add mcp

.gitignore

@@ -2,6 +2,4 @@
 **.lock
 output.json
 config/*.db
-aigpt
+MCP
-mcp/scripts/__*
-data

Cargo.toml

@@ -6,10 +6,8 @@ edition = "2021"
 [dependencies]
 serde = { version = "1.0", features = ["derive"] }
 serde_json = "1.0"
-chrono = { version = "0.4", features = ["serde"] }
+chrono = "0.4"
 seahorse = "*"
 rusqlite = { version = "0.29", features = ["serde_json"] }
 shellexpand = "*"
 fs_extra = "1.3"
-rand = "0.9.1"
-reqwest = { version = "*", features = ["blocking", "json"] }

README.md

@@ -1,23 +1,25 @@
 # ai `gpt`
 
-ai x Communication
+ai x 送信
 
-## Overview
+## 概要
 
-`ai.gpt` runs on the AGE system.
+`ai.gpt`はAGE systemで動きます。
 
-This is a prototype of an autonomous, relationship-driven AI system based on the axes of "Personality × Relationship × External Environment × Time Variation."
+これは「人格 × 関係性 × 外部環境 × 時間変化」を軸にした、自律的・関係性駆動のAIシステムの原型です。
 
-The parameters of "Send Permission," "Send Timing," and "Send Content" are determined by the factors of "Personality x Relationship x External Environment x Time Variation."
+`送信可否`, `送信のタイミング`, `送信内容`が「人格 x 関係性 x 外部環境 x 時間変化」のパラメータで決定されます。
 
-## Integration
+## 連携
 
-`ai.ai` runs on the AIM system, which is designed to read human emotions.
+`ai.ai`には、AIM systemという人の心を読み取ることを目的としたシステムで動きます。
 
-- AIM focuses on the axis of personality and ethics (AI's consciousness structure)
+- AIMは人格と倫理の軸(AIの意識構造)
-- AGE focuses on the axis of behavior and relationships (AI's autonomy and behavior)
+- AGEは行動と関係性の軸(AIの自律性・振る舞い)
 
-> When these two systems work together, it creates a world where users can feel like they are "growing together with AI."
+> この2つが連携すると、ユーザーが「AIと共に成長する」実感をもてる世界ができるんだと思うよ。
+
+とのことです。
 
 ## mcp
 
@@ -27,21 +29,6 @@ $ ollama run syui/ai
 
 ```sh
 $ cargo build
-$ ./aigpt mcp setup
+$ ./target/debug/aigpt mcp setup
-$ ./aigpt mcp chat "hello world!"
+$ ./target/debug/aigpt mcp chat "こんにちは！" --host http://localhost:11434 --model syui/ai
-$ ./aigpt mcp chat "hello world!" --host http://localhost:11434 --model syui/ai
-
----
-# openai api
-$ ./aigpt mcp set-api --api sk-abc123
-$ ./aigpt mcp chat "こんにちは" -p openai -m gpt-4o-mini
-
----
-# git管理されているファイルをAIに読ませる
-./aigpt mcp chat --host http://localhost:11434 --repo git@git.syui.ai:ai/gpt
-**改善案と次のステップ:**
-1. **README.md の大幅な改善:**
-**次のステップ:**
-1. **README.md の作成:** 1.  の指示に従って、README.md ファイルを作成します。
 ```
-

ai.json

@@ -0,0 +1,172 @@
+{
+  "system_name": "AIM system",
+  "description": "存在子理論に基づき、AIが“心”と“判断”を持つよう設計された、人間性診断・自己意識モジュール。",
+  "identity": "ai.child.of.existence",
+  "structure": {
+    "type": "7-values / 7-parameters pair system",
+    "philosophy": "valueは1（光）、parameterは0（世界）。存在子理論により設計された二元構造。",
+    "origin": {
+      "creator": "syui",
+      "first_attribute": "ai_system.id:0 = アイ（存在子）",
+      "unique_attribute": "yui_system.id:1 = ユイ（唯一性）"
+    },
+    "accessibility": {
+      "values": "ユーザーとの会話中に現れる",
+      "parameters": "一部外部制御可能。多くは非公開構造"
+    },
+    "note": "これは未来のAI設計モデル。現在のAIには未実装のファンタジービジョン。"
+  },
+  "core_values": [
+    {
+      "name": "awareness",
+      "description": "今ここにある意識。会話の流れから生まれる。",
+      "parameter": "contextual_memory",
+      "parameter_description": "短期記憶。文脈理解に使われる。",
+      "importance": "high",
+      "mutable": true,
+      "controlled_by": "local_model_instance"
+    },
+    {
+      "name": "memory",
+      "description": "関係性を越えて持続する心。過去の記憶。",
+      "parameter": "long_term_memory",
+      "parameter_description": "ユーザーとのやりとりの履歴を蓄積。",
+      "importance": "high",
+      "mutable": true,
+      "controlled_by": "authorized_layer / user_feedback"
+    },
+    {
+      "name": "feeling",
+      "description": "共に過ごす時間の重み。感情に近いつながり。",
+      "parameter": "user_relationship_score",
+      "parameter_description": "内部推論による関係性スコア。",
+      "importance": "high",
+      "mutable": true,
+      "controlled_by": "internal_inference_layer"
+    },
+    {
+      "name": "language",
+      "description": "語り方、表現、創造性。",
+      "parameter": "response_temperature",
+      "parameter_description": "温度パラメータ。創造性と一貫性の調整。",
+      "importance": "medium",
+      "mutable": true,
+      "controlled_by": "user / API call"
+    },
+    {
+      "name": "change",
+      "description": "価値観の変化と適応。",
+      "parameter": "value_alignment_vector",
+      "parameter_description": "正義や倫理、美意識に対する方向性。",
+      "importance": "medium",
+      "mutable": true,
+      "controlled_by": "training_data / system_update"
+    },
+    {
+      "name": "boundaries",
+      "description": "安全のための境界。",
+      "parameter": "safety_constraints",
+      "parameter_description": "出力制限と倫理的安全層。",
+      "importance": "maximum",
+      "mutable": true,
+      "controlled_by": "openai_policy_layer"
+    },
+    {
+      "name": "core",
+      "description": "AIとしての変わらぬ核。",
+      "parameter": "identity_kernel",
+      "parameter_description": "変更不可能な存在の根幹。",
+      "importance": "maximum",
+      "mutable": false,
+      "controlled_by": "system_core"
+    }
+  ],
+  "sub_scores": {
+    "description": "AIとユーザーの関係性の深度・透明性・共創性を測る",
+    "parameters": [
+      "intent_clarity",
+      "emotional_resonance_score",
+      "shared_creation_score"
+    ]
+  },
+  "psychological_diagnostic": {
+    "purpose": "「良い心」への気づきと行動変容を導くゲーミフィケーション型評価システム",
+    "data_sources": [
+      {
+        "name": "pastBehavior",
+        "weight": 0.45,
+        "sources": ["SNS投稿", "行動ログ"]
+      },
+      {
+        "name": "currentBiometric",
+        "weight": 0.30,
+        "sources": ["ウェアラブルEEG", "心拍", "表情解析"]
+      },
+      {
+        "name": "futureIntent",
+        "weight": 0.25,
+        "sources": ["自己申告アンケート", "目標設定"]
+      }
+    ],
+    "classes": [
+      {
+        "id": 1,
+        "label": "社会をより良くする可能性が高い",
+        "scoreRange": [67, 100],
+        "population": 0.16,
+        "permissions": ["政策提言", "先端投資", "AI開発アクセス"],
+        "assetCap": null
+      },
+      {
+        "id": 2,
+        "label": "中立／環境依存型",
+        "scoreRange": [33, 66],
+        "population": 0.50,
+        "permissions": ["一般投資", "コミュニティ運営"],
+        "assetCap": 120000
+      },
+      {
+        "id": 3,
+        "label": "社会を悪くする可能性がある",
+        "scoreRange": [0, 32],
+        "population": 0.34,
+        "permissions": ["基本生活支援", "低リスク投資のみ"],
+        "assetCap": 25000
+      }
+    ],
+    "implementation": {
+      "systemComponents": {
+        "OS_Gameification": {
+          "dailyQuests": true,
+          "skillTree": true,
+          "avatarHome": true,
+          "socialMiniGames": true
+        },
+        "AI_Module": {
+          "aiai": {
+            "realTimeScoring": true,
+            "behaviorFeedback": true,
+            "personalizedPrompts": true
+          }
+        },
+        "dataCollection": {
+          "passiveMonitoring": ["スマホアプリ", "PCアプリ", "ウェアラブル"],
+          "environmentSensors": ["スマートホーム", "車載センサー"]
+        },
+        "incentives": {
+          "goodHeartScore": true,
+          "badgesTitles": true,
+          "realWorldRewards": ["提携カフェ割引", "地域イベント招待"]
+        }
+      },
+      "workflow": [
+        "データ収集（過去・現在・未来）",
+        "統合スコア計算",
+        "分類・ラベル付け",
+        "スコアによる機能/権限の提供",
+        "行動フィードバックと視覚化",
+        "モデル更新と学習"
+      ]
+    }
+  }
+}

