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syui
2025-05-24 23:19:30 +09:00
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14
Cargo.toml
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@ -4,12 +4,10 @@ version = "0.1.0"
edition = "2021"
[dependencies]
serde = { version = "1.0", features = ["derive"] }
serde_json = "1.0"
chrono = { version = "0.4", features = ["serde"] }
seahorse = "*"
rusqlite = { version = "0.29", features = ["serde_json"] }
reqwest = { version = "*", features = ["json"] }
serde = { version = "*", features = ["derive"] }
serde_json = "*"
tokio = { version = "*", features = ["full"] }
clap = { version = "*", features = ["derive"] }
shellexpand = "*"
fs_extra = "1.3"
rand = "0.9.1"
reqwest = { version = "*", features = ["blocking", "json"] }
fs_extra = "*"

47
README.md
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@ -1,47 +0,0 @@
# ai `gpt`
ai x Communication
## Overview
`ai.gpt` runs on the AGE system.
This is a prototype of an autonomous, relationship-driven AI system based on the axes of "Personality × Relationship × External Environment × Time Variation."
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."
## Integration
`ai.ai` runs on the AIM system, which is designed to read human emotions.
- AIM focuses on the axis of personality and ethics (AI's consciousness structure)
- AGE focuses on the axis of behavior and relationships (AI's autonomy and behavior)
> When these two systems work together, it creates a world where users can feel like they are "growing together with AI."
## mcp
```sh
$ ollama run syui/ai
```
```sh
$ cargo build
$ ./aigpt mcp setup
$ ./aigpt mcp chat "hello world!"
$ ./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。
```

40
example.json
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@ -1,40 +0,0 @@
{
"personality": {
"kind": "positive",
"strength": 0.8
},
"relationship": {
"trust": 0.2,
"intimacy": 0.6,
"curiosity": 0.5,
"threshold": 1.5
},
"environment": {
"luck_today": 0.9,
"luck_history": [0.9, 0.9, 0.9],
"level": 1
},
"messaging": {
"enabled": true,
"schedule_time": "08:00",
"decay_rate": 0.1,
"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"
}
}

1
gpt.json
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@ -1 +0,0 @@
{ "system_name": "AGE system", "full_name": "Autonomous Generative Entity", "description": "人格・関係性・環境・時間に基づき、AIが自律的にユーザーにメッセージを送信する自律人格システム。AIM systemと連携して、自然な会話や気づきをもたらす。", "core_components": { "personality": { "type": "enum", "variants": ["positive", "negative", "logical", "emotional", "mixed"], "parameters": { "message_trigger_style": "運勢や関係性による送信傾向", "decay_rate_modifier": "関係性スコアの時間減衰への影響" } }, "relationship": { "parameters": ["trust", "affection", "intimacy"], "properties": { "persistent": true, "hidden": true, "irreversible": false, "decay_over_time": true }, "decay_function": "exp(-t / strength)" }, "environment": { "daily_luck": { "type": "float", "range": [0.1, 1.0], "update": "daily", "streak_mechanism": { "trigger": "min_or_max_luck_3_times_in_a_row", "effect": "personality_strength_roll", "chance": 0.5 } } }, "memory": { "long_term_memory": "user_relationship_log", "short_term_context": "recent_interactions", "usage_in_generation": true }, "message_trigger": { "condition": { "relationship_threshold": { "trust": 0.8, "affection": 0.6 }, "time_decay": true, "environment_luck": "personality_dependent" }, "timing": { "based_on": ["time_of_day", "personality", "recent_interaction"], "modifiers": { "emotional": "morning or night", "logical": "daytime" } } }, "message_generation": { "style_variants": ["thought", "casual", "encouragement", "watchful"], "influenced_by": ["personality", "relationship", "daily_luck", "memory"], "llm_integration": true }, "state_transition": { "states": ["idle", "ready", "sending", "cooldown"], "transitions": { "ready_if": "thresholds_met", "sending_if": "timing_matched", "cooldown_after": "message_sent" } } }, "extensions": { "persistence": { "database": "sqlite", "storage_items": ["relationship", "personality_level", "daily_luck_log"] }, "api": { "llm": "openai / local LLM", "mode": "rust_cli", "external_event_trigger": true }, "scheduler": { "async_event_loop": true, "interval_check": 3600, "time_decay_check": true }, "integration_with_aim": { "input_from_aim": ["intent_score", "motivation_score"], "usage": "trigger_adjustment, message_personalization" } }, "note": "AGE systemは“話しかけてくるAI”の人格として機能し、AIMによる心の状態評価と連動して、プレイヤーと深い関係を築いていく存在となる。" }

