hindsight-api                ← 后端引擎（數(shù)據(jù)平面）
    ↓                           http://localhost:8888
hindsight-control-plane      ← Web 管理界面（控制平面）
    ↓                           http://localhost:9998
Hermes Desktop               ← 客戶端集成

# 全局安裝 hindsight-api（推薦）
npm install -g hindsight-api

# 或者本地安裝
npm install hindsight-api

REM ===== LLM 配置（DeepSeek）=====
setx HINDSIGHT_API_LLM_PROVIDER "deepseek"
setx DEEPSEEK_API_KEY "sk-你的deepseek密鑰"
setx HINDSIGHT_API_LLM_MODEL "deepseek-v4-flash"

REM ===== Embedding 配置（SiliconFlow）=====
setx HINDSIGHT_API_EMBEDDINGS_PROVIDER "openai"
setx HINDSIGHT_API_EMBEDDINGS_OPENAI_API_KEY "sk-你的硅基流動密鑰"
setx HINDSIGHT_API_EMBEDDINGS_OPENAI_BASE_URL "https://api.siliconflow.cn/v1"
setx HINDSIGHT_API_EMBEDDINGS_OPENAI_MODEL "Qwen/Qwen3-Embedding-0.6B"

REM ===== Reranker 配置（SiliconFlow）=====
setx HINDSIGHT_API_RERANKER_PROVIDER "siliconflow"
setx HINDSIGHT_API_RERANKER_SILICONFLOW_API_KEY "sk-你的硅基流動密鑰"
setx HINDSIGHT_API_RERANKER_MODEL "BAAI/bge-reranker-v2-m3"

REM 設(shè)置后需重新打開終端

# 直接啟動（前臺）
hindsight-api
# 指定參數(shù)啟動
hindsight-api --host 0.0.0.0 --port 8888 --log-level info

curl http://localhost:8888/health
# 返回: {"status":"healthy","database":"connected"}

# 通過 npx 啟動（無需全局安裝）
npx @vectorize-io/hindsight-control-plane --api-url http://localhost:8888 --port 9998

memory:
  provider: hindsight
  memory_enabled: true
  user_profile_enabled: true

{
  "mode": "local_external",
  "api_url": "http://0.0.0.0:8888",
  "bank_id": "hermes",
  "recall_budget": "mid"
}

# 錯誤的
npm install -g @hindsight/mcp-server

# 正確的
npm install -g hindsight-mcp

setx HINDSIGHT_API_EMBEDDINGS_OPENAI_MODEL "Qwen/Qwen3-Embedding-0.6B"
REM 設(shè)置后需重新打開終端

setx HINDSIGHT_API_LLM_MODEL "xopglm52"
REM 或其他支持 structured output 的模型
REM 設(shè)置后需重新打開終端

REM retain 繼續(xù)使用 DeepSeek-v4-flash（簡單事實提取）
setx HINDSIGHT_API_LLM_MODEL "deepseek-v4-flash"

REM reflect 換用其他模型（需要 structured output 支持）
setx HINDSIGHT_API_REFLECT_LLM_MODEL "xopglm52"
REM 注意：此配置需 Hindsight v0.8.4+ 支持

@echo off
REM start-hindsight.bat
REM 確保所有環(huán)境變量正確設(shè)置后啟動 hindsight-api
REM 注意：以下變量已通過 setx 永久設(shè)置，此處僅為保險起見

set HINDSIGHT_API_LLM_PROVIDER=deepseek
set DEEPSEEK_API_KEY=sk-xxx
set HINDSIGHT_API_LLM_MODEL=deepseek-v4-flash

set HINDSIGHT_API_EMBEDDINGS_PROVIDER=openai
set HINDSIGHT_API_EMBEDDINGS_OPENAI_API_KEY=sk-xxx
set HINDSIGHT_API_EMBEDDINGS_OPENAI_BASE_URL=https://api.siliconflow.cn/v1
set HINDSIGHT_API_EMBEDDINGS_OPENAI_MODEL=Qwen/Qwen3-Embedding-0.6B

set HINDSIGHT_API_RERANKER_PROVIDER=siliconflow
set HINDSIGHT_API_RERANKER_SILICONFLOW_API_KEY=sk-xxx
set HINDSIGHT_API_RERANKER_MODEL=BAAI/bge-reranker-v2-m3