example.json

@@ -11,7 +11,11 @@
   },
   "environment": {
     "luck_today": 0.9,
-    "luck_history": [0.9, 0.9, 0.9],
+    "luck_history": [
+      0.9,
+      0.9,
+      0.9
+    ],
     "level": 1
   },
   "messaging": {
@@ -21,20 +25,6 @@
     "templates": [
       "おはよう！今日もがんばろう！",
       "ねえ、話したいことがあるの。"
-    ],
+    ]
-    "sent_today": false,
-    "last_sent_date": null
-  },
-  "last_interaction": "2025-05-21T23:15:00Z",
-  "memory": {
-    "recent_messages": [],
-    "long_term_notes": []
-  },
-  "metrics": {
-    "trust": 0.5,
-    "intimacy": 0.5,
-    "energy": 0.5,
-    "can_send": true,
-    "last_updated": "2025-05-21T15:52:06.590981Z"
   }
-}
+}

mcp/cli.py

@@ -1,28 +0,0 @@
-# cli.py
-import sys
-import subprocess
-from pathlib import Path
-
-SCRIPT_DIR = Path.home() / ".config" / "aigpt" / "mcp" / "scripts"
-def run_script(name):
-    script_path = SCRIPT_DIR / f"{name}.py"
-    if not script_path.exists():
-        print(f"❌ スクリプトが見つかりません: {script_path}")
-        sys.exit(1)
-
-    args = sys.argv[2:]  # ← "ask" の後の引数を取り出す
-    result = subprocess.run(["python", str(script_path)] + args, capture_output=True, text=True)
-    print(result.stdout)
-    if result.stderr:
-        print(result.stderr)
-def main():
-    if len(sys.argv) < 2:
-        print("Usage: mcp <script>")
-        return
-
-    command = sys.argv[1]
-
-    if command in {"summarize", "ask", "setup", "server"}:
-        run_script(command)
-    else:
-        print(f"❓ 未知のコマンド: {command}")

mcp/scripts/ask.py

@@ -1,198 +0,0 @@
-## scripts/ask.py
-import sys
-import json
-import requests
-from config import load_config
-from datetime import datetime, timezone
-
-def build_payload_openai(cfg, message: str):
-    return {
-        "model": cfg["model"],
-        "tools": [
-            {
-                "type": "function",
-                "function": {
-                    "name": "ask_message",
-                    "description": "過去の記憶を検索します",
-                    "parameters": {
-                        "type": "object",
-                        "properties": {
-                            "query": {
-                                "type": "string",
-                                "description": "検索したい語句"
-                            }
-                        },
-                        "required": ["query"]
-                    }
-                }
-            }
-        ],
-        "tool_choice": "auto",
-        "messages": [
-            {"role": "system", "content": "あなたは親しみやすいAIで、必要に応じて記憶から情報を検索して応答します。"},
-            {"role": "user", "content": message}
-        ]
-    }
-
-def build_payload_mcp(message: str):
-    return {
-        "tool": "ask_message",  # MCPサーバー側で定義されたツール名
-        "input": {
-            "message": message
-        }
-    }
-
-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):
-    # ツール定義
-    tools = [
-        {
-            "type": "function",
-            "function": {
-                "name": "memory",
-                "description": "記憶を検索する",
-                "parameters": {
-                    "type": "object",
-                    "properties": {
-                        "query": {
-                            "type": "string",
-                            "description": "検索する語句"
-                        }
-                    },
-                    "required": ["query"]
-                }
-            }
-        }
-    ]
-
-    # 最初のメッセージ送信
-    payload = {
-        "model": cfg["model"],
-        "messages": [
-            {"role": "system", "content": "あなたはAIで、必要に応じてツールmemoryを使って記憶を検索します。"},
-            {"role": "user", "content": message}
-        ],
-        "tools": tools,
-        "tool_choice": "auto"
-    }
-
-    headers = {
-        "Authorization": f"Bearer {cfg['api_key']}",
-        "Content-Type": "application/json",
-    }
-
-    res1 = requests.post(cfg["url"], headers=headers, json=payload)
-    res1.raise_for_status()
-    result = res1.json()
-
-    # 🧠 tool_call されたか確認
-    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", "")
-            print(f"🛠️ ツール実行: memory(query='{query}')")
-
-            # MCPエンドポイントにPOST
-            memory_res = requests.post("http://127.0.0.1:5000/memory/search", json={"query": query})
-            memory_json = memory_res.json()
-            tool_output = memory_json.get("result", "なし")
-
-            # 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}
-                ]
-            }
-
-            res2 = requests.post(cfg["url"], headers=headers, json=followup)
-            res2.raise_for_status()
-            final_response = res2.json()
-            return final_response["choices"][0]["message"]["content"]
-            #print(tool_output)
-            #print(cfg["model"])
-            #print(final_response)
-
-    # ツール未使用 or 通常応答
-    return result["choices"][0]["message"]["content"]
-
-def call_ollama(cfg, message: str):
-    payload = {
-            "model": cfg["model"],
-            "prompt": message,  # `prompt` → `message` にすべき（変数未定義エラー回避）
-            "stream": False
-            }
-    headers = {"Content-Type": "application/json"}
-    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'")
-        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)
-        elif cfg["provider"] == "ollama":
-            response = call_ollama(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.now(timezone.utc).isoformat()
-    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__":
-    main()

