feat: model and agent config in web console

This commit is contained in:
zhayujie
2026-02-26 21:01:37 +08:00
parent 3ddbdd713d
commit 5edbf4ce32
6 changed files with 794 additions and 84 deletions
+213 -9
View File
@@ -14,6 +14,8 @@ from bridge.context import *
from bridge.reply import Reply, ReplyType
from channel.chat_channel import ChatChannel, check_prefix
from channel.chat_message import ChatMessage
from collections import OrderedDict
from common import const
from common.log import logger
from common.singleton import singleton
from config import conf
@@ -379,16 +381,137 @@ class ChatHandler:
class ConfigHandler:
_RECOMMENDED_MODELS = [
const.MINIMAX_M2_5, const.MINIMAX_M2_1, const.MINIMAX_M2_1_LIGHTNING,
const.GLM_5, const.GLM_4_7,
const.QWEN3_MAX, const.QWEN35_PLUS,
const.KIMI_K2_5, const.KIMI_K2,
const.DOUBAO_SEED_2_PRO, const.DOUBAO_SEED_2_CODE,
const.CLAUDE_4_6_SONNET, const.CLAUDE_4_6_OPUS, const.CLAUDE_4_5_SONNET,
const.GEMINI_31_PRO_PRE, const.GEMINI_3_FLASH_PRE,
const.GPT_5, const.GPT_41, const.GPT_4o,
const.DEEPSEEK_CHAT, const.DEEPSEEK_REASONER,
]
PROVIDER_MODELS = OrderedDict([
("minimax", {
"label": "MiniMax",
"api_key_field": "minimax_api_key",
"api_base_key": None,
"api_base_default": None,
"models": [const.MINIMAX_M2_5, const.MINIMAX_M2_1, const.MINIMAX_M2_1_LIGHTNING],
}),
("glm-4", {
"label": "智谱AI",
"api_key_field": "zhipu_ai_api_key",
"api_base_key": "zhipu_ai_api_base",
"api_base_default": "https://open.bigmodel.cn/api/paas/v4",
"models": [const.GLM_5, const.GLM_4_7],
}),
("dashscope", {
"label": "通义千问",
"api_key_field": "dashscope_api_key",
"api_base_key": None,
"api_base_default": None,
"models": [const.QWEN3_MAX, const.QWEN35_PLUS],
}),
("moonshot", {
"label": "Kimi",
"api_key_field": "moonshot_api_key",
"api_base_key": "moonshot_base_url",
"api_base_default": "https://api.moonshot.cn/v1",
"models": [const.KIMI_K2_5, const.KIMI_K2],
}),
("doubao", {
"label": "豆包",
"api_key_field": "ark_api_key",
"api_base_key": "ark_base_url",
"api_base_default": "https://ark.cn-beijing.volces.com/api/v3",
"models": [const.DOUBAO_SEED_2_PRO, const.DOUBAO_SEED_2_CODE],
}),
("claudeAPI", {
"label": "Claude",
"api_key_field": "claude_api_key",
"api_base_key": "claude_api_base",
"api_base_default": "https://api.anthropic.com/v1",
"models": [const.CLAUDE_4_6_SONNET, const.CLAUDE_4_6_OPUS, const.CLAUDE_4_5_SONNET],
}),
("gemini", {
"label": "Gemini",
"api_key_field": "gemini_api_key",
"api_base_key": "gemini_api_base",
"api_base_default": "https://generativelanguage.googleapis.com",
"models": [const.GEMINI_31_PRO_PRE, const.GEMINI_3_FLASH_PRE],
}),
("openAI", {
"label": "OpenAI",
"api_key_field": "open_ai_api_key",
"api_base_key": "open_ai_api_base",
"api_base_default": "https://api.openai.com/v1",
"models": [const.GPT_5, const.GPT_41, const.GPT_4o],
}),
("deepseek", {
"label": "DeepSeek",
"api_key_field": "open_ai_api_key",
"api_base_key": None,
"api_base_default": None,
"models": [const.DEEPSEEK_CHAT, const.DEEPSEEK_REASONER],
}),
("linkai", {
"label": "LinkAI",
"api_key_field": "linkai_api_key",
"api_base_key": None,
"api_base_default": None,
"models": _RECOMMENDED_MODELS,
}),
])
EDITABLE_KEYS = {
"model", "use_linkai",
"open_ai_api_base", "claude_api_base", "gemini_api_base",
"zhipu_ai_api_base", "moonshot_base_url", "ark_base_url",
"open_ai_api_key", "claude_api_key", "gemini_api_key",
"zhipu_ai_api_key", "dashscope_api_key", "moonshot_api_key",
"ark_api_key", "minimax_api_key", "linkai_api_key",
"agent_max_context_tokens", "agent_max_context_turns", "agent_max_steps",
}
@staticmethod
def _mask_key(value: str) -> str:
"""Mask the middle part of an API key for display."""
if not value or len(value) <= 8:
return value
return value[:4] + "*" * (len(value) - 8) + value[-4:]
def GET(self):
"""Return configuration info for the web console."""
