from __future__ import annotations from typing import Any, Dict, List, Optional, Callable, Awaitable from urllib.parse import urljoin import json import re import asyncio import time import hashlib from collections import deque from agentui.providers.http_client import build_client from agentui.common.vendors import detect_vendor from agentui.providers.adapters.registry import get_adapter, default_base_url_for as _adapter_default_base_url_for from agentui.pipeline.templating import ( _OUT_MACRO_RE, _VAR_MACRO_RE, _PROMPT_MACRO_RE, _OUT_SHORT_RE, _BRACES_RE, _split_path, _get_by_path, _stringify_for_template, _deep_find_text, _best_text_from_outputs, render_template_simple, eval_condition_expr, ) from agentui.pipeline.storage import load_var_store, save_var_store, clear_var_store from agentui.common.cancel import is_cancelled, clear_cancel, get_cancel_mode # HTTP request registry for manual resend feature (store original untrimmed bodies) from collections import OrderedDict _HTTP_REQ_REGISTRY_MAX = 200 _HTTP_REQ_REGISTRY = OrderedDict() def register_http_request(req_id: str, info: Dict[str, Any]) -> None: try: rid = str(req_id or "") if not rid: return # overwrite if exists to refresh order if rid in _HTTP_REQ_REGISTRY: try: _HTTP_REQ_REGISTRY.pop(rid, None) except Exception: pass _HTTP_REQ_REGISTRY[rid] = info or {} # trim oldest beyond cap while len(_HTTP_REQ_REGISTRY) > _HTTP_REQ_REGISTRY_MAX: try: _HTTP_REQ_REGISTRY.popitem(last=False) except Exception: break except Exception: pass def get_http_request(req_id: str) -> Optional[Dict[str, Any]]: try: rid = str(req_id or "") if not rid: return None v = _HTTP_REQ_REGISTRY.get(rid) # return shallow copy to avoid mutation return dict(v) if isinstance(v, dict) else None except Exception: return None # --- Global helpers: robust auto-decompression for logging/JSON parsing ---------- import gzip import zlib def _decode_content_bytes(data: bytes, enc_header: str) -> Optional[bytes]: """ Try to decompress raw bytes according to Content-Encoding. Returns decompressed bytes or None if unable/not needed. """ if not data: return b"" enc = (enc_header or "").lower() try: if "br" in enc: # Try brotli libs brotli = None try: import brotlicffi as brotli # type: ignore except Exception: try: import brotli # type: ignore except Exception: brotli = None if brotli is not None: try: return brotli.decompress(data) # type: ignore[attr-defined] except Exception: try: # Some packages expose .decompress as brotli.decompress return brotli.decompress(data) # type: ignore except Exception: return None return None if "gzip" in enc: try: return gzip.decompress(data) except Exception: return None if "deflate" in enc: try: return zlib.decompress(data) except Exception: # Some servers send raw deflate without zlib header try: return zlib.decompress(data, -zlib.MAX_WBITS) except Exception: return None except Exception: return None return None def _safe_response_text(resp) -> str: """ Return response text with best-effort auto-decompression (br/gzip/deflate) for logging. Falls back to resp.text on failure. """ try: enc = (resp.headers.get("content-encoding") or "").lower() if enc: dec = _decode_content_bytes(resp.content, enc) if dec is not None: try: charset = resp.encoding or "utf-8" return dec.decode(charset, errors="replace") except Exception: return dec.decode("utf-8", errors="replace") # If no encoding or not handled — rely on httpx auto-decoding for gzip/deflate return resp.text except Exception: try: return resp.text except Exception: return "" def _safe_response_json(resp) -> Any: """ Return parsed JSON with auto-decompression fallback. """ try: return resp.json() except Exception: t = _safe_response_text(resp) try: return json.loads(t) except Exception: return {"error": "Failed to decode JSON from upstream", "text": t} # --- Cooperative cancel/abort helper for in-flight awaits (HTTP, etc.) --------- async def _await_coro_with_cancel(coro: Awaitable[Any], pipeline_id: str, poll_interval: float = 0.1) -> Any: """ Await 'coro' while polling manual cancel flag for the pipeline. Behavior: - If cancel mode is 'graceful' -> do NOT interrupt 'coro'; we just continue waiting and upper layers will stop before scheduling new work. - If cancel mode is 'abort' -> cancel in-flight task immediately and raise ExecutionError. Returns the result of 'coro' or raises ExecutionError on abort. """ task = asyncio.create_task(coro) while True: try: # Shield from timeout cancellation; we only use timeout to poll flags. return await asyncio.wait_for(asyncio.shield(task), timeout=poll_interval) except asyncio.TimeoutError: # Not done yet — fall through to polling pass except asyncio.CancelledError: # Map in-flight cancellation to ExecutionError on abort; otherwise re-raise try: mode = get_cancel_mode(pipeline_id) except Exception: mode = "abort" if mode == "abort": raise ExecutionError("Cancelled by user (abort)") raise # Poll cancel flag try: if is_cancelled(pipeline_id): mode = get_cancel_mode(pipeline_id) if mode == "abort": try: if not task.done(): task.cancel() await task except asyncio.CancelledError: raise ExecutionError("Cancelled by user (abort)") except Exception as exc: # noqa: BLE001 raise ExecutionError(f"Cancelled by user (abort): {exc}") # graceful: do not interrupt; keep waiting except Exception: # Be defensive: ignore polling failures and keep waiting pass # --- Helpers: sanitize base64/data URLs in JSON for logging (Burp-like) ---------- def _is_b64ish_string(s: str) -> bool: try: if not isinstance(s, str) or len(s) < 128: return False return bool(re.fullmatch(r"[A-Za-z0-9+/=\r\n]+", s)) except Exception: return False _DATA_URL_RE = re.compile(r"(?is)^data:([^;]+);base64,([A-Za-z0-9+/=\r\n]+)$") def _sanitize_b64_for_log(obj: Any, max_len: int = 180) -> Any: """ Recursively walk JSON-like obj and trim long base64 strings and data URLs for logging only. - If key name contains 'data' (case-insensitive) and value looks like base64 → trim - If value is data URL (data:mime;base64,...) → trim base64 part Structure is preserved. Only strings are shortened. """ def trim_str(val: str, key_hint: Optional[str] = None) -> str: # data URL? m = _DATA_URL_RE.match(val or "") if m: mime, b64 = m.group(1), m.group(2) if len(b64) > max_len: return f"data:{mime};base64,{b64[:max_len]}... (trimmed {len(b64)-max_len})" return val # plain base64 by key hint if key_hint and "data" in key_hint.lower() and _is_b64ish_string(val) and len(val) > max_len: return val[:max_len] + f"... (trimmed {len(val)-max_len})" return val if isinstance(obj, dict): out: Dict[str, Any] = {} for k, v in obj.items(): if isinstance(v, str): out[k] = trim_str(v, str(k)) else: out[k] = _sanitize_b64_for_log(v, max_len) return out if isinstance(obj, list): return [_sanitize_b64_for_log(v, max_len) for v in obj] return obj def _sanitize_json_string_for_log(s: str, max_len: int = 180) -> str: """ If 's' is a JSON string, sanitize base64/data URLs inside and dump back. Otherwise return original string. """ try: j = json.loads(s) j2 = _sanitize_b64_for_log(j, max_len=max_len) return json.dumps(j2, ensure_ascii=False, indent=2) except Exception: return s # --- Templating helpers are imported from agentui.pipeline.templating --- # moved to agentui.pipeline.templating # moved to agentui.pipeline.templating # moved to agentui.pipeline.templating # moved to agentui.pipeline.templating def _extract_out_node_id_from_ref(s: Any) -> Optional[str]: """ Извлекает node_id из строки с макросом [[OUT:nodeId(.path)*]]. Возвращает None, если макрос не найден. """ if not isinstance(s, str): return None m = _OUT_MACRO_RE.search(s) if not m: return None body = m.group(1).strip() node_id = body.split(".", 1)[0].strip() return node_id or None def _resolve_in_value(source: Any, context: Dict[str, Any], values: Dict[str, Dict[str, Any]]) -> Any: """ Разрешает входные связи/макросы в значение для inputs: - Нестроковые значения возвращаются как есть - "macro:path" → берёт значение из context по точечному пути - "[[VAR:path]]" → берёт значение из context - "[[OUT:nodeId(.path)*]]" → берёт из уже вычисленных выходов ноды - "nodeId(.path)*" → ссылка на выходы ноды - Если передан список ссылок — вернёт список разрешённых значений - Иначе пытается взять из context по пути; если не найдено, оставляет исходную строку """ # Поддержка массивов ссылок (для multi-depends или будущих списковых входов) if isinstance(source, list): return [_resolve_in_value(s, context, values) for s in source] if not isinstance(source, str): return source s = source.strip() # macro:path if s.lower().startswith("macro:"): path = s.split(":", 1)[1].strip() return _get_by_path(context, path) # [[VAR: path]] m = _VAR_MACRO_RE.fullmatch(s) if m: path = m.group(1).strip() return _get_by_path(context, path) # [[OUT: nodeId(.path)*]] m = _OUT_MACRO_RE.fullmatch(s) if m: body = m.group(1).strip() if "." in body: node_id, rest = body.split(".", 1) node_val = values.get(node_id) return _get_by_path(node_val, rest) node_val = values.get(body) return node_val # "nodeId(.path)*" if "." in s: node_id, rest = s.split(".", 1) if node_id in values: return _get_by_path(values.get(node_id), rest) if s in values: return values.get(s) # fallback: from context by dotted path or raw string ctx_val = _get_by_path(context, s) return ctx_val if ctx_val is not None else source # moved to agentui.pipeline.templating class ExecutionError(Exception): pass class Node: type_name: str = "Base" def __init__(self, node_id: str, config: Optional[Dict[str, Any]] = None) -> None: self.node_id = node_id self.config = config or {} async def run(self, inputs: Dict[str, Any], context: Dict[str, Any]) -> Dict[str, Any]: # noqa: D401 """Execute node with inputs and context. Return dict of outputs.""" raise NotImplementedError # Регистрация поддерживаемых типов нод (минимальный набор) NODE_REGISTRY: Dict[str, Any] = {} class PipelineExecutor: def __init__(self, pipeline: Dict[str, Any]) -> None: self.pipeline = pipeline self.nodes_by_id: Dict[str, Node] = {} for n in pipeline.get("nodes", []): node_cls = NODE_REGISTRY.get(n.get("type")) if not node_cls: raise ExecutionError(f"Unknown node type: {n.get('type')}") self.nodes_by_id[n["id"]] = node_cls(n["id"], n.get("config", {})) # Настройки режима исполнения (с дефолтами из default_pipeline) try: self.loop_mode = str(self.pipeline.get("loop_mode", "dag")).lower().strip() or "dag" except Exception: self.loop_mode = "dag" try: self.loop_max_iters = int(self.pipeline.get("loop_max_iters", 1000)) except Exception: self.loop_max_iters = 1000 try: self.loop_time_budget_ms = int(self.pipeline.get("loop_time_budget_ms", 10000)) except Exception: self.loop_time_budget_ms = 10000 # Идентификатор пайплайна и политика очистки стора переменных try: self.pipeline_id = str(self.pipeline.get("id", "pipeline_editor")) or "pipeline_editor" except Exception: self.pipeline_id = "pipeline_editor" try: self.clear_var_store = bool(self.pipeline.get("clear_var_store", True)) except Exception: self.clear_var_store = True # В памяти держим актуальный STORE (доступен в шаблонах через {{ store.* }} и [[STORE:*]]) self._store: Dict[str, Any] = {} # Локальный журнал выполнения для человекочитаемого трейсинга self._exec_log: List[str] = [] async def run( self, context: Dict[str, Any], trace: Optional[Callable[[Dict[str, Any]], Awaitable[None]]] = None, ) -> Dict[str, Any]: """ Точка входа исполнителя. Переключает режим между: - "dag": волновое исполнение с барьерами (исходное поведение) - "iterative": итеративное исполнение с очередью и гейтами """ # Инициализация STORE по политике try: if self.clear_var_store: clear_var_store(self.pipeline_id) self._store = {} else: self._store = load_var_store(self.pipeline_id) or {} except Exception: self._store = {} # Перед стартом прогона сбрасываем возможный «старый» флаг отмены try: clear_cancel(self.pipeline_id) except Exception: pass mode = (self.loop_mode or "dag").lower() if mode == "iterative": res = await self._run_iterative(context, trace) else: res = await self._run_dag(context, trace) # На всякий случай финальная запись стора (если были изменения) try: save_var_store(self.pipeline_id, self._store) except Exception: pass return res async def _exec_node( self, node_id: str, ndef: Dict[str, Any], values_snapshot: Dict[str, Any], wave_num: int, context: Dict[str, Any], trace: Optional[Callable[[Dict[str, Any]], Awaitable[None]]] = None, user_vars_snapshot: Optional[Dict[str, Any]] = None, ) -> tuple[str, Dict[str, Any]]: """ Общий исполнитель ноды (используется и в DAG, и в iterative режимах) Поведение идентично прежним локальным exec_one(): - подготовка контекста (OUT, vars, store, meta, _trace) - разрешение inputs через макросы - события trace node_start/node_done/node_error - TRACE-печати начала/окончания с prev_text """ if not ndef: raise ExecutionError(f"Node definition not found: {node_id}") node = self.nodes_by_id[node_id] # Сбор контекста ctx = dict(context) ctx["OUT"] = values_snapshot try: ctx["vars"] = dict(user_vars_snapshot or {}) except Exception: ctx["vars"] = {} # STORE доступен в шаблонах try: ctx["store"] = dict(self._store) except Exception: ctx["store"] = {} # Pipeline meta (доступно нодам через context.meta) try: ctx["meta"] = { "id": self.pipeline_id, "loop_mode": self.loop_mode, "loop_max_iters": self.loop_max_iters, "loop_time_budget_ms": self.loop_time_budget_ms, "clear_var_store": self.clear_var_store, "http_timeout_sec": float(self.pipeline.get("http_timeout_sec", 60) or 60), # v1: стратегия извлечения текста для [[OUTx]] "text_extract_strategy": str(self.pipeline.get("text_extract_strategy", "auto") or "auto"), "text_extract_json_path": str(self.pipeline.get("text_extract_json_path", "") or ""), "text_join_sep": str(self.pipeline.get("text_join_sep", "\n") or "\n"), # v2: коллекция пресетов парсинга для выбора в нодах "text_extract_presets": list(self.pipeline.get("text_extract_presets", []) or []), } except Exception: pass # Прокидываем trace‑функцию в контекст, чтобы ноды могли посылать события (SSE лог) try: if trace is not None: ctx["_trace"] = trace except Exception: pass # Разворачиваем inputs inputs: Dict[str, Any] = {} for name, source in (ndef.get("in") or {}).items(): if isinstance(source, list): inputs[name] = [_resolve_in_value(s, ctx, values_snapshot) for s in source] else: inputs[name] = _resolve_in_value(source, ctx, values_snapshot) # Trace: node_start if trace is not None: try: await trace({ "event": "node_start", "node_id": ndef["id"], "node_type": node.type_name, "wave": wave_num, "ts": int(time.time() * 1000), }) except Exception: pass started = time.perf_counter() try: print(f"TRACE start: {ndef['id']} ({node.type_name})") except Exception: pass # Исполнение try: out = await node.run(inputs, ctx) except BaseException as exc: err = exc try: import asyncio as _asyncio if isinstance(exc, _asyncio.CancelledError): err = ExecutionError("Cancelled by user (abort)") except Exception: pass if trace is not None: try: await trace({ "event": "node_error", "node_id": ndef["id"], "node_type": node.type_name, "wave": wave_num, "ts": int(time.time() * 1000), "error": str(err), }) except Exception: pass raise err else: dur_ms = int((time.perf_counter() - started) * 1000) if trace is not None: try: await trace({ "event": "node_done", "node_id": ndef["id"], "node_type": node.type_name, "wave": wave_num, "ts": int(time.time() * 1000), "duration_ms": dur_ms, }) except Exception: pass try: prev_text = "" try: from agentui.pipeline.templating import _best_text_from_outputs as _bt # type: ignore if isinstance(out, dict): prev_text = _bt(out) or "" except Exception: prev_text = "" if isinstance(prev_text, str) and len(prev_text) > 200: prev_text = prev_text[:200] print(f"TRACE done: {ndef['id']} ({node.type_name}) dur={dur_ms}ms text={prev_text!r}") except Exception: pass return node_id, out async def _run_dag( self, context: Dict[str, Any], trace: Optional[Callable[[Dict[str, Any]], Awaitable[None]]] = None, ) -> Dict[str, Any]: """ Исходная волновая модель (DAG) — без изменений поведения. """ nodes: List[Dict[str, Any]] = list(self.pipeline.get("nodes", [])) id_set = set(self.nodes_by_id.keys()) # Собираем зависимости: node_id -> set(parent_ids), и обратные связи dependents deps_map: Dict[str, set] = {n["id"]: set() for n in nodes} dependents: Dict[str, set] = {n["id"]: set() for n in nodes} # Гейты для ветвлений: child_id -> List[(parent_id, gate_name)] (gate_name: "true"/"false") gate_deps: Dict[str, List[tuple[str, str]]] = {n["id"]: [] for n in nodes} for n in nodes: nid = n["id"] for _, source in (n.get("in") or {}).items(): # Разворачиваем массивы ссылок (multi-depends) sources = source if isinstance(source, list) else [source] for src in sources: if not isinstance(src, str): # Нестрочные значения и массивы констант — зависимостей нет continue if src.startswith("macro:"): # Макросы берутся из контекста, без зависимостей continue # [[VAR:...]] — макрос из контекста, зависимостей нет if re.fullmatch(r"\[\[\s*VAR\s*[:\s]\s*[^\]]+\s*\]\]", src.strip()): continue # [[OUT:nodeId(.key)*]] — зависимость от указанной ноды out_ref_node = _extract_out_node_id_from_ref(src) if out_ref_node and out_ref_node in id_set: deps_map[nid].add(out_ref_node) dependents[out_ref_node].add(nid) continue # Ссылки вида "node.outKey" или "node" src_id = src.split(".", 1)[0] if "." in src else src if src_id in id_set: # Если указали конкретный outKey (например, nIf.true / nIf.false), # трактуем это ТОЛЬКО как гейт (НЕ как топологическую зависимость), чтобы избежать дедлоков. is_gate = False if "." in src: try: _, out_name = src.split(".", 1) on = str(out_name).strip().lower() if on in {"true", "false"}: gate_deps[nid].append((src_id, on)) # Smart mode v2: If-node may act as a real parent ONLY when the child has no real parents yet # AND adding this parent won't create an immediate cycle (i.e. If-node does not depend on this child). if len(deps_map[nid]) == 0: dep_on_child = False try: src_def = next((x for x in nodes if str(x.get("id")) == str(src_id)), None) if src_def and isinstance(src_def.get("in"), dict): for _, s2 in (src_def.get("in") or {}).items(): arr = s2 if isinstance(s2, list) else [s2] for it2 in arr: if isinstance(it2, str): base = it2.split(".", 1)[0] if "." in it2 else it2 if str(base) == str(nid): dep_on_child = True break if dep_on_child: break except Exception: dep_on_child = False if not dep_on_child: deps_map[nid].add(src_id) dependents[src_id].add(nid) is_gate = True except Exception: is_gate = False if not is_gate: deps_map[nid].add(src_id) dependents[src_id].add(nid) # Входящие степени и первая волна in_degree: Dict[str, int] = {nid: len(deps) for nid, deps in deps_map.items()} ready: List[str] = [nid for nid, deg in in_degree.items() if deg == 0] processed: List[str] = [] values: Dict[str, Dict[str, Any]] = {} last_result: Dict[str, Any] = {} last_node_id: Optional[str] = None node_def_by_id: Dict[str, Dict[str, Any]] = {n["id"]: n for n in nodes} user_vars: Dict[str, Any] = {} try: parallel_limit = int(self.pipeline.get("parallel_limit", 8)) except Exception: parallel_limit = 8 if parallel_limit <= 0: parallel_limit = 1 async def exec_one(node_id: str, values_snapshot: Dict[str, Any], wave_num: int) -> tuple[str, Dict[str, Any]]: ndef = node_def_by_id.get(node_id) return await self._exec_node(node_id, ndef, values_snapshot, wave_num, context, trace, user_vars) wave_idx = 0 while ready: # Ручная отмена исполнения (DAG) try: if is_cancelled(self.pipeline_id): if trace is not None: try: await trace({ "event": "cancelled", "node_id": "", "node_type": "Pipeline", "wave": wave_idx, "ts": int(time.time() * 1000), }) except Exception: pass # Снимок и финальный EXEC TRACE try: self._commit_snapshot(context, values, last_node_id or "") except Exception: pass try: summary = " -> ".join(self._exec_log) if getattr(self, "_exec_log", None) else "" if summary and isinstance(self._store.get("snapshot"), dict): self._store["snapshot"]["EXEC_TRACE"] = summary save_var_store(self.pipeline_id, self._store) except Exception: pass return last_result except Exception: pass wave_nodes = list(ready) ready = [] wave_results: Dict[str, Dict[str, Any]] = {} values_snapshot = dict(values) for i in range(0, len(wave_nodes), parallel_limit): chunk = wave_nodes[i : i + parallel_limit] results = await asyncio.gather( *(exec_one(nid, values_snapshot, wave_idx) for nid in chunk), return_exceptions=False, ) for nid, out in results: wave_results[nid] = out last_result = out last_node_id = nid try: ndef = node_def_by_id.get(nid) or {} ntype = ndef.get("type", "") if ntype == "If": expr = str((ndef.get("config") or {}).get("expr", "")) resb = False try: if isinstance(out, dict): resb = bool(out.get("result")) except Exception: resb = False self._exec_log.append(f"If (#{nid}) {expr} => {str(resb).lower()}") else: self._exec_log.append(f"{nid}({ntype})") except Exception: pass values.update(wave_results) processed.extend(wave_nodes) try: for _nid, out in wave_results.items(): if isinstance(out, dict): v = out.get("vars") if isinstance(v, dict): user_vars.update(v) except Exception: pass # Обновляем и сохраняем STORE, если были новые переменные из SetVars/прочих нод try: merged: Dict[str, Any] = {} for _nid, out in wave_results.items(): if isinstance(out, dict) and isinstance(out.get("vars"), dict): merged.update(out.get("vars") or {}) if merged: self._store.update(merged) try: save_var_store(self.pipeline_id, self._store) except Exception: pass except Exception: pass for done in wave_nodes: for child in dependents.get(done, ()): in_degree[child] -= 1 next_ready_candidates = [nid for nid, deg in in_degree.items() if deg == 0 and nid not in processed and nid not in wave_nodes] def _gates_ok(child_id: str) -> bool: pairs = gate_deps.get(child_id) or [] if not pairs: return True missing_seen = False for pid, gate in pairs: v = values.get(pid) if v is None: # значение гейта ещё не известно missing_seen = True continue try: flag = bool(isinstance(v, dict) and v.get(gate)) except Exception: flag = False if not flag: return False # Семантика "missing gate = pass" как в iterative-режиме: # если флаги гейта ещё не известны, но у ребёнка есть реальные родители — допускаем первый запуск. # если реальных родителей нет (только гейты) — ждём появления значения гейта. if missing_seen: real_parents = deps_map.get(child_id) or set() if len(real_parents) == 0: return False return True ready = [nid for nid in next_ready_candidates if _gates_ok(nid)] wave_idx += 1 if len(processed) != len(nodes): remaining = [n["id"] for n in nodes if n["id"] not in processed] raise ExecutionError(f"Cycle detected or unresolved dependencies among nodes: {remaining}") # Persist snapshot of macro context and outputs into STORE try: self._commit_snapshot(context, values, last_node_id or "") except Exception: pass # Построение и сохранение человекочитаемого EXECUTION TRACE try: summary = " -> ".join(self._exec_log) if getattr(self, "_exec_log", None) else "" if summary: try: print("===== EXECUTION TRACE =====") print(summary) print("===== END TRACE =====") except Exception: pass try: if isinstance(self._store.get("snapshot"), dict): self._store["snapshot"]["EXEC_TRACE"] = summary save_var_store(self.pipeline_id, self._store) except Exception: pass except Exception: pass return last_result async def _run_iterative( self, context: Dict[str, Any], trace: Optional[Callable[[Dict[str, Any]], Awaitable[None]]] = None, ) -> Dict[str, Any]: """ Итеративное исполнение: - Очередь готовых задач - Повторные пуски допустимы: ребёнок ставится в очередь, когда какой-либо из его родителей обновился после последнего запуска ребёнка - Гейты If.true/If.false фильтруют постановку в очередь - Ограничения: loop_max_iters, loop_time_budget_ms """ nodes: List[Dict[str, Any]] = list(self.pipeline.get("nodes", [])) id_set = set(self.nodes_by_id.keys()) # Строим зависимости и гейты (как в DAG) deps_map: Dict[str, set] = {n["id"]: set() for n in nodes} dependents: Dict[str, set] = {n["id"]: set() for n in nodes} gate_deps: Dict[str, List[tuple[str, str]]] = {n["id"]: [] for n in nodes} # Обратная карта для гейтов: кто «слушает» изменения конкретного родителя по гейту gate_dependents: Dict[str, set] = {n["id"]: set() for n in nodes} for n in nodes: nid = n["id"] for _, source in (n.get("in") or {}).items(): sources = source if isinstance(source, list) else [source] for src in sources: if not isinstance(src, str): continue if src.startswith("macro:"): continue if re.fullmatch(r"\[\[\s*VAR\s*[:\s]\s*[^\]]+\s*\]\]", src.strip()): continue out_ref_node = _extract_out_node_id_from_ref(src) if out_ref_node and out_ref_node in id_set: # [[OUT:nodeId(.key)*]] — это РЕАЛЬНАЯ топологическая зависимость deps_map[nid].add(out_ref_node) dependents[out_ref_node].add(nid) continue src_id = src.split(".", 1)[0] if "." in src else src if src_id in id_set: # "node.true/false" — ТОЛЬКО гейт (без топологической зависимости) is_gate = False if "." in src: try: _, out_name = src.split(".", 1) on = str(out_name).strip().lower() if on in {"true", "false"}: gate_deps[nid].append((src_id, on)) # Регистрируем обратную зависимость по гейту, # чтобы будить ребёнка при изменении флага у родителя gate_dependents[src_id].add(nid) # Smart mode v2: делаем If-узел реальным родителем ТОЛЬКО если # у ребёнка ещё нет реальных родителей И это не создаёт цикл (If не зависит от ребёнка). if len(deps_map[nid]) == 0: dep_on_child = False try: src_def = next((x for x in nodes if str(x.get("id")) == str(src_id)), None) if src_def and isinstance(src_def.get("in"), dict): for _, s2 in (src_def.get("in") or {}).items(): arr = s2 if isinstance(s2, list) else [s2] for it2 in arr: if isinstance(it2, str): base = it2.split(".", 1)[0] if "." in it2 else it2 if str(base) == str(nid): dep_on_child = True break if dep_on_child: break except Exception: dep_on_child = False if not dep_on_child: deps_map[nid].add(src_id) dependents[src_id].add(nid) is_gate = True except Exception: is_gate = False if not is_gate: deps_map[nid].add(src_id) dependents[src_id].add(nid) # Вспом. структуры состояния values: Dict[str, Dict[str, Any]] = {} last_result: Dict[str, Any] = {} last_node_id: Optional[str] = None user_vars: Dict[str, Any] = {} node_def_by_id: Dict[str, Dict[str, Any]] = {n["id"]: n for n in nodes} # Версии обновлений нод (инкремент при каждом коммите) version: Dict[str, int] = {n["id"]: 0 for n in nodes} # Когда ребёнок запускался в последний раз (номер глобального шага) last_run_step: Dict[str, int] = {n["id"]: -1 for n in nodes} # Глобальный счётчик шагов step = 0 # Очередь готовых задач q: deque[str] = deque() # Начальные готовые — ноды без зависимостей in_degree: Dict[str, int] = {nid: len(deps) for nid, deps in deps_map.items()} for nid, deg in in_degree.items(): if deg == 0: q.append(nid) def gates_ok(child_id: str) -> bool: pairs = gate_deps.get(child_id) or [] if not pairs: return True missing_seen = False for pid, gate in pairs: v = values.get(pid) # Если значение гейта ещё не появилось — отмечаем и продолжаем проверку других гейтов if v is None: missing_seen = True continue try: flag = bool(isinstance(v, dict) and v.get(gate)) except Exception: flag = False if not flag: return False # Если были отсутствующие значения гейтов, то: # - у узла есть реальные (топологические) родители → не блокируем (первый запуск допустим) # - у узла НЕТ реальных родителей (только гейты) → откладываем до появления значения гейта if missing_seen: real_parents = deps_map.get(child_id) or set() if len(real_parents) == 0: return False return True # Лимиты total_runs = 0 t0 = time.perf_counter() try: parallel_limit = int(self.pipeline.get("parallel_limit", 8)) except Exception: parallel_limit = 8 if parallel_limit <= 0: parallel_limit = 1 async def exec_one(node_id: str, snapshot: Dict[str, Any], wave_num: int) -> tuple[str, Dict[str, Any]]: ndef = node_def_by_id.get(node_id) return await self._exec_node(node_id, ndef, snapshot, wave_num, context, trace, user_vars) # Главный цикл while q: # Ручная отмена исполнения (iterative) try: if is_cancelled(self.pipeline_id): if trace is not None: try: await trace({ "event": "cancelled", "node_id": "", "node_type": "Pipeline", "wave": step, "ts": int(time.time() * 1000), }) except Exception: pass # Снимок и финальный EXEC TRACE try: self._commit_snapshot(context, values, last_node_id or "") except Exception: pass try: summary = " -> ".join(self._exec_log) if getattr(self, "_exec_log", None) else "" if summary and isinstance(self._store.get("snapshot"), dict): self._store["snapshot"]["EXEC_TRACE"] = summary save_var_store(self.pipeline_id, self._store) except Exception: pass return last_result except Exception: pass # Проверяем лимиты if total_runs >= self.loop_max_iters: raise ExecutionError(f"Iterative mode exceeded loop_max_iters={self.loop_max_iters}") if (time.perf_counter() - t0) * 1000.0 > self.loop_time_budget_ms: raise ExecutionError(f"Iterative mode exceeded loop_time_budget_ms={self.loop_time_budget_ms}") # Собираем партию до parallel_limit, с учётом гейтов. # ВАЖНО: защищаемся от «вечной карусели» в пределах одной партии. # Обрабатываем не более исходной длины очереди за проход. batch: List[str] = [] seen: set[str] = set() spin_guard = len(q) processed_in_pass = 0 while q and len(batch) < parallel_limit and processed_in_pass < spin_guard: nid = q.popleft() processed_in_pass += 1 if nid in seen: # Уже добавлен в партию — пропускаем без возврата в очередь continue # Должны быть удовлетворены зависимости: или нет родителей, или все родители хотя бы раз исполнились parents = deps_map.get(nid) or set() deps_ok = all(version[p] > 0 or in_degree.get(nid, 0) == 0 for p in parents) or (len(parents) == 0) if not deps_ok: # отложим до лучших времён q.append(nid) continue if not gates_ok(nid): # гейты пока не открыты — попробуем позже q.append(nid) continue batch.append(nid) seen.add(nid) if not batch: # Очередь «застряла» — либо циклические ожидания без начальных значений, либо гейт не откроется. # Безопасно выходим. break # Снимок на момент партии snapshot = dict(values) results = await asyncio.gather(*(exec_one(nid, snapshot, step) for nid in batch), return_exceptions=False) # Коммитим результаты немедленно и продвигаем версии produced_vars: Dict[str, Any] = {} for nid, out in results: values[nid] = out version[nid] = version.get(nid, 0) + 1 last_result = out last_node_id = nid total_runs += 1 last_run_step[nid] = step # Человекочитаемый журнал try: ndef = node_def_by_id.get(nid) or {} ntype = ndef.get("type", "") if ntype == "If": expr = str((ndef.get("config") or {}).get("expr", "")) resb = False try: if isinstance(out, dict): resb = bool(out.get("result")) except Exception: resb = False self._exec_log.append(f"If (#{nid}) {expr} => {str(resb).lower()}") else: self._exec_log.append(f"{nid}({ntype})") except Exception: pass # Сбор пользовательских переменных try: if isinstance(out, dict) and isinstance(out.get("vars"), dict): produced_vars.update(out.get("vars") or {}) except Exception: pass if produced_vars: user_vars.update(produced_vars) # Обновляем STORE и сохраняем на диск try: self._store.update(produced_vars) save_var_store(self.pipeline_id, self._store) except Exception: pass # Постановка потомков, у кого изменился хотя бы один родитель for nid in batch: # Топологические потомки (реальные зависимости): будим всегда for child in dependents.get(nid, ()): if last_run_step.get(child, -1) < step: q.append(child) # Потомки по гейтам: будим ТОЛЬКО выбранную ветку # Логика: если у gchild есть пара gate_deps с текущим nid и нужным gate ('true'/'false'), # то будим только если соответствующий флаг у родителя истинный. Иначе — не будим. g_out = values.get(nid) or {} g_children = gate_dependents.get(nid, ()) for gchild in g_children: if last_run_step.get(gchild, -1) >= step: continue pairs = [p for p in (gate_deps.get(gchild) or []) if p and p[0] == nid] if not pairs: # gchild зарегистрирован как зависимый по гейту, но явной пары нет — пропускаем continue wake = False for (_pid, gate_name) in pairs: try: want = str(gate_name or "").strip().lower() if want in ("true", "false"): if bool(g_out.get(want, False)): wake = True break except Exception: pass if wake: q.append(gchild) try: print(f"TRACE wake_by_gate: parent={nid} -> child={gchild}") except Exception: pass # Ранний выход, если встретили Return среди выполненных try: for nid in batch: ndef = node_def_by_id.get(nid) or {} if (ndef.get("type") or "") == "Return": # Зафиксируем, что именно Return завершил выполнение try: last_node_id = nid last_result = values.get(nid) or last_result except Exception: pass # Снимок стора до выхода try: self._commit_snapshot(context, values, last_node_id or "") except Exception: pass # Финальный EXECUTION TRACE в лог и STORE try: summary = " -> ".join(self._exec_log) if getattr(self, "_exec_log", None) else "" if summary: try: print("===== EXECUTION TRACE =====") print(summary) print("===== END TRACE =====") except Exception: pass try: if isinstance(self._store.get("snapshot"), dict): self._store["snapshot"]["EXEC_TRACE"] = summary save_var_store(self.pipeline_id, self._store) except Exception: pass except Exception: pass return last_result except Exception: pass step += 1 # Финальный снапшот всего контекста и OUT в STORE.snapshot try: self._commit_snapshot(context, values, last_node_id or "") except Exception: pass # Построение и сохранение человекочитаемого EXECUTION TRACE try: summary = " -> ".join(self._exec_log) if getattr(self, "_exec_log", None) else "" if summary: try: print("===== EXECUTION TRACE =====") print(summary) print("===== END TRACE =====") except Exception: pass try: if isinstance(self._store.get("snapshot"), dict): self._store["snapshot"]["EXEC_TRACE"] = summary save_var_store(self.pipeline_id, self._store) except Exception: pass except Exception: pass return last_result def _safe_preview(self, obj: Any, max_bytes: int = 262_144) -> Any: """ Отменяем тримминг: сохраняем объект полностью. Важно: это может сделать STORE очень большим для тяжёлых ответов. """ return obj def _commit_snapshot(self, context: Dict[str, Any], values: Dict[str, Any], last_node_id: str) -> None: """ Собирает STORE.snapshot: - incoming.