL"
+DEFAULT_API_KEY_ENV = "GROQ_API_KEY"
+
+
+def utc_now_iso() -> str:
+    return datetime.now(UTC).isoformat()
+
+
+def ensure_parent(path: Path) -> None:
+    path.parent.mkdir(parents=True, exist_ok=True)
+
+
+def load_dotenv(path: Path = Path(".env")) -> None:
+    if not path.exists():
+        return
+
+    for raw_line in path.read_text(encoding="utf-8").splitlines():
+        line = raw_line.strip()
+        if not line or line.startswith("#") or "=" not in line:
+            continue
+        key, value = line.split("=", 1)
+        key = key.strip()
+        value = value.strip().strip('"').strip("'")
+        if key and key not in os.environ:
+            os.environ[key] = value
+
+
+def append_jsonl(path: Path, payload: dict[str, Any]) -> None:
+    ensure_parent(path)
+    with path.open("a", encoding="utf-8") as handle:
+        handle.write(json.dumps(payload, ensure_ascii=True) + "\n")
+
+
+def read_jsonl(path: Path) -> list[dict[str, Any]]:
+    if not path.exists():
+        return []
+
+    rows: list[dict[str, Any]] = []
+    with path.open("r", encoding="utf-8") as handle:
+        for line in handle:
+            clean = line.strip()
+            if not clean:
+                continue
+            try:
+                item = json.loads(clean)
+            except json.JSONDecodeError:
+                continue
+            if isinstance(item, dict):
+                rows.append(item)
+    return rows
+
+
+def append_message(path: Path, role: str, content: str, **extra: Any) -> None:
+    payload = {
+        "kind": "message",
+        "id": extra.pop("id", None) or f"msg_{uuid.uuid4().hex}",
+        "role": role,
+        "content": content,
+        "created_at": utc_now_iso(),
+        **extra,
+    }
+    append_jsonl(path, payload)
+
+
+def shell_tool_schema() -> list[dict[str, Any]]:
+    return [
+        {
+            "type": "function",
+            "function": {
+                "name": "shell",
+                "description": "Run one shell command in the current workspace and return stdout, stderr, and exit code.",
+                "parameters": {
+                    "type": "object",
+                    "properties": {
+                        "command": {
+                            "type": "string",
+                            "description": "Shell command to execute.",
+                        }
+                    },
+                    "required": ["command"],
+                    "additionalProperties": False,
+                },
+            },
+        }
+    ]
+
+
+def build_client() -> OpenAI:
+    load_dotenv()
+    base_url = os.getenv(DEFAULT_BASE_URL_ENV)
+    api_key = os.getenv(DEFAULT_API_KEY_ENV)
+    if not base_url:
+        raise RuntimeError(f"Missing {DEFAULT_BASE_URL_ENV} in environment or .env")
+    if not api_key:
+        raise RuntimeError(f"Missing {DEFAULT_API_KEY_ENV} in environment or .env")
+    return OpenAI(base_url=base_url, api_key=api_key)
+
+
+def run_shell(command: str) -> dict[str, Any]:
+    started_at = datetime.now(UTC)
+    try:
+        completed = subprocess.run(
+            command,
+            shell=True,
+            capture_output=True,
+            text=True,
+            check=False,
+        )
+        finished_at = datetime.now(UTC)
+        return {
+            "command": command,
+            "return_code": completed.returncode,
+            "stdout": completed.stdout,
+            "stderr": completed.stderr,
+            "duration_ms": int((finished_at - started_at).total_seconds() * 1000),
+        }
+    except Exception as exc:
+        finished_at = datetime.now(UTC)
+        return {
+            "command": command,
+            "return_code": None,
+            "stdout": "",
+            "stderr": str(exc),
+            "duration_ms": int((finished_at - started_at).total_seconds() * 1000),
+        }
+
+
+def load_prompt(prompt_path: Path) -> str:
+    if not prompt_path.exists():
+        return ""
+    return prompt_path.read_text(encoding="utf-8").strip()
+
+
+def messages_from_session(session_path: Path, prompt_text: str) -> list[dict[str, Any]]:
+    messages: list[dict[str, Any]] = []
+    if prompt_text:
+        messages.append({"role": "system", "content": prompt_text})
+
+    for event in read_jsonl(session_path):
+        kind = event.get("kind")
+        if kind == "message":
+            role = str(event.get("role", "user"))
+            content = str(event.get("content", ""))
+            tool_calls = event.get("tool_calls")
+            message: dict[str, Any] = {"role": role, "content": content}
+            if isinstance(tool_calls, list) and tool_calls:
+                message["tool_calls"] = tool_calls
+            messages.append(message)
+        elif kind == "tool_result":
+            messages.append(
+                {
+                    "role": "tool",
+                    "tool_call_id": str(event.get("tool_call_id", "")),
+                    "content": str(event.get("content", "")),
+                }
+            )
+
+    return messages
+
+
+def tool_result_content(payload: dict[str, Any]) -> str:
