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sashatrask
2025-10-03 21:55:24 +03:00
parent 2abfbb4b1a
commit 86182c0808
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agentui/providers/adapters/openai.py Normal file
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from __future__ import annotations
import json
import re
from typing import Any, Dict, List, Optional, Tuple
from agentui.providers.adapters.base import ( # [ProviderAdapter](agentui/providers/adapters/base.py:10)
ProviderAdapter,
insert_items,
split_pos_spec,
)
def _try_json(s: str) -> Any: # [_try_json()](agentui/providers/adapters/openai.py:16)
"""
Парсит JSON из строки. Пермиссивный режим и двукратная распаковка строк, как в старой логике.
Возвращает dict/list/примитив или None при неудаче.
"""
try:
obj = json.loads(s)
except Exception:
try:
obj = json.loads(s, strict=False) # type: ignore[call-arg]
except Exception:
return None
# Если это строка, которая сама похожа на JSON — пробуем распаковать до 2 раз
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
class OpenAIAdapter(ProviderAdapter): # [OpenAIAdapter.__init__()](agentui/providers/adapters/openai.py:39)
name = "openai"
# --- Дефолты HTTP ---
def default_base_url(self) -> str:
return "https://api.openai.com"
def default_endpoint(self, model: str) -> str:
return "/v1/chat/completions"
# --- PROMPT: построение провайдерных структур ---
def blocks_struct_for_template(
self,
unified_messages: List[Dict[str, Any]],
context: Dict[str, Any],
node_config: Dict[str, Any],
) -> Dict[str, Any]:
"""
Совместимо с веткой provider=='openai' из [ProviderCallNode._blocks_struct_for_template()](agentui/pipeline/executor.py:1958).
"""
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 "")}
# system_text — склейка всех system-блоков (только текст, 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 (unified_messages or [])
if m.get("role") == "system"
]
).strip()
return {
"messages": [_map(m) for m in (unified_messages or [])],
"system_text": sys_text,
}
def normalize_segment(self, x: Any) -> List[Dict[str, Any]]:
"""
Совместимо с [_as_openai_messages()](agentui/pipeline/executor.py:2451).
- Поддерживает dict with messages (openai)
- Поддерживает dict/list в стиле Gemini.contents (склейка текстов частей)
- Поддерживает list openai-like messages (нормализация parts)
- Строки/прочее упаковываются как один user message
"""
msgs: List[Dict[str, Any]] = []
try:
# Dict inputs
if isinstance(x, dict):
if isinstance(x.get("messages"), list):
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"}:
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 self.normalize_segment(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 filter_items(self, arr: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
"""
Совместимо с [_filter_openai()](agentui/pipeline/executor.py:2801).
"""
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 extract_system_text_from_obj(self, x: Any, render_ctx: Dict[str, Any]) -> Optional[str]:
"""
Совместимо с [_extract_sys_text_from_obj()](agentui/pipeline/executor.py:2676).
Умеет читать:
- Gemini: systemInstruction.parts[].text
- Claude: top-level system (string/list of blocks)
- OpenAI: messages[*] with role=system (string content or parts[].text)
- List форматы: openai messages list и gemini contents list (в последнем случае смотрит incoming.json.systemInstruction)
"""
try:
# 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()
# 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:
# Рекурсивно используем себя
return self.extract_system_text_from_obj({"systemInstruction": si}, render_ctx)
except Exception:
pass
return None
except Exception:
return None
def combine_segments(
self,
blocks_struct: Dict[str, Any],
pre_segments_raw: List[Dict[str, Any]],
raw_segs: List[str],
render_ctx: Dict[str, Any],
pre_var_paths: set[str],
render_template_simple_fn,
var_macro_fullmatch_re,
detect_vendor_fn,
) -> Dict[str, Any]:
"""
Повторяет ветку provider=='openai' из prompt_combine в [ProviderCallNode.run()](agentui/pipeline/executor.py:2936).
"""
built: List[Dict[str, Any]] = []
sys_texts: List[str] = []
# 1) Пред‑сегменты (prompt_preprocess)
for _pre in (pre_segments_raw or []):
try:
_obj = _pre.get("obj")
items = self.normalize_segment(_obj)
items = self.filter_items(items)
built = insert_items(built, items, _pre.get("pos"))
try:
sx = self.extract_system_text_from_obj(_obj, render_ctx)
if isinstance(sx, str) and sx.strip():
sys_texts.append(sx.strip())
except Exception:
pass
except Exception:
pass
# 2) Основные сегменты (prompt_combine)
for raw_seg in (raw_segs or []):
body_seg, pos_spec = split_pos_spec(raw_seg)
if body_seg == "[[PROMPT]]":
items = self.filter_items(list(blocks_struct.get("messages", []) or []))
built = insert_items(built, items, pos_spec)
continue
# Спрятать дубли plain [[VAR:path]] если уже вставляли этим путём в pre_var_overrides
m_pre = var_macro_fullmatch_re.fullmatch(body_seg)
if m_pre:
_p = (m_pre.group(1) or "").strip()
try:
if _p in pre_var_paths:
# Уже вставлено через prompt_preprocess с фильтрацией — пропускаем
continue
except Exception:
pass
resolved = render_template_simple_fn(body_seg, render_ctx, render_ctx.get("OUT") or {})
obj = _try_json(resolved)
# debug provider guess
try:
pg = detect_vendor_fn(obj if isinstance(obj, dict) else {})
print(f"DEBUG: prompt_combine seg provider_guess={pg} -> target=openai pos={pos_spec}")
except Exception:
pass
items = self.normalize_segment(obj if obj is not None else resolved)
items = self.filter_items(items)
built = insert_items(built, items, pos_spec)
try:
sx = self.extract_system_text_from_obj(obj, render_ctx) if obj is not None else None
if isinstance(sx, str) and sx.strip():
sys_texts.append(sx.strip())
except Exception:
pass
# Если ничего не собрали — берём исходные blocks
if not built:
built = self.filter_items(list(blocks_struct.get("messages", []) or []))
# Препендинг системных сообщений из sys_texts
if sys_texts:
sys_msgs = [{"role": "system", "content": s} for s in sys_texts if s]
if sys_msgs:
built = sys_msgs + built
# 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()])
return {"messages": built, "system_text": st}
def prompt_fragment(self, pm_struct: Dict[str, Any], node_config: Dict[str, Any]) -> str:
"""
Совместимо с веткой provider=='openai' в построении [[PROMPT]] из [ProviderCallNode.run()](agentui/pipeline/executor.py:3103).
"""
return '"messages": ' + json.dumps(pm_struct.get("messages", []), ensure_ascii=False)