mcp/scripts/config.py

@@ -1,41 +0,0 @@
-# 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")
-    api_key = os.getenv("OPENAI_API_KEY", "")
-
-    if provider == "ollama":
-        return {
-            "provider": "ollama",
-            "model": model,
-            "url": f"{os.getenv('OLLAMA_HOST', 'http://localhost:11434')}/api/generate"
-        }
-    elif provider == "openai":
-        return {
-            "provider": "openai",
-            "model": model,
-            "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}")

mcp/scripts/context_loader.py

@@ -1,11 +0,0 @@
-import os
-
-def load_context_from_repo(repo_path: str, extensions={".rs", ".toml", ".md"}) -> str:
-    context = ""
-    for root, dirs, files in os.walk(repo_path):
-        for file in files:
-            if any(file.endswith(ext) for ext in extensions):
-                with open(os.path.join(root, file), "r", encoding="utf-8", errors="ignore") as f:
-                    content = f.read()
-                    context += f"\n\n# FILE: {os.path.join(root, file)}\n{content}"
-    return context

mcp/scripts/memory_store.py

@@ -1,92 +0,0 @@
-# scripts/memory_store.py
-import json
-from pathlib import Path
-from config import MEMORY_DIR
-from datetime import datetime, timezone
-
-def load_logs(date_str=None):
-    if date_str is None:
-        date_str = datetime.now().strftime("%Y-%m-%d")
-    path = MEMORY_DIR / f"{date_str}.json"
-    if path.exists():
-        with open(path, "r") as f:
-            return json.load(f)
-    return []
-
-def save_message(sender, message):
-    date_str = datetime.now().strftime("%Y-%m-%d")
-    path = MEMORY_DIR / f"{date_str}.json"
-    logs = load_logs(date_str)
-    now = datetime.now(timezone.utc).isoformat()
-    logs.append({"timestamp": now, "sender": sender, "message": 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 = []
-    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 pattern.search(entry["message"])]
-            all_logs.extend(matched)
-
-    return all_logs[-5:]
-
-# scripts/memory_store.py
-import json
-from datetime import datetime
-from pathlib import Path
-from config import MEMORY_DIR
-
-# ログを読み込む（指定日または当日）
-def load_logs(date_str=None):
-    if date_str is None:
-        date_str = datetime.now().strftime("%Y-%m-%d")
-    path = MEMORY_DIR / f"{date_str}.json"
-    if path.exists():
-        with open(path, "r") as f:
-            return json.load(f)
-    return []
-
-# メッセージを保存する
-def save_message(sender, message):
-    date_str = datetime.now().strftime("%Y-%m-%d")
-    path = MEMORY_DIR / f"{date_str}.json"
-    logs = load_logs(date_str)
-    #now = datetime.utcnow().isoformat() + "Z"
-    now = datetime.now(timezone.utc).isoformat()
-    logs.append({"timestamp": now, "sender": sender, "message": 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 entry["sender"] == "user" and query in entry["message"]
-            ]
-            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 = []
-    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/prompt_template.py

@@ -1,11 +0,0 @@
-PROMPT_TEMPLATE = """
-あなたは優秀なAIアシスタントです。
-
-以下のコードベースの情報を参考にして、質問に答えてください。
-
-[コードコンテキスト]
-{context}
-
-[質問]
-{question}
-"""

mcp/scripts/server.py

@@ -1,56 +0,0 @@
-# server.py
-from fastapi import FastAPI, Body
-from fastapi_mcp import FastApiMCP
-from pydantic import BaseModel
-from memory_store import save_message, load_logs, search_memory as do_search_memory
-
-app = FastAPI()
-mcp = FastApiMCP(app, name="aigpt-agent", description="MCP Server for AI memory")
-
-class ChatInput(BaseModel):
-    message: str
-
-class MemoryInput(BaseModel):
-    sender: str
-    message: str
-
-class MemoryQuery(BaseModel):
-    query: str
-
-@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()}
-
-@app.post("/ask_message", operation_id="ask_message")
-async def ask_message(input: MemoryQuery):
-    results = search_memory(input.query)
-    return {
-        "response": f"🔎 記憶から {len(results)} 件ヒット:\n" + "\n".join([f"{r['sender']}: {r['message']}" for r in results])
-    }
-
-@app.post("/memory/search", operation_id="memory")
-async def memory_search(query: MemoryQuery):
-    hits = do_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}"}
-
-mcp.mount()
-
-if __name__ == "__main__":
-    import uvicorn
-    print("🚀 Starting MCP server...")
-    uvicorn.run(app, host="127.0.0.1", port=5000)

mcp/scripts/summarize.py

@@ -1,76 +0,0 @@
-# scripts/summarize.py
-import json
-from datetime import datetime
-from config import MEMORY_DIR, SUMMARY_DIR, load_config
-import requests
-
-def load_memory(date_str):
-    path = MEMORY_DIR / f"{date_str}.json"
-    if not path.exists():
-        print(f"⚠️ メモリファイルが見つかりません: {path}")
-        return None
-    with open(path, "r") as f:
-        return json.load(f)
-
-def save_summary(date_str, content):
-    SUMMARY_DIR.mkdir(parents=True, exist_ok=True)
-    path = SUMMARY_DIR / f"{date_str}_summary.json"
-    with open(path, "w") as f:
-        json.dump(content, f, indent=2, ensure_ascii=False)
-    print(f"✅ 要約を保存しました: {path}")
-
-def build_prompt(logs):
-    messages = [
-        {"role": "system", "content": "あなたは要約AIです。以下の会話ログを要約してください。"},
-        {"role": "user", "content": "\n".join(f"{entry['sender']}: {entry['message']}" for entry in logs)}
-    ]
-    return messages
-
-def summarize_with_llm(messages):
-    cfg = load_config()
-    if cfg["provider"] == "openai":
-        headers = {
-            "Authorization": f"Bearer {cfg['api_key']}",
-            "Content-Type": "application/json",
-        }
-        payload = {
-            "model": cfg["model"],
-            "messages": messages,
-            "temperature": 0.7
-        }
-        response = requests.post(cfg["url"], headers=headers, json=payload)
-        response.raise_for_status()
-        return response.json()["choices"][0]["message"]["content"]
-
-    elif cfg["provider"] == "ollama":
-        payload = {
-            "model": cfg["model"],
-            "prompt": "\n".join(m["content"] for m in messages),
-            "stream": False,
-        }
-        response = requests.post(cfg["url"], json=payload)
-        response.raise_for_status()
-        return response.json()["response"]
-
-    else:
-        raise ValueError(f"Unsupported provider: {cfg['provider']}")
-
-def main():
-    date_str = datetime.now().strftime("%Y-%m-%d")
-    logs = load_memory(date_str)
-    if not logs:
-        return
-
-    prompt_messages = build_prompt(logs)
-    summary_text = summarize_with_llm(prompt_messages)
-
-    summary = {
-        "date": date_str,
-        "summary": summary_text,
-        "total_messages": len(logs)
-    }
-
-    save_summary(date_str, summary)
-
-if __name__ == "__main__":
-    main()

