initial commit

.env

@@ -0,0 +1,61 @@
+# API Key (required)
+# Get yours at: https://console.anthropic.com/
+ANTHROPIC_API_KEY=sk-9wTK68ZO58_s4w5_SUsR7w
+
+# Model ID (required)
+MODEL_ID=gemini-3-flash-thinking
+
+# Base URL (optional, for Anthropic-compatible providers)
+ANTHROPIC_BASE_URL=https://coding.qunhequnhe.com
+
+# =============================================================================
+#  Anthropic-compatible providers
+#
+#  Provider         MODEL_ID              SWE-bench  TB2     Base URL
+#  ---------------  --------------------  ---------  ------  -------------------
+#  Anthropic        claude-sonnet-4-6     79.6%      59.1%   (default)
+#  MiniMax          MiniMax-M2.5          80.2%        -     see below
+#  GLM (Zhipu)      glm-5                77.8%        -     see below
+#  Kimi (Moonshot)  kimi-k2.5            76.8%        -     see below
+#  DeepSeek         deepseek-chat        73.0%        -     see below
+#                   (V3.2)
+#
+#  SWE-bench = SWE-bench Verified (Feb 2026)
+#  TB2       = Terminal-Bench 2.0 (Feb 2026)
+# =============================================================================
+
+# ---- International ----
+
+# MiniMax          https://www.minimax.io
+# ANTHROPIC_BASE_URL=https://api.minimax.io/anthropic
+# MODEL_ID=MiniMax-M2.5
+
+# GLM (Zhipu)      https://z.ai
+# ANTHROPIC_BASE_URL=https://api.z.ai/api/anthropic
+# MODEL_ID=glm-5
+
+# Kimi (Moonshot)  https://platform.moonshot.ai
+# ANTHROPIC_BASE_URL=https://api.moonshot.ai/anthropic
+# MODEL_ID=kimi-k2.5
+
+# DeepSeek         https://platform.deepseek.com
+# ANTHROPIC_BASE_URL=https://api.deepseek.com/anthropic
+# MODEL_ID=deepseek-chat
+
+# ---- China mainland ----
+
+# MiniMax          https://platform.minimax.io
+# ANTHROPIC_BASE_URL=https://api.minimaxi.com/anthropic
+# MODEL_ID=MiniMax-M2.5
+
+# GLM (Zhipu)      https://open.bigmodel.cn
+# ANTHROPIC_BASE_URL=https://open.bigmodel.cn/api/anthropic
+# MODEL_ID=glm-5
+
+# Kimi (Moonshot)  https://platform.moonshot.cn
+# ANTHROPIC_BASE_URL=https://api.moonshot.cn/anthropic
+# MODEL_ID=kimi-k2.5
+
+# DeepSeek (no regional split, same endpoint globally)
+# ANTHROPIC_BASE_URL=https://api.deepseek.com/anthropic
+# MODEL_ID=deepseek-chat

AGENTS.md

@@ -0,0 +1,5 @@
+# 本项目致力于搭建一个基于终端交互的agent，用于生成CAD模型或3D模型
+# 这是一个python项目，使用conda管理虚拟环境，虚拟环境名字是：aigc
+# 开发过程中，不要过度设计，少即是多
+# agent迭代方式仍会遵循敏捷迭代，也就是每个版本都独立、可交付
+# 推理、设计、改动等过程中任何一环，出现拿不准的情况，不要擅自主张，可以拆解问题或向用户提问

