first claude
This commit is contained in:
125
mcp/chat.py
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125
mcp/chat.py
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@ -0,0 +1,125 @@
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# mcp/chat.py
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"""
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Chat client for aigpt CLI
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"""
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import sys
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import json
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import requests
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from datetime import datetime
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from config import init_directories, load_config, MEMORY_DIR
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def save_conversation(user_message, ai_response):
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"""会話をファイルに保存"""
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init_directories()
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conversation = {
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"timestamp": datetime.now().isoformat(),
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"user": user_message,
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"ai": ai_response
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}
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# 日付ごとのファイルに保存
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today = datetime.now().strftime("%Y-%m-%d")
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chat_file = MEMORY_DIR / f"chat_{today}.jsonl"
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with open(chat_file, "a", encoding="utf-8") as f:
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f.write(json.dumps(conversation, ensure_ascii=False) + "\n")
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def chat_with_ollama(config, message):
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"""Ollamaとチャット"""
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try:
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payload = {
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"model": config["model"],
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"prompt": message,
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"stream": False
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}
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response = requests.post(config["url"], json=payload, timeout=30)
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response.raise_for_status()
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result = response.json()
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return result.get("response", "No response received")
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except requests.exceptions.RequestException as e:
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return f"Error connecting to Ollama: {e}"
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except Exception as e:
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return f"Error: {e}"
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def chat_with_openai(config, message):
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"""OpenAIとチャット"""
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try:
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headers = {
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"Authorization": f"Bearer {config['api_key']}",
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"Content-Type": "application/json"
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}
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payload = {
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"model": config["model"],
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"messages": [
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{"role": "user", "content": message}
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]
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}
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response = requests.post(config["url"], json=payload, headers=headers, timeout=30)
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response.raise_for_status()
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result = response.json()
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return result["choices"][0]["message"]["content"]
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except requests.exceptions.RequestException as e:
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return f"Error connecting to OpenAI: {e}"
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except Exception as e:
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return f"Error: {e}"
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def chat_with_mcp(config, message):
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"""MCPサーバーとチャット"""
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try:
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payload = {
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"message": message,
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"model": config["model"]
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}
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response = requests.post(config["url"], json=payload, timeout=30)
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response.raise_for_status()
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result = response.json()
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return result.get("response", "No response received")
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except requests.exceptions.RequestException as e:
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return f"Error connecting to MCP server: {e}"
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except Exception as e:
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return f"Error: {e}"
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def main():
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if len(sys.argv) != 2:
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print("Usage: python chat.py <message>", file=sys.stderr)
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sys.exit(1)
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message = sys.argv[1]
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try:
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config = load_config()
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print(f"🤖 Using {config['provider']} with model {config['model']}", file=sys.stderr)
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# プロバイダに応じてチャット実行
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if config["provider"] == "ollama":
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response = chat_with_ollama(config, message)
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elif config["provider"] == "openai":
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response = chat_with_openai(config, message)
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elif config["provider"] == "mcp":
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response = chat_with_mcp(config, message)
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else:
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response = f"Unsupported provider: {config['provider']}"
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# 会話を保存
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save_conversation(message, response)
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# レスポンスを出力
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print(response)
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except Exception as e:
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print(f"❌ Error: {e}", file=sys.stderr)
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sys.exit(1)
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if __name__ == "__main__":
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main()
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28
mcp/cli.py
28
mcp/cli.py
@ -1,28 +0,0 @@
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# cli.py
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import sys
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import subprocess
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from pathlib import Path
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SCRIPT_DIR = Path.home() / ".config" / "aigpt" / "mcp" / "scripts"
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def run_script(name):
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script_path = SCRIPT_DIR / f"{name}.py"
