MemClaw + Ollama 本地部署指南：打造本地 AI 记忆系统

OpenClaw
    └── MemClaw 插件 (v0.9.36)
            ├── Qdrant（向量数据库，端口 6333/6334）
            ├── cortex-mem-service（记忆服务，端口 8085）
            ├── LLM → Ollama（qwen2.5:3b，端口 11434）
            └── Embedding → Ollama（nomic-embed-text，端口 11434）

Web 控制台
    └── Cortex Memory Insights（端口 8159）

// 修改前（Ollama 旧版本）
struct EmbeddingRequest {
    prompt: Vec<String>,  // ❌ 数组格式
    model: String,
}

// 修改后（Ollama 0.19+）
struct EmbeddingRequest {
    prompt: String,  // ✅ 单个字符串
    model: String,
}

// 遍历每个文本，单独调用 API
for text in texts.iter() {
    let request = EmbeddingRequest {
        prompt: text.clone(),
        model: self.config.model_name.clone(),
    };
    // ... 调用 API
}

[llm]
api_base_url = "http://localhost:11434/v1"   # ✅ OpenAI 兼容格式

[embedding]
api_base_url = "http://localhost:11434/api"   # ✅ Ollama 原生格式

$qdrantBin = "$env:USERPROFILE\.openclaw\extensions\memclaw\node_modules\@memclaw\bin-win-x64\bin\qdrant.exe"
Start-Process -FilePath $qdrantBin

[qdrant]
url = "http://localhost:6334"
collection_name = "cortex-memory"
embedding_dim = 768
timeout_secs = 30

[embedding]
api_base_url = "http://localhost:11434/api"
api_key = "ollama"
model_name = "nomic-embed-text"
batch_size = 10
timeout_secs = 60

[llm]
api_base_url = "http://localhost:11434/v1"
api_key = "ollama"
model_efficient = "qwen2.5:3b"
temperature = 0.7
max_tokens = 100
timeout_secs = 60

[server]
host = "0.0.0.0"
port = 8085
cors_origins = ["*"]

[logging]
enabled = false
log_directory = "logs"
level = "info"

[cortex]
enable_intent_analysis = false

# MemClaw Auto-Start Script

$ErrorActionPreference = "Stop"

Write-Host "Starting MemClaw services..."

# 1. 启动 Qdrant
$qdrantPath = "$env:USERPROFILE\.openclaw\extensions\memclaw\node_modules\@memclaw\bin-win-x64\bin\qdrant.exe"
$qdrantWorkDir = "$env:USERPROFILE\.openclaw\extensions\memclaw"

if (Get-NetTCPConnection -LocalPort 6333 -ErrorAction SilentlyContinue | Where-Object { $_.State -eq "Listen" }) {
    Write-Host "Qdrant already running"
} else {
    Write-Host "Starting Qdrant..."
    Start-Process -FilePath $qdrantPath -WorkingDirectory $qdrantWorkDir
    Start-Sleep -Seconds 3
}

# 2. 启动 cortex-mem-service
$cortexPath = "$env:USERPROFILE\.openclaw\extensions\memclaw\node_modules\@memclaw\bin-win-x64\bin\cortex-mem-service.exe"
$configPath = "$env:USERPROFILE\.openclaw\extensions\memclaw\config.toml"

if (Get-NetTCPConnection -LocalPort 8085 -ErrorAction SilentlyContinue | Where-Object { $_.State -eq "Listen" }) {
    Write-Host "cortex-mem-service already running"
} else {
    Write-Host "Starting cortex-mem-service..."
    Start-Process -FilePath $cortexPath -ArgumentList "--config", $configPath -WorkingDirectory $qdrantWorkDir
    Start-Sleep -Seconds 5
}

# 3. 验证服务状态
Write-Host "`nVerifying services..."

$qdrantRunning = Get-NetTCPConnection -LocalPort 6333 -ErrorAction SilentlyContinue | Where-Object { $_.State -eq "Listen" }
if ($qdrantRunning) { Write-Host "✅ Qdrant (6333) - running" } else { Write-Host "❌ Qdrant - NOT running" }

try {
    $health = Invoke-RestMethod -Uri "http://localhost:8085/health" -TimeoutSec 5
    Write-Host "✅ cortex-mem-service - running (status: $($health.status))"
} catch {
    Write-Host "❌ cortex-mem-service - NOT running"
}

Write-Host "`nDone."

# 存入一条记忆
$body = @{
    role = "user"
    content = "今天完成了MemClaw的Ollama embedding API修复，解决了Ollama API从input改为prompt的问题"
} | ConvertTo-Json

Invoke-RestMethod -Uri "http://localhost:8085/api/v2/sessions/default/messages" `
    -Method Post `
    -ContentType "application/json" `
    -Body $body

# 检索记忆
$body = @{
    query = "MemClaw embedding 修复"
    limit = 3
} | ConvertTo-Json

$r = Invoke-RestMethod -Uri "http://localhost:8085/api/v2/search" `
    -Method Post `
    -ContentType "application/json" `
    -Body $body

$r.data | ForEach-Object {
    Write-Host "Score: $($_.score) - $($_.uri)"
}