"""Return configuration info and provider/model metadata."""
web.header('Content-Type', 'application/json; charset=utf-8')
try:
local_config = conf()
use_agent = local_config.get("agent", False)
title = "CowAgent" if use_agent else "AI Assistant"
if use_agent:
title = "CowAgent"
else:
title = "AI Assistant"
api_bases = {}
api_keys_masked = {}
for pid, pinfo in self.PROVIDER_MODELS.items():
base_key = pinfo.get("api_base_key")
if base_key:
api_bases[base_key] = local_config.get(base_key, pinfo["api_base_default"])
key_field = pinfo.get("api_key_field")
if key_field and key_field not in api_keys_masked:
raw = local_config.get(key_field, "")
api_keys_masked[key_field] = self._mask_key(raw) if raw else ""
providers = {}
for pid, p in self.PROVIDER_MODELS.items():
providers[pid] = {
"label": p["label"],
"models": p["models"],
"api_base_key": p["api_base_key"],
"api_base_default": p["api_base_default"],
"api_key_field": p.get("api_key_field"),
}
return json.dumps({
"status": "success",
@@ -396,14 +519,58 @@ class ConfigHandler:
"title": title,
"model": local_config.get("model", ""),
"channel_type": local_config.get("channel_type", ""),
"agent_max_context_tokens": local_config.get("agent_max_context_tokens", ""),
"agent_max_context_turns": local_config.get("agent_max_context_turns", ""),
"agent_max_steps": local_config.get("agent_max_steps", ""),
})
"agent_max_context_tokens": local_config.get("agent_max_context_tokens", 50000),
"agent_max_context_turns": local_config.get("agent_max_context_turns", 30),
"agent_max_steps": local_config.get("agent_max_steps", 15),
"api_bases": api_bases,
"api_keys": api_keys_masked,
"providers": providers,
}, ensure_ascii=False)
except Exception as e:
logger.error(f"Error getting config: {e}")
return json.dumps({"status": "error", "message": str(e)})
def POST(self):
"""Update configuration values in memory and persist to config.json."""
web.header('Content-Type', 'application/json; charset=utf-8')
try:
data = json.loads(web.data())
updates = data.get("updates", {})
if not updates:
return json.dumps({"status": "error", "message": "no updates provided"})
local_config = conf()
applied = {}
for key, value in updates.items():
if key not in self.EDITABLE_KEYS:
continue
if key in ("agent_max_context_tokens", "agent_max_context_turns", "agent_max_steps"):
value = int(value)
if key == "use_linkai":
value = bool(value)
local_config[key] = value
applied[key] = value
if not applied:
return json.dumps({"status": "error", "message": "no valid keys to update"})
config_path = os.path.join(os.path.dirname(os.path.dirname(os.path.dirname(
os.path.abspath(__file__)))), "config.json")
if os.path.exists(config_path):
with open(config_path, "r", encoding="utf-8") as f:
file_cfg = json.load(f)
else:
file_cfg = {}
file_cfg.update(applied)
with open(config_path, "w", encoding="utf-8") as f:
json.dump(file_cfg, f, indent=4, ensure_ascii=False)
logger.info(f"[WebChannel] Config updated: {list(applied.keys())}")
return json.dumps({"status": "success", "applied": applied}, ensure_ascii=False)
except Exception as e:
logger.error(f"Error updating config: {e}")
return json.dumps({"status": "error", "message": str(e)})
def _get_workspace_root():
"""Resolve the agent workspace directory."""
@@ -411,6 +578,19 @@ def _get_workspace_root():
return expand_path(conf().get("agent_workspace", "~/cow"))
class ToolsHandler:
def GET(self):
web.header('Content-Type', 'application/json; charset=utf-8')
try:
from agent.tools.tool_manager import ToolManager
tm = ToolManager()
loaded = list(tm.tool_classes.keys())
return json.dumps({"status": "success", "tools": loaded}, ensure_ascii=False)
except Exception as e:
logger.error(f"[WebChannel] Tools API error: {e}")
return json.dumps({"status": "error", "message": str(e)})
class SkillsHandler:
def GET(self):
web.header('Content-Type', 'application/json; charset=utf-8')
@@ -426,6 +606,30 @@ class SkillsHandler:
logger.error(f"[WebChannel] Skills API error: {e}")
return json.dumps({"status": "error", "message": str(e)})
def POST(self):
web.header('Content-Type', 'application/json; charset=utf-8')
try:
from agent.skills.service import SkillService
from agent.skills.manager import SkillManager
body = json.loads(web.data())
action = body.get("action")
name = body.get("name")
if not action or not name:
return json.dumps({"status": "error", "message": "action and name are required"})
workspace_root = _get_workspace_root()
manager = SkillManager(custom_dir=os.path.join(workspace_root, "skills"))
service = SkillService(manager)
if action == "open":
service.open({"name": name})
elif action == "close":
service.close({"name": name})
else:
return json.dumps({"status": "error", "message": f"unknown action: {action}"})
return json.dumps({"status": "success"}, ensure_ascii=False)
except Exception as e:
logger.error(f"[WebChannel] Skills POST error: {e}")
return json.dumps({"status": "error", "message": str(e)})
class MemoryHandler:
def GET(self):