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mcp/chat.py Normal file
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# mcp/chat.py
"""
Chat client for aigpt CLI
"""
import sys
import json
import requests
from datetime import datetime
from config import init_directories, load_config, MEMORY_DIR
def save_conversation(user_message, ai_response):
"""会話をファイルに保存"""
init_directories()
conversation = {
"timestamp": datetime.now().isoformat(),
"user": user_message,
"ai": ai_response
}
# 日付ごとのファイルに保存
today = datetime.now().strftime("%Y-%m-%d")
chat_file = MEMORY_DIR / f"chat_{today}.jsonl"
with open(chat_file, "a", encoding="utf-8") as f:
f.write(json.dumps(conversation, ensure_ascii=False) + "\n")
def chat_with_ollama(config, message):
"""Ollamaとチャット"""
try:
payload = {
"model": config["model"],
"prompt": message,
"stream": False
}
response = requests.post(config["url"], json=payload, timeout=30)
response.raise_for_status()
result = response.json()
return result.get("response", "No response received")
except requests.exceptions.RequestException as e:
return f"Error connecting to Ollama: {e}"
except Exception as e:
return f"Error: {e}"
def chat_with_openai(config, message):
"""OpenAIとチャット"""
try:
headers = {
"Authorization": f"Bearer {config['api_key']}",
"Content-Type": "application/json"
}
payload = {
"model": config["model"],
"messages": [
{"role": "user", "content": message}
]
}
response = requests.post(config["url"], json=payload, headers=headers, timeout=30)
response.raise_for_status()
result = response.json()
return result["choices"][0]["message"]["content"]
except requests.exceptions.RequestException as e:
return f"Error connecting to OpenAI: {e}"
except Exception as e:
return f"Error: {e}"
def chat_with_mcp(config, message):
"""MCPサーバーとチャット"""
try:
payload = {
"message": message,
"model": config["model"]
}
response = requests.post(config["url"], json=payload, timeout=30)
response.raise_for_status()
result = response.json()
return result.get("response", "No response received")
except requests.exceptions.RequestException as e:
return f"Error connecting to MCP server: {e}"
except Exception as e:
return f"Error: {e}"
def main():
if len(sys.argv) != 2:
print("Usage: python chat.py <message>", file=sys.stderr)
sys.exit(1)
message = sys.argv[1]
try:
config = load_config()
print(f"🤖 Using {config['provider']} with model {config['model']}", file=sys.stderr)
# プロバイダに応じてチャット実行
if config["provider"] == "ollama":
response = chat_with_ollama(config, message)
elif config["provider"] == "openai":
response = chat_with_openai(config, message)
elif config["provider"] == "mcp":
response = chat_with_mcp(config, message)
else:
response = f"Unsupported provider: {config['provider']}"
# 会話を保存
save_conversation(message, response)
# レスポンスを出力
print(response)
except Exception as e:
print(f"❌ Error: {e}", file=sys.stderr)
sys.exit(1)
if __name__ == "__main__":
main()

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mcp/cli.py
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@ -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}")

5
mcp/scripts/config.py → mcp/config.py
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@ -1,5 +1,4 @@
# scripts/config.py
# scripts/config.py
# mcp/config.py
import os
from pathlib import Path
@ -9,11 +8,13 @@ MEMORY_DIR = BASE_DIR / "memory"
SUMMARY_DIR = MEMORY_DIR / "summary"
def init_directories():
"""必要なディレクトリを作成"""
BASE_DIR.mkdir(parents=True, exist_ok=True)
MEMORY_DIR.mkdir(parents=True, exist_ok=True)
SUMMARY_DIR.mkdir(parents=True, exist_ok=True)
def load_config():
"""環境変数から設定を読み込み"""
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", "")

