fix mcp

Cargo.toml

@@ -12,3 +12,4 @@ rusqlite = { version = "0.29", features = ["serde_json"] }
 shellexpand = "*"
 fs_extra = "1.3"
 rand = "0.9.1"
+reqwest = { version = "*", features = ["blocking", "json"] }

mcp/scripts/ask.py

@@ -1,28 +1,118 @@
 ## scripts/ask.py
+#import sys
+#import requests
+#from config import load_config
+#
+#def ask(prompt):
+#    cfg = load_config()
+#    if cfg["provider"] == "ollama":
+#        payload = {"model": cfg["model"], "prompt": prompt, "stream": False}
+#        response = requests.post(cfg["url"], json=payload)
+#        print(response.json().get("response", "❌ No response"))
+#    else:
+#        headers = {
+#            "Authorization": f"Bearer {cfg['api_key']}",
+#            "Content-Type": "application/json"
+#        }
+#        payload = {
+#            "model": cfg["model"],
+#            "messages": [{"role": "user", "content": prompt}]
+#        }
+#        response = requests.post(cfg["url"], headers=headers, json=payload)
+#        print(response.json().get("choices", [{}])[0].get("message", {}).get("content", "❌ No content"))
+#
+#if __name__ == "__main__":
+#    if len(sys.argv) < 2:
+#        print("Usage: python ask.py 'your message'")
+#        sys.exit(1)
+#    ask(sys.argv[1])
+
 import sys
+import json
 import requests
+from datetime import datetime
 from config import load_config
 
-def ask(prompt):
+def build_payload_mcp(message: str):
-    cfg = load_config()
+    return {
-    if cfg["provider"] == "ollama":
+        "tool": "ask_message",  # MCPサーバー側で定義されたツール名
-        payload = {"model": cfg["model"], "prompt": prompt, "stream": False}
+        "input": {
-        response = requests.post(cfg["url"], json=payload)
+            "message": message
-        print(response.json().get("response", "❌ No response"))
+        }
-    else:
+    }
+
+def build_payload_openai(cfg, message: str):
+    return {
+        "model": cfg["model"],
+        "messages": [
+            {"role": "system", "content": "あなたは思いやりのあるAIです。"},
+            {"role": "user", "content": message}
+        ],
+        "temperature": 0.7
+    }
+
+def call_mcp(cfg, message: str):
+    payload = build_payload_mcp(message)
+    headers = {"Content-Type": "application/json"}
+    response = requests.post(cfg["url"], headers=headers, json=payload)
+    response.raise_for_status()
+    return response.json().get("output", {}).get("response", "❓ 応答が取得できませんでした")
+
+def call_openai(cfg, message: str):
+    payload = build_payload_openai(cfg, message)
     headers = {
         "Authorization": f"Bearer {cfg['api_key']}",
-            "Content-Type": "application/json"
+        "Content-Type": "application/json",
-        }
-        payload = {
-            "model": cfg["model"],
-            "messages": [{"role": "user", "content": prompt}]
     }
     response = requests.post(cfg["url"], headers=headers, json=payload)
-        print(response.json().get("choices", [{}])[0].get("message", {}).get("content", "❌ No content"))
+    response.raise_for_status()
+    return response.json()["choices"][0]["message"]["content"]
+
+def main():
+    if len(sys.argv) < 2:
+        print("Usage: ask.py 'your message'")
+        return
+
+    message = sys.argv[1]
+    cfg = load_config()
+
+    print(f"🔍 使用プロバイダー: {cfg['provider']}")
+
+    try:
+        if cfg["provider"] == "openai":
+            response = call_openai(cfg, message)
+        elif cfg["provider"] == "mcp":
+            response = call_mcp(cfg, message)
+        else:
+            raise ValueError(f"未対応のプロバイダー: {cfg['provider']}")
+
+        print("💬 応答:")
+        print(response)
+
+        # ログ保存（オプション）
+        save_log(message, response)
+
+    except Exception as e:
+        print(f"❌ 実行エラー: {e}")
+
+def save_log(user_msg, ai_msg):
+    from config import MEMORY_DIR
+    date_str = datetime.now().strftime("%Y-%m-%d")
+    path = MEMORY_DIR / f"{date_str}.json"
+    path.parent.mkdir(parents=True, exist_ok=True)
+
+    if path.exists():
+        with open(path, "r") as f:
+            logs = json.load(f)
+    else:
+        logs = []
+
+    now = datetime.utcnow().isoformat() + "Z"
+    logs.append({"timestamp": now, "sender": "user", "message": user_msg})
+    logs.append({"timestamp": now, "sender": "ai", "message": ai_msg})
+
+    with open(path, "w") as f:
+        json.dump(logs, f, indent=2, ensure_ascii=False)
 
 if __name__ == "__main__":
-    if len(sys.argv) < 2:
+    main()
-        print("Usage: python ask.py 'your message'")
-        sys.exit(1)
-    ask(sys.argv[1])

mcp/scripts/config.py

@@ -1,7 +1,18 @@
 # scripts/config.py
+# scripts/config.py
 import os
 from pathlib import Path
 