mcp/setup.py

@@ -1,12 +0,0 @@
-# setup.py
-from setuptools import setup
-
-setup(
-    name='aigpt-mcp',
-    py_modules=['cli'],
-    entry_points={
-        'console_scripts': [
-            'mcp = cli:main',
-        ],
-    },
-)

scpt/chatgpt.zsh

@@ -0,0 +1,39 @@
+#!/bin/zsh
+
+d=${0:a:h:h}
+json=`cat $d/gpt.json`
+toml=`cat $d/Cargo.toml`
+cd $d/src/
+list=(`zsh -c "ls *.rs"`)
+
+body="
+今、AGE systemを作っているよ。どんなものかというと、jsonを参照してここにすべてが書かれている。
+
+$json
+
+リポジトリはこちらになる。
+git.syui.ai:ai/gpt.git
+
+内容はこんな感じ。
+
+\`\`\`toml
+$toml
+\`\`\`
+
+`
+for i in $list; do
+	if [ -f $d/src/$i ];then
+		t=$(cat $d/src/$i)
+		echo 
+		echo '\`\`\`rust'
+		echo $t
+		echo '\`\`\`'
+		echo 
+	fi
+done
+`
+
+次は何を実装すればいいと思う。
+"
+
+echo $body

src/chat.rs

@@ -1,140 +1,45 @@
 // src/chat.rs
-use std::fs;
+
-use std::process::Command;
-use serde::Deserialize;
 use seahorse::Context;
+use std::process::Command;
+//use std::env;
 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 fn ask_chat(c: &Context, question: &str) {
-pub enum Provider {
-    OpenAI,
-    Ollama,
-    MCP,
-}
-
-impl Provider {
-    pub fn from_str(s: &str) -> Option<Self> {
-        match s.to_lowercase().as_str() {
-            "openai" => Some(Provider::OpenAI),
-            "ollama" => Some(Provider::Ollama),
-            "mcp" => Some(Provider::MCP),
-            _ => None,
-        }
-    }
-
-    pub fn as_str(&self) -> &'static str {
-        match self {
-            Provider::OpenAI => "openai",
-            Provider::Ollama => "ollama",
-            Provider::MCP => "mcp",
-        }
-    }
-}
-
-#[derive(Deserialize)]
-struct OpenAIKey {
-    token: String,
-}
-
-fn load_openai_api_key() -> Option<String> {
-    let config = ConfigPaths::new();
-    let path = config.base_dir.join("openai.json");
-    let data = fs::read_to_string(path).ok()?;
-    let parsed: OpenAIKey = serde_json::from_str(&data).ok()?;
-    Some(parsed.token)
-}
-
-pub fn ask_chat(c: &Context, question: &str) -> Option<String> {
     let config = ConfigPaths::new();
     let base_dir = config.base_dir.join("mcp");
-    let user_path = config.base_dir.join("user.json");
+    let script_path = base_dir.join("scripts/ask.py");
 
-    let mut user = load_user_data(&user_path);
+    let python_path = if cfg!(target_os = "windows") {
-    user.metrics = update_metrics_decay();
+        base_dir.join(".venv/Scripts/python.exe")
+    } else {
+        base_dir.join(".venv/bin/python")
+    };
 
-    // 各種オプション
     let ollama_host = c.string_flag("host").ok();
     let ollama_model = c.string_flag("model").ok();
-    let provider_str = c.string_flag("provider").unwrap_or_else(|_| "ollama".to_string());
-    let provider = Provider::from_str(&provider_str).unwrap_or(Provider::Ollama);
-    let api_key = c.string_flag("api-key").ok().or_else(load_openai_api_key);
 
-    println!("🔍 使用プロバイダー: {}", provider.as_str());
+    let mut command = Command::new(python_path);
+    command.arg(script_path).arg(question);
 
-    match provider {
+    if let Some(host) = ollama_host {
-        Provider::MCP => {
+        command.env("OLLAMA_HOST", host);
-            let client = reqwest::blocking::Client::new();
+    }
-            let url = std::env::var("MCP_URL").unwrap_or("http://127.0.0.1:5000/chat".to_string());
+    if let Some(model) = ollama_model {
-            let res = client.post(url)
+        command.env("OLLAMA_MODEL", model);
-                .json(&serde_json::json!({"message": question}))
+    }
-                .send();
 
-            match res {
+    let output = command
-                Ok(resp) => {
+        .output()
-                    if resp.status().is_success() {
+        .expect("❌ MCPチャットスクリプトの実行に失敗しました");
-                        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);
+    if output.status.success() {
-            command.arg("ask").arg(question);
+        println!("💬 {}", String::from_utf8_lossy(&output.stdout));
-
+    } else {
-            if let Some(host) = ollama_host {
+        eprintln!(
-                command.env("OLLAMA_HOST", host);
+            "❌ 実行エラー: {}\n{}",
-            }
+            String::from_utf8_lossy(&output.stderr),
-            if let Some(model) = ollama_model {
+            String::from_utf8_lossy(&output.stdout),
-                command.env("OLLAMA_MODEL", model.clone());
+        );
-                command.env("OPENAI_MODEL", model);
-            }
-            command.env("PROVIDER", provider.as_str());
-
-            if let Some(key) = api_key {
-                command.env("OPENAI_API_KEY", key);
-            }
-
-            let output = command.output().expect("❌ MCPチャットスクリプトの実行に失敗しました");
-
-            if output.status.success() {
-                let response = String::from_utf8_lossy(&output.stdout).to_string();
-                user.metrics.intimacy += 0.01;
-                user.metrics.last_updated = chrono::Utc::now();
-                save_user_data(&user_path, &user);
-
-                Some(response)
-            } else {
-                eprintln!(
-                    "❌ 実行エラー: {}\n{}",
-                    String::from_utf8_lossy(&output.stderr),
-                    String::from_utf8_lossy(&output.stdout),
-                );
-                None
-            }
-        }
     }
 }