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if not script_path.exists():
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print(f"❌ スクリプトが見つかりません: {script_path}")
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sys.exit(1)
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args = sys.argv[2:] # ← "ask" の後の引数を取り出す
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result = subprocess.run(["python", str(script_path)] + args, capture_output=True, text=True)
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print(result.stdout)
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if result.stderr:
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print(result.stderr)
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def main():
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if len(sys.argv) < 2:
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print("Usage: mcp <script>")
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return
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command = sys.argv[1]
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if command in {"summarize", "ask", "setup", "server"}:
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run_script(command)
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else:
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print(f"❓ 未知のコマンド: {command}")
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@ -1,5 +1,4 @@
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# scripts/config.py
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# scripts/config.py
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# mcp/config.py
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import os
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from pathlib import Path
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@ -9,11 +8,13 @@ MEMORY_DIR = BASE_DIR / "memory"
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SUMMARY_DIR = MEMORY_DIR / "summary"
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def init_directories():
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"""必要なディレクトリを作成"""
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BASE_DIR.mkdir(parents=True, exist_ok=True)
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MEMORY_DIR.mkdir(parents=True, exist_ok=True)
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SUMMARY_DIR.mkdir(parents=True, exist_ok=True)
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def load_config():
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"""環境変数から設定を読み込み"""
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provider = os.getenv("PROVIDER", "ollama")
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model = os.getenv("MODEL", "syui/ai" if provider == "ollama" else "gpt-4o-mini")
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api_key = os.getenv("OPENAI_API_KEY", "")
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3
mcp/requirements.txt
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3
mcp/requirements.txt
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fastmcp>=0.1.0
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uvicorn>=0.24.0
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requests>=2.31.0
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@ -1,198 +0,0 @@
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## scripts/ask.py
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import sys
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import json
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import requests
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from config import load_config
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from datetime import datetime, timezone
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def build_payload_openai(cfg, message: str):
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return {
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"model": cfg["model"],
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"tools": [
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{
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"type": "function",
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"function": {
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"name": "ask_message",
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"description": "過去の記憶を検索します",
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"parameters": {
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"type": "object",
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"properties": {
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"query": {
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"type": "string",
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"description": "検索したい語句"
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}
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},
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"required": ["query"]
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}
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}
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}
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],
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"tool_choice": "auto",
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"messages": [
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{"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。"},
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{"role": "user", "content": message}
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]
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}
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def build_payload_mcp(message: str):
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return {
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"tool": "ask_message", # MCPサーバー側で定義されたツール名
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"input": {
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"message": message
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}
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}
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def build_payload_openai(cfg, message: str):
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return {
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"model": cfg["model"],
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"messages": [
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{"role": "system", "content": "あなたは思いやりのあるAIです。"},
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{"role": "user", "content": message}
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],
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"temperature": 0.7
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}
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def call_mcp(cfg, message: str):
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payload = build_payload_mcp(message)
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headers = {"Content-Type": "application/json"}
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response = requests.post(cfg["url"], headers=headers, json=payload)
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response.raise_for_status()
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return response.json().get("output", {}).get("response", "❓ 応答が取得できませんでした")
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def call_openai(cfg, message: str):
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# ツール定義
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tools = [
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{
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"type": "function",
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"function": {
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"name": "memory",
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"description": "記憶を検索する",
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"parameters": {
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"type": "object",
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"properties": {
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"query": {
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"type": "string",
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"description": "検索する語句"
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}
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},
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"required": ["query"]
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}
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}
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}
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]