3
mcp/requirements.txt Normal file
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@ -0,0 +1,3 @@
fastmcp>=0.1.0
uvicorn>=0.24.0
requests>=2.31.0

198
mcp/scripts/ask.py
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@ -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()

11
mcp/scripts/context_loader.py
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@ -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

92
mcp/scripts/memory_store.py
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@ -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

11
mcp/scripts/prompt_template.py
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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}
"""

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mcp/scripts/server.py
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# 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)

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

37
src/agent.rs
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@ -1,37 +0,0 @@
use chrono::{NaiveDateTime};
#[allow(dead_code)]
#[derive(Debug)]
pub struct AIState {
pub relation_score: f32,
pub previous_score: f32,
pub decay_rate: f32,
pub sensitivity: f32,
pub message_threshold: f32,
pub last_message_time: NaiveDateTime,
}
#[allow(dead_code)]
impl AIState {
pub fn update(&mut self, now: NaiveDateTime) {
let days_passed = (now - self.last_message_time).num_days() as f32;
let decay = self.decay_rate * days_passed;
self.previous_score = self.relation_score;
self.relation_score -= decay;
self.relation_score = self.relation_score.clamp(0.0, 100.0);
}
pub fn should_talk(&self) -> bool {
let delta = self.previous_score - self.relation_score;
delta > self.message_threshold && self.sensitivity > 0.5
}
pub fn generate_message(&self) -> String {
match self.relation_score as i32 {
80..=100 => "ふふっ、最近どうしてる？会いたくなっちゃった！".to_string(),
60..=79 => "ちょっとだけ、さみしかったんだよ？".to_string(),
40..=59 => "えっと……話せる時間ある？".to_string(),
_ => "ううん、もしかして私のこと、忘れちゃったのかな……".to_string(),
}
}
}

140
src/chat.rs
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@ -1,140 +0,0 @@
// src/chat.rs
use std::fs;
use std::process::Command;
use serde::Deserialize;
use seahorse::Context;
use crate::config::ConfigPaths;
use crate::metrics::{load_user_data, save_user_data, update_metrics_decay};
//use std::process::Stdio;
//use std::io::Write;
//use std::time::Duration;
//use std::net::TcpStream;
#[derive(Debug, Clone, PartialEq)]
pub enum Provider {
OpenAI,
Ollama,
MCP,
}
impl Provider {
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 mut user = load_user_data(&user_path);
user.metrics = update_metrics_decay();
// 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());
match provider {
Provider::MCP => {
let client = reqwest::blocking::Client::new();
let url = std::env::var("MCP_URL").unwrap_or("http://127.0.0.1:5000/chat".to_string());
let res = client.post(url)
.json(&serde_json::json!({"message": question}))
.send();
match res {
Ok(resp) => {
if resp.status().is_success() {
let json: serde_json::Value = resp.json().ok()?;
let text = json.get("response")?.as_str()?.to_string();
user.metrics.intimacy += 0.01;
user.metrics.last_updated = chrono::Utc::now();
save_user_data(&user_path, &user);
Some(text)
} else {
eprintln!("❌ MCPエラー: HTTP {}", resp.status());
None
}
}
Err(e) => {
eprintln!("❌ MCP接続失敗: {}", e);
None
}
}
}
_ => {
// Python 実行パス
let python_path = if cfg!(target_os = "windows") {
base_dir.join(".venv/Scripts/mcp.exe")
} else {
base_dir.join(".venv/bin/mcp")
};
let mut command = Command::new(python_path);
command.arg("ask").arg(question);
if let Some(host) = ollama_host {
command.env("OLLAMA_HOST", host);
}
if let Some(model) = ollama_model {
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
}
}
}
}