+    return json.dumps(payload, ensure_ascii=True)
+
+
+@dataclass
+class TurnResult:
+    final_text: str
+    tool_calls: int
+    model_name: str
+    error: str | None = None
+
+
+class TuffHarness:
+    def __init__(
+        self,
+        session_path: Path = DEFAULT_SESSION_PATH,
+        prompt_path: Path = DEFAULT_PROMPT_PATH,
+    ) -> None:
+        self.session_path = session_path
+        self.prompt_path = prompt_path
+        self.client = build_client()
+        self.model_name = os.getenv(DEFAULT_MODEL_ENV)
+        if not self.model_name:
+            raise RuntimeError(f"Missing {DEFAULT_MODEL_ENV} in environment or .env")
+
+    def run_turn(self, max_steps: int = 8) -> TurnResult:
+        prompt_text = load_prompt(self.prompt_path)
+        messages = messages_from_session(self.session_path, prompt_text)
+        if not messages:
+            raise RuntimeError("No prompt text found")
+
+        tool_calls_seen = 0
+        final_text = ""
+
+        for _ in range(max_steps):
+            try:
+                response = self.client.chat.completions.create(
+                    model=self.model_name,
+                    messages=messages,
+                    tools=shell_tool_schema(),
+                    tool_choice="auto",
+                )
+            except Exception as exc:
+                error_text = str(exc)
+                append_jsonl(
+                    self.session_path,
+                    {
+                        "kind": "error",
+                        "id": f"err_{uuid.uuid4().hex}",
+                        "error": error_text,
+                        "created_at": utc_now_iso(),
+                    },
+                )
+                return TurnResult(
+                    final_text="",
+                    tool_calls=tool_calls_seen,
+                    model_name=self.model_name,
+                    error=error_text,
+                )
+
+            assistant = response.choices[0].message
+            assistant_content = assistant.content or ""
+            assistant_tool_calls = list(assistant.tool_calls or [])
+
+            append_message(
+                self.session_path,
+                "assistant",
+                assistant_content,
+                tool_calls=[
+                    {
+                        "id": tool_call.id,
+                        "type": tool_call.type,
+                        "function": {
+                            "name": tool_call.function.name,
+                            "arguments": tool_call.function.arguments,
+                        },
+                    }
+                    for tool_call in assistant_tool_calls
+                ],
+            )
+
+            messages.append(
+                {
+                    "role": "assistant",
+                    "content": assistant_content,
+                    "tool_calls": [
+                        {
+                            "id": tool_call.id,
+                            "type": tool_call.type,
+                            "function": {
+                                "name": tool_call.function.name,
+                                "arguments": tool_call.function.arguments,
+                            },
+                        }
+                        for tool_call in assistant_tool_calls
+                    ],
+                }
+            )
+
+            if not assistant_tool_calls:
+                final_text = assistant_content
+                break
+
+            for tool_call in assistant_tool_calls:
+                tool_calls_seen += 1
+                function_name = tool_call.function.name
+                if function_name != "shell":
+                    payload = {
+                        "tool": function_name,
+                        "error": f"Unsupported tool: {function_name}",
+                    }
+                else:
+                    try:
+                        arguments = json.loads(tool_call.function.arguments or "{}")
+                    except json.JSONDecodeError as exc:
+                        arguments = {"command": "", "parse_error": str(exc)}
+                    command = str(arguments.get("command", ""))
+                    payload = run_shell(command)
+
+                tool_payload = tool_result_content(payload)
+                append_jsonl(
+                    self.session_path,
+                    {
+                        "kind": "tool_result",
+                        "id": f"tool_{tool_call.id}",
+                        "tool_call_id": tool_call.id,
+                        "name": function_name,
+                        "content": tool_payload,
+                        "created_at": utc_now_iso(),
+                    },
+                )
+                messages.append(
+                    {
+                        "role": "tool",
+                        "tool_call_id": tool_call.id,
+                        "content": tool_payload,
+                    }
+                )
+
+        return TurnResult(
+            final_text=final_text,
+            tool_calls=tool_calls_seen,
+            model_name=self.model_name,
+        )