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# 最初のメッセージ送信
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payload = {
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"model": cfg["model"],
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"messages": [
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{"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。"},
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{"role": "user", "content": message}
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],
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"tools": tools,
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"tool_choice": "auto"
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}
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headers = {
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"Authorization": f"Bearer {cfg['api_key']}",
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"Content-Type": "application/json",
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}
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res1 = requests.post(cfg["url"], headers=headers, json=payload)
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res1.raise_for_status()
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result = res1.json()
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# 🧠 tool_call されたか確認
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if "tool_calls" in result["choices"][0]["message"]:
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tool_call = result["choices"][0]["message"]["tool_calls"][0]
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if tool_call["function"]["name"] == "memory":
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args = json.loads(tool_call["function"]["arguments"])
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query = args.get("query", "")
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print(f"🛠️ ツール実行: memory(query='{query}')")
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# MCPエンドポイントにPOST
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memory_res = requests.post("http://127.0.0.1:5000/memory/search", json={"query": query})
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memory_json = memory_res.json()
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tool_output = memory_json.get("result", "なし")
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# tool_outputをAIに返す
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followup = {
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"model": cfg["model"],
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"messages": [
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{"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。"},
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{"role": "user", "content": message},
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{"role": "assistant", "tool_calls": result["choices"][0]["message"]["tool_calls"]},
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{"role": "tool", "tool_call_id": tool_call["id"], "name": "memory", "content": tool_output}
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]
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}
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res2 = requests.post(cfg["url"], headers=headers, json=followup)
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res2.raise_for_status()
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final_response = res2.json()
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return final_response["choices"][0]["message"]["content"]
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#print(tool_output)
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#print(cfg["model"])
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#print(final_response)
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# ツール未使用 or 通常応答
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return result["choices"][0]["message"]["content"]
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def call_ollama(cfg, message: str):
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payload = {
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"model": cfg["model"],
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"prompt": message, # `prompt` → `message` にすべき（変数未定義エラー回避）
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"stream": False
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}
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headers = {"Content-Type": "application/json"}
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response = requests.post(cfg["url"], headers=headers, json=payload)
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response.raise_for_status()
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return response.json().get("response", "❌ 応答が取得できませんでした")
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def main():
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if len(sys.argv) < 2:
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print("Usage: ask.py 'your message'")
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return
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message = sys.argv[1]
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cfg = load_config()
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print(f"🔍 使用プロバイダー: {cfg['provider']}")
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try:
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if cfg["provider"] == "openai":
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response = call_openai(cfg, message)
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elif cfg["provider"] == "mcp":
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response = call_mcp(cfg, message)
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elif cfg["provider"] == "ollama":
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response = call_ollama(cfg, message)
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else:
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raise ValueError(f"未対応のプロバイダー: {cfg['provider']}")
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print("💬 応答:")
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print(response)
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# ログ保存（オプション）
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save_log(message, response)
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except Exception as e:
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print(f"❌ 実行エラー: {e}")
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def save_log(user_msg, ai_msg):
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from config import MEMORY_DIR
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date_str = datetime.now().strftime("%Y-%m-%d")
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path = MEMORY_DIR / f"{date_str}.json"
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path.parent.mkdir(parents=True, exist_ok=True)
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if path.exists():
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with open(path, "r") as f:
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logs = json.load(f)
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else:
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logs = []
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now = datetime.now(timezone.utc).isoformat()
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logs.append({"timestamp": now, "sender": "user", "message": user_msg})
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logs.append({"timestamp": now, "sender": "ai", "message": ai_msg})
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with open(path, "w") as f:
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json.dump(logs, f, indent=2, ensure_ascii=False)
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if __name__ == "__main__":
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main()
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@ -1,11 +0,0 @@
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import os
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def load_context_from_repo(repo_path: str, extensions={".rs", ".toml", ".md"}) -> str:
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context = ""
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for root, dirs, files in os.walk(repo_path):
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for file in files:
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if any(file.endswith(ext) for ext in extensions):
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with open(os.path.join(root, file), "r", encoding="utf-8", errors="ignore") as f:
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content = f.read()