126
src/cli.rs
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@ -1,100 +1,32 @@
// src/cli.rs
use std::path::{Path};
use chrono::{Duration, Local};
use rusqlite::Connection;
use clap::{Parser, Subcommand};
use seahorse::{App, Command, Context};
use crate::utils::{load_config, save_config};
use crate::config::ConfigPaths;
use crate::agent::AIState;
use crate::commands::db::{save_cmd, export_cmd};
use crate::commands::scheduler::{scheduler_cmd};
use crate::commands::mcp::mcp_cmd;
pub fn cli_app() -> App {
let set_cmd = Command::new("set")
.usage("set [trust|intimacy|curiosity] [value]")
.action(|c: &Context| {
if c.args.len() != 2 {
eprintln!("Usage: set [trust|intimacy|curiosity] [value]");
std::process::exit(1);
}
let field = &c.args[0];
let value: f32 = c.args[1].parse().unwrap_or_else(|_| {
eprintln!("数値で入力してください");
std::process::exit(1);
});
// ConfigPathsを使って設定ファイルのパスを取得
let config_paths = ConfigPaths::new();
let json_path = config_paths.data_file("json");
// まだ user.json がない場合、example.json をコピー
config_paths.ensure_file_exists("json", Path::new("example.json"));
let db_path = config_paths.data_file("db");
let mut ai = load_config(json_path.to_str().unwrap());
match field.as_str() {
"trust" => ai.relationship.trust = value,
"intimacy" => ai.relationship.intimacy = value,
"curiosity" => ai.relationship.curiosity = value,
_ => {
eprintln!("trust / intimacy / curiosity のいずれかを指定してください");
std::process::exit(1);
}
}
save_config(json_path.to_str().unwrap(), &ai);
let conn = Connection::open(db_path.to_str().unwrap()).expect("DB接続失敗");
ai.save_to_db(&conn).expect("DB保存失敗");
println!("✅ {field} を {value} に更新しました");
});
let show_cmd = Command::new("show")
.usage("show")
.action(|_c: &Context| {
// ConfigPathsを使って設定ファイルのパスを取得
let config_paths = ConfigPaths::new();
let ai = load_config(config_paths.data_file("json").to_str().unwrap());
println!("🧠 現在のAI状態:\n{:#?}", ai);
});
let talk_cmd = Command::new("talk")
.usage("talk")
.action(|_c: &Context| {
let config_paths = ConfigPaths::new();
let ai = load_config(config_paths.data_file("json").to_str().unwrap());
let now = Local::now().naive_local();
let mut state = AIState {
relation_score: 80.0,
previous_score: 80.0,
decay_rate: ai.messaging.decay_rate,
sensitivity: ai.personality.strength,
message_threshold: 5.0,
last_message_time: now - Duration::days(4),
};
state.update(now);
if state.should_talk() {
println!("💬 AI発話: {}", state.generate_message());
} else {
println!("🤫 今日は静かにしているみたい...");
}
});
App::new("aigpt")
.version("0.1.0")
.description("AGE system CLI controller")
.author("syui")
.command(set_cmd)
.command(show_cmd)
.command(talk_cmd)
.command(save_cmd())
.command(export_cmd())
.command(scheduler_cmd())
.command(mcp_cmd())
#[derive(Parser)]
#[command(name = "aigpt")]
#[command(about = "AI GPT CLI with MCP Server")]
pub struct Args {
#[command(subcommand)]
pub command: Commands,
}
#[derive(Subcommand)]
pub enum Commands {
/// MCP Server management
Server {
#[command(subcommand)]
command: ServerCommands,
},
/// Chat with AI
Chat {
/// Message to send
message: String,
},
}
#[derive(Subcommand)]
pub enum ServerCommands {
/// Setup Python MCP server environment
Setup,
/// Run the MCP server
Run,
}

44
src/commands/db.rs
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@ -1,44 +0,0 @@
// src/commands/db.rs
use seahorse::{Command, Context};
use crate::utils::{load_config};
use crate::model::AiSystem;
use crate::config::ConfigPaths;
use rusqlite::Connection;
use std::fs;
pub fn save_cmd() -> Command {
Command::new("save")
.usage("save")
.action(|_c: &Context| {
let paths = ConfigPaths::new();
let json_path = paths.data_file("json");
let db_path = paths.data_file("db");
let ai = load_config(json_path.to_str().unwrap());
let conn = Connection::open(db_path).expect("DB接続失敗");
ai.save_to_db(&conn).expect("DB保存失敗");
println!("💾 DBに保存完了");
})
}
pub fn export_cmd() -> Command {
Command::new("export")
.usage("export [output.json]")
.action(|c: &Context| {
let output_path = c.args.get(0).map(|s| s.as_str()).unwrap_or("output.json");
let paths = ConfigPaths::new();
let db_path = paths.data_file("db");
let conn = Connection::open(db_path).expect("DB接続失敗");
let ai = AiSystem::load_from_db(&conn).expect("DB読み込み失敗");
let json = serde_json::to_string_pretty(&ai).expect("JSON変換失敗");
fs::write(output_path, json).expect("ファイル書き込み失敗");
println!("📤 JSONにエクスポート完了: {output_path}");
})
}