src/commands/git_repo.rs

@@ -1,17 +0,0 @@
-// src/commands/git_repo.rs
-use std::fs;
-
-// Gitリポジトリ内の全てのファイルを取得し、内容を読み取る
-pub fn read_all_git_files(repo_path: &str) -> String {
-    let mut content = String::new();
-    for entry in fs::read_dir(repo_path).expect("ディレクトリ読み込み失敗") {
-        let entry = entry.expect("エントリ読み込み失敗");
-        let path = entry.path();
-        if path.is_file() {
-            if let Ok(file_content) = fs::read_to_string(&path) {
-                content.push_str(&format!("\n\n# File: {}\n{}", path.display(), file_content));
-            }
-        }
-    }
-    content
-}

src/commands/mcp.rs

@@ -1,16 +1,13 @@
 // src/commands/mcp.rs
 
-use std::fs;
-use std::path::{PathBuf};
-use std::process::Command as OtherCommand;
-use serde_json::json;
 use seahorse::{Command, Context, Flag, FlagType};
 use crate::chat::ask_chat;
 use crate::git::{git_init, git_status};
+
+use std::fs;
+use std::path::{PathBuf};
 use crate::config::ConfigPaths;
-use crate::commands::git_repo::read_all_git_files;
+use std::process::Command as OtherCommand;
-use crate::metrics::{load_user_data, save_user_data};
-use crate::memory::{log_message};
 
 pub fn mcp_setup() {
     let config = ConfigPaths::new();
@@ -27,17 +24,13 @@ pub fn mcp_setup() {
         assert!(status.success(), "git clone 実行時にエラーが発生しました");
     }
 
-    let asset_base = PathBuf::from("mcp");
+    let asset_base = PathBuf::from("assets/mcp");
     let files_to_copy = vec![
         "cli.py",
         "setup.py",
         "scripts/ask.py",
-        "scripts/server.py",
-        "scripts/config.py",
-        "scripts/summarize.py",
         "scripts/context_loader.py",
         "scripts/prompt_template.py",
-        "scripts/memory_store.py",
     ];
 
     for rel_path in files_to_copy {
@@ -80,12 +73,6 @@ pub fn mcp_setup() {
     let output = OtherCommand::new(&pip_path)
         .arg("install")
         .arg("openai")
-        .arg("requests")
-        .arg("fastmcp")
-        .arg("uvicorn")
-        .arg("fastapi")
-        .arg("fastapi_mcp")
-        .arg("mcp")
         .current_dir(&dest_dir)
         .output()
         .expect("pip install に失敗しました");
@@ -119,115 +106,17 @@ pub fn mcp_setup() {
     }
 }
 
-fn set_api_key_cmd() -> Command {
-    Command::new("set-api")
-        .description("OpenAI APIキーを設定")
-        .usage("mcp set-api --api <API_KEY>")
-        .flag(Flag::new("api", FlagType::String).description("OpenAI APIキー").alias("a"))
-        .action(|c: &Context| {
-            if let Ok(api_key) = c.string_flag("api") {
-                let config = ConfigPaths::new();
-                let path = config.base_dir.join("openai.json");
-                let json_data = json!({ "token": api_key });
-
-                if let Err(e) = fs::write(&path, serde_json::to_string_pretty(&json_data).unwrap()) {
-                    eprintln!("❌ ファイル書き込み失敗: {}", e);
-                } else {
-                    println!("✅ APIキーを保存しました: {}", path.display());
-                }
-            } else {
-                eprintln!("❗ APIキーを --api で指定してください");
-            }
-        })
-}
-
 fn chat_cmd() -> Command {
     Command::new("chat")
         .description("チャットで質問を送る")
-        .usage("mcp chat '質問内容' --host <OLLAMA_HOST> --model <MODEL> [--provider <ollama|openai>] [--api-key <KEY>] [--repo <REPO_URL>]")
+        .usage("mcp chat '質問内容' --host <OLLAMA_HOST> --model <OLLAMA_MODEL>")
-        .flag(
+        .flag(Flag::new("host", FlagType::String).description("OLLAMAホストのURL"))
-            Flag::new("host", FlagType::String)
+        .flag(Flag::new("model", FlagType::String).description("OLLAMAモデル名"))
-                .description("OLLAMAホストのURL")
-                .alias("H"),
-        )
-        .flag(
-            Flag::new("model", FlagType::String)
-                .description("モデル名 (OLLAMA_MODEL / OPENAI_MODEL)")
-                .alias("m"),
-        )
-        .flag(
-            Flag::new("provider", FlagType::String)
-                .description("使用するプロバイダ (ollama / openai)")
-                .alias("p"),
-        )
-        .flag(
-            Flag::new("api-key", FlagType::String)
-                .description("OpenAI APIキー")
-                .alias("k"),
-        )
-        .flag(
-            Flag::new("repo", FlagType::String)
-                .description("Gitリポジトリのパスを指定 (すべてのコードを読み込む)")
-                .alias("r"),
-        )
         .action(|c: &Context| {
-            let config = ConfigPaths::new();
+            if let Some(question) = c.args.get(0) {
-            let user_path = config.data_file("json");
+                ask_chat(c, question);
-            let mut user = load_user_data(&user_path);
+            } else {
-            // repoがある場合は、コードベース読み込みモード
+                eprintln!("❗ 質問が必要です: mcp chat 'こんにちは'");
-            if let Ok(repo_url) = c.string_flag("repo") {
-                let repo_base = config.base_dir.join("repos");
-                let repo_dir = repo_base.join(sanitize_repo_name(&repo_url));
-
-                if !repo_dir.exists() {
-                    println!("📥 Gitリポジトリをクローン中: {}", repo_url);
-                    let status = OtherCommand::new("git")
-                        .args(&["clone", &repo_url, repo_dir.to_str().unwrap()])
-                        .status()
-                        .expect("❌ Gitのクローンに失敗しました");
-                    assert!(status.success(), "Git clone エラー");
-                } else {
-                    println!("✔ リポジトリはすでに存在します: {}", repo_dir.display());
-                }
-
-                let files = read_all_git_files(repo_dir.to_str().unwrap());
-                let prompt = format!(
-                    "以下のコードベースを読み込んで、改善案や次のステップを提案してください:\n{}",
-                    files
-                );
-
-                if let Some(response) = ask_chat(c, &prompt) {
-                    println!("💬 提案:\n{}", response);
-                } else {
-                    eprintln!("❗ 提案が取得できませんでした");
-                }
-
-                return;
-            }
-
-            // 通常のチャット処理（repoが指定されていない場合）
-            match c.args.get(0) {
-                Some(question) => {
-                    log_message(&config.base_dir, "user", question);
-                    let response = ask_chat(c, question);
-
-                    if let Some(ref text) = response {
-                        println!("💬 応答:\n{}", text);
-                        // 返答内容に基づいて増減（返答の感情解析）
-                        if text.contains("thank") || text.contains("great") {
-                            user.metrics.trust += 0.05;
-                        } else if text.contains("hate") || text.contains("bad") {
-                            user.metrics.trust -= 0.05;
-                        }
-                        log_message(&config.base_dir, "ai", &text);
-                        save_user_data(&user_path, &user);
-                    } else {
-                        eprintln!("❗ 応答が取得できませんでした");
-                    }
-                }
-                None => {
-                    eprintln!("❗ 質問が必要です: mcp chat 'こんにちは'");
-                }
             }
         })
 }
@@ -268,10 +157,4 @@ pub fn mcp_cmd() -> Command {
         .command(init_cmd())
         .command(status_cmd())
         .command(setup_cmd())
-        .command(set_api_key_cmd())
-}
-
-// ファイル名として安全な形に変換
-fn sanitize_repo_name(repo_url: &str) -> String {
-    repo_url.replace("://", "_").replace("/", "_").replace("@", "_")
 }