hindsight-api

setx HINDSIGHT_API_LLM_PROVIDER "deepseek"
setx DEEPSEEK_API_KEY "sk-xxx"
setx HINDSIGHT_API_LLM_MODEL "deepseek-v4-flash"
setx HINDSIGHT_API_EMBEDDINGS_PROVIDER "openai"
setx HINDSIGHT_API_EMBEDDINGS_OPENAI_API_KEY "sk-xxx"
setx HINDSIGHT_API_EMBEDDINGS_OPENAI_BASE_URL "https://api.siliconflow.cn/v1"
setx HINDSIGHT_API_EMBEDDINGS_OPENAI_MODEL "Qwen/Qwen3-Embedding-0.6B"
setx HINDSIGHT_API_RERANKER_PROVIDER "siliconflow"
setx HINDSIGHT_API_RERANKER_SILICONFLOW_API_KEY "sk-xxx"
setx HINDSIGHT_API_RERANKER_MODEL "BAAI/bge-reranker-v2-m3"
REM 設(shè)置后需重新打開終端

# 必須在 Hermes 的 venv 中安裝，不能裝在系統(tǒng) Python 中
pip install attrs

# 然后重啟 Hermes Desktop

setx PATH "%PATH%;C:\Users\gongc\AppData\Local\hermes\venv\Scripts"
REM 設(shè)置后需重新打開終端

REM 清空 tech-stack
curl -X PATCH http://localhost:8888/banks/hermes/mental-models/tech-stack -H "Content-Type: application/json" -d "{\"content\":\"\",\"history\":[]}"}

REM 清空 ops-playbook
curl -X PATCH http://localhost:8888/banks/hermes/mental-models/ops-playbook -H "Content-Type: application/json" -d "{\"content\":\"\",\"history\":[]}"}

REM 觸發(fā)刷新
curl -X POST http://localhost:8888/banks/hermes/mental-models/tech-stack/refresh
curl -X POST http://localhost:8888/banks/hermes/mental-models/ops-playbook/refresh

{
  "source_query": "技術(shù)棧與工具配置",
  "max_tokens": 2048,
  "mode": "delta",
  "tags": ["config", "tech-stack"]
}

#!/usr/bin/env python3
"""
Hindsight MCP stdio wrapper for Cherry Studio
Connects to local Hindsight API via HTTP and exposes MCP tools via stdio
"""
import sys
import json
import requests
API_BASE = "http://localhost:8888"
BANK_ID = "cherry"
def handle_request(req):
    method = req.get("method")
    params = req.get("params", {})
    if method == "tools/list":
        # Return available tools
        return {
            "tools": [
                {
                    "name": "retain",
                    "description": "Store information to long-term memory",
                    "inputSchema": {
                        "type": "object",
                        "properties": {
                            "items": {
                                "type": "array",
                                "items": {
                                    "type": "object",
                                    "properties": {
                                        "content": {"type": "string"},
                                        "context": {"type": "string"},
                                        "tags": {"type": "array", "items": {"type": "string"}}
                                    },
                                    "required": ["content"]
                                }
                            }
                        },
                        "required": ["items"]
                    }
                },
                {
                    "name": "recall",
                    "description": "Search long-term memory",
                    "inputSchema": {
                        "type": "object",
                        "properties": {
                            "query": {"type": "string"},
                            "limit": {"type": "integer", "default": 10}
                        },
                        "required": ["query"]
                    }
                },
                {
                    "name": "reflect",
                    "description": "Synthesize reasoning across memories",
                    "inputSchema": {
                        "type": "object",
                        "properties": {
                            "query": {"type": "string"},
                            "budget": {"type": "string", "default": "mid"}
                        },
                        "required": ["query"]
                    }
                },
                {
                    "name": "getBankStats",
                    "description": "Get memory bank statistics",
                    "inputSchema": {
                        "type": "object",
                        "properties": {}
                    }
                }
            ]
        }
    elif method == "tools/call":
        tool_name = params.get("name")
        arguments = params.get("arguments", {})
        if tool_name == "retain":
            items = arguments.get("items", [])
            response = requests.post(
                f"{API_BASE}/banks/{BANK_ID}/memories",
                json={"items": items}
            )
            return {"content": [{"type": "text", "text": json.dumps(response.json())}]}
        elif tool_name == "recall":
            query = arguments.get("query")
            limit = arguments.get("limit", 10)
            response = requests.post(
                f"{API_BASE}/banks/{BANK_ID}/recall",
                json={"query": query, "limit": limit}
            )
            return {"content": [{"type": "text", "text": json.dumps(response.json())}]}
        elif tool_name == "reflect":
            query = arguments.get("query")
            budget = arguments.get("budget", "mid")
            response = requests.post(
                f"{API_BASE}/banks/{BANK_ID}/reflect",
                json={"query": query, "budget": budget}
            )
            return {"content": [{"type": "text", "text": json.dumps(response.json())}]}
        elif tool_name == "getBankStats":
            response = requests.get(f"{API_BASE}/banks/{BANK_ID}/stats")
            return {"content": [{"type": "text", "text": json.dumps(response.json())}]}
    return {"error": {"code": -32601, "message": "Method not found"}}
def main():
    for line in sys.stdin:
        try:
            req = json.loads(line)
            result = handle_request(req)
            response = {
                "jsonrpc": "2.0",
                "id": req.get("id"),
                "result": result
            }
            print(json.dumps(response), flush=True)
        except Exception as e:
            error_response = {
                "jsonrpc": "2.0",
                "id": req.get("id") if 'req' in locals() else None,
                "error": {"code": -32603, "message": str(e)}
            }
            print(json.dumps(error_response), flush=True)
if __name__ == "__main__":
    main()