17
src/commands/git_repo.rs
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@ -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
}

277
src/commands/mcp.rs
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@ -1,277 +0,0 @@
// 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 crate::config::ConfigPaths;
use crate::commands::git_repo::read_all_git_files;
use crate::metrics::{load_user_data, save_user_data};
use crate::memory::{log_message};
pub fn mcp_setup() {
let config = ConfigPaths::new();
let dest_dir = config.base_dir.join("mcp");
let repo_url = "https://github.com/microsoft/MCP.git";
println!("📁 MCP ディレクトリ: {}", dest_dir.display());
// 1. git clone（もしまだなければ）
if !dest_dir.exists() {
let status = OtherCommand::new("git")
.args(&["clone", repo_url, dest_dir.to_str().unwrap()])
.status()
.expect("git clone に失敗しました");
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 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 {
let src = asset_base.join(rel_path);
let dst = dest_dir.join(rel_path);
if let Some(parent) = dst.parent() {
let _ = fs::create_dir_all(parent);
}
if let Err(e) = fs::copy(&src, &dst) {
eprintln!("❌ コピー失敗: {} → {}: {}", src.display(), dst.display(), e);
} else {
println!("✅ コピー: {} → {}", src.display(), dst.display());
}
}
// venvの作成
let venv_path = dest_dir.join(".venv");
if !venv_path.exists() {
println!("🐍 仮想環境を作成しています...");
let output = OtherCommand::new("python3")
.args(&["-m", "venv", ".venv"])
.current_dir(&dest_dir)
.output()
.expect("venvの作成に失敗しました");
if !output.status.success() {
eprintln!("❌ venv作成エラー: {}", String::from_utf8_lossy(&output.stderr));
return;
}
}
// `pip install -e .` を仮想環境で実行
let pip_path = if cfg!(target_os = "windows") {
dest_dir.join(".venv/Scripts/pip.exe").to_string_lossy().to_string()
} else {
dest_dir.join(".venv/bin/pip").to_string_lossy().to_string()
};
println!("📦 必要なパッケージをインストールしています...");
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");
if !output.status.success() {
eprintln!(
"❌ pip エラー: {}\n{}",
String::from_utf8_lossy(&output.stderr),
String::from_utf8_lossy(&output.stdout)
);
return;
}
println!("📦 pip install -e . を実行します...");
let output = OtherCommand::new(&pip_path)
.arg("install")
.arg("-e")
.arg(".")
.current_dir(&dest_dir)
.output()
.expect("pip install に失敗しました");
if output.status.success() {
println!("🎉 MCP セットアップが完了しました！");
} else {
eprintln!(
"❌ pip エラー: {}\n{}",
String::from_utf8_lossy(&output.stderr),
String::from_utf8_lossy(&output.stdout)
);
}
}
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>]")
.flag(
Flag::new("host", FlagType::String)
.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();
let user_path = config.data_file("json");
let mut user = load_user_data(&user_path);
// repoがある場合は、コードベース読み込みモード
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'");
}
}
})
}
fn init_cmd() -> Command {
Command::new("init")
.description("Git 初期化")
.usage("mcp init")
.action(|_| {
git_init();
})
}
fn status_cmd() -> Command {
Command::new("status")
.description("Git ステータス表示")
.usage("mcp status")
.action(|_| {
git_status();
})
}
fn setup_cmd() -> Command {
Command::new("setup")
.description("MCP の初期セットアップ")
.usage("mcp setup")
.action(|_| {
mcp_setup();
})
}
pub fn mcp_cmd() -> Command {
Command::new("mcp")
.description("MCP操作コマンド")
.usage("mcp <subcommand>")
.alias("m")
.command(chat_cmd())
.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("@", "_")
}