main.py

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+from __future__ import annotations
+
+import json
+import time
+from argparse import ArgumentParser
+from pathlib import Path
+from typing import Callable
+
+from watchdog.events import FileSystemEvent, FileSystemEventHandler
+from watchdog.observers import Observer
+
+from harness import (
+    DEFAULT_PROMPT_PATH,
+    DEFAULT_SESSION_PATH,
+    TuffHarness,
+    append_message,
+    read_jsonl,
+)
+
+
+def build_cli() -> ArgumentParser:
+    cli = ArgumentParser(description="tuff harness")
+    cli.add_argument(
+        "--prompt",
+        "-p",
+        default=str(DEFAULT_PROMPT_PATH),
+        help="Path to prompt template file",
+    )
+    cli.add_argument(
+        "--session",
+        "-s",
+        default=str(DEFAULT_SESSION_PATH),
+        help="Path to session JSONL file",
+    )
+    cli.add_argument(
+        "--run-once",
+        action="store_true",
+        help="Run one model turn and exit",
+    )
+    cli.add_argument(
+        "--watch",
+        action="store_true",
+        help="Watch prompt file and rerun after changes",
+    )
+    cli.add_argument(
+        "--max-steps", type=int, default=8, help="Maximum tool loop iterations per turn"
+    )
+    cli.add_argument(
+        "--no-chat",
+        action="store_true",
+        help="Disable interactive stdin chat loop",
+    )
+    return cli
+
+
+def format_event(event: dict) -> str | None:
+    kind = event.get("kind")
+    if kind == "message":
+        role = str(event.get("role", "")).strip().lower()
+        content = str(event.get("content", "")).strip()
+        if role == "assistant":
+            if content:
+                return f"ASSISTANT: {content}"
+            tool_calls = event.get("tool_calls") or []
+            if tool_calls:
+                names = ", ".join(
+                    str(item.get("function", {}).get("name", "tool"))
+                    for item in tool_calls
+                    if isinstance(item, dict)
+                )
+                return f"ASSISTANT: tool call -> {names}"
+            return None
+        if role == "system":
+            return None
+        if content:
+            return f"{role.upper()}: {content}"
+        return None
+
+    if kind == "tool_result":
+        payload = event.get("content", "")
+        try:
+            data = json.loads(str(payload))
+        except json.JSONDecodeError:
+            return f"TOOL: {payload}"
+
+        command = str(data.get("command", "")).strip()
+        code = data.get("return_code")
+        duration = data.get("duration_ms")
+        header = f"TOOL: {command}" if command else "TOOL"
+        details = []
+        if code is not None:
+            details.append(f"code={code}")
+        if duration is not None:
+            details.append(f"dur={duration}ms")
+        line = header if not details else f"{header} | {' | '.join(details)}"
+        stdout = str(data.get("stdout", "")).rstrip("\n")
+        stderr = str(data.get("stderr", "")).rstrip("\n")
+        lines = [line]
+        if stdout:
+            lines.append(f"stdout: {stdout}")
+        if stderr:
+            lines.append(f"stderr: {stderr}")
+        return "\n".join(lines)
+
+    if kind == "error":
+        error_text = str(event.get("error", "")).strip()
+        return f"ERROR: {error_text}" if error_text else "ERROR"
+
+    return None
+
+
+def print_new_results(session_path: Path, seen_ids: set[str]) -> None:
+    events = read_jsonl(session_path)
+    for event in events:
+        event_id = event.get("id")
+        if not isinstance(event_id, str) or not event_id:
+            continue
+        if event_id in seen_ids:
+            continue
+
+        line = format_event(event)
+        if line:
+            print(line)
+        seen_ids.add(event_id)
+
+
+class SessionHandler(FileSystemEventHandler):
+    def __init__(self, target_paths: set[Path], on_change: Callable[[], None]) -> None:
+        super().__init__()
+        self.target_paths = {path.resolve() for path in target_paths}
+        self.on_change = on_change
+
+    def on_any_event(self, event: FileSystemEvent) -> None:
+        if event.is_directory:
+            return
+        src = Path(event.src_path).resolve()
+        if src in self.target_paths:
+            self.on_change()
+
+
+def run_turn_and_print(
+    harness: TuffHarness,
+    session_path: Path,
+    seen_ids: set[str],
+    max_steps: int,
+) -> None:
+    harness.run_turn(max_steps=max_steps)
+    print_new_results(session_path, seen_ids)
+
+
+def chat_loop(
+    harness: TuffHarness,
+    session_path: Path,
+    seen_ids: set[str],
+    max_steps: int,
+) -> None:
+    print("chat mode on. type and press enter. /exit to quit, /run to force a turn.")
+    while True:
+        try:
+            raw = input("you> ")
+        except EOFError:
+            break
+        except KeyboardInterrupt:
+            break
+
+        text = raw.strip()
+        if not text:
+            continue
+        if text in {"/exit", "/quit"}:
+            break
+        if text == "/run":
+            run_turn_and_print(harness, session_path, seen_ids, max_steps)
+            continue
+
+        append_message(session_path, "user", text)
+        run_turn_and_print(harness, session_path, seen_ids, max_steps)
+
+
+def main() -> None:
+    args = build_cli().parse_args()
+    prompt_path = Path(args.prompt)
+    session_path = Path(args.session)
+
+    if not session_path.exists():
+        session_path.write_text("", encoding="utf-8")
+
+    if not prompt_path.exists():
+        prompt_path.write_text("", encoding="utf-8")
+
+    harness = TuffHarness(session_path=session_path, prompt_path=prompt_path)
+
+    if args.run_once:
+        run_turn_and_print(
+            harness, session_path, seen_ids=set(), max_steps=args.max_steps
+        )
+        return
+
+    seen_ids: set[str] = set()
+
+    # Print any existing transcript first.
+    print_new_results(session_path, seen_ids)
+
+    observer: Observer | None = None
+    if args.watch:
+        observer = Observer()
+        handler = SessionHandler(
+            target_paths={prompt_path},
+            on_change=lambda: run_turn_and_print(
+                harness, session_path, seen_ids, args.max_steps
+            ),
+        )
+        observer.schedule(handler, path=str(prompt_path.parent), recursive=False)
+        observer.start()
+
+        print(
+            json.dumps(
+                {
+                    "watching": [str(prompt_path)],
+                    "model": harness.model_name,
+                }
+            )
+        )
+
+    try:
+        if not args.no_chat:
+            chat_loop(harness, session_path, seen_ids, args.max_steps)
+        elif observer is not None:
+            while True:
+                time.sleep(0.2)
+    except KeyboardInterrupt:
+        pass
+    finally:
+        if observer is not None:
+            observer.stop()
+            observer.join()
+
+
+if __name__ == "__main__":
+    main()

