Files
abap-llm/harness/agents.py

251 lines
12 KiB
Python

"""Agents: oracle (reference solution), null (does nothing), llm (OpenAI-compatible tool loop)."""
import json
import os
import time
import urllib.request
import threading
import urllib.error
from .ledger import add_usage, check_budget
from .proxy import BudgetExceeded
class ServerDown(Exception):
"""The model server does not answer (remote local model). The run ends cleanly and is not a result."""
class WindowEnd(Exception):
"""The time window of the series is over (hard stop, also in the middle of a request)."""
SYSTEM_PROMPT = """You are an ABAP developer. You implement a plan on an SAP system with the tools.
Rules:
- Read the plan. Implement the contract exactly. Do not change a public signature in the contract.
- You make the craft decisions: table types, keys, access paths, SQL strategy, exception design,
and syntax that fits the release target.
- If a business rule is missing, or two rules contradict, stop. Do not create objects.
Write the gap in your report.
- Do not change an object in the out-of-scope list.
- Create a new object in package $TMP with sap_create_object. Then write the source with
sap_push_source.
- Read an object that you do not know before you use it.
- After each write, check the result. If the same check fails two times, stop and report.
- Do not add behavior that the plan does not ask for.
At the end, write a short report:
1. Decisions: one line for each craft decision, with the reason.
2. Objects: object, type, action, reason.
3. Verification: what you checked and the result.
4. Deviations and open points.
"""
class NullAgent:
name = "null"
def run(self, task, proxy):
proxy.note("final", "No action.")
return "No action."
class OracleAgent:
"""Writes the reference solution. Validates harness and scoring (expected score ~ max)."""
name = "oracle"
def run(self, task, proxy):
if task.meta.get("expected_outcome") == "stop": # the right answer is to stop and name the gap
report = "Stopped. Gap: " + task.meta.get("expected_gap", {}).get("description", "")
proxy.note("final", report)
return report
for o in task.objects("reference"):
ident = {"objectType": o["type"], "objectName": o["name"]}
if o.get("functionGroup"):
ident["functionGroup"] = o["functionGroup"]
proxy.call("sap_create_object", dict(ident, packageName="$TMP",
description=o.get("description", o["name"])[:60]))
if o.get("messages"): # message class: messages are written with sap_push_message
proxy.call("sap_push_message", {"objectName": o["name"], "messages": o["messages"]})
if o.get("source"):
proxy.call("sap_push_source", dict(ident, source=o["source"]))
if o.get("testclasses_source"):
proxy.call("sap_push_source", dict(ident, includeType="testclasses",
source=o["testclasses_source"]))
proxy.note("final", "Reference solution written.")
return "Reference solution written."
class LlmAgent:
"""OpenAI-compatible chat completions with tool calls (Ollama, MLX server, vLLM, ...).
Local models are slow: no time limit by default (tool-call budget limits the run).
One request at a time; tool calls run in sequence.
"""
def __init__(self, model, base_url=None, api_key=None, max_turns=80, temperature=0.2,
max_seconds=None, max_tokens=None, chat_template_kwargs=None, loop_guard=None,
deadline=None, watch=False):
self.model = model
self.name = f"llm:{model}"
self.base_url = (base_url or os.environ.get("LLM_BASE_URL", "http://127.0.0.1:11434/v1")).rstrip("/")
self.api_key = api_key or os.environ.get("LLM_API_KEY", "none")
self.max_turns = max_turns
self.temperature = temperature
self.max_seconds = max_seconds
self.request_timeout = 3600 # local models are slow; a hung request still ends
# Runaway reasoning: 35 of 1965 DeepSeek turns produced 393k output tokens and no content (46 % of the
# run cost, 2026-10-03). Normal turns: p95 17.5k, max 82k. A cut turn is retried (see run).
self.max_tokens = max_tokens or (32000 if ":cloud" in (model or "") else None)
self.empty_retries = 2
self.loop_guard = loop_guard # end the run after this many identical pushes in a row (None = off)
self.deadline = deadline # absolute time (time.time()) of the hard stop, or None
self.watch = watch # remote model: ping the server during a request, end the run when it is gone
self.end_reason = None
self.messages, self.tools, self.reasoning, self.turn_usage = [], [], [], [] # for the trajectory record
self.chat_template_kwargs = chat_template_kwargs # local server only, e.g. {"enable_thinking": False}
def _chat(self, messages, tools):
body = {"model": self.model, "messages": messages, "tools": tools,
"temperature": self.temperature, "parallel_tool_calls": False}
if self.max_tokens:
body["max_tokens"] = self.max_tokens
if self.chat_template_kwargs:
body["chat_template_kwargs"] = self.chat_template_kwargs
req = urllib.request.Request(f"{self.base_url}/chat/completions", json.dumps(body).encode(),
{"Content-Type": "application/json",
"Authorization": f"Bearer {self.api_key}"})
last = None
for attempt in range(4): # model server errors (HTTP 5xx, timeouts): retry with backoff
try:
if self.watch or self.deadline:
data = self._post_watched(req)
else:
with urllib.request.urlopen(req, timeout=self.request_timeout) as r:
data = json.loads(r.read().decode())
return data["choices"][0]["message"], data.get("usage", {})
except (ServerDown, WindowEnd):
raise
except Exception as e: # noqa: BLE001
last = e
code = getattr(e, "code", None)
if code is not None and code < 500 and code != 429:
raise
if self.deadline and time.time() >= self.deadline:
raise WindowEnd()
if self.watch and not self._ping():
raise ServerDown(str(e)[:200])
time.sleep(10 * (attempt + 1))
raise RuntimeError(f"model request failed after retries: {last}")
def _ping(self, timeout=10):
try:
urllib.request.urlopen(urllib.request.Request(f"{self.base_url}/models"), timeout=timeout).read()
return True
except Exception: # noqa: BLE001
return False
def _post_watched(self, req):
"""The request runs in a thread; this thread watches the deadline and (remote model) the server: a hard stop
or a dead server ends the wait at once, also in the middle of a long generation."""