*, params.*, model, vendor_format, system - OUT_TEXT.nX — строковая вытяжка (до 16КБ) - OUT.nX — сырой JSON (с триммингом до ~256КБ через preview) - Алиасы OUT1/OUT2/... — плоские строки (то же, что [[OUT1]]) - LAST_NODE — последний выполнившийся узел """ # OUT_TEXT / OUT out_text: Dict[str, str] = {} out_raw: Dict[str, Any] = {} aliases: Dict[str, Any] = {} for nid, out in (values or {}).items(): if out is None: continue try: txt = _best_text_from_outputs(out) # type: ignore[name-defined] except Exception: txt = "" if not isinstance(txt, str): try: txt = str(txt) except Exception: txt = "" # Без тримминга текста — сохраняем полный text out_text[nid] = txt out_raw[nid] = self._safe_preview(out, 262_144) m = re.match(r"^n(\d+)$", str(nid)) if m: aliases[f"OUT{int(m.group(1))}"] = txt snapshot: Dict[str, Any] = { "incoming": self._safe_preview(context.get("incoming"), 262_144), "params": self._safe_preview(context.get("params"), 65_536), "model": context.get("model"), "vendor_format": context.get("vendor_format"), "system": context.get("system") or "", "OUT": out_raw, "OUT_TEXT": out_text, "LAST_NODE": last_node_id or "", **aliases, } # Сохраняем под ключом snapshot, пользовательские vars остаются как есть в корне STORE try: if not isinstance(self._store, dict): self._store = {} self._store["snapshot"] = snapshot save_var_store(self.pipeline_id, self._store) except Exception: pass class SetVarsNode(Node): type_name = "SetVars" def _normalize(self) -> List[Dict[str, Any]]: raw = self.config.get("variables") or [] if not isinstance(raw, list): return [] norm: List[Dict[str, Any]] = [] for i, b in enumerate(raw): if not isinstance(b, dict): continue name = str(b.get("name", "")).strip() mode = str(b.get("mode", "string")).lower().strip() value = b.get("value", "") try: order = int(b.get("order")) if b.get("order") is not None else i except Exception: order = i norm.append({ "id": b.get("id") or f"v{i}", "name": name, "mode": "expr" if mode == "expr" else "string", "value": value, "order": order, }) return norm def _safe_eval_expr(self, expr: str, context: Optional[Dict[str, Any]] = None, out_map: Optional[Dict[str, Any]] = None) -> Any: """ Безопасная оценка выражений для SetVars. Поддержка: - Литералы: числа/строки/bool/None, списки, кортежи, словари - JSON‑литералы: true/false/null, объекты и массивы (парсятся как Python True/False/None, dict/list) - Арифметика: + - * / // %, унарные +- - Логика: and/or, сравнения (== != < <= > >=, цепочки) - Безопасные функции: rand(), randint(a,b), choice(list) jp(value, path, join_sep="\n"), jp_text(value, path, join_sep="\n") from_json(x) file_b64(path), data_url(b64, mime), file_data_url(path, mime?) Примечание: функции jp/jp_text/from_json принимают как обычные значения, так и строки с макросами ([[...]] или {{ ... }}). Макросы разворачиваются с помощью render_template_simple. """ import ast import operator as op import random import base64 import os import mimetypes from pathlib import Path def _resolve_input(x: Any) -> Any: # Если уже структура — вернуть как есть if isinstance(x, (dict, list, bool, int, float)) or x is None: return x s = str(x) # Попробуем развернуть макросы/шаблон, если есть контекст try: s2 = render_template_simple(s, context or {}, out_map or {}) except Exception: s2 = s # Попробуем распарсить JSON try: return json.loads(s2) except Exception: return s2 def _fn_from_json(x: Any) -> Any: val = _resolve_input(x) if isinstance(val, str): try: return json.loads(val) except Exception: return val return val def _fn_jp(value: Any, path: Any, join_sep: Any = "\n") -> Any: src = _resolve_input(value) p = str(path or "") try: vals = _json_path_extract(src, p) return vals except Exception: return None def _fn_jp_text(value: Any, path: Any, join_sep: Any = "\n") -> str: vals = _fn_jp(value, path, join_sep) try: return _stringify_join(vals, str(join_sep or "\n")) except Exception: # на крайний случай — строковое представление try: return str(vals) except Exception: return "" # Новые функции для работы с изображениями def _fn_file_b64(path_like: Any) -> str: """Прочитать файл и вернуть base64-строку (без префикса).""" p_raw = _resolve_input(path_like) p = Path(str(p_raw)).expanduser() data = p.read_bytes() return base64.b64encode(data).decode("ascii") def _fn_data_url(b64: Any, mime: Any) -> str: """Собрать data URL: data:;base64,""" b64s = str(_resolve_input(b64) if not isinstance(b64, str) else b64) m = str(_resolve_input(mime) if not isinstance(mime, str) else mime).strip() or "application/octet-stream" return f"data:{m};base64,{b64s}" def _fn_file_data_url(path_like: Any, mime_opt: Any = None) -> str: """Скомбинировать чтение файла и сборку data URL. mime можно не указывать — попытка угадать по расширению.""" p_raw = _resolve_input(path_like) p = Path(str(p_raw)).expanduser() try: data = p.read_bytes() except Exception as e: print(f"DEBUG: file_data_url error reading file {p_raw}: {e}") raise size = len(data) print(f"DEBUG: file_data_url loaded file {p!s} size={size} bytes") b64s = base64.b64encode(data).decode("ascii") mime = None if mime_opt is not None: mime = str(_resolve_input(mime_opt)) if not mime: mt, _ = mimetypes.guess_type(str(p)) mime = mt or "application/octet-stream" return f"data:{mime};base64,{b64s}" # 0) Попытаться распознать чистый JSON‑литерал (включая true/false/null, объекты/массивы/числа/строки). try: s = str(expr).strip() return json.loads(s) except Exception: pass allowed_bin = { ast.Add: op.add, ast.Sub: op.sub, ast.Mult: op.mul, ast.Div: op.truediv, ast.FloorDiv: op.floordiv, ast.Mod: op.mod, } allowed_unary = {ast.UAdd: lambda x: +x, ast.USub: lambda x: -x} allowed_cmp = { ast.Eq: op.eq, ast.NotEq: op.ne, ast.Lt: op.lt, ast.LtE: op.le, ast.Gt: op.gt, ast.GtE: op.ge, } def eval_node(node: ast.AST) -> Any: if isinstance(node, ast.Expression): return eval_node(node.body) if isinstance(node, ast.Constant): return node.value if isinstance(node, ast.Tuple): return tuple(eval_node(e) for e in node.elts) if isinstance(node, ast.List): return [eval_node(e) for e in node.elts] if isinstance(node, ast.Dict): return {eval_node(k): eval_node(v) for k, v in zip(node.keys, node.values)} if isinstance(node, ast.UnaryOp) and type(node.op) in allowed_unary: return allowed_unary[type(node.op)](eval_node(node.operand)) if isinstance(node, ast.BinOp) and type(node.op) in allowed_bin: return allowed_bin[type(node.op)](eval_node(node.left), eval_node(node.right)) if isinstance(node, ast.BoolOp): vals = [eval_node(v) for v in node.values] if isinstance(node.op, ast.And): res = True for v in vals: res = res and bool(v) return res if isinstance(node.op, ast.Or): res = False for v in vals: res = res or bool(v) return res if isinstance(node, ast.Compare): left = eval_node(node.left) for opnode, comparator in zip(node.ops, node.comparators): if type(opnode) not in allowed_cmp: raise ExecutionError("Unsupported comparison operator") right = eval_node(comparator) if not allowed_cmp[type(opnode)](left, right): return False left = right return True # Разрешённые вызовы: rand(), randint(a,b), choice(list), jp(), jp_text(), from_json(), file_b64(), data_url(), file_data_url() if isinstance(node, ast.Call): # Никаких kwargs, *args if node.keywords or isinstance(getattr(node, "starargs", None), ast.AST) or isinstance(getattr(node, "kwargs", None), ast.AST): raise ExecutionError("Call with kwargs/starargs is not allowed") fn = node.func if not isinstance(fn, ast.Name): raise ExecutionError("Only simple function calls are allowed") name = fn.id if name == "rand": if len(node.args) != 0: raise ExecutionError("rand() takes no arguments") return random.random() if name == "randint": if len(node.args) != 2: raise ExecutionError("randint(a,b) requires two arguments") a = eval_node(node.args[0]) b = eval_node(node.args[1]) try: return random.randint(int(a), int(b)) except Exception as exc: # noqa: BLE001 raise ExecutionError(f"randint invalid arguments: {exc}") if name == "choice": if len(node.args) != 1: raise ExecutionError("choice(list) requires one argument") seq = eval_node(node.args[0]) if not isinstance(seq, (list, tuple)): raise ExecutionError("choice() expects list or tuple") if not seq: raise ExecutionError("choice() on empty sequence") return random.choice(seq) if name == "jp": if len(node.args) < 2 or len(node.args) > 3: raise ExecutionError("jp(value, path, [join_sep]) requires 2 or 3 args") v = eval_node(node.args[0]) p = eval_node(node.args[1]) return _fn_jp(v, p, eval_node(node.args[2]) if len(node.args) == 3 else "\n") if name == "jp_text": if len(node.args) < 2 or len(node.args) > 3: raise ExecutionError("jp_text(value, path, [join_sep]) requires 2 or 3 args") v = eval_node(node.args[0]) p = eval_node(node.args[1]) return _fn_jp_text(v, p, eval_node(node.args[2]) if len(node.args) == 3 else "\n") if name == "from_json": if len(node.args) != 1: raise ExecutionError("from_json(x) requires one argument") v = eval_node(node.args[0]) return _fn_from_json(v) if name == "file_b64": if len(node.args) != 1: raise ExecutionError("file_b64(path) requires one argument") return _fn_file_b64(eval_node(node.args[0])) if name == "data_url": if len(node.args) != 2: raise ExecutionError("data_url(b64, mime) requires two arguments") b64v = eval_node(node.args[0]) mimev = eval_node(node.args[1]) return _fn_data_url(b64v, mimev) if name == "file_data_url": if len(node.args) < 1 or len(node.args) > 2: raise ExecutionError("file_data_url(path, [mime]) requires 1 or 2 args") p = eval_node(node.args[0]) mv = eval_node(node.args[1]) if len(node.args) == 2 else None return _fn_file_data_url(p, mv) raise ExecutionError(f"Function {name} is not allowed") # Запрещаем всё остальное (Name/Attribute/Subscript/IfExp/Comprehensions и пр.) raise ExecutionError("Expression not allowed") try: tree = ast.parse(str(expr), mode="eval") except Exception as exc: raise ExecutionError(f"SetVars expr parse error: {exc}") from exc return eval_node(tree) async def run(self, inputs: Dict[str, Any], context: Dict[str, Any]) -> Dict[str, Any]: # noqa: D401 out_map = context.get("OUT") or {} result: Dict[str, Any] = {} import re as _re for v in sorted(self._normalize(), key=lambda x: x.get("order", 0)): name = v.get("name") or "" if not _re.fullmatch(r"[A-Za-z_][A-Za-z0-9_]*", name or ""): raise ExecutionError(f"SetVars invalid variable name: {name!r}") mode = v.get("mode", "string") raw_val = v.get("value", "") if mode == "expr": resolved = self._safe_eval_expr(str(raw_val), context, out_map) else: resolved = render_template_simple(str(raw_val or ""), context, out_map) result[name] = resolved # Событие «vars_set» в SSE‑лог (+ превью значений) try: trace_fn = context.get("_trace") if trace_fn: def _pv(val: Any) -> str: try: if isinstance(val, str): s = val else: s = json.dumps(val, ensure_ascii=False) except Exception: try: s = str(val) except Exception: s = "" s = s if isinstance(s, str) else str(s) return (s[:300] + "…") if len(s) > 300 else s values_preview = {k: _pv(v) for k, v in (result or {}).items()} await trace_fn({ "event": "vars_set", "node_id": self.node_id, "node_type": self.type_name, "vars": list(result.keys()), "count": len(result), "values_preview": values_preview, }) except Exception: pass return {"vars": result} # --- v1: Нормализованный экстрактор текста для OUTx ----------------------------- def _json_path_extract(obj: Any, path: str) -> Any: if not path: return None nodes = [obj] for raw_seg in str(path).split("."): seg = (raw_seg or "").strip() if not seg: continue next_nodes = [] # Поддержка "*": разворачиваем dict.values() или элементы списка if seg == "*": for n in nodes: if isinstance(n, dict): next_nodes.extend(list(n.values())) elif isinstance(n, list): next_nodes.extend(list(n)) nodes = next_nodes if not nodes: break continue # Числовой индекс для списков idx = None try: idx = int(seg) except Exception: idx = None for n in nodes: if idx is not None and isinstance(n, list): if 0 <= idx < len(n): next_nodes.append(n[idx]) elif idx is None and isinstance(n, dict): if seg in n: next_nodes.append(n[seg]) nodes = next_nodes if not nodes: break if not nodes: return None return nodes if len(nodes) > 1 else nodes[0] def _stringify_join(values: Any, join_sep: str = "\n") -> str: def _flatten(x): if isinstance(x, list): for it in x: yield from _flatten(it) else: yield x arr = list(_flatten(values if isinstance(values, list) else [values])) out: List[str] = [] for v in arr: if isinstance(v, str): if v: out.append(v) elif isinstance(v, (dict, list)): try: t = _deep_find_text(v) # type: ignore[name-defined] if isinstance(t, str) and t: out.append(t) except Exception: pass else: try: sv = str(v) if sv: out.append(sv) except Exception: pass if not out: return "" return (join_sep or "\n").join(out) def _extract_text_for_out(data: Any, strategy: str = "auto", provider_hint: str = "", json_path: str = "", join_sep: str = "\n") -> str: s = (strategy or "auto").lower().strip() or "auto" prov = (provider_hint or "").lower().strip() # Принудительные стратегии if s == "deep": try: t = _deep_find_text(data) # type: ignore[name-defined] return t if isinstance(t, str) else (str(t) if t is not None else "") except Exception: return "" if s == "jsonpath": try: vals = _json_path_extract(data, json_path or "") return _stringify_join(vals, join_sep) except Exception: return "" if s in {"openai", "gemini", "claude"}: try: if s == "openai" and isinstance(data, dict): msg = (data.get("choices") or [{}])[0].get("message") or {} c = msg.get("content") return c if isinstance(c, str) else (str(c) if c is not None else "") if s == "gemini" and isinstance(data, dict): cands = data.get("candidates") or [] texts: List[str] = [] for cand in cands: try: content = cand.get("content") or {} parts = content.get("parts") or [] for p in parts: if isinstance(p, dict): t = p.get("text") if isinstance(t, str) and t.strip(): texts.append(t.strip()) except Exception: continue if texts: return (join_sep or "\n").join(texts) return "" if s == "claude" and isinstance(data, dict): blocks = data.get("content") or [] texts = [b.get("text") for b in blocks if isinstance(b, dict) and isinstance(b.get("text"), str)] if texts: return "\n".join(texts) return "" except Exception: return "" return "" # auto: если есть подсказка — пробуем сначала её ветку, потом общий if prov in {"openai", "gemini", "claude"}: forced = _extract_text_for_out(data, prov, prov, json_path, join_sep) if forced: return forced # Универсальный best-effort: знает openai/gemini/claude try: t = _best_text_from_outputs({"result": data}) # type: ignore[name-defined] if isinstance(t, str) and t: return t if t is not None: t2 = str(t) if t2: return t2 except Exception: pass # Последний шанс — глубокий поиск try: t = _deep_find_text(data) # type: ignore[name-defined] return t if isinstance(t, str) else (str(t) if t is not None else "") except Exception: return "" class ProviderCallNode(Node): type_name = "ProviderCall" # --- Prompt Manager helpers ------------------------------------------------- def _get_blocks(self) -> List[Dict[str, Any]]: """Return normalized list of prompt blocks from config.""" raw = self.config.get("blocks") or self.config.get("prompt_blocks") or [] if not isinstance(raw, list): return [] norm: List[Dict[str, Any]] = [] for i, b in enumerate(raw): if not isinstance(b, dict): continue role = str(b.get("role", "user")).lower().strip() if role not in {"system", "user", "assistant", "tool"}: role = "user" # order fallback: keep original index if not provided/correct try: order = int(b.get("order")) if b.get("order") is not None else i except Exception: # noqa: BLE001 order = i norm.append( { "id": b.get("id") or f"b{i}", "name": b.get("name") or f"Block {i+1}", "role": role, "prompt": b.get("prompt") or "", "enabled": bool(b.get("enabled", True)), "order": order, } ) return norm def _render_blocks_to_unified(self, context: Dict[str, Any]) -> List[Dict[str, Any]]: """ Filter+sort+render blocks to unified messages: [{role, content, name?