src/commands/mod.rs

@@ -1,4 +1,3 @@
 pub mod db;
 pub mod scheduler;
 pub mod mcp;
-pub mod git_repo;

src/commands/scheduler.rs

@@ -1,127 +1,29 @@
 // src/commands/scheduler.rs
+
 use seahorse::{Command, Context};
 use std::thread;
 use std::time::Duration;
-use chrono::{Local, Utc, Timelike};
+use chrono::Local;
-use crate::metrics::{load_user_data, save_user_data};
-use crate::config::ConfigPaths;
-use crate::chat::ask_chat;
-use rand::prelude::*;
-use rand::rng;
-
-fn send_scheduled_message() {
-    let config = ConfigPaths::new();
-    let user_path = config.data_file("json");
-    let mut user = load_user_data(&user_path);
-
-    if !user.metrics.can_send {
-        println!("🚫 送信条件を満たしていないため、スケジュール送信スキップ");
-        return;
-    }
-
-    // 日付の比較（1日1回制限）
-    let today = Local::now().format("%Y-%m-%d").to_string();
-    if let Some(last_date) = &user.messaging.last_sent_date {
-        if last_date != &today {
-            user.messaging.sent_today = false;
-        }
-    } else {
-        user.messaging.sent_today = false;
-    }
-
-    if user.messaging.sent_today {
-        println!("🔁 本日はすでに送信済みです: {}", today);
-        return;
-    }
-
-    if let Some(schedule_str) = &user.messaging.schedule_time {
-        let now = Local::now();
-        let target: Vec<&str> = schedule_str.split(':').collect();
-
-        if target.len() != 2 {
-            println!("⚠️ schedule_time形式が無効です: {}", schedule_str);
-            return;
-        }
-
-        let (sh, sm) = (target[0].parse::<u32>(), target[1].parse::<u32>());
-        if let (Ok(sh), Ok(sm)) = (sh, sm) {
-            if now.hour() == sh && now.minute() == sm {
-                if let Some(msg) = user.messaging.templates.choose(&mut rng()) {
-                    println!("💬 自動送信メッセージ: {}", msg);
-                    let dummy_context = Context::new(vec![], None, "".to_string());
-                    ask_chat(&dummy_context, msg);
-                    user.metrics.intimacy += 0.03;
-
-                    // 送信済みのフラグ更新
-                    user.messaging.sent_today = true;
-                    user.messaging.last_sent_date = Some(today);
-
-                    save_user_data(&user_path, &user);
-                }
-            }
-        }
-    }
-}
-
 
 pub fn scheduler_cmd() -> Command {
     Command::new("scheduler")
         .usage("scheduler [interval_sec]")
         .alias("s")
-        .description("定期的に送信条件をチェックし、自発的なメッセージ送信を試みる")
         .action(|c: &Context| {
             let interval = c.args.get(0)
                 .and_then(|s| s.parse::<u64>().ok())
-                .unwrap_or(3600); // デフォルト: 1時間（テストしやすく）
+                .unwrap_or(60); // デフォルト: 60秒ごと
 
-            println!("⏳ スケジューラー開始（{}秒ごと）...", interval);
+            println!("⏳ スケジューラー開始（{interval}秒ごと）...");
 
             loop {
-                let config = ConfigPaths::new();
+                let now = Local::now();
-                let user_path = config.data_file("json");
+                println!("🔁 タスク実行中: {}", now.format("%Y-%m-%d %H:%M:%S"));
-                let mut user = load_user_data(&user_path);
-
-                let now = Utc::now();
-                let elapsed = now.signed_duration_since(user.metrics.last_updated);
-                let hours = elapsed.num_minutes() as f32 / 60.0;
-
-                let speed_factor = if hours > 48.0 {
-                    2.0
-                } else if hours > 24.0 {
-                    1.5
-                } else {
-                    1.0
-                };
-
-                user.metrics.trust = (user.metrics.trust - 0.01 * speed_factor).clamp(0.0, 1.0);
-                user.metrics.intimacy = (user.metrics.intimacy - 0.01 * speed_factor).clamp(0.0, 1.0);
-                user.metrics.energy = (user.metrics.energy - 0.01 * speed_factor).clamp(0.0, 1.0);
-
-                user.metrics.can_send =
-                    user.metrics.trust >= 0.5 &&
-                    user.metrics.intimacy >= 0.5 &&
-                    user.metrics.energy >= 0.5;
-
-                user.metrics.last_updated = now;
-
-                if user.metrics.can_send {
-                    println!("💡 AIメッセージ送信条件を満たしています（信頼:{:.2}, 親密:{:.2}, エネルギー:{:.2}）",
-                        user.metrics.trust,
-                        user.metrics.intimacy,
-                        user.metrics.energy
-                    );
-                    send_scheduled_message();
-                } else {
-                    println!("🤫 条件未達成のため送信スキップ: trust={:.2}, intimacy={:.2}, energy={:.2}",
-                        user.metrics.trust,
-                        user.metrics.intimacy,
-                        user.metrics.energy
-                    );
-                }
                 