+# ディレクトリ設定
+BASE_DIR = Path.home() / ".config" / "aigpt"
+MEMORY_DIR = BASE_DIR / "memory"
+SUMMARY_DIR = MEMORY_DIR / "summary"
+
+def init_directories():
+    BASE_DIR.mkdir(parents=True, exist_ok=True)
+    MEMORY_DIR.mkdir(parents=True, exist_ok=True)
+    SUMMARY_DIR.mkdir(parents=True, exist_ok=True)
+
 def load_config():
     provider = os.getenv("PROVIDER", "ollama")
     model = os.getenv("MODEL", "syui/ai" if provider == "ollama" else "gpt-4o-mini")
@@ -20,15 +31,11 @@ def load_config():
             "api_key": api_key,
             "url": f"{os.getenv('OPENAI_API_BASE', 'https://api.openai.com/v1')}/chat/completions"
         }
+    elif provider == "mcp":
+        return {
+            "provider": "mcp",
+            "model": model,
+            "url": os.getenv("MCP_URL", "http://localhost:5000/chat")
+        }
     else:
         raise ValueError(f"Unsupported provider: {provider}")
-
-# ディレクトリ設定
-BASE_DIR = Path.home() / ".config" / "aigpt"
-MEMORY_DIR = BASE_DIR / "memory"
-SUMMARY_DIR = MEMORY_DIR / "summary"
-
-# 初期化（必要に応じて作成）
-BASE_DIR.mkdir(parents=True, exist_ok=True)
-MEMORY_DIR.mkdir(parents=True, exist_ok=True)
-SUMMARY_DIR.mkdir(parents=True, exist_ok=True)

mcp/scripts/memory_store.py

@@ -0,0 +1,37 @@
+# scripts/memory_store.py
+from pathlib import Path
+import json
+from datetime import datetime
+
+MEMORY_DIR = Path.home() / ".config" / "aigpt" / "memory"
+MEMORY_DIR.mkdir(parents=True, exist_ok=True)
+
+def get_today_path():
+    today = datetime.utcnow().strftime("%Y-%m-%d")
+    return MEMORY_DIR / f"{today}.json"
+
+def save_message(sender: str, message: str):
+    entry = {
+        "timestamp": datetime.utcnow().isoformat(),
+        "sender": sender,
+        "message": message
+    }
+
+    path = get_today_path()
+    data = []
+
+    if path.exists():
+        with open(path, "r") as f:
+            data = json.load(f)
+
+    data.append(entry)
+
+    with open(path, "w") as f:
+        json.dump(data, f, indent=2, ensure_ascii=False)
+
+def load_messages():
+    path = get_today_path()
+    if not path.exists():
+        return []
+    with open(path, "r") as f:
+        return json.load(f)

mcp/scripts/server.py

@@ -1,21 +1,62 @@
 # server.py
+#from fastapi import FastAPI
+#from fastapi_mcp import FastApiMCP
+#
+#app = FastAPI()
+#
+#@app.get("/items/{item_id}", operation_id="get_item")
+#async def read_item(item_id: int):
+#    return {"item_id": item_id, "name": f"Item {item_id}"}
+#
+## MCPサーバを作成し、FastAPIアプリにマウント
+#mcp = FastApiMCP(
+#    app,
+#    name="My API MCP",
+#    description="My API description"
+#)
+#mcp.mount()
+#
+#if __name__ == "__main__":
+#    import uvicorn
+#    uvicorn.run(app, host="0.0.0.0", port=8000)
+
 from fastapi import FastAPI
 from fastapi_mcp import FastApiMCP
+from pydantic import BaseModel
+from memory_store import save_message, load_messages
 
 app = FastAPI()
+mcp = FastApiMCP(app, name="aigpt-agent", description="MCP Server for AI memory")
 
-@app.get("/items/{item_id}", operation_id="get_item")
+# --- モデル定義 ---
-async def read_item(item_id: int):
+class ChatInput(BaseModel):
-    return {"item_id": item_id, "name": f"Item {item_id}"}
+    message: str
 
