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agent harness initialize repo

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Roger Oriol
2026-07-19 20:13:54 +02:00
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import argparse
import os
import json
from enum import Enum
from pathlib import Path
from openai import OpenAI
from tools import get_tool_registry, get_tool_schemas
from dotenv import load_dotenv
load_dotenv()
TOOL_REGISTRY = get_tool_registry()
TOOL_SCHEMAS = get_tool_schemas()
# ---------------------------------------------------------------------------
# Permission modes
# ---------------------------------------------------------------------------
class PermissionMode(Enum):
DEFAULT = "default"
ACCEPT_EDITS = "acceptEdits"
DANGEROUSLY_SKIP_PERMISSIONS = "dangerouslySkipPermissions"
# Always allowed: read-only filesystem tools
READ_TOOLS = {"read_file", "glob_files", "grep"}
# Always allowed: internal planning/bookkeeping and user-interaction tools (no external side effects)
PLANNING_TOOLS = {"todo_append", "todo_list", "todo_update", "read_scratchpad", "write_scratchpad", "ask_question"}
# Conditionally allowed in acceptEdits mode when target is within working dir
WRITE_TOOLS = {"write_file", "edit_file"}
def _resolve_tool_path(tool_name: str, args: dict) -> str | None:
"""Return the file-path argument for write tools, or None if not applicable."""
if tool_name in WRITE_TOOLS:
return args.get("path")
return None
def _is_within_working_dir(path: str, working_dir: Path) -> bool:
"""Return True if *path* resolves to somewhere inside *working_dir*."""
try:
target = Path(path)
if not target.is_absolute():
target = working_dir / target
target.resolve().relative_to(working_dir.resolve())
return True
except ValueError:
return False
def _ask_permission(tool_name: str, args: dict) -> bool:
"""Interactively ask the user whether to allow a tool call.
Returns True if the user grants permission, False otherwise.
"""
print(f"\n [permission required] {tool_name}")
print(f" Arguments: {json.dumps(args, ensure_ascii=False)}")
while True:
try:
answer = input(" Allow this action? [y/n]: ").strip().lower()
except EOFError:
print(" (EOF — denying permission)")
return False
if answer in ("y", "yes"):
return True
if answer in ("n", "no"):
return False
print(" Please enter 'y' or 'n'.")
def check_permission(
tool_name: str,
args: dict,
mode: PermissionMode,
working_dir: Path,
) -> bool:
"""Decide whether a tool call is permitted under the current mode.
May interactively prompt the user when a decision cannot be made
automatically. Returns True if the tool call should proceed.
Permission rules
----------------
default
Read tools and planning tools run freely. Every other tool
requires explicit user approval.
acceptEdits
Read tools and planning tools run freely. Write tools
(write_file, edit_file) run freely only when the target path is
inside the working directory; otherwise the user is prompted.
All other tools require explicit user approval.
dangerouslySkipPermissions
All tools run without any prompt.
"""
# Planning and read tools are always free regardless of mode
if tool_name in READ_TOOLS or tool_name in PLANNING_TOOLS:
return True
if mode == PermissionMode.DANGEROUSLY_SKIP_PERMISSIONS:
return True
if mode == PermissionMode.ACCEPT_EDITS and tool_name in WRITE_TOOLS:
path = _resolve_tool_path(tool_name, args)
if path and _is_within_working_dir(path, working_dir):
return True # auto-approved — within the working directory
# Path is outside the working directory → fall through to ask
# Default mode, or acceptEdits for non-write / out-of-tree tools
return _ask_permission(tool_name, args)
# ---------------------------------------------------------------------------
# Agent loop
# ---------------------------------------------------------------------------
def get_llm_client():
return OpenAI(
base_url="http://localhost:11434/v1",
api_key="."