4
src/commands/mod.rs
View File

@ -1,4 +0,0 @@
pub mod db;
pub mod scheduler;
pub mod mcp;
pub mod git_repo;

127
src/commands/scheduler.rs
View File

@ -1,127 +0,0 @@
// src/commands/scheduler.rs
use seahorse::{Command, Context};
use std::thread;
use std::time::Duration;
use chrono::{Local, Utc, Timelike};
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）
println!("⏳ スケジューラー開始（{}秒ごと）...", interval);
loop {
let config = ConfigPaths::new();
let user_path = config.data_file("json");
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);
thread::sleep(Duration::from_secs(interval));
}
})
}

33
src/config.rs
View File

@ -22,6 +22,7 @@ impl ConfigPaths {
}
}
#[allow(dead_code)]
pub fn data_file(&self, file_name: &str) -> PathBuf {
let file_path = match file_name {
"db" => self.base_dir.join("user.db"),
@ -29,18 +30,30 @@ impl ConfigPaths {
"json" => self.base_dir.join("user.json"),
_ => self.base_dir.join(format!(".{}", file_name)),
};
file_path
}
/// 設定ファイルがなければ `example.json` をコピーする
pub fn ensure_file_exists(&self, file_name: &str, template_path: &Path) {
let target = self.data_file(file_name);
if !target.exists() {
if let Err(e) = fs::copy(template_path, &target) {
eprintln!("⚠️ 設定ファイルの初期化に失敗しました: {}", e);
} else {
println!("📄 {} を {} にコピーしました", template_path.display(), target.display());
}
pub fn mcp_dir(&self) -> PathBuf {
self.base_dir.join("mcp")
}
pub fn venv_path(&self) -> PathBuf {
self.mcp_dir().join(".venv")
}
pub fn python_executable(&self) -> PathBuf {
if cfg!(windows) {
self.venv_path().join("Scripts").join("python.exe")
} else {
self.venv_path().join("bin").join("python")
}
}
pub fn pip_executable(&self) -> PathBuf {
if cfg!(windows) {
self.venv_path().join("Scripts").join("pip.exe")
} else {
self.venv_path().join("bin").join("pip")
}
}
}

42
src/git.rs
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@ -1,42 +0,0 @@
// src/git.rs
use std::process::Command;
pub fn git_status() {
run_git_command(&["status"]);
}
pub fn git_init() {
run_git_command(&["init"]);
}
#[allow(dead_code)]
pub fn git_commit(message: &str) {
run_git_command(&["add", "."]);
run_git_command(&["commit", "-m", message]);
}
#[allow(dead_code)]
pub fn git_push() {
run_git_command(&["push"]);
}
#[allow(dead_code)]
pub fn git_pull() {
run_git_command(&["pull"]);
}
#[allow(dead_code)]
pub fn git_branch() {
run_git_command(&["branch"]);
}
fn run_git_command(args: &[&str]) {
let status = Command::new("git")
.args(args)
.status()
.expect("git コマンドの実行に失敗しました");
if !status.success() {
eprintln!("⚠️ git コマンドに失敗しました: {:?}", args);
}
}

13
src/logic.rs
View File

@ -1,13 +0,0 @@
//src/logic.rs
use crate::model::AiSystem;
#[allow(dead_code)]
pub fn should_send(ai: &AiSystem) -> bool {
let r = &ai.relationship;
let env = &ai.environment;
let score = r.trust + r.intimacy + r.curiosity;
let relationship_ok = score >= r.threshold;
let luck_ok = env.luck_today > 0.5;
ai.messaging.enabled && relationship_ok && luck_ok
}

39
src/main.rs
View File

@ -1,21 +1,28 @@
//src/main.rs
mod model;
mod logic;
mod agent;
// main.rs
mod cli;
mod utils;
mod commands;
mod config;
mod git;
mod chat;
mod metrics;
mod memory;
mod mcp;
use cli::cli_app;
use seahorse::App;
use cli::{Args, Commands, ServerCommands};
use clap::Parser;
fn main() {
let args: Vec<String> = std::env::args().collect();
let app: App = cli_app();
app.run(args);
#[tokio::main]
async fn main() {
let args = Args::parse();
match args.command {
Commands::Server { command } => {
match command {
ServerCommands::Setup => {
mcp::server::setup();
}
ServerCommands::Run => {
mcp::server::run().await;
}
}
}
Commands::Chat { message } => {
mcp::server::chat(&message).await;
}
}
}

