feat(llm): 增加 Kimi 文本适配器与 KIMI_* 环境变量

纯文本可选 MA_LLM_TEXT_PROVIDER=kimi,与 OPENAI_* 配料/视觉分离;.env.example 与测试补充。

Made-with: Cursor
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hub-gif 2026-04-27 10:47:58 +08:00
parent 5e70bb1be3
commit 2b595f794e
6 changed files with 210 additions and 3 deletions

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@ -32,8 +32,18 @@ CSRF_TRUSTED_ORIGINS=http://localhost:5173,http://127.0.0.1:5173
# 报告/策略等「纯文本」任务的后端选择:
# crawler_openai_compatible默认= 经 pipeline.openai_gateway 调自建 OpenAI 兼容网关
# openai_official / openai_chatgpt / chatgpt = 直连 OpenAI 官方 api.openai.com与上项凭据独立
# kimi / moonshot / kimi_moonshot = 月之暗面 KimiMoonshotOpenAI 兼容,与下节 KIMI_* 独立;配料/视觉仍用上面 OPENAI_*
# MA_LLM_TEXT_PROVIDER=crawler_openai_compatible
# Kimi / Moonshot 纯文本(仅当 MA_LLM_TEXT_PROVIDER 为 kimi / moonshot / kimi_moonshot 时需要;与 OPENAI_* 分离)
# KIMI_API_KEY=sk-...
# KIMI_BASE_URL=https://api.moonshot.cn/v1
# KIMI_TEXT_MODEL=moonshot-v1-8k
# 与预检 token 上界;若用 moonshot-v1-128k 可设 128000
# KIMI_CONTEXT_WINDOW=8192
# 别名MOONSHOT_API_KEY、MOONSHOT_MODEL
# KIMI_TIMEOUT=600
# OpenAI 官方 Chat Completions仅当 MA_LLM_TEXT_PROVIDER 为 openai_official / openai_chatgpt / chatgpt 时需要)
# OPENAI_OFFICIAL_API_KEY=sk-...
# OPENAI_OFFICIAL_BASE_URL=https://api.openai.com/v1

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@ -2,12 +2,17 @@
from __future__ import annotations
from .adapters import CrawlerOpenAiCompatibleTextLlm, OpenAiOfficialChatGptTextLlm
from .adapters import (
CrawlerOpenAiCompatibleTextLlm,
KimiMoonshotTextLlm,
OpenAiOfficialChatGptTextLlm,
)
from .factory import get_text_llm, reset_text_llm_client_for_tests
from .protocol import TextLlmClient
__all__ = [
"CrawlerOpenAiCompatibleTextLlm",
"KimiMoonshotTextLlm",
"OpenAiOfficialChatGptTextLlm",
"TextLlmClient",
"get_text_llm",

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@ -2,9 +2,11 @@
from __future__ import annotations
from .crawler_openai_compatible import CrawlerOpenAiCompatibleTextLlm
from .kimi_moonshot_text import KimiMoonshotTextLlm
from .openai_official_chatgpt import OpenAiOfficialChatGptTextLlm
__all__ = [
"CrawlerOpenAiCompatibleTextLlm",
"KimiMoonshotTextLlm",
"OpenAiOfficialChatGptTextLlm",
]