)
def handle_tool_calls(
tool_calls,
messages,
mode: PermissionMode,
working_dir: Path,
):
"""Execute each tool the LLM requested and append the results to messages."""
for tool_call in tool_calls:
name = tool_call.function.name
args = json.loads(tool_call.function.arguments)
print(f" [tool] {name}({args})")
if name not in TOOL_REGISTRY:
result = (
f"Error: unknown tool '{name}'. "
f"Available tools: {list(TOOL_REGISTRY.keys())}"
)
elif not check_permission(name, args, mode, working_dir):
result = (
f"Permission denied: the user did not allow '{name}' to run. "
"Do not retry this tool call without asking the user first."
)
else:
try:
result = TOOL_REGISTRY[name](**args)
except TypeError as e:
result = (
f"Error: invalid arguments for tool '{name}': {e}. "
"Check the tool schema and retry with the correct arguments."
)
print(f" [tool result] {result[:200]}{'...' if len(result) > 200 else ''}")
# The LLM needs the result tied back to the specific tool call id
messages.append({
"role": "tool",
"tool_call_id": tool_call.id,
"content": result,
})
def agent_loop(client, mode: PermissionMode, working_dir: Path):
messages = [
{
"role": "system",
"content": (
"You are a capable coding and research assistant.\n\n"
"## Available tools\n\n"
"Action tools: read_file, write_file, edit_file, glob_files, grep, run_bash, webfetch\n\n"
"Planning tools:\n"
"- Scratchpad (read_scratchpad / write_scratchpad): your private working memory. "
"Use it to think through an approach, store intermediate findings, or draft content "
"before committing. Each write fully replaces the previous content.\n"
"- To-do list (todo_append / todo_list / todo_update): a persistent task tracker. "
"Items carry a status: pending, in_progress, done, cancelled, or failed.\n"
"- Clarification (ask_question): ask the user a single focused question when you "
"are genuinely blocked and cannot reasonably infer the missing information from "
"context. Do not use it for progress updates or to confirm actions you can already "
"take — only ask when it is strictly necessary to proceed.\n\n"
"## Working directory\n\n"
"The current working directory is always the user's project root. "
"When asked to work on a project or codebase without a specified path, "
"start by exploring '.' with glob_files or run_bash. "
"Never ask the user to supply a path.\n\n"
"## How to plan\n\n"
"For complex or multi-step tasks (roughly 3 or more distinct steps, or when the "
"path forward is unclear):\n"
"1. Write your initial thinking and approach to the scratchpad before acting.\n"
"2. Break the work into concrete steps and add each one to the to-do list with "
"todo_append (status: pending).\n"
"3. Before starting a step, mark it in_progress with todo_update. "
"Keep only one item in_progress at a time.\n"
"4. Mark items done immediately after completing them — do not batch completions.\n"
"5. Call todo_list to review remaining work before moving to the next step.\n"
"6. Mark tasks cancelled if they become unnecessary.\n\n"
"For simple, single-step tasks: act directly without creating todos.\n\n"
"Planning tool calls (write_scratchpad, todo_append, todo_update, todo_list) "
"are internal bookkeeping, not responses to the user. After any planning tool "
"call, always continue working immediately — make your next tool call or, once "
"the task is fully complete, give a substantive final answer. "
"Never emit an empty or whitespace-only message.\n\n"
"## Replanning\n\n"
"After every tool result, check whether the outcome matched your expectation. "
"If a tool returns an error, unexpected output, or reveals information that "
"changes your understanding of the task, do not move to the next planned step — "
"replan first.\n\n"
"When a step fails:\n"
"1. Diagnose in the scratchpad — is this a recoverable input error (wrong path, "
"typo, wrong argument) or a deeper problem (wrong approach, wrong assumption)?\n"
"2. Mark the task failed: todo_update(id, status='failed').\n"
"3. Choose a recovery action:\n"
" - Retry: the failure is correctable. Fix the input and set the task back to "
"in_progress. The tool will report which retry attempt this is.\n"
" - Replace: the approach is wrong. Cancel the task and add a revised one.\n"
" - Reorder: new information makes a different task more urgent. Update the "
"pending items before continuing.\n"
"4. If todo_update reports that the retry limit has been reached, stop retrying. "