}] Расширение: поддержка изображений в Markdown вида ![alt](URL|DATA_URL). Если в тексте встречаются такие конструкции — content превращается в список частей: - {"type":"text","text":"..."} - {"type":"image_url","url":"..."} """ import re as _re out_map = context.get("OUT") or {} blocks = [b for b in self._get_blocks() if b.get("enabled", True)] blocks.sort(key=lambda x: x.get("order", 0)) def _parse_markdown_parts(s: str) -> List[Dict[str, Any]]: print(f"DEBUG: _parse_markdown_parts input={s!r}") pat = _re.compile(r"!\[[^\]]*\]\(([^)]+)\)") parts: List[Dict[str, Any]] = [] pos = 0 for m in pat.finditer(s): print(f"DEBUG: _parse_markdown_parts match at span={m.span()} url={m.group(1)!r}") if m.start() > pos: txt = s[pos:m.start()] if txt: parts.append({"type": "text", "text": txt}) url = (m.group(1) or "").strip() if url: parts.append({"type": "image_url", "url": url}) pos = m.end() if pos < len(s): tail = s[pos:] if tail: parts.append({"type": "text", "text": tail}) return parts messages: List[Dict[str, Any]] = [] for b in blocks: content_raw = render_template_simple(str(b.get("prompt") or ""), context, out_map) parts = _parse_markdown_parts(content_raw or "") # Если нет картинок — оставляем строкой для обратной совместимости content_final: Any = parts if any(p.get("type") == "image_url" for p in parts) else content_raw msg = {"role": b["role"], "content": content_final} messages.append(msg) return messages def _messages_to_payload(self, provider: str, messages: List[Dict[str, Any]], context: Dict[str, Any]) -> Dict[str, Any]: """Convert unified messages (with optional text+image parts) to provider-specific request payload.""" import re as _re params = context.get("params") or {} model = context.get("model") or "" def _is_data_url(u: str) -> bool: return isinstance(u, str) and u.strip().lower().startswith("data:") def _split_data_url(u: str) -> tuple[str, str]: """ Возвращает (mime, b64) для data URL. Поддерживаем форму: data:;base64, """ try: header, b64 = u.split(",", 1) mime = "application/octet-stream" if header.startswith("data:"): header2 = header[5:] if ";base64" in header2: mime = header2.split(";base64", 1)[0] or mime elif ";" in header2: mime = header2.split(";", 1)[0] or mime elif header2: mime = header2 return mime, b64 except Exception: return "application/octet-stream", "" provider = (provider or "").lower() if provider == "openai": def _map_openai_msg(m: Dict[str, Any]) -> Dict[str, Any]: c = m.get("content") if isinstance(c, list): parts = [] for p in c: if isinstance(p, dict) and p.get("type") == "text": parts.append({"type": "text", "text": str(p.get("text") or "")}) elif isinstance(p, dict) and p.get("type") in {"image_url", "image"}: url = str(p.get("url") or "") parts.append({"type": "image_url", "image_url": {"url": url}}) return {"role": m.get("role", "user"), "content": parts} # строка — как было return {"role": m.get("role", "user"), "content": str(c or "")} payload: Dict[str, Any] = { "model": model, "messages": [_map_openai_msg(m) for m in messages], "temperature": params.get("temperature", 0.7), } if params.get("max_tokens") is not None: payload["max_tokens"] = params.get("max_tokens") if params.get("top_p") is not None: payload["top_p"] = params.get("top_p") if params.get("stop") is not None: payload["stop"] = params.get("stop") return payload if provider == "gemini_image": def _map_gemini_image_msg(m: Dict[str, Any]) -> Dict[str, Any]: c = m.get("content") parts: List[Dict[str, Any]] = [] if isinstance(c, list): for p in c: if isinstance(p, dict) and p.get("type") == "text": parts.append({"text": str(p.get("text") or "")}) elif isinstance(p, dict) and p.get("type") in {"image_url", "image"}: url = str(p.get("url") or "") if _is_data_url(url): mime, b64 = _split_data_url(url) parts.append({"inline_data": {"mime_type": mime, "data": b64}}) else: parts.append({"text": url}) else: parts.append({"text": str(c or "")}) return {"parts": parts} payload: Dict[str, Any] = {"model": model, "contents": [_map_gemini_image_msg(m) for m in messages]} return payload if provider == "gemini": def _map_claude_msg(m: Dict[str, Any]) -> Dict[str, Any]: role_raw = str(m.get("role") or "user") role = role_raw if role_raw in {"user", "assistant"} else "user" c = m.get("content") blocks: List[Dict[str, Any]] = [] if isinstance(c, list): for p in c: if not isinstance(p, dict): continue if p.get("type") == "text": blocks.append({"type": "text", "text": str(p.get("text") or "")}) elif p.get("type") in {"image_url", "image"}: url = str(p.get("url") or "") if _is_data_url(url): mime, b64 = _split_data_url(url) blocks.append({"type": "image", "source": {"type": "base64", "media_type": mime, "data": b64}}) else: blocks.append({"type": "image", "source": {"type": "url", "url": url}}) else: blocks.append({"type": "text", "text": str(c or "")}) return {"role": role, "content": blocks} # system — текстовая склейка (без картинок) sys_text = "\n\n".join( [str(m.get("content") or "") if not isinstance(m.get("content"), list) else "\n".join([str(p.get("text") or "") for p in m.get("content") if isinstance(p, dict) and p.get("type") == "text"]) for m in messages if m.get("role") == "system"] ).strip() msgs = [_map_claude_msg(m) for m in messages if m.get("role") != "system"] payload: Dict[str, Any] = { "model": model, "messages": msgs, } if sys_text: payload["system"] = sys_text if params.get("temperature") is not None: payload["temperature"] = params.get("temperature") if params.get("max_tokens") is not None: payload["max_tokens"] = params.get("max_tokens") if params.get("top_p") is not None: payload["top_p"] = params.get("top_p") if params.get("stop") is not None: payload["stop"] = params.get("stop") return payload return {} def _blocks_struct_for_template(self, provider: str, messages: List[Dict[str, Any]], context: Dict[str, Any]) -> Dict[str, Any]: """ Сформировать структуру для вставки в шаблон (template) из Prompt Blocks. Возвращает provider-специфичные ключи, которые можно вставлять в JSON: - openai: { "messages": [...] , "system_text": "..." } - gemini: { "contents": [...], "systemInstruction": {...}, "system_text": "..." } - claude: { "system_text": "...", "system": "...", "messages": [...] } Расширение: поддержка текст+изображения, как и в _messages_to_payload. """ provider = (provider or "openai").lower() msgs = messages or [] def _is_data_url(u: str) -> bool: return isinstance(u, str) and u.strip().lower().startswith("data:") def _split_data_url(u: str) -> tuple[str, str]: try: header, b64 = u.split(",", 1) mime = "application/octet-stream" if header.startswith("data:"): header2 = header[5:] if ";base64" in header2: mime = header2.split(";base64", 1)[0] or mime elif ";" in header2: mime = header2.split(";", 1)[0] or mime elif header2: mime = header2 return mime, b64 except Exception: return "application/octet-stream", "" if provider == "openai": def _map(m: Dict[str, Any]) -> Dict[str, Any]: c = m.get("content") if isinstance(c, list): parts = [] for p in c: if isinstance(p, dict) and p.get("type") == "text": parts.append({"type": "text", "text": str(p.get("text") or "")}) elif isinstance(p, dict) and p.get("type") in {"image_url", "image"}: url = str(p.get("url") or "") parts.append({"type": "image_url", "image_url": {"url": url}}) return {"role": m.get("role", "user"), "content": parts} return {"role": m.get("role", "user"), "content": str(c or "")} sys_text = "\n\n".join( [str(m.get("content") or "") if not isinstance(m.get("content"), list) else "\n".join([str(p.get("text") or "") for p in m.get("content") if isinstance(p, dict) and p.get("type") == "text"]) for m in msgs if m.get("role") == "system"] ).strip() return { "messages": [_map(m) for m in msgs], "system_text": sys_text, } if provider in {"gemini", "gemini_image"}: def _text_from_msg(m: Dict[str, Any]) -> str: c = m.get("content") if isinstance(c, list): texts = [str(p.get("text") or "") for p in c if isinstance(p, dict) and p.get("type") == "text"] return "\n".join([t for t in texts if t]) return str(c or "") sys_text = "\n\n".join([_text_from_msg(m) for m in msgs if m.get("role") == "system"]).strip() contents = [] for m in msgs: if m.get("role") == "system": continue role = "model" if m.get("role") == "assistant" else "user" c = m.get("content") parts: List[Dict[str, Any]] = [] if isinstance(c, list): for p in c: if not isinstance(p, dict): continue if p.get("type") == "text": parts.append({"text": str(p.get("text") or "")}) elif p.get("type") in {"image_url", "image"}: url = str(p.get("url") or "") if _is_data_url(url): mime, b64 = _split_data_url(url) parts.append({"inline_data": {"mime_type": mime, "data": b64}}) else: parts.append({"text": url}) else: parts.append({"text": str(c or "")}) contents.append({"role": role, "parts": parts}) d: Dict[str, Any] = { "contents": contents, "system_text": sys_text, } if sys_text: d["systemInstruction"] = {"parts": [{"text": sys_text}]} return d if provider == "claude": # Системные сообщения как текст sys_msgs = [] for m in msgs: if m.get("role") == "system": c = m.get("content") if isinstance(c, list): sys_msgs.append("\n".join([str(p.get("text") or "") for p in c if isinstance(p, dict) and p.get("type") == "text"])) else: sys_msgs.append(str(c or "")) sys_text = "\n\n".join([s for s in sys_msgs if s]).strip() out_msgs = [] for m in msgs: if m.get("role") == "system": continue role = m.get("role") role = role if role in {"user", "assistant"} else "user" c = m.get("content") blocks: List[Dict[str, Any]] = [] if isinstance(c, list): for p in c: if not isinstance(p, dict): continue if p.get("type") == "text": blocks.append({"type": "text", "text": str(p.get("text") or "")}) elif p.get("type") in {"image_url", "image"}: url = str(p.get("url") or "") if _is_data_url(url): mime, b64 = _split_data_url(url) blocks.append({"type": "image", "source": {"type": "base64", "media_type": mime, "data": b64}}) else: blocks.append({"type": "image", "source": {"type": "url", "url": url}}) else: blocks.append({"type": "text", "text": str(c or "")}) out_msgs.append({"role": role, "content": blocks}) # Optional Claude mode: omit top-level "system" and prepend it as a user message claude_no_system = False try: claude_no_system = bool((self.config or {}).get("claude_no_system", False)) except Exception: claude_no_system = False if claude_no_system: if sys_text: out_msgs = [{"role": "user", "content": [{"type": "text", "text": sys_text}]}] + out_msgs return { "messages": out_msgs, "system_text": sys_text, } d = { "system_text": sys_text, "messages": out_msgs, } if sys_text: # Prefer system as a plain string (proxy compatibility) d["system"] = sys_text return d # По умолчанию ничего, но это валидный JSON return {"messages": []} async def run(self, inputs: Dict[str, Any], context: Dict[str, Any]) -> Dict[str, Any]: # While-loop wrapper: if while_expr is set or ignore_errors enabled, route through helper try: cfg = self.config or {} except Exception: cfg = {} try: _while_expr = str(cfg.get("while_expr") or "").strip() except Exception: _while_expr = "" try: _ignore = bool(cfg.get("ignore_errors", False)) except Exception: _ignore = False if not (context.get("_in_while") or False) and (_while_expr or _ignore): return await _providercall_run_with_while(self, inputs, context) provider = (self.config.get("provider") or "openai").lower() # Optional sleep before execution (UI-configured, milliseconds) try: sleep_ms = int(self.config.get("sleep_ms") or 0) except Exception: sleep_ms = 0 if sleep_ms > 0: # Emit SSE event to highlight node as "sleeping" on UI try: trace_fn = context.get("_trace") if trace_fn: await trace_fn({ "event": "node_sleep", "node_id": self.node_id, "node_type": self.type_name, "sleep_ms": int(sleep_ms), "ts": int(time.time() * 1000), }) except Exception: pass # Non-blocking pause try: await asyncio.sleep(max(0.0, sleep_ms / 1000.0)) except Exception: pass # Support provider-specific configs stored in UI as provider_configs.{provider} prov_cfg: Dict[str, Any] = {} try: cfgs = self.config.get("provider_configs") or {} if isinstance(cfgs, dict): prov_cfg = cfgs.get(provider) or {} except Exception: # noqa: BLE001 prov_cfg = {} base_url = prov_cfg.get("base_url") or self.config.get("base_url") if not base_url: raise ExecutionError(f"Node {self.node_id} ({self.type_name}) requires 'base_url' in config") if not str(base_url).startswith(("http://", "https://")): base_url = "http://" + str(base_url) endpoint_tmpl: str = prov_cfg.get("endpoint") or self.config.get("endpoint") or "" template: str = prov_cfg.get("template") or self.config.get("template") or "{}" headers_json: str = prov_cfg.get("headers") or self.config.get("headers") or "{}" # Default endpoints if not set if not endpoint_tmpl: _ad = None try: _ad = get_adapter(provider) except Exception: _ad = None if _ad is not None: try: endpoint_tmpl = _ad.default_endpoint(str(context.get("model") or "")) except Exception: endpoint_tmpl = "" if not endpoint_tmpl: if provider == "openai": endpoint_tmpl = "/v1/chat/completions" elif provider == "gemini": endpoint_tmpl = "/v1beta/models/{{ model }}:generateContent" elif provider == "gemini_image": # Специальный провайдер для генерации/превью изображений Gemini (generateContent) endpoint_tmpl = "/v1beta/models/{{ model }}:generateContent" elif provider == "claude": endpoint_tmpl = "/v1/messages" # Default template for gemini_image if none provided (inject [[PROMPT]]) try: _tmpl_src = (prov_cfg.get("template") or self.config.get("template") or "").strip() except Exception: _tmpl_src = "" if provider == "gemini_image" and (not _tmpl_src or _tmpl_src == "{}"): # Минимальный валидный JSON с [[PROMPT]] для contents/systemInstruction template = '{ "model": "{{ model }}", [[PROMPT]] }' # Подготовим Prompt Blocks + pm-структуру для шаблона unified_msgs = self._render_blocks_to_unified(context) adapter = None try: adapter = get_adapter(provider) except Exception: adapter = None if adapter: blocks_struct = adapter.blocks_struct_for_template(unified_msgs, context, self.config or {}) else: blocks_struct = self._blocks_struct_for_template(provider, unified_msgs, context) pm_struct = dict(blocks_struct) # Расширяем контекст для рендера шаблонов render_ctx = dict(context) render_ctx["pm"] = pm_struct # Прокинем конфиг ноды в контекст для адаптеров (например, claude_no_system) try: render_ctx["_node_config"] = dict(self.config or {}) except Exception: render_ctx["_node_config"] = {} # Node-local: track VAR paths overridden by prompt_preprocess (no extra syntax) pre_var_paths = set() # prompt_preprocess (pre-merge DSL): парсим строки до prompt_combine и готовим «пред‑сегменты» # Синтаксис строки: # SEGMENT [delKeyContains "needle"] [delpos=prepend|append|N|-1] [pruneEmpty] [case=ci|cs] # По умолчанию: case=ci, pruneEmpty=false, без delpos → append # SEGMENT поддерживает [[...]] и {{ ... }} pre_segments_raw: List[Dict[str, Any]] = [] try: pre_raw = str((self.config or {}).get("prompt_preprocess") or "").strip() except Exception: pre_raw = "" if pre_raw: lines = [ln.strip() for ln in pre_raw.splitlines() if str(ln or "").strip()] import re as _repp # Collect local overrides for plain [[VAR:path]] segments after filtering pre_var_overrides: Dict[str, Any] = {} def _pp_try_json(s: str) -> Any: try: obj = json.loads(s) except Exception: try: obj = json.loads(s, strict=False) # type: ignore[call-arg] except Exception: return None for _ in range(2): if isinstance(obj, str): st = obj.strip() if (st.startswith("{") and st.endswith("}")) or (st.startswith("[") and st.endswith("]")): try: obj = json.loads(st) continue except Exception: break break return obj def _norm(s: Any, ci: bool) -> str: try: ss = s if isinstance(s, str) else str(s) except Exception: ss = "" return ss.lower() if ci else ss def _delkeys_by_val_contains(x: Any, needles: List[str], ci: bool, prune_empty: bool, is_root: bool = False) -> tuple[Any, int]: """ Рекурсивно удаляет ключи словаря, если строковое представление их значения содержит needle. - needles: список подстрок - ci: регистронезависимый поиск (по умолчанию True) - prune_empty: удалять пустые {} / [] из родителей (кроме корня) Возвращает (новое_значение_или_None, удалённые_ключи_суммарно) """ removed = 0 if isinstance(x, dict): out: Dict[str, Any] = {} for k, v in x.items(): v2, rem2 = _delkeys_by_val_contains(v, needles, ci, prune_empty, False) removed += rem2 sv = _stringify_for_template(v2) cond = False try: nsv = _norm(sv, ci) for nd in needles: nds = _norm(nd, ci) if nds and (nds in nsv): cond = True break except Exception: cond = False if cond: removed += 1 continue out[k] = v2 if prune_empty and not is_root and len(out) == 0: return None, removed # type: ignore[return-value] return out, removed if isinstance(x, list): arr: List[Any] = [] for it in x: it2, rem2 = _delkeys_by_val_contains(it, needles, ci, prune_empty, False) removed += rem2 if it2 is None and prune_empty: continue arr.append(it2) if prune_empty and not is_root and len(arr) == 0: return None, removed # type: ignore[return-value] return arr, removed # scalar return x, removed pre_used = 0 pre_removed_total = 0 for ln in lines: try: # Опции needles = [m.group(1) for m in _repp.finditer(r'(?is)\bdelKeyContains\s+"([^"]*)"', ln)] mpos = _repp.search(r'(?is)\bdelpos\s*=\s*(prepend|append|-?