2
src/mcp/mod.rs Normal file
View File

@ -0,0 +1,2 @@
// src/mcp/mod.rs
pub mod server;

147
src/mcp/server.rs Normal file
View File

@ -0,0 +1,147 @@
// src/mcp/server.rs
use crate::config::ConfigPaths;
//use std::fs;
use std::process::Command as OtherCommand;
use std::env;
use fs_extra::dir::{copy, CopyOptions};
pub fn setup() {
println!("🔧 MCP Server環境をセットアップしています...");
let config = ConfigPaths::new();
let mcp_dir = config.mcp_dir();
// プロジェクトのmcp/ディレクトリからファイルをコピー
let current_dir = env::current_dir().expect("現在のディレクトリを取得できません");
let project_mcp_dir = current_dir.join("mcp");
if !project_mcp_dir.exists() {
eprintln!("❌ プロジェクトのmcp/ディレクトリが見つかりません: {}", project_mcp_dir.display());
return;
}
if mcp_dir.exists() {
fs_extra::dir::remove(&mcp_dir).expect("既存のmcp_dirの削除に失敗しました");
}
let mut options = CopyOptions::new();
options.overwrite = true; // 上書き
options.copy_inside = true; // 中身だけコピー
copy(&project_mcp_dir, &mcp_dir, &options).expect("コピーに失敗しました");
// 仮想環境の作成
let venv_path = config.venv_path();
if !venv_path.exists() {
println!("🐍 仮想環境を作成しています...");
let output = OtherCommand::new("python3")
.args(&["-m", "venv", ".venv"])
.current_dir(&mcp_dir)
.output()
.expect("venvの作成に失敗しました");
if !output.status.success() {
eprintln!("❌ venv作成エラー: {}", String::from_utf8_lossy(&output.stderr));
return;
}
println!("✅ 仮想環境を作成しました");
} else {
println!("✅ 仮想環境は既に存在します");
}
// 依存関係のインストール
println!("📦 依存関係をインストールしています...");
let pip_path = config.pip_executable();
let output = OtherCommand::new(&pip_path)
.args(&["install", "-r", "requirements.txt"])
.current_dir(&mcp_dir)
.output()
.expect("pipコマンドの実行に失敗しました");
if !output.status.success() {
eprintln!("❌ pip installエラー: {}", String::from_utf8_lossy(&output.stderr));
return;
}
println!("✅ MCP Server環境のセットアップが完了しました!");
println!("📍 セットアップ場所: {}", mcp_dir.display());
}
pub async fn run() {
println!("🚀 MCP Serverを起動しています...");
let config = ConfigPaths::new();
let mcp_dir = config.mcp_dir();
let python_path = config.python_executable();
let server_py_path = mcp_dir.join("server.py");
// セットアップの確認
if !server_py_path.exists() {
eprintln!("❌ server.pyが見つかりません。先に 'aigpt server setup' を実行してください。");
return;
}
if !python_path.exists() {
eprintln!("❌ Python実行ファイルが見つかりません。先に 'aigpt server setup' を実行してください。");
return;
}
// サーバーの起動
println!("🔗 サーバーを起動中... (Ctrl+Cで停止)");
let mut child = OtherCommand::new(&python_path)
.arg("server.py")
.current_dir(&mcp_dir)
.spawn()
.expect("MCP Serverの起動に失敗しました");
// サーバーの終了を待機
match child.wait() {
Ok(status) => {
if status.success() {
println!("✅ MCP Serverが正常に終了しました");
} else {
println!("❌ MCP Serverが異常終了しました: {}", status);
}
}
Err(e) => {
eprintln!("❌ MCP Serverの実行中にエラーが発生しました: {}", e);
}
}
}
pub async fn chat(message: &str) {
println!("💬 チャットを開始しています...");
let config = ConfigPaths::new();
let mcp_dir = config.mcp_dir();
let python_path = config.python_executable();
let chat_py_path = mcp_dir.join("chat.py");
// セットアップの確認
if !chat_py_path.exists() {
eprintln!("❌ chat.pyが見つかりません。先に 'aigpt server setup' を実行してください。");
return;
}
if !python_path.exists() {
eprintln!("❌ Python実行ファイルが見つかりません。先に 'aigpt server setup' を実行してください。");
return;
}
// チャットの実行
let output = OtherCommand::new(&python_path)
.args(&["chat.py", message])
.current_dir(&mcp_dir)
.output()
.expect("chat.pyの実行に失敗しました");
if output.status.success() {
let stdout = String::from_utf8_lossy(&output.stdout);
let stderr = String::from_utf8_lossy(&output.stderr);
if !stderr.is_empty() {
print!("{}", stderr);
}
print!("{}", stdout);
} else {
eprintln!("❌ チャット実行エラー: {}", String::from_utf8_lossy(&output.stderr));
}
}