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@ -0,0 +1,146 @@
"""
月之暗面 KimiMoonshotOpenAI 兼容 `chat/completions`**仅用于纯文本**`call_llm` / 报告 / 策略
`OPENAI_*` / `LLM_*` 分离避免与自建网关配料多模态等混用同一套 Key
启用`MA_LLM_TEXT_PROVIDER=kimi` `moonshot` / `kimi_moonshot`
环境变量`KIMI_API_KEY`必填`KIMI_BASE_URL`默认 Moonshot 官方 v1`KIMI_TEXT_MODEL`
`KIMI_CONTEXT_WINDOW``KIMI_TIMEOUT` `.env.example`
"""
from __future__ import annotations
import os
from typing import Any
import requests
from pipeline.openai_gateway.chat_content import normalize_message_content
from pipeline.openai_gateway.estimate import (
estimate_chat_input_tokens as estimate_crawler_style_input_tokens,
)
_DEFAULT_BASE = "https://api.moonshot.cn/v1"
_DEFAULT_MODEL = "moonshot-v1-8k"
# 与常见 8k 窗口一致;若使用 moonshot-v1-128k 等请调大 KIMI_CONTEXT_WINDOW
_DEFAULT_CTX = 8192
_BUF = 256
_WANT_MAX = 8192
def _read_timeout() -> tuple[float, float]:
read = 600
raw = (
os.environ.get("KIMI_TIMEOUT")
or os.environ.get("LLM_CHAT_TIMEOUT")
or os.environ.get("OPENAI_TIMEOUT")
or ""
).strip()
if raw:
try:
read = max(60, int(raw))
except ValueError:
pass
conn = 30.0
raw_c = (os.environ.get("LLM_CHAT_CONNECT_TIMEOUT") or "").strip()
if raw_c:
try:
conn = max(5.0, float(raw_c))
except ValueError:
pass
return (conn, float(read))
def _resolve_kimi_credentials() -> tuple[str, str, str]:
key = (
(os.environ.get("KIMI_API_KEY") or os.environ.get("MOONSHOT_API_KEY") or "").strip()
)
if not key:
raise ValueError(
"使用 kimi 文本适配器需设置 KIMI_API_KEY或 MOONSHOT_API_KEY"
"与配料/视觉所用 OPENAI_API_KEY 分开配置。"
)
base = (os.environ.get("KIMI_BASE_URL") or _DEFAULT_BASE).strip().rstrip("/")
model = (
os.environ.get("KIMI_TEXT_MODEL")
or os.environ.get("KIMI_MODEL")
or os.environ.get("MOONSHOT_MODEL")
or _DEFAULT_MODEL
).strip()
return key, base, model
def _context_window() -> int:
raw = (os.environ.get("KIMI_CONTEXT_WINDOW") or str(_DEFAULT_CTX)).strip()
try:
return max(4096, int(raw))
except ValueError:
return _DEFAULT_CTX
def _default_temperature() -> float:
return 0.2
class KimiMoonshotTextLlm:
"""Kimi OpenAI 兼容文本补全;行为与 `OpenAiOfficialChatGptTextLlm` 同形max_tokens 预检)。"""
def complete_text(
self,
system_prompt: str,
user_prompt: str,
*,
temperature: float | None = None,
) -> str:
api_key, base, model = _resolve_kimi_credentials()
body: dict[str, Any] = {
"model": model,
"messages": [
{"role": "system", "content": system_prompt},
{"role": "user", "content": user_prompt},
],
"temperature": _default_temperature() if temperature is None else float(temperature),
"max_tokens": _WANT_MAX,
}
est = estimate_crawler_style_input_tokens(system_prompt, user_prompt)
context_window = _context_window()
if est >= context_window - _BUF - 256:
raise ValueError(
f"提示词过长(估算输入约 {est} tokensKIMI_CONTEXT_WINDOW={context_window}"
"请缩小输入或换更大上下文的 KIMI_TEXT_MODEL / KIMI_CONTEXT_WINDOW。"
)
avail = context_window - est - _BUF
want = int(body.get("max_tokens") or _WANT_MAX)
body["max_tokens"] = max(256, min(want, max(avail, 256)))
r = requests.post(
f"{base}/chat/completions",
headers={
"Authorization": f"Bearer {api_key}",
"Content-Type": "application/json",
},
json=body,
timeout=_read_timeout(),
)
try:
r.raise_for_status()
except requests.HTTPError as e:
snippet = ""
if e.response is not None:
snippet = (e.response.text or "")[:1200].replace("\r\n", "\n").replace("\n", " ")
if snippet:
raise requests.HTTPError(
f"{e!s} | body: {snippet}",
response=e.response,
request=e.request,
) from e
raise
data = r.json()
msg = (data.get("choices") or [{}])[0].get("message") or {}
return normalize_message_content(msg.get("content"))
def estimate_input_tokens(self, system_prompt: str, user_prompt: str) -> int:
return estimate_crawler_style_input_tokens(system_prompt, user_prompt)
def context_window_tokens(self) -> int:
return _context_window()