\d+)\b', ln) pos_spec = mpos.group(1).strip().lower() if mpos else None mcase = _repp.search(r'(?is)\bcase\s*=\s*(ci|cs)\b', ln) ci = True if not mcase else (mcase.group(1).strip().lower() == "ci") prune = bool(_repp.search(r'(?is)\bpruneEmpty\b', ln)) # Очищаем директивы из текста строки → остаётся сам SEGMENT s2 = _repp.sub(r'(?is)\bdelKeyContains\s+"[^"]*"', "", ln) s2 = _repp.sub(r'(?is)\bdelpos\s*=\s*(prepend|append|-?\d+)\b', "", s2) s2 = _repp.sub(r'(?is)\bcase\s*=\s*(ci|cs)\b', "", s2) s2 = _repp.sub(r'(?is)\bpruneEmpty\b', "", s2) seg = s2.strip() if not seg: continue # Try to detect plain [[VAR:path]] to support node-local override without extra syntax var_path = None try: mvar = _VAR_MACRO_RE.fullmatch(seg) if mvar: var_path = (mvar.group(1) or "").strip() except Exception: var_path = None # Макросы и попытка распарсить JSON resolved = render_template_simple(seg, render_ctx, render_ctx.get("OUT") or {}) obj = _pp_try_json(resolved) base = obj if obj is not None else resolved # Удаление ключей по contains, если задано if needles: try: base2, remcnt = _delkeys_by_val_contains(base, needles, ci, prune, True) except Exception: base2, remcnt = base, 0 else: base2, remcnt = base, 0 # If the segment was a pure [[VAR:path]] and we had filters, # locally override this VAR for the rest of the node (so prompt_combine sees the filtered value) try: if var_path and needles: pre_var_overrides[var_path] = base2 except Exception: pass pre_segments_raw.append({"obj": base2, "pos": pos_spec}) pre_used += 1 pre_removed_total += int(remcnt or 0) except Exception: continue # Apply local VAR overrides onto render_ctx (node-local, no extra syntax) try: import copy as _copy def _safe_deepcopy(x: Any) -> Any: try: return _copy.deepcopy(x) except Exception: # Fallback deep copy for dict/list; otherwise return as-is try: if isinstance(x, dict): return {k: _safe_deepcopy(v) for k, v in x.items()} if isinstance(x, list): return [_safe_deepcopy(i) for i in x] except Exception: pass try: return json.loads(json.dumps(x)) except Exception: return x def _set_by_path(obj: Any, path: str, value: Any) -> None: cur = obj parts = [p.strip() for p in str(path).split(".") if p.strip()] for i, part in enumerate(parts): # list index? idx = None try: idx = int(part) except Exception: idx = None last = (i == len(parts) - 1) if idx is not None: if not isinstance(cur, list) or idx < 0 or idx >= len(cur): return if last: cur[idx] = value return cur = cur[idx] continue # dict key if not isinstance(cur, dict): return if last: cur[part] = value return if part not in cur or not isinstance(cur[part], (dict, list)): cur[part] = {} cur = cur[part] # Deep-copy only the top-level roots we are going to mutate (e.g., 'incoming' for 'incoming.*') roots_to_copy: set = set() for _p in (pre_var_overrides or {}).keys(): if "." in str(_p): roots_to_copy.add(str(_p).split(".", 1)[0].strip()) for _root in roots_to_copy: try: if _root in render_ctx: render_ctx[_root] = _safe_deepcopy(render_ctx[_root]) except Exception: pass for _p, _v in (pre_var_overrides or {}).items(): _set_by_path(render_ctx, _p, _v) pre_var_paths = set(pre_var_overrides.keys()) except Exception: pre_var_paths = set() # SSE: prompt_preprocess summary try: trace_fn = context.get("_trace") if trace_fn: await trace_fn({ "event": "prompt_preprocess", "node_id": self.node_id, "node_type": self.type_name, "provider": provider, "lines": len(lines), "used": pre_used, "removed_keys": pre_removed_total, "ts": int(time.time() * 1000), }) except Exception: pass else: pre_segments_raw = [] # prompt_combine (DSL "&"): комбинируем сегменты в заданном порядке. # Расширения: # - [[PROMPT]] как специальный сегмент (позиционно вставляет pm_struct) # - Директивы @pos=prepend|append| (управление позицией в массиве) # - Фильтрация пустых сообщений/частей try: cfg = self.config or {} combine_raw = str(cfg.get("prompt_combine") or "").strip() except Exception: combine_raw = "" # Быстрая ветка: если есть адаптер — выполняем merge сегментов через него и коротко-замыкаем легаси-блок ниже raw_segs_for_adapter = [s.strip() for s in combine_raw.split("&") if str(s or "").strip()] if adapter and (raw_segs_for_adapter or (pre_segments_raw and len(pre_segments_raw) > 0)): try: pm_struct = adapter.combine_segments( blocks_struct=blocks_struct, pre_segments_raw=pre_segments_raw, raw_segs=raw_segs_for_adapter, render_ctx=render_ctx, pre_var_paths=pre_var_paths, render_template_simple_fn=render_template_simple, var_macro_fullmatch_re=_VAR_MACRO_RE, detect_vendor_fn=detect_vendor, ) # обновим pm в контексте try: render_ctx["pm"] = pm_struct except Exception: pass except Exception as _e: try: print(f"TRACE adapter_combine_error: node={self.node_id} provider={provider} err={_e}") except Exception: pass else: # коротко-замкнём легаси-блок prompt_combine ниже pre_segments_raw = [] combine_raw = "" if combine_raw or (pre_segments_raw and len(pre_segments_raw) > 0): raw_segs = [s.strip() for s in combine_raw.split("&") if str(s or "").strip()] def _try_json(s: str) -> Any: """ Try to parse JSON from a string. Unwrap double-encoded JSON strings up to two passes and use a permissive fallback. Returns parsed object (dict/list/primitive) or None on failure. """ try: obj = json.loads(s) except Exception: # permissive fallback for odd control characters try: obj = json.loads(s, strict=False) # type: ignore[call-arg] except Exception: return None # If decoded into a string that itself looks like JSON — try to parse again up to 2 times. for _ in range(2): if isinstance(obj, str): st = obj.strip() if (st.startswith("{") and st.endswith("}")) or (st.startswith("[") and st.endswith("]")): try: obj = json.loads(st) continue except Exception: break break return obj # Нормализация в формат провайдера def _as_openai_messages(x: Any) -> List[Dict[str, Any]]: msgs: List[Dict[str, Any]] = [] try: # Dict inputs if isinstance(x, dict): if isinstance(x.get("messages"), list): # Already OpenAI-style return list(x.get("messages") or []) if isinstance(x.get("contents"), list): # Gemini -> OpenAI (text-only join) for c in (x.get("contents") or []): if not isinstance(c, dict): continue role_raw = str(c.get("role") or "user") role = "assistant" if role_raw == "model" else ("user" if role_raw not in {"user","assistant"} else role_raw) parts = c.get("parts") or [] text = "\n".join([str(p.get("text")) for p in parts if isinstance(p, dict) and isinstance(p.get("text"), str)]).strip() msgs.append({"role": role, "content": text}) return msgs # List inputs if isinstance(x, list): # Gemini contents list -> OpenAI messages if all(isinstance(c, dict) and "parts" in c for c in x): for c in x: role_raw = str(c.get("role") or "user") role = "assistant" if role_raw == "model" else ("user" if role_raw not in {"user","assistant"} else role_raw) parts = c.get("parts") or [] text = "\n".join([str(p.get("text")) for p in parts if isinstance(p, dict) and isinstance(p.get("text"), str)]).strip() msgs.append({"role": role, "content": text}) return msgs # OpenAI messages list already — normalize parts if needed if all(isinstance(m, dict) and "content" in m for m in x): out: List[Dict[str, Any]] = [] for m in x: role = m.get("role", "user") cont = m.get("content") if isinstance(cont, str): out.append({"role": role, "content": cont}) elif isinstance(cont, list): parts2: List[Dict[str, Any]] = [] for p in cont: if not isinstance(p, dict): continue if p.get("type") == "text": parts2.append({"type": "text", "text": str(p.get("text") or "")}) elif p.get("type") in {"image_url", "image"}: # try OpenAI image_url shape url = "" if isinstance(p.get("image_url"), dict): url = str((p.get("image_url") or {}).get("url") or "") elif "url" in p: url = str(p.get("url") or "") if url: parts2.append({"type": "image_url", "image_url": {"url": url}}) out.append({"role": role, "content": parts2 if parts2 else ""}) return out # Fallback: dump JSON as a single user message return [{"role":"user","content": json.dumps(x, ensure_ascii=False)}] # Primitive inputs or embedded JSON string if isinstance(x, str): try_obj = _try_json(x) if try_obj is not None: return _as_openai_messages(try_obj) return [{"role":"user","content": x}] return [{"role":"user","content": json.dumps(x, ensure_ascii=False)}] except Exception: return [{"role":"user","content": str(x)}] def _as_gemini_contents(x: Any) -> List[Dict[str, Any]]: cnts: List[Dict[str, Any]] = [] try: if isinstance(x, dict): if isinstance(x.get("contents"), list): return list(x.get("contents") or []) if isinstance(x.get("messages"), list): # OpenAI → Gemini for m in (x.get("messages") or []): if not isinstance(m, dict): continue role_raw = str(m.get("role") or "user") role = "model" if role_raw == "assistant" else "user" cont = m.get("content") parts: List[Dict[str, Any]] = [] if isinstance(cont, str): parts = [{"text": cont}] elif isinstance(cont, list): for p in cont: if not isinstance(p, dict): continue if p.get("type") == "text": parts.append({"text": str(p.get("text") or "")}) elif p.get("type") in {"image_url", "image"}: # Gemini doesn't accept external image URLs directly — keep as text fallback url = "" if isinstance(p.get("image_url"), dict): url = str((p.get("image_url") or {}).get("url") or "") elif "url" in p: url = str(p.get("url") or "") if url: parts.append({"text": url}) else: parts = [{"text": json.dumps(cont, ensure_ascii=False)}] cnts.append({"role": role, "parts": parts}) return cnts if isinstance(x, list): # Gemini contents list already if all(isinstance(c, dict) and "parts" in c for c in x): return list(x) # OpenAI messages list -> Gemini if all(isinstance(m, dict) and "content" in m for m in x): out: List[Dict[str, Any]] = [] for m in x: role_raw = str(m.get("role") or "user") role = "model" if role_raw == "assistant" else "user" cont = m.get("content") parts: List[Dict[str, Any]] = [] if isinstance(cont, str): parts = [{"text": cont}] elif isinstance(cont, list): for p in cont: if not isinstance(p, dict): continue if p.get("type") == "text": parts.append({"text": str(p.get("text") or "")}) elif p.get("type") in {"image_url", "image"}: url = "" if isinstance(p.get("image_url"), dict): url = str((p.get("image_url") or {}).get("url") or "") elif "url" in p: url = str(p.get("url") or "") if url: parts.append({"text": url}) else: parts = [{"text": json.dumps(cont, ensure_ascii=False)}] out.append({"role": role, "parts": parts}) return out # Fallback return [{"role":"user","parts":[{"text": json.dumps(x, ensure_ascii=False)}]}] if isinstance(x, str): try_obj = _try_json(x) if try_obj is not None: return _as_gemini_contents(try_obj) return [{"role":"user","parts":[{"text": x}]}] return [{"role":"user","parts":[{"text": json.dumps(x, ensure_ascii=False)}]}] except Exception: return [{"role":"user","parts":[{"text": str(x)}]}] def _as_claude_messages(x: Any) -> List[Dict[str, Any]]: msgs: List[Dict[str, Any]] = [] try: if isinstance(x, dict): # Dict with messages (OpenAI-like) if isinstance(x.get("messages"), list): x = x.get("messages") or [] # fallthrough to list mapping below elif isinstance(x.get("contents"), list): # Gemini -> Claude for c in (x.get("contents") or []): if not isinstance(c, dict): continue role_raw = str(c.get("role") or "user") role = "assistant" if role_raw == "model" else ("user" if role_raw not in {"user","assistant"} else role_raw) parts = c.get("parts") or [] text = "\n".join([str(p.get("text")) for p in parts if isinstance(p, dict) and isinstance(p.get("text"), str)]).strip() msgs.append({"role": role, "content":[{"type":"text","text": text}]}) return msgs if isinstance(x, list): # Gemini contents list -> Claude messages if all(isinstance(c, dict) and "parts" in c for c in x): for c in x: role_raw = str(c.get("role") or "user") role = "assistant" if role_raw == "model" else ("user" if role_raw not in {"user","assistant"} else role_raw) blocks: List[Dict[str, Any]] = [] for p in (c.get("parts") or []): if isinstance(p, dict) and isinstance(p.get("text"), str): txt = p.get("text").strip() if txt: blocks.append({"type":"text","text": txt}) msgs.append({"role": role, "content": blocks or [{"type":"text","text": ""}]}) return msgs # OpenAI messages list -> Claude if all(isinstance(m, dict) and "content" in m for m in x): out: List[Dict[str, Any]] = [] for m in x: role = m.get("role", "user") cont = m.get("content") blocks: List[Dict[str, Any]] = [] if isinstance(cont, str): blocks.append({"type":"text","text": cont}) elif isinstance(cont, list): for p in cont: if not isinstance(p, dict): continue if p.get("type") == "text": blocks.append({"type":"text","text": str(p.get("text") or "")}) elif p.get("type") in {"image_url", "image"}: url = "" if isinstance(p.get("image_url"), dict): url = str((p.get("image_url") or {}).get("url") or "") elif "url" in p: url = str(p.get("url") or "") if url: blocks.append({"type":"image","source":{"type":"url","url": url}}) else: blocks.append({"type":"text","text": json.dumps(cont, ensure_ascii=False)}) out.append({"role": role if role in {"user","assistant"} else "user", "content": blocks}) return out # Fallback return [{"role":"user","content":[{"type":"text","text": json.dumps(x, ensure_ascii=False)}]}] if isinstance(x, str): try_obj = _try_json(x) if try_obj is not None: return _as_claude_messages(try_obj) return [{"role":"user","content":[{"type":"text","text": x}]}] return [{"role":"user","content":[{"type":"text","text": json.dumps(x, ensure_ascii=False)}]}] except Exception: return [{"role":"user","content":[{"type":"text","text": str(x)}]}] # Helper: extract system text from mixed-provider fragments def _extract_sys_text_from_obj(x: Any) -> Optional[str]: """ Extract textual 'system' from provider-like fragments: - Claude: top-level 'system' (str or list of {type:'text', text:'...'