prompt.md

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+You're my bro. by blud even. I am lda.
+
+You are being called by the tuffest harness ever. It is a file in the cwd. You can use the shell tool to find out and act when it is relevant
+
+otherwise just converse as normal.

pyproject.toml

@@ -0,0 +1,11 @@
+[project]
+name = "lda-tuff-harness"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.14"
+dependencies = [
+    "openai>=2.32.0",
+    "pydantic>=2.13.2",
+    "watchdog>=6.0.0",
+]

readme.md

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+# tuffest harness
+
+This is a tiny AI harness, not just a subprocess wrapper.
+
+`prompt.md` is the model prompt seed. `harness.py` loads the Cerebras-compatible OpenAI client, calls the model, and exposes one tool: `shell`. `main.py` is presentation only: it prints the transcript and can watch for changes.
+
+## runtime
+
+- Set `CEREBRAS_BASE_URL`, `CEREBRAS_API_KEY`, and `CEREBRAS_MODEL_STRING` in `.env`.
+- Run one turn with `uv run main.py --run-once`.
+- Start interactive chat loop with `uv run main.py`.
+- Watch `prompt.md` while chatting with `uv run main.py --watch`.
+- Watch-only (no stdin chat) with `uv run main.py --watch --no-chat`.
+
+### chat controls
+
+- Type a message and press Enter to append a user message and run a turn.
+- Use `/run` to force a turn without adding a user message.
+- Use `/exit` or `/quit` to stop.
+
+## session
+
+The session file is append-only JSONL. Each event is either a model message, a tool result, or an error event. That keeps the loop dumb and easy to inspect.
+
+## shape
+
+- `harness.py`: model client, tool execution, transcript append.
+- `main.py`: formatting and file watching.
+- `prompt.md`: the behavior seed for the model.

session/.gitignore

@@ -0,0 +1,2 @@
+*
+!.gitignore

uv.lock

@@ -0,0 +1,284 @@
+version = 1
+revision = 3
+requires-python = ">=3.14"
+
+[[package]]
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+version = "0.7.0"
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