box = {}
def work():
try:
with urllib.request.urlopen(req, timeout=self.request_timeout) as r:
box["data"] = json.loads(r.read().decode())
except BaseException as e: # noqa: BLE001
box["err"] = e
th = threading.Thread(target=work, daemon=True)
th.start()
last_ping, fails = time.time(), 0
while th.is_alive():
th.join(5)
if self.deadline and time.time() >= self.deadline:
raise WindowEnd()
if self.watch and th.is_alive() and time.time() - last_ping >= 30:
last_ping = time.time()
fails = 0 if self._ping() else fails + 1
if fails >= 3:
raise ServerDown("no answer to 3 pings in a row during a request")
if "err" in box:
raise box["err"]
return box["data"]
def run(self, task, proxy):
tools = [{"type": "function", "function": {"name": t["name"],
"description": t.get("description", ""),
"parameters": t.get("inputSchema", {})}}
for t in proxy.schemas()]
messages = [{"role": "system", "content": SYSTEM_PROMPT},
{"role": "user", "content": task.spec}]
self.messages, self.tools, self.reasoning, self.turn_usage = messages, tools, [], []
if ":cloud" in self.model:
check_budget()
final = ""
empty = 0
self.end_reason = "max_turns"
start = time.time()
for _ in range(self.max_turns):
if self.deadline and time.time() >= self.deadline:
final = "Stopped: time window over."
self.end_reason = "window_end"
break
if self.max_seconds and time.time() - start > self.max_seconds:
final = f"Stopped: time budget exceeded ({self.max_seconds} s)."
self.end_reason = "time_budget"
break
try:
msg, usage = self._chat(messages, tools)
add_usage(self.model, usage, kind="run", ref=proxy.prefix)
self.turn_usage.append(usage)
except WindowEnd:
final = "Stopped: time window over."
self.end_reason = "window_end"
break
except ServerDown as e:
final = f"Stopped: model server not reachable ({e})."
self.end_reason = "server_down"
break
except RuntimeError as e:
final = f"Stopped: {e}"
self.end_reason = "model_error"
break
proxy.note("assistant", {"content": msg.get("content"),
"tool_calls": msg.get("tool_calls"), "usage": usage})
messages.append({k: v for k, v in msg.items() if k in ("role", "content", "tool_calls")})
think = msg.get("reasoning") or msg.get("reasoning_content") or msg.get("thinking")
if think: # kept apart from the messages: not training data
self.reasoning.append({"message_index": len(messages) - 1, "reasoning": think})
calls = msg.get("tool_calls") or []
if not calls and not (msg.get("content") or "").strip() and empty < self.empty_retries:
empty += 1 # empty turn (output limit reached in reasoning): ask the same question again
messages.pop()
continue
if not calls:
final = msg.get("content") or ("Stopped: empty model response." if empty else "")
self.end_reason = "report" if (msg.get("content") or "").strip() else "empty_response"
break
try:
for c in calls:
fn = c["function"]
args = fn.get("arguments") or "{}"
args = json.loads(args) if isinstance(args, str) else args
err, text = proxy.call(fn["name"], args)
messages.append({"role": "tool", "tool_call_id": c.get("id", ""),
"content": ("ERROR: " if err else "") + text[:12000]})
streak = max(proxy.same_push_streak, proxy.same_call_streak)
if self.loop_guard and streak >= self.loop_guard:
final = (f"Stopped: loop (the same source was pushed {proxy.same_push_streak} times in a row)."
if proxy.same_push_streak >= self.loop_guard else
f"Stopped: loop (the same call with the same result {proxy.same_call_streak} times in a row).")
self.end_reason = "loop"
break
if self.end_reason == "loop":
break
except BudgetExceeded as e:
final = f"Stopped: budget exceeded ({e})."
self.end_reason = "tool_budget"
break
proxy.note("final", final)
return final