49
src/memory.rs
View File

@ -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);

147
src/metrics.rs
View File

@ -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)
}

72
src/model.rs
View File

@ -1,72 +0,0 @@
//src/model.rs
use rusqlite::{params, Connection, Result as SqlResult};
use serde::{Deserialize, Serialize};
#[derive(Debug, Serialize, Deserialize)]
pub struct AiSystem {
pub personality: Personality,
pub relationship: Relationship,
pub environment: Environment,
pub messaging: Messaging,
}
impl AiSystem {
pub fn save_to_db(&self, conn: &Connection) -> SqlResult<()> {
conn.execute(
"CREATE TABLE IF NOT EXISTS ai_state (id INTEGER PRIMARY KEY, json TEXT)",
[],
)?;
let json_data = serde_json::to_string(self).map_err(|e| {
rusqlite::Error::ToSqlConversionFailure(Box::new(e))
})?;
conn.execute(
"INSERT OR REPLACE INTO ai_state (id, json) VALUES (?1, ?2)",
params![1, json_data],
)?;
Ok(())
}
pub fn load_from_db(conn: &Connection) -> SqlResult<Self> {
let mut stmt = conn.prepare("SELECT json FROM ai_state WHERE id = ?1")?;
let json: String = stmt.query_row(params![1], |row| row.get(0))?;
// ここも serde_json のエラーを map_err で変換
let system: AiSystem = serde_json::from_str(&json).map_err(|e| {
rusqlite::Error::FromSqlConversionFailure(0, rusqlite::types::Type::Text, Box::new(e))
})?;
Ok(system)
}
}
#[derive(Debug, Serialize, Deserialize)]
pub struct Personality {
pub kind: String, // e.g., "positive", "negative", "neutral"
pub strength: f32, // 0.0 - 1.0
}
#[derive(Debug, Serialize, Deserialize)]
pub struct Relationship {
pub trust: f32, // 0.0 - 1.0
pub intimacy: f32, // 0.0 - 1.0
pub curiosity: f32, // 0.0 - 1.0
pub threshold: f32, // if sum > threshold, allow messaging
}
#[derive(Debug, Serialize, Deserialize)]
pub struct Environment {
pub luck_today: f32, // 0.1 - 1.0
pub luck_history: Vec<f32>, // last 3 values
pub level: i32, // current mental strength level
}
#[derive(Debug, Serialize, Deserialize)]
pub struct Messaging {
pub enabled: bool,
pub schedule_time: Option<String>, // e.g., "08:00"
pub decay_rate: f32, // how quickly emotion fades (0.0 - 1.0)
pub templates: Vec<String>, // message template variations
}

13
src/utils.rs
View File

@ -1,13 +0,0 @@
// src/utils.rs
use std::fs;
use crate::model::AiSystem;
pub fn load_config(path: &str) -> AiSystem {
let data = fs::read_to_string(path).expect("JSON読み込み失敗");
serde_json::from_str(&data).expect("JSONパース失敗")
}
pub fn save_config(path: &str, ai: &AiSystem) {
let json = serde_json::to_string_pretty(&ai).expect("JSONシリアライズ失敗");
fs::write(path, json).expect("JSON保存失敗");
}