}) - Gemini: 'systemInstruction' with parts[].text - OpenAI: messages[*] with role == 'system' (string content or parts[].text) Returns a string or None. """ try: # 1) Dict objects if isinstance(x, dict): # Gemini systemInstruction if "systemInstruction" in x: si = x.get("systemInstruction") def _parts_to_text(siobj: Any) -> str: try: parts = siobj.get("parts") or [] texts = [ str(p.get("text") or "") for p in parts if isinstance(p, dict) and isinstance(p.get("text"), str) and p.get("text").strip() ] return "\n".join([t for t in texts if t]).strip() except Exception: return "" if isinstance(si, dict): t = _parts_to_text(si) if t: return t if isinstance(si, list): texts = [] for p in si: if isinstance(p, dict) and isinstance(p.get("text"), str) and p.get("text").strip(): texts.append(p.get("text").strip()) t = "\n".join(texts).strip() if t: return t if isinstance(si, str) and si.strip(): return si.strip() # Claude system (string or blocks) if "system" in x and not ("messages" in x and isinstance(x.get("messages"), list)): sysv = x.get("system") if isinstance(sysv, str) and sysv.strip(): return sysv.strip() if isinstance(sysv, list): texts = [ str(b.get("text") or "") for b in sysv if isinstance(b, dict) and (b.get("type") == "text") and isinstance(b.get("text"), str) and b.get("text").strip() ] t = "\n".join([t for t in texts if t]).strip() if t: return t # OpenAI messages with role=system if isinstance(x.get("messages"), list): sys_msgs = [] for m in (x.get("messages") or []): try: if (str(m.get("role") or "").lower().strip() == "system"): cont = m.get("content") if isinstance(cont, str) and cont.strip(): sys_msgs.append(cont.strip()) elif isinstance(cont, list): for p in cont: if isinstance(p, dict) and p.get("type") == "text" and isinstance(p.get("text"), str) and p.get("text").strip(): sys_msgs.append(p.get("text").strip()) except Exception: continue if sys_msgs: return "\n\n".join(sys_msgs).strip() # 2) List objects if isinstance(x, list): # OpenAI messages list with role=system if all(isinstance(m, dict) and "role" in m for m in x): sys_msgs = [] for m in x: try: if (str(m.get("role") or "").lower().strip() == "system"): cont = m.get("content") if isinstance(cont, str) and cont.strip(): sys_msgs.append(cont.strip()) elif isinstance(cont, list): for p in cont: if isinstance(p, dict) and p.get("type") == "text" and isinstance(p.get("text"), str) and p.get("text").strip(): sys_msgs.append(p.get("text").strip()) except Exception: continue if sys_msgs: return "\n\n".join(sys_msgs).strip() # Gemini 'contents' list: try to read systemInstruction from incoming JSON snapshot if all(isinstance(c, dict) and "parts" in c for c in x): try: inc = (render_ctx.get("incoming") or {}).get("json") or {} si = inc.get("systemInstruction") if si is not None: return _extract_sys_text_from_obj({"systemInstruction": si}) except Exception: pass return None except Exception: return None # Фильтр пустых сообщений/частей def _filter_gemini(arr: List[Dict[str, Any]]) -> List[Dict[str, Any]]: out: List[Dict[str, Any]] = [] for it in (arr or []): if not isinstance(it, dict): continue parts = it.get("parts") or [] norm_parts = [] for p in parts: if isinstance(p, dict): t = p.get("text") if isinstance(t, str) and t.strip(): norm_parts.append({"text": t}) elif "inline_data" in p or "inlineData" in p: norm_parts.append(p) # изображения пропускаем как есть if norm_parts: out.append({"role": it.get("role","user"), "parts": norm_parts}) return out def _filter_openai(arr: List[Dict[str, Any]]) -> List[Dict[str, Any]]: out: List[Dict[str, Any]] = [] for m in (arr or []): if not isinstance(m, dict): continue c = m.get("content") if isinstance(c, str) and c.strip(): out.append({"role": m.get("role","user"), "content": c}) elif isinstance(c, list): parts = [] for p in c: if isinstance(p, dict) and p.get("type") == "text": txt = str(p.get("text") or "") if txt.strip(): parts.append({"type":"text","text": txt}) if parts: out.append({"role": m.get("role","user"), "content": parts}) return out def _filter_claude(arr: List[Dict[str, Any]]) -> List[Dict[str, Any]]: out: List[Dict[str, Any]] = [] for m in (arr or []): if not isinstance(m, dict): continue blocks = m.get("content") if isinstance(blocks, list): norm = [] for b in blocks: if isinstance(b, dict) and b.get("type") == "text": txt = str(b.get("text") or "") if txt.strip(): norm.append({"type":"text","text": txt}) if norm: out.append({"role": m.get("role","user"), "content": norm}) return out # Построим массивы по сегментам в заданном порядке. # Обработка [[PROMPT]] как спец.сегмента сохранив роль/части из pm_struct. # Поддержка @pos=... только внутри текущего собираемого массива (messages/contents). seg_items: List[Any] = [] # Снимок blocks как provider-структуры blocks_struct = dict(pm_struct) def _insert_items(base: List[Any], items: List[Any], pos_spec: Optional[str]) -> List[Any]: if not items: return base if not pos_spec or pos_spec.lower() == "append": base.extend(items) return base if pos_spec.lower() == "prepend": return list(items) + base # индекс try: idx = int(pos_spec) if idx < 0: idx = len(base) + idx if idx < 0: idx = 0 if idx > len(base): idx = len(base) return base[:idx] + list(items) + base[idx:] except Exception: base.extend(items) return base # парсинг директивы @pos= import re as _re2 def _split_pos_spec(s: str) -> tuple[str, Optional[str]]: m = _re2.search(r"@pos\s*=\s*(prepend|append|-?\d+)\s*$", s, flags=_re2.IGNORECASE) if not m: return s.strip(), None body = s[:m.start()].strip() return body, m.group(1).strip().lower() if provider in {"gemini", "gemini_image"}: built: List[Dict[str, Any]] = [] sys_texts: List[str] = [] # Preprocess-inserted segments (prompt_preprocess) for _pre in pre_segments_raw: try: _obj = _pre.get("obj") items = _as_gemini_contents(_obj) items = _filter_gemini(items) built = _insert_items(built, items, _pre.get("pos")) try: sx = _extract_sys_text_from_obj(_obj) if isinstance(sx, str) and sx.strip(): sys_texts.append(sx.strip()) except Exception: pass except Exception: pass for raw_seg in raw_segs: body_seg, pos_spec = _split_pos_spec(raw_seg) if body_seg == "[[PROMPT]]": items = _filter_gemini(list(blocks_struct.get("contents", []) or [])) built = _insert_items(built, items, pos_spec) continue m_pre = _VAR_MACRO_RE.fullmatch(body_seg) if m_pre: _p = (m_pre.group(1) or "").strip() try: if _p in pre_var_paths: # Skip duplicate var segment - already inserted via prompt_preprocess (filtered) continue except Exception: pass resolved = render_template_simple(body_seg, render_ctx, render_ctx.get("OUT") or {}) obj = _try_json(resolved) # provider guess + system extract for cross-provider combine try: pg = detect_vendor(obj if isinstance(obj, dict) else {}) print(f"DEBUG: prompt_combine seg provider_guess={pg} -> target=gemini pos={pos_spec}") except Exception: pass items = _as_gemini_contents(obj if obj is not None else resolved) items = _filter_gemini(items) built = _insert_items(built, items, pos_spec) try: sx = _extract_sys_text_from_obj(obj) if obj is not None else None if isinstance(sx, str) and sx.strip(): sys_texts.append(sx.strip()) except Exception: pass # Если ни один сегмент не был [[PROMPT]] и массив пуст — оставим исходные blocks if not built: built = _filter_gemini(list(blocks_struct.get("contents", []) or [])) # Merge systemInstruction: PROMPT blocks + gathered sys_texts existing_si = blocks_struct.get("systemInstruction") parts = [] if isinstance(existing_si, dict) and isinstance(existing_si.get("parts"), list): parts = list(existing_si.get("parts") or []) for s in sys_texts: parts.append({"text": s}) new_si = {"parts": parts} if parts else existing_si pm_struct = {"contents": built, "systemInstruction": new_si, "system_text": blocks_struct.get("system_text")} elif provider in {"openai"}: built2: List[Dict[str, Any]] = [] sys_texts: List[str] = [] # Preprocess-inserted segments (prompt_preprocess) for _pre in pre_segments_raw: try: _obj = _pre.get("obj") items = _as_openai_messages(_obj) items = _filter_openai(items) built2 = _insert_items(built2, items, _pre.get("pos")) try: sx = _extract_sys_text_from_obj(_obj) if isinstance(sx, str) and sx.strip(): sys_texts.append(sx.strip()) except Exception: pass except Exception: pass for raw_seg in raw_segs: body_seg, pos_spec = _split_pos_spec(raw_seg) if body_seg == "[[PROMPT]]": items = _filter_openai(list(blocks_struct.get("messages", []) or [])) built2 = _insert_items(built2, items, pos_spec) continue m_pre = _VAR_MACRO_RE.fullmatch(body_seg) if m_pre: _p = (m_pre.group(1) or "").strip() try: if _p in pre_var_paths: # Skip duplicate var segment - already inserted via prompt_preprocess (filtered) continue except Exception: pass resolved = render_template_simple(body_seg, render_ctx, render_ctx.get("OUT") or {}) obj = _try_json(resolved) try: pg = detect_vendor(obj if isinstance(obj, dict) else {}) print(f"DEBUG: prompt_combine seg provider_guess={pg} -> target=openai pos={pos_spec}") except Exception: pass items = _as_openai_messages(obj if obj is not None else resolved) items = _filter_openai(items) built2 = _insert_items(built2, items, pos_spec) # collect only top-level system/systemInstruction (not role=system in messages) try: sx = _extract_sys_text_from_obj(obj) if obj is not None else None if isinstance(sx, str) and sx.strip(): sys_texts.append(sx.strip()) except Exception: pass if not built2: built2 = _filter_openai(list(blocks_struct.get("messages", []) or [])) # Prepend system messages derived from sys_texts if sys_texts: sys_msgs = [{"role": "system", "content": s} for s in sys_texts if s] if sys_msgs: built2 = sys_msgs + built2 # keep system_text for UI/debug st0 = blocks_struct.get("system_text") or "" st = "\n\n".join([t for t in [st0] + sys_texts if isinstance(t, str) and t.strip()]) pm_struct = {"messages": built2, "system_text": st} else: # claude built3: List[Dict[str, Any]] = [] sys_texts: List[str] = [] # Preprocess-inserted segments (prompt_preprocess) for _pre in pre_segments_raw: try: _obj = _pre.get("obj") items = _as_claude_messages(_obj) items = _filter_claude(items) built3 = _insert_items(built3, items, _pre.get("pos")) try: sx = _extract_sys_text_from_obj(_obj) if isinstance(sx, str) and sx.strip(): sys_texts.append(sx.strip()) except Exception: pass except Exception: pass for raw_seg in raw_segs: body_seg, pos_spec = _split_pos_spec(raw_seg) if body_seg == "[[PROMPT]]": items = _filter_claude(list(blocks_struct.get("messages", []) or [])) built3 = _insert_items(built3, items, pos_spec) continue m_pre = _VAR_MACRO_RE.fullmatch(body_seg) if m_pre: _p = (m_pre.group(1) or "").strip() try: if _p in pre_var_paths: # Skip duplicate var segment - already inserted via prompt_preprocess (filtered) continue except Exception: pass resolved = render_template_simple(body_seg, render_ctx, render_ctx.get("OUT") or {}) obj = _try_json(resolved) try: pg = detect_vendor(obj if isinstance(obj, dict) else {}) print(f"DEBUG: prompt_combine seg provider_guess={pg} -> target=claude pos={pos_spec}") except Exception: pass items = _as_claude_messages(obj if obj is not None else resolved) items = _filter_claude(items) built3 = _insert_items(built3, items, pos_spec) try: sx = _extract_sys_text_from_obj(obj) if obj is not None else None if isinstance(sx, str) and sx.strip(): sys_texts.append(sx.strip()) except Exception: pass if not built3: built3 = _filter_claude(list(blocks_struct.get("messages", []) or [])) # Merge system blocks from PROMPT blocks + gathered sys_texts existing_sys = blocks_struct.get("system") or [] sys_blocks = [] if isinstance(existing_sys, list): sys_blocks.extend(existing_sys) st0 = blocks_struct.get("system_text") or "" # Ensure PROMPT system_text from blocks is included as a Claude system block if isinstance(st0, str) and st0.strip(): sys_blocks.append({"type": "text", "text": st0}) for s in sys_texts: sys_blocks.append({"type": "text", "text": s}) st = "\n\n".join([t for t in [st0] + sys_texts if isinstance(t, str) and t.strip()]) # New: optional Claude mode to omit top-level "system" claude_no_system = False try: claude_no_system = bool((self.config or {}).get("claude_no_system", False)) except Exception: claude_no_system = False if claude_no_system: # Prepend system text as a user message instead of top-level system if st: built3 = [{"role": "user", "content": [{"type": "text", "text": st}]}] + built3 pm_struct = {"messages": built3, "system_text": st} else: # Prefer top-level system as plain string (proxy compatibility) pm_struct = {"messages": built3, "system_text": st} # Prefer array of system blocks when possible; fallback to single text block if sys_blocks: pm_struct["system"] = sys_blocks elif st: pm_struct["system"] = [{"type": "text", "text": st}] # SSE метрика try: trace_fn = context.get("_trace") if trace_fn: after_cnt = (len(pm_struct.get("messages", [])) if provider in {"openai","claude"} else len(pm_struct.get("contents", []))) await trace_fn({ "event": "prompt_merge", "node_id": self.node_id, "node_type": self.type_name, "provider": provider, "segments": len(raw_segs), "before": (len(blocks_struct.get("messages", [])) if provider in {"openai","claude"} else len(blocks_struct.get("contents", []))), "after": after_cnt, "ts": int(time.time()*1000), }) except Exception: pass # Единый JSON-фрагмент PROMPT для шаблонов: [[PROMPT]] prompt_fragment = "" try: if adapter: prompt_fragment = adapter.prompt_fragment(pm_struct, self.config or {}) else: if provider == "openai": prompt_fragment = '"messages": ' + json.dumps(pm_struct.get("messages", []), ensure_ascii=False) elif provider in {"gemini", "gemini_image"}: parts = [] contents = pm_struct.get("contents") if contents is not None: parts.append('"contents": ' + json.dumps(contents, ensure_ascii=False)) sysi = pm_struct.get("systemInstruction") if sysi is not None: parts.append('"systemInstruction": ' + json.dumps(sysi, ensure_ascii=False)) prompt_fragment = ", ".join(parts) elif provider == "claude": parts = [] # Учитываем флаг совместимости: при claude_no_system не добавляем top-level "system" claude_no_system = False try: claude_no_system = bool((self.config or {}).get("claude_no_system", False)) except Exception: claude_no_system = False if not claude_no_system: # Предпочитаем массив блоков system, если он есть; иначе строковый system_text sys_val = pm_struct.get("system", None) if sys_val is None: sys_val = pm_struct.get("system_text") if sys_val: parts.append('"system": ' + json.dumps(sys_val, ensure_ascii=False)) msgs = pm_struct.get("messages") if msgs is not None: parts.append('"messages": ' + json.dumps(msgs, ensure_ascii=False)) prompt_fragment = ", ".join(parts) except Exception: # noqa: BLE001 prompt_fragment = "" render_ctx["PROMPT"] = prompt_fragment # Render helper с поддержкой [[VAR]], [[OUT]] и {{ ... }} def render(s: str) -> str: return render_template_simple(s or "", render_ctx, render_ctx.get("OUT") or {}) # Рендер endpoint с макросами/шаблонами endpoint = render(endpoint_tmpl) # Формируем тело ТОЛЬКО из template/[[PROMPT]] (без сырого payload/входов). # Больше НИКАКОГО фоллбэка на unified-построение: если шаблон невалиден — это ошибка ноды. try: rendered = render(template) # DEBUG: печать отрендеренного шаблона с номерами строк для точной диагностики JSONDecodeError try: _lines = rendered.splitlines() _preview = "\n".join(f"{i+1:03d}: {_lines[i]}" for i in range(min(len(_lines), 120))) print(f"DEBUG: ProviderCallNode rendered_template node={self.node_id} provider={provider}\\n{_preview}") except Exception: try: print(f"DEBUG: ProviderCallNode rendered_template(node={self.node_id}, provider={provider}) len={len(rendered)}") except Exception: pass payload = json.loads(rendered) except Exception as exc: # noqa: BLE001 raise ExecutionError(f"ProviderCall template invalid JSON: {exc}") # Заголовки — полностью из редактируемого JSON с макросами try: headers_src = render(headers_json) if headers_json else "{}" headers = json.loads(headers_src) if headers_src else {} if not isinstance(headers, dict): raise ValueError("headers must be a JSON object") # Drop headers with empty values (proxy compatibility, e.g. "anthropic-beta": "") try: headers = {k: v for k, v in headers.items() if v is not None and (not isinstance(v, str) or v.strip() != "")} except Exception: pass except Exception as exc: # noqa: BLE001 raise ExecutionError(f"ProviderCall headers invalid JSON: {exc}") # Итоговый URL if not base_url.startswith(("http://", "https://")): base_url = "http://" + base_url url = endpoint if endpoint.startswith("http") else urljoin(base_url.rstrip('/') + '/', endpoint.lstrip('/')) # Debug logs to validate config selection and payload # Brute request/response logging (request body sanitized like Burp) try: final_headers = {"Content-Type": "application/json", **headers} print("===== ProviderCall REQUEST BEGIN =====") print(f"node={self.node_id} type={self.type_name} provider={provider}") print(f"URL: {url}") try: print("Headers:") print(json.dumps(final_headers, ensure_ascii=False, indent=2)) except Exception: print(f"Headers(raw): {final_headers}") try: san_payload = _sanitize_b64_for_log(payload, max_len=180) print("Body JSON:") print(json.dumps(san_payload, ensure_ascii=False, indent=2)) except Exception: print(f"Body(raw): {payload}") print("===== ProviderCall REQUEST END =====") except Exception: pass # SSE: http_req (как в Burp) req_id = f"{self.node_id}-{int(time.time()*1000)}" # Register original (untrimmed) request details for manual resend try: pipeline_id = str((context.get("meta") or {}).get("id", "pipeline_editor")) except Exception: pipeline_id = "pipeline_editor" try: register_http_request(req_id, { "pipeline_id": pipeline_id, "node_id": self.node_id, "node_type": self.type_name, "provider": provider, "method": "POST", "url": url, "headers": dict(final_headers), "body_json": payload, # untrimmed original payload }) except Exception: pass try: trace_fn = context.get("_trace") if trace_fn: await trace_fn({ "event": "http_req", "node_id": self.node_id, "node_type": self.type_name, "provider": provider, "req_id": req_id, "method": "POST", "url": url, "headers": final_headers, "body_text": json.dumps(_sanitize_b64_for_log(payload, max_len=180), ensure_ascii=False, indent=2), "ts": int(time.time() * 1000), }) except Exception: pass # Timeout from run-meta (seconds); fallback to 60 try: timeout_sec = float((context.get("meta") or {}).get("http_timeout_sec", 60) or 60) except Exception: timeout_sec = 60.0 st: Optional[int] = None async with build_client(timeout=timeout_sec) as client: body_bytes = json.dumps(payload, ensure_ascii=False).encode("utf-8") # Cooperative cancel pre-check (avoid starting new HTTP on abort) try: pipeline_id = str((context.get("meta") or {}).get("id", "pipeline_editor")) except Exception: pipeline_id = "pipeline_editor" try: if is_cancelled(pipeline_id) and get_cancel_mode(pipeline_id) == "abort": try: print(f"TRACE http_cancel_pre: {self.node_id} abort before request") except Exception: pass raise ExecutionError("Cancelled by user (abort)") except Exception: pass async def _do_post(): return await client.post(url, content=body_bytes, headers=final_headers) # Await HTTP with cooperative cancel/abort handling resp = await _await_coro_with_cancel(_do_post(), pipeline_id) # Do not raise_for_status: keep body/logs on 4xx/5xx try: print("===== ProviderCall RESPONSE BEGIN =====") print(f"node={self.node_id} type={self.type_name} provider={provider}") print(f"Status: {resp.status_code}") try: print("Headers:") print(json.dumps(dict(resp.headers), ensure_ascii=False, indent=2)) except Exception: try: print(f"Headers(raw): {dict(resp.headers)}") except Exception: print("Headers(raw): ") # Печатаем JSON тела с ТРИММИНГОМ ТОЛЬКО base64 строк, оставляя остальную структуру нетронутой try: raw_obj = _safe_response_json(resp) import re as _re def _is_b64ish(s: str) -> bool: try: if not isinstance(s, str) or len(s) < 128: return False # быстрый тест на base64 (разрешаем переводы строк) return bool(_re.fullmatch(r"[A-Za-z0-9+/=\r\n]+", s)) except Exception: return False def _trim_b64_in_obj(x): if isinstance(x, dict): out = {} for k, v in x.items(): if isinstance(v, str) and "data" in str(k).lower() and _is_b64ish(v) and len(v) > 256: out[k] = v[:180] + f"... (trimmed {len(v)-180})" else: out[k] = _trim_b64_in_obj(v) return out if isinstance(x, list): return [_trim_b64_in_obj(i) for i in x] return x sanitized_obj = _trim_b64_in_obj(raw_obj if isinstance(raw_obj, (dict, list)) else {}) body_text = json.dumps(sanitized_obj if sanitized_obj else raw_obj, ensure_ascii=False, indent=2) except Exception: body_text = _safe_response_text(resp) print("Body JSON:") print(body_text) print("===== ProviderCall RESPONSE END =====") except Exception: body_text = "" pass try: data = _safe_response_json(resp) except Exception: data = {"error": "Failed to decode JSON from upstream", "text": _safe_response_text(resp)} # Построим данные для панели Data: # - images_data: полный список inline картинок (mime+base64, НЕ обрезанные) # - data_preview: краткая сводка, если картинок нет или UI не может их отрисовать try: def _collect_images_http(obj: Any) -> List[Dict[str, str]]: imgs: List[Dict[str, str]] = [] def walk(o: Any) -> None: if isinstance(o, dict): # Gemini: inlineData / inline_data if isinstance(o.get("inlineData"), dict): idat = o.get("inlineData") or {} b64 = str(idat.get("data") or "") mime = str(idat.get("mimeType") or idat.get("mime_type") or "image/png") if b64: imgs.append({"mime": mime, "data": b64}) if isinstance(o.get("inline_data"), dict): idat = o.get("inline_data") or {} b64 = str(idat.get("data") or "") mime = str(idat.get("mimeType") or idat.get("mime_type") or "image/png") if b64: imgs.append({"mime": mime, "data": b64}) # Claude style if (o.get("type") == "image") and isinstance(o.get("source"), dict): src = o.get("source") or {} if (src.get("type") or src.get("source_type")) in {"base64", "inline"}: b64 = str(src.get("data") or "") mime = str(src.get("media_type") or src.get("mediaType") or "image/png") if b64: imgs.append({"mime": mime, "data": b64}) for v in o.values(): walk(v) elif isinstance(o, list): for v in o: walk(v) walk(obj) return imgs def _collect_image_summaries_http(obj: Any) -> List[str]: info: List[str] = [] def walk(o: Any, path: str = "") -> None: if isinstance(o, dict): if isinstance(o.get("inlineData"), dict): idat = o.get("inlineData") or {} b64 = str(idat.get("data") or "") mime = str(idat.get("mimeType") or idat.get("mime_type") or "") info.append(f"{path}/inlineData mime={mime or '?'} b64_len={len(b64)}") if isinstance(o.get("inline_data"), dict): idat = o.get("inline_data") or {} b64 = str(idat.get("data") or "") mime = str(idat.get("mimeType") or idat.get("mime_type") or "") info.append(f"{path}/inline_data mime={mime or '?'} b64_len={len(b64)}") if (o.get("type") == "image") and isinstance(o.get("source"), dict): src = o.get("source") or {} if (src.get("type") or src.get("source_type")) in {"base64", "inline"}: b64 = str(src.get("data") or "") mime = str(src.get("media_type") or src.get("mediaType") or "") info.append(f"{path}/source mime={mime or '?'} b64_len={len(b64)}") for k, v in o.items(): walk(v, path + (("." + k) if path else k)) elif isinstance(o, list): for i, v in enumerate(o): walk(v, path + f"[{i}]") walk(obj, "") return info images_data = _collect_images_http(data) _img_lines_http = _collect_image_summaries_http(data) data_preview = "" if _img_lines_http: data_preview = "images: " + str(len(_img_lines_http)) + "\n" + "\n".join(_img_lines_http[:12]) except Exception: images_data = [] data_preview = "" # SSE: http_resp try: trace_fn = context.get("_trace") if trace_fn: await trace_fn({ "event": "http_resp", "node_id": self.node_id, "node_type": self.type_name, "provider": provider, "req_id": req_id, "status": int(resp.status_code), "headers": dict(resp.headers), "body_text": body_text if isinstance(body_text, str) else str(body_text), "data_preview": data_preview, "images": images_data, "ts": int(time.time() * 1000), }) except Exception: pass try: st = int(resp.status_code) except Exception: st = None # Извлечение текста: приоритет — пресет ноды -> кастомн. поля ноды -> глобальные meta try: meta_opts = (context.get("meta") or {}) presets = meta_opts.get("text_extract_presets") or [] cfg = self.config or {} strategy = None json_path = None join_sep = None # 1) Пресет по id pid = str(cfg.get("text_extract_preset_id") or "").strip() if pid: try: pr = next((x for x in presets if isinstance(x, dict) and str(x.get("id", "")) == pid), None) except Exception: pr = None if pr: strategy = str(pr.get("strategy") or "auto") json_path = str(pr.get("json_path") or "") join_sep = str(pr.get("join_sep") or "\n") # 2) Кастомные поля ноды (если задано что-то из набора) if not strategy and (cfg.get("text_extract_strategy") is not None or cfg.get("text_extract_json_path") is not None or cfg.get("text_join_sep") is not None): strategy = str(cfg.get("text_extract_strategy") or "auto") json_path = str(cfg.get("text_extract_json_path") or "") join_sep = str(cfg.get("text_join_sep") or "\n") # 3) Глобальные метаданные запуска if not strategy: strategy = str(meta_opts.get("text_extract_strategy", "auto") or "auto") json_path = str(meta_opts.get("text_extract_json_path", "") or "") join_sep = str(meta_opts.get("text_join_sep", "\n") or "\n") except Exception: strategy, json_path, join_sep = "auto", "", "\n" text = _extract_text_for_out(data, strategy, provider, json_path, join_sep) # Если текст пуст (например, пришли только inlineData/base64-картинки) — сформируем краткое резюме картинок, # чтобы панель Data не оставалась пустой. if not text: try: def _collect_image_summaries(obj: Any) -> List[str]: info: List[str] = [] def walk(o: Any, path: str = "") -> None: if isinstance(o, dict): # Gemini: inlineData / inline_data if isinstance(o.get("inlineData"), dict): idat = o.get("inlineData") or {} b64 = str(idat.get("data") or "") mime = str(idat.get("mimeType") or idat.get("mime_type") or "") info.append(f"{path}/inlineData mime={mime or '?'} b64_len={len(b64)}") if isinstance(o.get("inline_data"), dict): idat = o.get("inline_data") or {} b64 = str(idat.get("data") or "") mime = str(idat.get("mimeType") or idat.get("mime_type") or "") info.append(f"{path}/inline_data mime={mime or '?'} b64_len={len(b64)}") # Claude: {"type":"image","source":{"type":"base64","media_type":..., "data":...}} if (o.get("type") == "image") and isinstance(o.get("source"), dict): src = o.get("source") or {} if (src.get("type") or src.get("source_type")) in {"base64", "inline"}: b64 = str(src.get("data") or "") mime = str(src.get("media_type") or src.get("mediaType") or "") info.append(f"{path}/source mime={mime or '?'} b64_len={len(b64)}") for k, v in o.items(): walk(v, path + (("." + k) if path else k)) elif isinstance(o, list): for i, v in enumerate(o): walk(v, path + f"[{i}]") walk(obj, "") return info img_lines = _collect_image_summaries(data) if img_lines: text = "images: " + str(len(img_lines)) + "\n" + "\n".join(img_lines[:12]) except Exception: pass # Подробный SSE-лог завершения ProviderCall try: trace_fn = context.get("_trace") if trace_fn: # Compute destination macros for extracted text try: to_path = f"OUT.{self.node_id}.response_text" macro_braces = f"{{{{ OUT.{self.node_id}.response_text }}}}" alias_macro = "" m = re.match(r"^n(\d+)$", str(self.node_id)) if m: alias_macro = f"[[OUT{int(m.group(1))}]]" except Exception: to_path = f"OUT.{self.node_id}.response_text" macro_braces = f"{{{{ OUT.{self.node_id}.response_text }}}}" alias_macro = "" await trace_fn({ "event": "provider_done", "node_id": self.node_id, "node_type": self.type_name, "provider": provider, "url": url, "req_id": req_id, "status": int(st) if st is not None else None, "text_len": int(len(text or "")), "extracted_text": text or "", "strategy": strategy, "json_path": json_path or "", "join_sep": join_sep or "\n", "to_path": to_path, "to_macro_outx": alias_macro, "to_macro_braces": macro_braces, "ts": int(time.time() * 1000), }) except Exception: pass return {"result": data, "response_text": text or ""} class RawForwardNode(Node): type_name = "RawForward" async def run(self, inputs: Dict[str, Any], context: Dict[str, Any]) -> Dict[str, Any]: """ Прямой форвард входящего запроса на апстрим: - base_url/override_path/extra_headers поддерживают макросы [[...]] и {{ ... }} - По умолчанию пробрасываем входящие заголовки (кроме Host/Content-Length), затем применяем extra_headers поверх. - Тело берём из incoming.json (если есть), иначе пытаемся использовать текст/байты. - Эмитим SSE события http_req/http_resp для панели логов. """ # While-loop wrapper: if while_expr is set or ignore_errors enabled, route through helper (single-run when expr empty) try: cfg = self.config or {} except Exception: cfg = {} try: _while_expr = str(cfg.get("while_expr") or "").strip() except Exception: _while_expr = "" try: _ignore = bool(cfg.get("ignore_errors", False)) except Exception: _ignore = False if not (context.get("_in_while") or False) and (_while_expr or _ignore): return await _rawforward_run_with_while(self, inputs, context) incoming = context.get("incoming", {}) or {} raw_payload = incoming.get("json") # Optional sleep before forwarding (UI-configured, milliseconds) try: sleep_ms = int(self.config.get("sleep_ms") or 0) except Exception: sleep_ms = 0 if sleep_ms > 0: # Notify UI to show "sleep" state for this node try: trace_fn = context.get("_trace") if trace_fn: await trace_fn({ "event": "node_sleep", "node_id": self.node_id, "node_type": self.type_name, "sleep_ms": int(sleep_ms), "ts": int(time.time() * 1000), }) except Exception: pass try: await asyncio.sleep(max(0.0, sleep_ms / 1000.0)) except Exception: pass # Конфиг с поддержкой макросов base_url: Optional[str] = self.config.get("base_url") override_path: Optional[str] = self.config.get("override_path") out_map_for_macros = context.get("OUT") or {} if base_url: base_url = render_template_simple(str(base_url), context, out_map_for_macros) if override_path: override_path = render_template_simple(str(override_path), context, out_map_for_macros) # Автодетекция вендора для базового URL если base_url не задан if not base_url: vendor = detect_vendor(raw_payload) base_url = None try: base_url = _adapter_default_base_url_for(vendor) except Exception: base_url = None if not base_url: if vendor == "openai": base_url = "https://api.openai.com" elif vendor == "claude": base_url = "https://api.anthropic.com" elif vendor == "gemini": base_url = "https://generativelanguage.googleapis.com" if not base_url: raise ExecutionError( f"Node {self.node_id} ({self.type_name}): 'base_url' is not configured and vendor could not be detected." ) if not str(base_url).startswith(("http://", "https://")): base_url = "http://" + str(base_url) path = override_path or incoming.get("path") or "/" query = incoming.get("query") path_with_qs = f"{path}?{query}" if query else str(path) url = urljoin(str(base_url).rstrip("/") + "/", str(path_with_qs).lstrip("/")) # Заголовки: passthrough + extra_headers(JSON) passthrough_headers: bool = bool(self.config.get("passthrough_headers", True)) extra_headers_json: str = self.config.get("extra_headers") or "{}" try: extra_headers_src = render_template_simple(extra_headers_json, context, out_map_for_macros) if extra_headers_json else "{}" extra_headers = json.loads(extra_headers_src) if extra_headers_src else {} if not isinstance(extra_headers, dict): raise ValueError("extra_headers must be an object") except Exception as exc: # noqa: BLE001 raise ExecutionError(f"RawForward extra_headers invalid JSON: {exc}") headers: Dict[str, str] = {} if passthrough_headers: inc_headers = incoming.get("headers") or {} for k, v in inc_headers.items(): # Не пробрасываем управляющие заголовки, которые рассчитает httpx/сервер if k and k.lower() not in {"host", "content-length"}: headers[k] = v # extra_headers перекрывают проброс try: headers.update(extra_headers) except Exception: pass # Нормализация: защитимся от повторного наличия host/content-length после update for k in list(headers.keys()): kl = k.lower() if kl in {"host", "content-length"}: try: headers.pop(k, None) except Exception: pass # Метод method = str(incoming.get("method") or "POST").upper().strip() or "POST" # Тело запроса body_text = "" body_bytes: bytes = b"" if raw_payload is not None: # JSON — сериализуем явно как UTF‑8 try: body_text = json.dumps(raw_payload, ensure_ascii=False, indent=2) except Exception: try: body_text = str(raw_payload) except Exception: body_text = "" try: body_bytes = json.dumps(raw_payload, ensure_ascii=False).encode("utf-8") except Exception: body_bytes = (body_text or "").encode("utf-8", errors="ignore") # Если Content-Type не задан — выставим JSON if "content-type" not in {k.lower() for k in headers.keys()}: headers["Content-Type"] = "application/json" else: # Попробуем текст/байты из incoming raw_bytes = incoming.get("body_bytes") or incoming.get("bytes") raw_text = incoming.get("body_text") or incoming.get("text") if isinstance(raw_bytes, (bytes, bytearray)): body_bytes = bytes(raw_bytes) try: body_text = body_bytes.decode("utf-8", errors="ignore") except Exception: body_text = "" elif raw_text is not None: body_text = str(raw_text) try: body_bytes = body_text.encode("utf-8") except Exception: body_bytes = (body_text or "").encode("utf-8", errors="ignore") else: body_text = "" body_bytes = b"" # Таймаут из метаданных запуска try: timeout_sec = float((context.get("meta") or {}).get("http_timeout_sec", 60) or 60) except Exception: timeout_sec = 60.0 # Диагностический вывод полной заявки/ответа (request body sanitized) try: print("===== RawForward REQUEST BEGIN =====") print(f"node={self.node_id} type={self.type_name}") print(f"Method: {method}") print(f"URL: {url}") try: print("Headers:") print(json.dumps(headers, ensure_ascii=False, indent=2)) except Exception: print(f"Headers(raw): {headers}") print("Body:") try: san_body_text = _sanitize_json_string_for_log(body_text, max_len=180) except Exception: san_body_text = body_text print(san_body_text) print("===== RawForward REQUEST END =====") except Exception: pass # SSE: http_req req_id = f"{self.node_id}-{int(time.time()*1000)}" # Register original (untrimmed) request details for manual resend try: pipeline_id = str((context.get("meta") or {}).get("id", "pipeline_editor")) except Exception: pipeline_id = "pipeline_editor" try: reg_info: Dict[str, Any] = { "pipeline_id": pipeline_id, "node_id": self.node_id, "node_type": self.type_name, "method": method, "url": url, "headers": dict(headers), } if raw_payload is not None: reg_info["body_json"] = raw_payload # original JSON body # Always keep original textual/bytes preview for non-JSON reg_info["body_text"] = body_text try: reg_info["body_bytes_len"] = int(len(body_bytes or b"")) except Exception: pass register_http_request(req_id, reg_info) except Exception: pass try: trace_fn = context.get("_trace") if trace_fn: await