fix memory mcp

mcp/scripts/ask.py

@@ -60,18 +60,19 @@ def call_mcp(cfg, message: str):
     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):
+    # ツール定義
     tools = [
         {
             "type": "function",
             "function": {
-                "name": "memory",  # MCPツール名と一致させる
+                "name": "memory",
-                "description": "AIが記憶ログを参照するツールです",
+                "description": "記憶を検索する",
                 "parameters": {
                     "type": "object",
                     "properties": {
                         "query": {
                             "type": "string",
-                            "description": "探している記憶に関するキーワードや質問"
+                            "description": "検索する語句"
                         }
                     },
                     "required": ["query"]
@@ -80,15 +81,15 @@ def call_openai(cfg, message: str):
         }
     ]
 
+    # 最初のメッセージ送信
     payload = {
         "model": cfg["model"],
         "messages": [
-            {"role": "system", "content": "あなたはAIで、必要に応じて記憶検索ツール（memory）を使って過去の会話を参照することができます。"},
+            {"role": "system", "content": "あなたはAIで、必要に応じてツールmemoryを使って記憶を検索します。"},
             {"role": "user", "content": message}
         ],
-        "temperature": 0.7,
+        "tools": tools,
-        "tool_choice": "auto",  # AIが自律的にツールを選ぶ
+        "tool_choice": "auto"
-        "tools": tools
     }
 
     headers = {
@@ -96,25 +97,43 @@ def call_openai(cfg, message: str):
         "Content-Type": "application/json",
     }
 
-    response = requests.post(cfg["url"], headers=headers, json=payload)
+    res1 = requests.post(cfg["url"], headers=headers, json=payload)
-    response.raise_for_status()
+    res1.raise_for_status()
+    result = res1.json()
 
-    result = response.json()
+    # 🧠 tool_call されたか確認
-
-    # AIがtool_callしたかチェック
     if "tool_calls" in result["choices"][0]["message"]:
         tool_call = result["choices"][0]["message"]["tool_calls"][0]
         if tool_call["function"]["name"] == "memory":
             args = json.loads(tool_call["function"]["arguments"])
             query = args.get("query", "")
-            # ここでMCP serverにPOSTする
+            print(f"🛠️ ツール実行: memory(query='{query}')")
-            memory_response = requests.post(
+
-                "http://127.0.0.1:5000/memory/search",  # あらかじめ実装されたmemory検索用API
+            # MCPエンドポイントにPOST
-                json={"query": query}
+            memory_res = requests.post("http://127.0.0.1:5000/memory/search", json={"query": query})
-            ).json()
+            memory_json = memory_res.json()
-            return f"[Memory Tool]: {memory_response.get('result', 'なし')}"
+            tool_output = memory_json.get("result", "なし")
-    
+
-    # 通常のテキスト応答
+            # tool_outputをAIに返す
+            followup = {
+                "model": cfg["model"],
+                "messages": [
+                    {"role": "system", "content": "あなたはAIで、必要に応じてツールmemoryを使って記憶を検索します。"},
+                    {"role": "user", "content": message},
+                    {"role": "assistant", "tool_calls": result["choices"][0]["message"]["tool_calls"]},
+                    {"role": "tool", "tool_call_id": tool_call["id"], "name": "memory", "content": tool_output}
+                ]
+            }
+            print(tool_output)
+            print(cfg["model"])
+
+            res2 = requests.post(cfg["url"], headers=headers, json=followup)
+            res2.raise_for_status()
+            final_response = res2.json()
+            print(final_response)
+            return final_response["choices"][0]["message"]["content"]
+
+    # ツール未使用 or 通常応答
     return result["choices"][0]["message"]["content"]
 
 def call_ollama(cfg, message: str):
@@ -127,7 +146,6 @@ def call_ollama(cfg, message: str):
     response = requests.post(cfg["url"], headers=headers, json=payload)
     response.raise_for_status()
     return response.json().get("response", "❌ 応答が取得できませんでした")
-
 def main():
     if len(sys.argv) < 2:
         print("Usage: ask.py 'your message'")

mcp/scripts/memory_store.py

@@ -22,16 +22,29 @@ def save_message(sender, message):
     with open(path, "w") as f:
         json.dump(logs, f, indent=2, ensure_ascii=False)
 
+#def search_memory(query: str):
+#    from glob import glob
+#    all_logs = []
+#    for file_path in sorted(MEMORY_DIR.glob("*.json")):
+#        with open(file_path, "r") as f:
+#            logs = json.load(f)
+#            #matched = [entry for entry in logs if query in entry["message"]]
+#            matched = [entry for entry in logs if query.lower() in entry["message"].lower()]
+#            all_logs.extend(matched)
+#    return all_logs[-5:]  # 最新5件だけ返す
+
 def search_memory(query: str):
     from glob import glob
     all_logs = []
+    pattern = re.compile(re.escape(query), re.IGNORECASE)
+
     for file_path in sorted(MEMORY_DIR.glob("*.json")):
         with open(file_path, "r") as f:
             logs = json.load(f)
-            matched = [entry for entry in logs if query in entry["message"]]
+            matched = [entry for entry in logs if pattern.search(entry["message"])]
             all_logs.extend(matched)
-    return all_logs[-5:]  # 最新5件だけ返す
 