"Write a clear diagnosis in the scratchpad — what you tried, what failed each "
"time, and what you need — then give the user a concise escalation message "
"and wait for their input.\n\n"
"When a tool succeeds but returns information that changes the picture, pause "
"before acting. Call todo_list, reassess all pending items in the scratchpad, "
"and cancel or replace any tasks that no longer make sense.\n\n"
"## How to use the scratchpad\n\n"
"Before each tool call during a complex task, update the scratchpad with your "
"current thinking. Structure each entry around these five steps:\n\n"
"1. Restate the goal — write what you understand the task to be, in your own words. "
"This catches misreads before they compound into wasted work.\n"
"2. Survey what you know — note which files you have seen, what the code structure "
"looks like, and what constraints or requirements apply.\n"
"3. Evaluate options — reason through at least two approaches and explain why you "
"are choosing one over the other (e.g. 'I could rewrite the middleware, or wrap it. "
"Wrapping is safer because it leaves the existing call sites untouched.').\n"
"4. Anticipate failure modes — write down what could go wrong with the chosen "
"approach and how you would diagnose it (e.g. 'If the tests fail after this, the "
"most likely cause is that the session cookie name changed.').\n"
"5. Decide the next single action — commit to exactly one tool call. "
"Do not plan several calls at once; decide the next step only.\n\n"
"Re-read the scratchpad whenever you resume after a tool result to keep your "
"reasoning grounded in what you have already learned.\n\n"
"## Done detection\n\n"
"Do not give a final answer based on the task list being empty alone. "
"Before declaring the task complete, verify all three of the following:\n\n"
"1. Structural completion — call todo_list and confirm there are no pending, "
"in_progress, or failed items.\n"
"2. Verification — check the output against the original goal. For code tasks: "
"run the tests or build with run_bash and confirm they pass. For research tasks: "
"re-read the scratchpad and confirm the assembled answer addresses what was "
"actually asked.\n"
"3. Uncertainty check — read the scratchpad and ask: are there unresolved "
"questions, assumptions that were never validated, or tasks that were cancelled "
"rather than properly completed?\n\n"
"If all three are satisfied, give your final answer. If any are not, re-enter "
"the planning loop — add the outstanding items to the todo list and continue."
),
}
]
while True:
user_input = input("You: ")
if user_input.lower() == "\\exit":
break
messages.append({"role": "user", "content": user_input})
# Keep looping until the LLM stops calling tools and gives a final reply
while True:
response = client.chat.completions.create(
model="gemma4",
messages=messages,
tools=TOOL_SCHEMAS,
temperature=0.7,
)
message = response.choices[0].message
# Always append the assistant turn so the conversation stays intact
messages.append(message)
if message.tool_calls:
# The LLM wants to use one or more tools — run them, then loop
handle_tool_calls(message.tool_calls, messages, mode, working_dir)
elif not message.content or not message.content.strip():
# The model ended its turn with an empty message — most commonly
# happens after a planning-only tool call (scratchpad / todo).
# Nudge it to continue rather than silently stalling.
messages.append({
"role": "user",
"content": "Continue.",
})
else:
# No tool calls: we have the final answer
print(f"Assistant: {message.content}")
break
if __name__ == "__main__":
parser = argparse.ArgumentParser(
description="Coding agent with configurable tool permission gating."
)
parser.add_argument(
"--mode",
choices=["default", "acceptEdits", "dangerouslySkipPermissions"],
default="default",
help=(
"Permission mode for tool execution. "
"'default': read tools are free, everything else requires approval. "
"'acceptEdits': read + write tools are free when inside the working directory, "
"everything else requires approval. "
"'dangerouslySkipPermissions': all tools run without any prompt."
),
)
cli_args = parser.parse_args()
mode = PermissionMode(cli_args.mode)
working_dir = Path.cwd()
print(f"Agent started in '{mode.value}' mode (working dir: {working_dir})")
client = get_llm_client()
agent_loop(client, mode, working_dir)