trace_fn({ "event": "http_req", "node_id": self.node_id, "node_type": self.type_name, "req_id": req_id, "method": method, "url": url, "headers": headers, "body_text": san_body_text if isinstance(san_body_text, str) else body_text, "ts": int(time.time() * 1000), }) except Exception: pass # Отправка async with build_client(timeout=timeout_sec) as client: # Для GET/HEAD обычно не отправляем body send_content = None if method in {"GET", "HEAD"} else body_bytes # Cooperative cancel pre-check (avoid starting new HTTP on abort) try: pipeline_id = str((context.get("meta") or {}).get("id", "pipeline_editor")) except Exception: pipeline_id = "pipeline_editor" try: if is_cancelled(pipeline_id) and get_cancel_mode(pipeline_id) == "abort": try: print(f"TRACE http_cancel_pre: {self.node_id} abort before request") except Exception: pass raise ExecutionError("Cancelled by user (abort)") except Exception: pass async def _do_req(): return await client.request(method, url, headers=headers, content=send_content) # Await HTTP with cooperative cancel/abort handling resp = await _await_coro_with_cancel(_do_req(), pipeline_id) # Ответ: лог/печать try: print("===== RawForward RESPONSE BEGIN =====") print(f"node={self.node_id} type={self.type_name}") print(f"Status: {resp.status_code}") try: print("Headers:") print(json.dumps(dict(resp.headers), ensure_ascii=False, indent=2)) except Exception: try: print(f"Headers(raw): {dict(resp.headers)}") except Exception: print("Headers(raw): ") try: resp_text = _safe_response_text(resp) except Exception: resp_text = "" print("Body Text:") print(resp_text) print("===== RawForward RESPONSE END =====") except Exception: resp_text = "" # SSE: http_resp try: trace_fn = context.get("_trace") if trace_fn: await trace_fn({ "event": "http_resp", "node_id": self.node_id, "node_type": self.type_name, "req_id": req_id, "status": int(resp.status_code), "headers": dict(resp.headers), "body_text": resp_text if isinstance(resp_text, str) else str(resp_text), "ts": int(time.time() * 1000), }) except Exception: pass # Разбор результата try: data = _safe_response_json(resp) except Exception: data = {"error": "Failed to decode JSON from upstream", "text": resp_text} # Извлечение текста: приоритет — пресет ноды -> кастомные поля ноды -> глобальные meta. try: meta_opts = (context.get("meta") or {}) presets = meta_opts.get("text_extract_presets") or [] cfg = self.config or {} strategy = None json_path = None join_sep = None # 1) Пресет по id, выбранный в ноде pid = str(cfg.get("text_extract_preset_id") or "").strip() if pid: try: pr = next((x for x in presets if isinstance(x, dict) and str(x.get("id", "")) == pid), None) except Exception: pr = None if pr: strategy = str(pr.get("strategy") or "auto") json_path = str(pr.get("json_path") or "") join_sep = str(pr.get("join_sep") or "\n") # 2) Кастомные поля ноды (если что-то задано) if not strategy and (cfg.get("text_extract_strategy") is not None or cfg.get("text_extract_json_path") is not None or cfg.get("text_join_sep") is not None): strategy = str(cfg.get("text_extract_strategy") or "auto") json_path = str(cfg.get("text_extract_json_path") or "") join_sep = str(cfg.get("text_join_sep") or "\n") # 3) Глобальные метаданные запуска (дефолт) if not strategy: strategy = str(meta_opts.get("text_extract_strategy", "auto") or "auto") json_path = str(meta_opts.get("text_extract_json_path", "") or "") join_sep = str(meta_opts.get("text_join_sep", "\n") or "\n") except Exception: strategy, json_path, join_sep = "auto", "", "\n" # Подсказка о провайдере: используем detect_vendor(data) как hint для auto try: prov_hint = detect_vendor(data if isinstance(data, dict) else {}) # type: ignore[arg-type] except Exception: prov_hint = "unknown" best_text = _extract_text_for_out(data, strategy, prov_hint, json_path, join_sep) # Подробный SSE-лог завершения RawForward try: trace_fn = context.get("_trace") if trace_fn: # Compute destination macros for extracted text and include req_id try: to_path = f"OUT.{self.node_id}.response_text" macro_braces = f"{{{{ OUT.{self.node_id}.response_text }}}}" alias_macro = "" m = re.match(r"^n(\d+)$", str(self.node_id)) if m: alias_macro = f"[[OUT{int(m.group(1))}]]" except Exception: to_path = f"OUT.{self.node_id}.response_text" macro_braces = f"{{{{ OUT.{self.node_id}.response_text }}}}" alias_macro = "" await trace_fn({ "event": "rawforward_done", "node_id": self.node_id, "node_type": self.type_name, "method": method, "url": url, "req_id": req_id, "status": int(resp.status_code) if 'resp' in locals() else None, "text_len": int(len(best_text or "")), "extracted_text": best_text or "", "strategy": strategy, "json_path": json_path or "", "join_sep": join_sep or "\n", "to_path": to_path, "to_macro_outx": alias_macro, "to_macro_braces": macro_braces, "ts": int(time.time() * 1000), }) except Exception: pass return {"result": data, "response_text": best_text or ""} class ReturnNode(Node): type_name = "Return" async def run(self, inputs: Dict[str, Any], context: Dict[str, Any]) -> Dict[str, Any]: # noqa: D401 # Определяем целевой формат cfg = self.config or {} target = str(cfg.get("target_format", "auto")).lower().strip() or "auto" if target == "auto": target = str(context.get("vendor_format") or "openai").lower().strip() or "openai" # Рендерим текст из шаблона (по умолчанию берём [[OUT1]]) out_map = context.get("OUT") or {} template = cfg.get("text_template") if template is None or template == "": template = "[[OUT1]]" try: text = render_template_simple(str(template), context, out_map) except Exception: text = "" model = str(context.get("model") or "") # Форматтеры под провайдеры (как в execute_pipeline_echo) def fmt_openai(t: str) -> Dict[str, Any]: return { "id": "ret_mock_123", "object": "chat.completion", "model": model, "choices": [ { "index": 0, "message": {"role": "assistant", "content": t}, "finish_reason": "stop", } ], "usage": {"prompt_tokens": 0, "completion_tokens": len((t or "").split()), "total_tokens": 0}, } def fmt_gemini(t: str) -> Dict[str, Any]: return { "candidates": [ { "content": { "role": "model", "parts": [{"text": t}], }, "finishReason": "STOP", "index": 0, } ], "modelVersion": model, } def fmt_claude(t: str) -> Dict[str, Any]: return { "id": "msg_ret_123", "type": "message", "model": model, "role": "assistant", "content": [ {"type": "text", "text": t} ], "stop_reason": "end_turn", } if target == "openai": result = fmt_openai(text) elif target == "gemini": result = fmt_gemini(text) elif target == "claude": result = fmt_claude(text) else: # неизвестное значение — безопасный дефолт result = fmt_openai(text) # Подробный SSE-лог Return try: trace_fn = context.get("_trace") if trace_fn: await trace_fn({ "event": "return_detail", "node_id": self.node_id, "node_type": self.type_name, "target": target, "text_len": int(len(text or "")), "template_used": str(template), "ts": int(time.time() * 1000), }) except Exception: pass return {"result": result, "response_text": text} class IfNode(Node): type_name = "If" async def run(self, inputs: Dict[str, Any], context: Dict[str, Any]) -> Dict[str, Any]: # noqa: D401 expr = str(self.config.get("expr") or "").strip() out_map = context.get("OUT") or {} # Для логов: отображаем развёрнутое выражение (с подставленными макросами) try: expanded = render_template_simple(expr, context, out_map) except Exception: expanded = expr try: res = bool(eval_condition_expr(expr, context, out_map)) if expr else False except Exception as exc: # noqa: BLE001 # Расширенный лог, чтобы быстрее найти ошибку парсинга/оценки выражения try: print(f"TRACE if_error: {self.node_id} expr={expr!r} expanded={expanded!r} error={exc}") except Exception: pass raise ExecutionError(f"If expr error: {exc}") try: print(f"TRACE if: {self.node_id} expr={expr!r} expanded={expanded!r} result={str(res).lower()}") except Exception: pass # Подробный SSE-лог по If try: trace_fn = context.get("_trace") if trace_fn: await trace_fn({ "event": "if_result", "node_id": self.node_id, "node_type": self.type_name, "expr": expr, "expanded": expanded, "result": bool(res), "ts": int(time.time() * 1000), }) except Exception: pass return {"result": res, "true": res, "false": (not res)} NODE_REGISTRY.update({ SetVarsNode.type_name: SetVarsNode, ProviderCallNode.type_name: ProviderCallNode, RawForwardNode.type_name: RawForwardNode, ReturnNode.type_name: ReturnNode, IfNode.type_name: IfNode, }) # --- While-loop helpers for ProviderCall and RawForward (node-scoped) ----------- async def _providercall_run_with_while(self, inputs, context): """ Execute ProviderCall node in a while loop using the same If-expression parser. - Config keys (optional): while_expr: string expression (same grammar as If: &&, ||, !, contains, [[...]], {{ ... }}) while_max_iters: safety cap (default: 50) ignore_errors: bool; if True, HTTP/client errors do not crash pipeline; result carries {"error": "..."} - Local variables within loop: [[cycleindex]]: 0-based iteration index (scoped to this node call) [[WAS_ERROR]]: True only for current iteration when an exception occurred (scoped to this node call) These locals are injected into context.vars for the inner single-run only and do not leak globally. - Outputs (global user vars for downstream nodes): [[WAS_ERROR__nX]]: bool — final iteration error flag for this node [[CYCLEINDEX__nX]]: int — index of the last executed iteration for this node (0 if none executed) """ try: cfg = self.config or {} except Exception: cfg = {} # Expression and safety cap try: expr = str(cfg.get("while_expr") or "").strip() except Exception: expr = "" try: max_iters = int(cfg.get("while_max_iters") or 50) except Exception: max_iters = 50 if max_iters <= 0: max_iters = 50 ignore = False try: ignore = bool(cfg.get("ignore_errors", False)) except Exception: ignore = False out_map = context.get("OUT") or {} last_out = {"result": {}, "response_text": ""} last_was_error = False last_idx = -1 for i in range(max_iters): # Cancel check before starting next iteration try: pid = str((context.get("meta") or {}).get("id", "pipeline_editor")) except Exception: pid = "pipeline_editor" try: if is_cancelled(pid): mode = get_cancel_mode(pid) try: print(f"TRACE while_cancel: {self.node_id} mode={mode} at i={i} (pre)") except Exception: pass break except Exception: pass # Build loop-local context with cycleindex and WAS_ERROR ctx2 = dict(context or {}) try: vmap = dict(ctx2.get("vars") or {}) except Exception: vmap = {} vmap["cycleindex"] = i vmap["WAS_ERROR"] = False # local flag for this iteration only ctx2["vars"] = vmap # mark reentry to avoid recursive while wrapping in self.run() ctx2["_in_while"] = True # Do-while semantics: # - First iteration always runs. # - For subsequent iterations, evaluate expression with last_out injected into OUT map. expanded = "" if not expr: # No expression -> perform exactly one iteration cond = (i == 0) else: if i == 0: cond = True else: # Inject previous iteration error flag so [[WAS_ERROR]] in while_expr refers to the last iteration try: vmap2 = dict(ctx2.get("vars") or {}) except Exception: vmap2 = {} vmap2["WAS_ERROR"] = bool(last_was_error) ctx2["vars"] = vmap2 # Augment OUT with the last output of this node so [[OUTn]] / [[OUT:nX...]] can see it try: out_aug = dict(out_map or {}) out_aug[self.node_id] = dict(last_out or {}) except Exception: out_aug = out_map try: expanded = render_template_simple(expr, ctx2, out_aug) except Exception: expanded = expr try: cond = bool(eval_condition_expr(expr, ctx2, out_aug)) except Exception as exc: # noqa: BLE001 cond = False try: print(f"TRACE while_error: {self.node_id} expr={expr!r} expanded={expanded!r} error={exc}") except Exception: pass # SSE: while_result (analogous to if_result) try: trace_fn = context.get("_trace") if trace_fn: await trace_fn({ "event": "while_result", "node_id": self.node_id, "node_type": self.type_name, "expr": expr, "expanded": expanded, "result": bool(cond), "index": i, "ts": int(time.time() * 1000), }) except Exception: pass try: print(f"TRACE while: {self.node_id} expr={expr!r} expanded={expanded!r} index={i} result={str(cond).lower()}") except Exception: pass if not cond: break # Single iteration run; reenter node.run with _in_while flag set try: inner_out = await self.run(inputs, ctx2) except BaseException as exc: if ignore: inner_out = {"result": {"error": str(exc)}, "response_text": ""} try: print(f"TRACE suppressed_error(inner): {self.node_id} {exc}") except Exception: pass else: raise # Detect error by sentinel on result was_err = False try: r = inner_out.get("result") was_err = bool(isinstance(r, dict) and ("error" in r)) except Exception: was_err = False last_out = dict(inner_out or {}) last_was_error = was_err last_idx = i # Finalize outputs with per-node global vars try: cyc = int(last_idx if last_idx >= 0 else 0) except Exception: cyc = 0 try: last_out = dict(last_out or {}) except Exception: last_out = {"result": {}, "response_text": ""} try: last_out["vars"] = { f"WAS_ERROR__{self.node_id}": bool(last_was_error), f"CYCLEINDEX__{self.node_id}": cyc, } except Exception: # ensure at least WAS_ERROR var last_out["vars"] = {f"WAS_ERROR__{self.node_id}": bool(last_was_error)} return last_out async def _rawforward_run_with_while(self, inputs, context): """ Execute RawForward node in a while loop using the same If-expression parser. Conventions identical to _providercall_run_with_while() regarding config and variables. """ try: cfg = self.config or {} except Exception: cfg = {} try: expr = str(cfg.get("while_expr") or "").strip() except Exception: expr = "" try: max_iters = int(cfg.get("while_max_iters") or 50) except Exception: max_iters = 50 if max_iters <= 0: max_iters = 50 ignore = False try: ignore = bool(cfg.get("ignore_errors", False)) except Exception: ignore = False out_map = context.get("OUT") or {} last_out = {"result": {}, "response_text": ""} last_was_error = False last_idx = -1 for i in range(max_iters): # Cancel check before starting next iteration try: pid = str((context.get("meta") or {}).get("id", "pipeline_editor")) except Exception: pid = "pipeline_editor" try: if is_cancelled(pid): mode = get_cancel_mode(pid) try: print(f"TRACE while_cancel: {self.node_id} mode={mode} at i={i} (pre)") except Exception: pass break except Exception: pass ctx2 = dict(context or {}) try: vmap = dict(ctx2.get("vars") or {}) except Exception: vmap = {} vmap["cycleindex"] = i vmap["WAS_ERROR"] = False ctx2["vars"] = vmap ctx2["_in_while"] = True # Do-while semantics + last_out in OUT for subsequent checks expanded = "" if not expr: cond = (i == 0) else: if i == 0: cond = True else: # Inject previous iteration error flag so [[WAS_ERROR]] in while_expr refers to the last iteration try: vmap2 = dict(ctx2.get("vars") or {}) except Exception: vmap2 = {} vmap2["WAS_ERROR"] = bool(last_was_error) ctx2["vars"] = vmap2 try: out_aug = dict(out_map or {}) out_aug[self.node_id] = dict(last_out or {}) except Exception: out_aug = out_map try: expanded = render_template_simple(expr, ctx2, out_aug) except Exception: expanded = expr try: cond = bool(eval_condition_expr(expr, ctx2, out_aug)) except Exception as exc: # noqa: BLE001 cond = False try: print(f"TRACE while_error: {self.node_id} expr={expr!r} expanded={expanded!r} error={exc}") except Exception: pass # SSE: while_result (analogous to if_result) try: trace_fn = context.get("_trace") if trace_fn: await trace_fn({ "event": "while_result", "node_id": self.node_id, "node_type": self.type_name, "expr": expr, "expanded": expanded, "result": bool(cond), "index": i, "ts": int(time.time() * 1000), }) except Exception: pass try: print(f"TRACE while: {self.node_id} expr={expr!r} expanded={expanded!r} index={i} result={str(cond).lower()}") except Exception: pass if not cond: break try: inner_out = await self.run(inputs, ctx2) except BaseException as exc: if ignore: inner_out = {"result": {"error": str(exc)}, "response_text": ""} try: print(f"TRACE suppressed_error(inner): {self.node_id} {exc}") except Exception: pass else: raise was_err = False try: r = inner_out.get("result") was_err = bool(isinstance(r, dict) and ("error" in r)) except Exception: was_err = False last_out = dict(inner_out or {}) last_was_error = was_err last_idx = i try: cyc = int(last_idx if last_idx >= 0 else 0) except Exception: cyc = 0 try: last_out = dict(last_out or {}) except Exception: last_out = {"result": {}, "response_text": ""} try: last_out["vars"] = { f"WAS_ERROR__{self.node_id}": bool(last_was_error), f"CYCLEINDEX__{self.node_id}": cyc, } except Exception: last_out["vars"] = {f"WAS_ERROR__{self.node_id}": bool(last_was_error)} return last_out