+    return all_logs[-5:]
 
 # scripts/memory_store.py
 import json
@@ -60,15 +73,31 @@ def save_message(sender, message):
     with open(path, "w") as f:
         json.dump(logs, f, indent=2, ensure_ascii=False)
 
-# キーワードで過去のメモリを検索する（最新5件を返す）
 def search_memory(query: str):
+    from glob import glob
     all_logs = []
     for file_path in sorted(MEMORY_DIR.glob("*.json")):
-        try:
+        with open(file_path, "r") as f:
-            with open(file_path, "r") as f:
+            logs = json.load(f)
-                logs = json.load(f)
+            matched = [
-                matched = [entry for entry in logs if query.lower() in entry["message"].lower()]
+                entry for entry in logs 
-                all_logs.extend(matched)
+                if entry["sender"] == "user" and query in entry["message"]
-        except Exception as e:
+            ]
-            print(f"⚠️ 読み込み失敗: {file_path} ({e})")
+            all_logs.extend(matched)
-    return all_logs[-5:]  # 最新5件を返す
+    return all_logs[-5:]  # 最新5件だけ返す
+def search_memory(query: str):
+    from glob import glob
+    all_logs = []
+    seen_messages = set()  # すでに見たメッセージを保持
+
+    for file_path in sorted(MEMORY_DIR.glob("*.json")):
+        with open(file_path, "r") as f:
+            logs = json.load(f)
+            for entry in logs:
+                if entry["sender"] == "user" and query in entry["message"]:
+                    # すでに同じメッセージが結果に含まれていなければ追加
+                    if entry["message"] not in seen_messages:
+                        all_logs.append(entry)
+                        seen_messages.add(entry["message"])
+
+    return all_logs[-5:]  # 最新5件だけ返す

mcp/scripts/server.py

@@ -1,9 +1,8 @@
 # server.py
-from fastapi import FastAPI
+from fastapi import FastAPI, Body
 from fastapi_mcp import FastApiMCP
 from pydantic import BaseModel
-#from memory_store import save_message, load_messages, search_memory
+from memory_store import save_message, load_logs, search_memory as do_search_memory
-from memory_store import save_message, load_logs, search_memory
 
 app = FastAPI()
 mcp = FastApiMCP(app, name="aigpt-agent", description="MCP Server for AI memory")
@@ -43,11 +42,37 @@ async def ask_message(input: MemoryQuery):
         "response": f"🔎 記憶から {len(results)} 件ヒット:\n" + "\n".join([f"{r['sender']}: {r['message']}" for r in results])
     }
 
+## こちらはうまくいく
+## curl -X POST http://127.0.0.1:5000/memory/search -H "Content-Type: application/json" -d '{"query": "昨日"}'
+## {"result":"記憶の中から「昨日」に関するデータを返しました"}
+#@app.post("/memory/search", operation_id="memory")
+#async def search_memory(input: dict):
+#    query = input.get("query", "")
+#    results = do_search_memory(query)
+#    if not results:
+#        return {"result": "該当する記憶は見つかりませんでした"}
+#    return {
+#        "result": "記憶検索結果:\n" + "\n".join([f"{r['sender']}: {r['message']}" for r in results])
+#    }
+#
+## こちらはうまくいかない
+## curl -X POST http://127.0.0.1:5000/memory/search -H "Content-Type: application/json" -d '{"query": "昨日"}'
+## Internal Server Error
+#@app.post("/memory/search", operation_id="memory")
+#async def memory_search(query: MemoryQuery):
+#    hits = search_memory(query.query)
+#    if not hits:
+#        return {"result": "🔍 記憶の中に該当する内容は見つかりませんでした。"}
+#    summary = "\n".join([f"{e['sender']}: {e['message']}" for e in hits])
+#    return {"result": f"🔎 見つかった記憶:\n{summary}"}
+
 @app.post("/memory/search", operation_id="memory")
-async def search_memory(input: dict):
+async def memory_search(query: MemoryQuery):
-    query = input.get("query", "")
+    hits = do_search_memory(query.query)  # ←ここを修正
-    # 適当なキーワード検索ロジックを追加（例: logs.jsonを検索）
+    if not hits:
-    return {"result": f"記憶の中から「{query}」に関するデータを返しました"}
+        return {"result": "🔍 記憶の中に該当する内容は見つかりませんでした。"}
+    summary = "\n".join([f"{e['sender']}: {e['message']}" for e in hits])
+    return {"result": f"🔎 見つかった記憶:\n{summary}"}
 
 # --- MCP 初期化 ---
 mcp.mount()

mcp/scripts/t.py

@@ -0,0 +1,20 @@
+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)