-# MCPサーバを作成し、FastAPIアプリにマウント
+class MemoryInput(BaseModel):
-mcp = FastApiMCP(
+    sender: str
-    app,
+    message: str
-    name="My API MCP",
+
-    description="My API description"
+# --- ツール（エンドポイント）定義 ---
-)
+@app.post("/chat", operation_id="chat")
+async def chat(input: ChatInput):
+    save_message("user", input.message)
+    response = f"AI: 「{input.message}」を受け取りました！"
+    save_message("ai", response)
+    return {"response": response}
+
+@app.post("/memory", operation_id="save_memory")
+async def memory_post(input: MemoryInput):
+    save_message(input.sender, input.message)
+    return {"status": "saved"}
+
+@app.get("/memory", operation_id="get_memory")
+async def memory_get():
+    return {"messages": load_messages()}
+
+# --- MCP 初期化 ---
 mcp.mount()
 
 if __name__ == "__main__":
     import uvicorn
-    uvicorn.run(app, host="0.0.0.0", port=8000)
+    print("🚀 Starting MCP server...")
+    uvicorn.run(app, host="127.0.0.1", port=5000)

src/chat.rs

@@ -5,11 +5,16 @@ use serde::Deserialize;
 use seahorse::Context;
 use crate::config::ConfigPaths;
 use crate::metrics::{load_user_data, save_user_data, update_metrics_decay};
+use std::process::Stdio;
+use std::io::Write;
+use std::time::Duration;
+use std::net::TcpStream;
 
 #[derive(Debug, Clone, PartialEq)]
 pub enum Provider {
     OpenAI,
     Ollama,
+    MCP,
 }
 
 impl Provider {
@@ -17,6 +22,7 @@ impl Provider {
         match s.to_lowercase().as_str() {
             "openai" => Some(Provider::OpenAI),
             "ollama" => Some(Provider::Ollama),
+            "mcp" => Some(Provider::MCP),
             _ => None,
         }
     }
@@ -25,6 +31,7 @@ impl Provider {
         match self {
             Provider::OpenAI => "openai",
             Provider::Ollama => "ollama",
+            Provider::MCP => "mcp",
         }
     }
 }
@@ -50,13 +57,6 @@ pub fn ask_chat(c: &Context, question: &str) -> Option<String> {
     let mut user = load_user_data(&user_path);
     user.metrics = update_metrics_decay();
 
-    // Python 実行パス
-    let python_path = if cfg!(target_os = "windows") {
-        base_dir.join(".venv/Scripts/mcp.exe")
-    } else {
-        base_dir.join(".venv/bin/mcp")
-    };
-
     // 各種オプション
     let ollama_host = c.string_flag("host").ok();
     let ollama_model = c.string_flag("model").ok();
@@ -66,7 +66,42 @@ pub fn ask_chat(c: &Context, question: &str) -> Option<String> {
 
     println!("🔍 使用プロバイダー: {}", provider.as_str());
 
-    // Python コマンド準備
+    match provider {
+        Provider::MCP => {
+            let client = reqwest::blocking::Client::new();
+            let url = std::env::var("MCP_URL").unwrap_or("http://127.0.0.1:5000/chat".to_string());
+            let res = client.post(url)
+                .json(&serde_json::json!({"message": question}))
+                .send();
+
+            match res {
+                Ok(resp) => {
+                    if resp.status().is_success() {
+                        let json: serde_json::Value = resp.json().ok()?;
+                        let text = json.get("response")?.as_str()?.to_string();
+                        user.metrics.intimacy += 0.01;
+                        user.metrics.last_updated = chrono::Utc::now();
+                        save_user_data(&user_path, &user);
+                        Some(text)
+                    } else {
+                        eprintln!("❌ MCPエラー: HTTP {}", resp.status());
+                        None
+                    }
+                }
+                Err(e) => {
+                    eprintln!("❌ MCP接続失敗: {}", e);
+                    None
+                }
+            }
+        }
+        _ => {
+            // Python 実行パス
+            let python_path = if cfg!(target_os = "windows") {
+                base_dir.join(".venv/Scripts/mcp.exe")
+            } else {
+                base_dir.join(".venv/bin/mcp")
+            };
+
             let mut command = Command::new(python_path);
             command.arg("ask").arg(question);
 
@@ -100,4 +135,6 @@ pub fn ask_chat(c: &Context, question: &str) -> Option<String> {
                 );
                 None
             }
+        }
+    }
 }