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@ -1,11 +1,12 @@
"""
根据 `MA_LLM_TEXT_PROVIDER` 选择文本大模型实现未设置时与历史行为一致 AI_crawler OpenAI 兼容网关
根据 `MA_LLM_TEXT_PROVIDER` 选择文本大模型实现未设置时与历史行为一致 `openai_gateway` 与自建兼容网关
"""
from __future__ import annotations
import os
from .adapters.crawler_openai_compatible import CrawlerOpenAiCompatibleTextLlm
from .adapters.kimi_moonshot_text import KimiMoonshotTextLlm
from .adapters.openai_official_chatgpt import OpenAiOfficialChatGptTextLlm
from .protocol import TextLlmClient
@ -32,9 +33,12 @@ def _build_client(pid: str) -> TextLlmClient:
return CrawlerOpenAiCompatibleTextLlm()
if pid in ("openai_official", "openai_chatgpt", "chatgpt"):
return OpenAiOfficialChatGptTextLlm()
if pid in ("kimi", "moonshot", "kimi_moonshot", "moonshot_kimi"):
return KimiMoonshotTextLlm()
known = (
"crawler_openai_compatible, crawler, default, openai_compatible, "
"openai_official, openai_chatgpt, chatgpt"
"openai_official, openai_chatgpt, chatgpt, "
"kimi, moonshot, kimi_moonshot"
)
raise ValueError(
f"不支持的 {_ENV_KEY}={pid!r};已知取值:{known}",

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@ -6,6 +6,7 @@ import pytest
from pipeline.llm.providers import (
CrawlerOpenAiCompatibleTextLlm,
KimiMoonshotTextLlm,
OpenAiOfficialChatGptTextLlm,
get_text_llm,
reset_text_llm_client_for_tests,
@ -37,6 +38,45 @@ def test_openai_official_complete_text_uses_post_and_returns_content(monkeypatch
assert out == "ok_out"
def test_kimi_complete_text_uses_post_and_returns_content(monkeypatch: pytest.MonkeyPatch) -> None:
monkeypatch.setenv("KIMI_API_KEY", "sk-kimi-test")
def _fake_post(
url: str,
headers: dict,
json: dict,
timeout: object,
) -> MagicMock:
assert "moonshot" in url or "chat/completions" in url
assert json["messages"][0]["role"] == "system"
assert headers.get("Authorization", "").startswith("Bearer sk-kimi-")
r = MagicMock()
r.json.return_value = {"choices": [{"message": {"content": "kimi_out"}}]}
r.raise_for_status = MagicMock()
return r
with patch(
"pipeline.llm.providers.adapters.kimi_moonshot_text.requests.post",
side_effect=_fake_post,
):
llm = KimiMoonshotTextLlm()
out = llm.complete_text("S", "U", temperature=0.1)
assert out == "kimi_out"
def test_factory_selects_kimi_when_env_set(monkeypatch: pytest.MonkeyPatch) -> None:
reset_text_llm_client_for_tests()
monkeypatch.setenv("MA_LLM_TEXT_PROVIDER", "kimi")
monkeypatch.setenv("KIMI_API_KEY", "sk-x")
try:
c = get_text_llm()
assert isinstance(c, KimiMoonshotTextLlm)
finally:
reset_text_llm_client_for_tests()
monkeypatch.delenv("MA_LLM_TEXT_PROVIDER", raising=False)
monkeypatch.delenv("KIMI_API_KEY", raising=False)
def test_factory_selects_openai_official_when_env_set(monkeypatch: pytest.MonkeyPatch) -> None:
reset_text_llm_client_for_tests()
monkeypatch.setenv("MA_LLM_TEXT_PROVIDER", "chatgpt")