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context += f"\n\n# FILE: {os.path.join(root, file)}\n{content}"
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return context
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@ -1,92 +0,0 @@
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# scripts/memory_store.py
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import json
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from pathlib import Path
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from config import MEMORY_DIR
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from datetime import datetime, timezone
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def load_logs(date_str=None):
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if date_str is None:
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date_str = datetime.now().strftime("%Y-%m-%d")
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path = MEMORY_DIR / f"{date_str}.json"
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if path.exists():
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with open(path, "r") as f:
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return json.load(f)
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return []
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def save_message(sender, message):
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date_str = datetime.now().strftime("%Y-%m-%d")
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path = MEMORY_DIR / f"{date_str}.json"
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logs = load_logs(date_str)
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now = datetime.now(timezone.utc).isoformat()
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logs.append({"timestamp": now, "sender": sender, "message": message})
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with open(path, "w") as f:
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json.dump(logs, f, indent=2, ensure_ascii=False)
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def search_memory(query: str):
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from glob import glob
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all_logs = []
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pattern = re.compile(re.escape(query), re.IGNORECASE)
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for file_path in sorted(MEMORY_DIR.glob("*.json")):
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with open(file_path, "r") as f:
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logs = json.load(f)
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matched = [entry for entry in logs if pattern.search(entry["message"])]
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all_logs.extend(matched)
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return all_logs[-5:]
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# scripts/memory_store.py
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import json
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from datetime import datetime
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from pathlib import Path
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from config import MEMORY_DIR
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# ログを読み込む（指定日または当日）
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def load_logs(date_str=None):
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if date_str is None:
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date_str = datetime.now().strftime("%Y-%m-%d")
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path = MEMORY_DIR / f"{date_str}.json"
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if path.exists():
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with open(path, "r") as f:
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return json.load(f)
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return []
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# メッセージを保存する
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def save_message(sender, message):
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date_str = datetime.now().strftime("%Y-%m-%d")
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path = MEMORY_DIR / f"{date_str}.json"
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logs = load_logs(date_str)
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#now = datetime.utcnow().isoformat() + "Z"
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now = datetime.now(timezone.utc).isoformat()
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logs.append({"timestamp": now, "sender": sender, "message": message})
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with open(path, "w") as f:
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json.dump(logs, f, indent=2, ensure_ascii=False)
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def search_memory(query: str):
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from glob import glob
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all_logs = []
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for file_path in sorted(MEMORY_DIR.glob("*.json")):
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with open(file_path, "r") as f:
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logs = json.load(f)
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matched = [
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entry for entry in logs
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if entry["sender"] == "user" and query in entry["message"]
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]
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all_logs.extend(matched)
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return all_logs[-5:] # 最新5件だけ返す
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def search_memory(query: str):
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from glob import glob
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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
|
||||
@ -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}
|
||||
"""
|
||||
@ -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)
|
||||
@ -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()
|
||||
79
mcp/server.py
Normal file
79
mcp/server.py
Normal file
@ -0,0 +1,79 @@
|
||||
# mcp/server.py
|
||||
"""
|
||||
MCP Server for aigpt CLI
|
||||
"""
|
||||
from fastmcp import FastMCP
|
||||
import platform
|
||||
import os
|
||||
import sys
|
||||
|
||||
mcp = FastMCP("AigptMCP")
|
||||
|
||||
@mcp.tool()
|
||||
def process_text(text: str) -> str:
|
||||
"""テキストを処理する"""
|
||||
return f"Processed: {text}"
|
||||
|
||||
@mcp.tool()
|
||||
def get_system_info() -> dict:
|
||||
"""システム情報を取得"""
|
||||
return {
|
||||
"platform": platform.system(),
|
||||
"version": platform.version(),
|
||||
"python_version": sys.version,
|
||||
"current_dir": os.getcwd()
|
||||
}
|
||||
|
||||
@mcp.tool()
|
||||
def execute_command(command: str) -> dict:
|
||||
"""安全なコマンドを実行する"""
|
||||
# セキュリティのため、許可されたコマンドのみ実行
|
||||
allowed_commands = ["ls", "pwd", "date", "whoami"]
|
||||
cmd_parts = command.split()
|
||||
|
||||
if not cmd_parts or cmd_parts[0] not in allowed_commands:
|
||||
return {
|
||||
"error": f"Command '{command}' is not allowed",
|
||||
"allowed": allowed_commands
|
||||
}
|
||||
|
||||
try:
|
||||
import subprocess
|
||||
result = subprocess.run(
|
||||
cmd_parts,
|
||||
capture_output=True,
|
||||
text=True,
|
||||
timeout=10
|
||||
)
|
||||
return {
|
||||
"stdout": result.stdout,
|
||||
"stderr": result.stderr,
|
||||
"returncode": result.returncode
|
||||
}
|
||||
except subprocess.TimeoutExpired:
|
||||
return {"error": "Command timed out"}
|
||||
except Exception as e:
|
||||
return {"error": str(e)}
|
||||
|
||||
@mcp.tool()
|
||||
def file_operations(operation: str, filepath: str, content: str = None) -> dict:
|
||||
"""ファイル操作を行う"""
|
||||
try:
|
||||
if operation == "read":
|
||||
with open(filepath, 'r', encoding='utf-8') as f:
|
||||
return {"content": f.read(), "success": True}
|
||||
elif operation == "write" and content is not None:
|
||||
with open(filepath, 'w', encoding='utf-8') as f:
|
||||
f.write(content)
|
||||
return {"message": f"File written to {filepath}", "success": True}
|
||||
elif operation == "exists":
|
||||
return {"exists": os.path.exists(filepath), "success": True}
|
||||
else:
|
||||
return {"error": "Invalid operation or missing content", "success": False}
|
||||
except Exception as e:
|
||||
return {"error": str(e), "success": False}
|
||||
|
||||
if __name__ == "__main__":
|
||||
print("🚀 AigptMCP Server starting...")
|
||||
mcp.run()
|
||||
|
||||
12
mcp/setup.py
12
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',
|
||||
],
|
||||
},
|
||||
)
|
||||
Reference in New Issue
Block a user