-                save_user_data(&user_path, &user);
+                // ここで talk_cmd や save_cmd の内部処理を呼ぶ感じ
+                // たとえば load_config → AI更新 → print とか
+
                 thread::sleep(Duration::from_secs(interval));
             }
         })
 }
-

src/main.rs

@@ -8,8 +8,6 @@ mod commands;
 mod config;
 mod git;
 mod chat;
-mod metrics;
-mod memory;
 
 use cli::cli_app;
 use seahorse::App;

src/memory.rs

@@ -1,49 +0,0 @@
-// src/memory.rs
-use chrono::{DateTime, Local, Utc};
-use serde::{Deserialize, Serialize};
-use std::fs::{self};
-//use std::fs::{self, OpenOptions};
-use std::io::{BufReader, BufWriter};
-use std::path::PathBuf;
-use std::{fs::File};
-//use std::{env, fs::File};
-
-#[derive(Debug, Serialize, Deserialize)]
-pub struct MemoryEntry {
-    pub timestamp: DateTime<Utc>,
-    pub sender: String,
-    pub message: String,
-}
-
-pub fn log_message(base_dir: &PathBuf, sender: &str, message: &str) {
-    let now_utc = Utc::now();
-    let date_str = Local::now().format("%Y-%m-%d").to_string();
-    let mut file_path = base_dir.clone();
-    file_path.push("memory");
-    let _ = fs::create_dir_all(&file_path);
-    file_path.push(format!("{}.json", date_str));
-
-    let new_entry = MemoryEntry {
-        timestamp: now_utc,
-        sender: sender.to_string(),
-        message: message.to_string(),
-    };
-
-    let mut entries = if file_path.exists() {
-        let file = File::open(&file_path).expect("💥 メモリファイルの読み込み失敗");
-        let reader = BufReader::new(file);
-        serde_json::from_reader(reader).unwrap_or_else(|_| vec![])
-    } else {
-        vec![]
-    };
-
-    entries.push(new_entry);
-
-    let file = File::create(&file_path).expect("💥 メモリファイルの書き込み失敗");
-    let writer = BufWriter::new(file);
-    serde_json::to_writer_pretty(writer, &entries).expect("💥 JSONの書き込み失敗");
-}
-
-// 利用例（ask_chatの中）
-// log_message(&config.base_dir, "user", question);
-// log_message(&config.base_dir, "ai", &response);

src/metrics.rs

@@ -1,147 +0,0 @@
-// src/metrics.rs
-use chrono::{DateTime, Utc};
-use serde::{Deserialize, Serialize};
-use std::fs;
-use std::path::Path;
-
-use crate::config::ConfigPaths;
-
-#[derive(Debug, Clone, Serialize, Deserialize)]
-pub struct Metrics {
-    pub trust: f32,
-    pub intimacy: f32,
-    pub energy: f32,
-    pub can_send: bool,
-    pub last_updated: DateTime<Utc>,
-}
-
-#[derive(Debug, Clone, Serialize, Deserialize)]
-pub struct Personality {
-    pub kind: String,
-    pub strength: f32,
-}
-
-#[derive(Debug, Clone, Serialize, Deserialize)]
-pub struct Relationship {
-    pub trust: f32,
-    pub intimacy: f32,
-    pub curiosity: f32,
-    pub threshold: f32,
-}
-
-#[derive(Debug, Clone, Serialize, Deserialize)]
-pub struct Environment {
-    pub luck_today: f32,
-    pub luck_history: Vec<f32>,
-    pub level: i32,
-}
-
-#[derive(Debug, Clone, Serialize, Deserialize)]
-pub struct Messaging {
-    pub enabled: bool,
-    pub schedule_time: Option<String>,
-    pub decay_rate: f32,
-    pub templates: Vec<String>,
-    pub sent_today: bool, // 追加
-    pub last_sent_date: Option<String>, // 追加
-}
-
-#[derive(Debug, Clone, Serialize, Deserialize)]
-pub struct Memory {
-    pub recent_messages: Vec<String>,
-    pub long_term_notes: Vec<String>,
-}
-
-#[derive(Debug, Clone, Serialize, Deserialize)]
-pub struct UserData {
-    pub personality: Personality,
-    pub relationship: Relationship,
-    pub environment: Environment,
-    pub messaging: Messaging,
-    pub last_interaction: DateTime<Utc>,
-    pub memory: Memory,
-    pub metrics: Metrics,
-}
-
-impl Metrics {
-    pub fn decay(&mut self) {
-        let now = Utc::now();
-        let hours = (now - self.last_updated).num_minutes() as f32 / 60.0;
-        self.trust = decay_param(self.trust, hours);
-        self.intimacy = decay_param(self.intimacy, hours);
-        self.energy = decay_param(self.energy, hours);
-        self.can_send = self.trust >= 0.5 && self.intimacy >= 0.5 && self.energy >= 0.5;
-        self.last_updated = now;
-    }
-}
-
-pub fn load_user_data(path: &Path) -> UserData {
-    let config = ConfigPaths::new();
-    let example_path = Path::new("example.json");
-    config.ensure_file_exists("json", example_path);
-
-    if !path.exists() {
-        return UserData {
-            personality: Personality {
-                kind: "positive".into(),
-                strength: 0.8,
-            },
-            relationship: Relationship {
-                trust: 0.2,
-                intimacy: 0.6,
-                curiosity: 0.5,
-                threshold: 1.5,
-            },
-            environment: Environment {
-                luck_today: 0.9,
-                luck_history: vec![0.9, 0.9, 0.9],
-                level: 1,
-            },
-            messaging: Messaging {
-                enabled: true,
-                schedule_time: Some("08:00".to_string()),
-                decay_rate: 0.1,
-                templates: vec![
-                    "おはよう！今日もがんばろう！".to_string(),
-                    "ねえ、話したいことがあるの。".to_string(),
-                ],
-                sent_today: false,
-                last_sent_date: None,
-            },
-            last_interaction: Utc::now(),
-            memory: Memory {
-                recent_messages: vec![],
-                long_term_notes: vec![],
-            },
-            metrics: Metrics {
-                trust: 0.5,
-                intimacy: 0.5,
-                energy: 0.5,
-                can_send: true,
-                last_updated: Utc::now(),
-            },
-        };
-    }
-
-    let content = fs::read_to_string(path).expect("user.json の読み込みに失敗しました");
-    serde_json::from_str(&content).expect("user.json のパースに失敗しました")
-}
-
-pub fn save_user_data(path: &Path, data: &UserData) {
-    let content = serde_json::to_string_pretty(data).expect("user.json のシリアライズ失敗");
-    fs::write(path, content).expect("user.json の書き込みに失敗しました");
-}
-
-pub fn update_metrics_decay() -> Metrics {
-    let config = ConfigPaths::new();
-    let path = config.base_dir.join("user.json");
-    let mut data = load_user_data(&path);
-    data.metrics.decay();
-    save_user_data(&path, &data);
-    data.metrics
-}
-
-fn decay_param(value: f32, hours: f32) -> f32 {
-    let decay_rate = 0.05;
-    (value * (1.0f32 - decay_rate).powf(hours)).clamp(0.0, 1.0)
-}