{
  "mcpServers": {
    "hindsight-cherry": {
      "type": "stdio",
      "command": "python",
      "args": [
        "C:\\Users\\gongc\\AppData\\Local\\Programs\\Python\\Python311\\Scripts\\hindsight-mcp-stdio.py"
      ],
      "env": {
        "HINDSIGHT_API_BASE_URL": "http://localhost:8888",
        "HINDSIGHT_MCP_BANK_ID": "cherry"
      }
    }
  }
}

npm install -g hindsight-mcp

{
  "mcpServers": {
    "hindsight": {
      "command": "npx",
      "args": ["-y", "hindsight-mcp"],
      "env": {
        "HINDSIGHT_API_BASE_URL": "http://localhost:8888",
        "HINDSIGHT_MCP_BANK_ID": "cherry"
      }
    }
  }
}

{
  "items": [
    {
      "content": "測試 Cherry Studio 到 Hindsight 的記憶存儲",
      "context": "MCP 配置測試",
      "tags": ["test", "cherry-studio"]
    }
  ]
}

' start-hindsight.vbs
' 后臺啟動 hindsight-api，無 CMD 窗口

Set WshShell = CreateObject("WScript.Shell")
WshShell.Run "cmd /c start-hindsight.bat", 0, False
Set WshShell = Nothing

# 1. hindsight-api 健康檢查
curl http://localhost:8888/health

# 2. Control Plane 訪問
# 瀏覽器打開 http://localhost:9998

# 3. MCP 工具列表
curl http://localhost:8888/mcp/default/tools

# 查看所有 mental models
curl http://localhost:8888/banks/hermes/mental-models

# 檢查具體內(nèi)容長度
curl http://localhost:8888/banks/hermes/mental-models/tech-stack

set HINDSIGHT_API_LLM_MODEL=deepseek-v4-flash
REM 關(guān)閉 CMD 窗口后，變量全部丟失！
REM 新開窗口啟動 hindsight-api → 401/400 錯誤

setx HINDSIGHT_API_LLM_MODEL "deepseek-v4-flash"
REM 關(guān)閉當(dāng)前 CMD，重新打開新窗口
REM 變量永久保存，重啟電腦仍然有效

REM ===== 一次性設(shè)置所有 Hindsight 變量 =====
setx HINDSIGHT_API_LLM_PROVIDER "deepseek"
setx DEEPSEEK_API_KEY "sk-xxx"
setx HINDSIGHT_API_LLM_MODEL "deepseek-v4-flash"

setx HINDSIGHT_API_EMBEDDINGS_PROVIDER "openai"
setx HINDSIGHT_API_EMBEDDINGS_OPENAI_API_KEY "sk-xxx"
setx HINDSIGHT_API_EMBEDDINGS_OPENAI_BASE_URL "https://api.siliconflow.cn/v1"
setx HINDSIGHT_API_EMBEDDINGS_OPENAI_MODEL "Qwen/Qwen3-Embedding-0.6B"

setx HINDSIGHT_API_RERANKER_PROVIDER "siliconflow"
setx HINDSIGHT_API_RERANKER_SILICONFLOW_API_KEY "sk-xxx"
setx HINDSIGHT_API_RERANKER_MODEL "BAAI/bge-reranker-v2-m3"

REM 設(shè)置后必須重新打開 CMD 窗口

REM 查看單個變量
echo %HINDSIGHT_API_LLM_MODEL%

REM 查看所有 Hindsight 變量
set HINDSIGHT

REM 驗證是否生效
curl http://localhost:8888/health