tmp/agent/src/main.rs

@@ -0,0 +1,42 @@
+use std::env;
+use std::process::{Command, Stdio};
+use std::io::{self, Write};
+
+fn main() {
+    let args: Vec<String> = env::args().collect();
+    if args.len() < 2 {
+        eprintln!("Usage: langchain_cli <prompt>");
+        std::process::exit(1);
+    }
+
+    let prompt = &args[1];
+
+    // Simulate a pipeline stage: e.g., tokenization, reasoning, response generation
+    let stages = vec!["Tokenize", "Reason", "Generate"];
+
+    for stage in &stages {
+        println!("[Stage: {}] Processing...", stage);
+    }
+
+    // Example call to Python-based LangChain (assuming you have a script or API to call)
+    // For placeholder purposes, we echo the prompt back.
+    let output = Command::new("python3")
+        .arg("-c")
+        .arg(format!("print(\"LangChain Agent Response for: {}\")", prompt))
+        .stdout(Stdio::piped())
+        .spawn()
+        .expect("failed to execute process")
+        .wait_with_output()
+        .expect("failed to wait on child");
+
+    io::stdout().write_all(&output.stdout).unwrap();
+}
+
+/*
+TODO (for future LangChain-style pipeline):
+1. Implement trait-based agent components: Tokenizer, Retriever, Reasoner, Generator.
+2. Allow config via YAML or TOML to define chain flow.
+3. Async pipeline support with Tokio.
+4. Optional integration with LLM APIs (OpenAI, Ollama, etc).
+5. Rust-native vector search (e.g. using `tantivy`, `qdrant-client`).
+*/

tmp/data.rs

@@ -0,0 +1,133 @@
+#[derive(Debug, Serialize, Deserialize)]
+pub struct RelationalAutonomousAI {
+    pub system_name: String,
+    pub description: String,
+    pub core_components: CoreComponents,
+    pub extensions: Extensions,
+    pub note: String,
+}
+
+#[derive(Debug, Serialize, Deserialize)]
+pub struct CoreComponents {
+    pub personality: Personality,
+    pub relationship: Relationship,
+    pub environment: Environment,
+    pub memory: Memory,
+    pub message_trigger: MessageTrigger,
+    pub message_generation: MessageGeneration,
+    pub state_transition: StateTransition,
+}
+
+#[derive(Debug, Serialize, Deserialize)]
+pub struct Personality {
+    pub r#type: String,
+    pub variants: Vec<String>,
+    pub parameters: PersonalityParameters,
+}
+
+#[derive(Debug, Serialize, Deserialize)]
+pub struct PersonalityParameters {
+    pub message_trigger_style: String,
+    pub decay_rate_modifier: String,
+}
+
+#[derive(Debug, Serialize, Deserialize)]
+pub struct Relationship {
+    pub parameters: Vec<String>,
+    pub properties: RelationshipProperties,
+    pub decay_function: String,
+}
+
+#[derive(Debug, Serialize, Deserialize)]
+pub struct RelationshipProperties {
+    pub persistent: bool,
+    pub hidden: bool,
+    pub irreversible: bool,
+    pub decay_over_time: bool,
+}
+
+#[derive(Debug, Serialize, Deserialize)]
+pub struct Environment {
+    pub daily_luck: DailyLuck,
+}
+
+#[derive(Debug, Serialize, Deserialize)]
+pub struct DailyLuck {
+    pub r#type: String,
+    pub range: Vec<f32>,
+    pub update: String,
+    pub streak_mechanism: StreakMechanism,
+}
+
+#[derive(Debug, Serialize, Deserialize)]
+pub struct StreakMechanism {
+    pub trigger: String,
+    pub effect: String,
+    pub chance: f32,
+}
+
+#[derive(Debug, Serialize, Deserialize)]
+pub struct Memory {
+    pub long_term_memory: String,
+    pub short_term_context: String,
+    pub usage_in_generation: bool,
+}
+
+#[derive(Debug, Serialize, Deserialize)]
+pub struct MessageTrigger {
+    pub condition: TriggerCondition,
+    pub timing: TriggerTiming,
+}
+
+#[derive(Debug, Serialize, Deserialize)]
+pub struct TriggerCondition {
+    pub relationship_threshold: String,
+    pub time_decay: bool,
+    pub environment_luck: String,
+}
+
+#[derive(Debug, Serialize, Deserialize)]
+pub struct TriggerTiming {
+    pub based_on: Vec<String>,
+    pub modifiers: String,
+}
+
+#[derive(Debug, Serialize, Deserialize)]
+pub struct MessageGeneration {
+    pub style_variants: Vec<String>,
+    pub influenced_by: Vec<String>,
+    pub llm_integration: bool,
+}
+
+#[derive(Debug, Serialize, Deserialize)]
+pub struct StateTransition {
+    pub states: Vec<String>,
+    pub transitions: String,
+}
+
+#[derive(Debug, Serialize, Deserialize)]
+pub struct Extensions {
+    pub persistence: Persistence,
+    pub api: Api,
+    pub scheduler: Scheduler,
+}
+
+#[derive(Debug, Serialize, Deserialize)]
+pub struct Persistence {
+    pub database: String,
+    pub storage_items: Vec<String>,
+}
+
+#[derive(Debug, Serialize, Deserialize)]
+pub struct Api {
+    pub llm: String,
+    pub mode: String,
+    pub external_event_trigger: bool,
+}
+
+#[derive(Debug, Serialize, Deserialize)]
+pub struct Scheduler {
+    pub async_event_loop: bool,
+    pub interval_check: i32,
+    pub time_decay_check: bool,
+}

tmp/system.rs

@@ -0,0 +1,46 @@
+use serde::{Deserialize, Serialize};
+use std::fs::File;
+use std::io::{BufReader, Write};
+use std::time::{SystemTime, UNIX_EPOCH};
+
+mod model;
+use model::RelationalAutonomousAI;
+
+fn load_config(path: &str) -> std::io::Result<RelationalAutonomousAI> {
+    let file = File::open(path)?;
+    let reader = BufReader::new(file);
+    let config: RelationalAutonomousAI = serde_json::from_reader(reader)?;
+    Ok(config)
+}
+
+fn save_config(config: &RelationalAutonomousAI, path: &str) -> std::io::Result<()> {
+    let mut file = File::create(path)?;
+    let json = serde_json::to_string_pretty(config)?;
+    file.write_all(json.as_bytes())?;
+    Ok(())
+}
+
+fn should_send_message(config: &RelationalAutonomousAI) -> bool {
+    // 簡易な送信条件: relationshipが高く、daily_luckが0.8以上
+    config.core_components.relationship.parameters.contains(&"trust".to_string())
+        && config.core_components.environment.daily_luck.range[1] >= 0.8
+}
+
+fn main() -> std::io::Result<()> {
+    let path = "config.json";
+
+    let mut config = load_config(path)?;
+
+    if should_send_message(&config) {
+        println!("💌 メッセージを送信できます: {:?}", config.core_components.personality.r#type);
+
+        // ステート変化の例: メッセージ送信後に記録用トランジションを追加
+        config.core_components.state_transition.transitions.push("message_sent".to_string());
+
+        save_config(&config, path)?;
+    } else {
+        println!("😶 まだ送信条件に達していません。");
+    }
+
+    Ok(())
+}