agent_loop.py

@@ -0,0 +1,128 @@
+import os
+import subprocess
+from pathlib import Path
+
+from anthropic import Anthropic
+from dotenv import load_dotenv
+
+load_dotenv(override=True)
+
+if os.getenv("ANTHROPIC_BASE_URL"):
+    os.environ.pop("ANTHROPIC_AUTH_TOKEN", None)
+
+WORKDIR = Path.cwd()
+client = Anthropic(base_url=os.getenv("ANTHROPIC_BASE_URL"))
+MODEL = os.environ["MODEL_ID"]
+
+SYSTEM = f"You are a coding agent at {WORKDIR}. Use tools to solve tasks. Act, don't explain."
+
+
+def safe_path(p: str) -> Path:
+    path = (WORKDIR / p).resolve()
+    if not path.is_relative_to(WORKDIR):
+        raise ValueError(f"Path escapes workspace: {p}")
+    return path
+
+
+def run_bash(command: str) -> str:
+    dangerous = ["rm -rf /", "sudo", "shutdown", "reboot", "> /dev/"]
+    if any(d in command for d in dangerous):
+        return "Error: Dangerous command blocked"
+    try:
+        r = subprocess.run(command, shell=True, cwd=WORKDIR,
+                           capture_output=True, text=True, timeout=120)
+        out = (r.stdout + r.stderr).strip()
+        return out[:50000] if out else "(no output)"
+    except subprocess.TimeoutExpired:
+        return "Error: Timeout (120s)"
+
+
+def run_read(path: str, limit: int = None) -> str:
+    try:
+        text = safe_path(path).read_text()
+        lines = text.splitlines()
+        if limit and limit < len(lines):
+            lines = lines[:limit] + [f"... ({len(lines) - limit} more lines)"]
+        return "\n".join(lines)[:50000]
+    except Exception as e:
+        return f"Error: {e}"
+
+
+def run_write(path: str, content: str) -> str:
+    try:
+        fp = safe_path(path)
+        fp.parent.mkdir(parents=True, exist_ok=True)
+        fp.write_text(content)
+        return f"Wrote {len(content)} bytes to {path}"
+    except Exception as e:
+        return f"Error: {e}"
+
+
+def run_edit(path: str, old_text: str, new_text: str) -> str:
+    try:
+        fp = safe_path(path)
+        content = fp.read_text()
+        if old_text not in content:
+            return f"Error: Text not found in {path}"
+        fp.write_text(content.replace(old_text, new_text, 1))
+        return f"Edited {path}"
+    except Exception as e:
+        return f"Error: {e}"
+
+
+# -- The dispatch map: {tool_name: handler} --
+TOOL_HANDLERS = {
+    "bash":       lambda **kw: run_bash(kw["command"]),
+    "read_file":  lambda **kw: run_read(kw["path"], kw.get("limit")),
+    "write_file": lambda **kw: run_write(kw["path"], kw["content"]),
+    "edit_file":  lambda **kw: run_edit(kw["path"], kw["old_text"], kw["new_text"]),
+}
+
+TOOLS = [
+    {"name": "bash", "description": "Run a shell command.",
+     "input_schema": {"type": "object", "properties": {"command": {"type": "string"}}, "required": ["command"]}},
+    {"name": "read_file", "description": "Read file contents.",
+     "input_schema": {"type": "object", "properties": {"path": {"type": "string"}, "limit": {"type": "integer"}}, "required": ["path"]}},
+    {"name": "write_file", "description": "Write content to file.",
+     "input_schema": {"type": "object", "properties": {"path": {"type": "string"}, "content": {"type": "string"}}, "required": ["path", "content"]}},
+    {"name": "edit_file", "description": "Replace exact text in file.",
+     "input_schema": {"type": "object", "properties": {"path": {"type": "string"}, "old_text": {"type": "string"}, "new_text": {"type": "string"}}, "required": ["path", "old_text", "new_text"]}},
+]
+
+
+def agent_loop(messages: list):
+    while True:
+        response = client.messages.create(
+            model=MODEL, system=SYSTEM, messages=messages,
+            tools=TOOLS, max_tokens=8000,
+        )
+        messages.append({"role": "assistant", "content": response.content})
+        if response.stop_reason != "tool_use":
+            return
+        results = []
+        for block in response.content:
+            if block.type == "tool_use":
+                handler = TOOL_HANDLERS.get(block.name)
+                output = handler(**block.input) if handler else f"Unknown tool: {block.name}"
+                print(f"> {block.name}: {output[:200]}")
+                results.append({"type": "tool_result", "tool_use_id": block.id, "content": output})
+        messages.append({"role": "user", "content": results})
+
+
+if __name__ == "__main__":
+    history = []
+    while True:
+        try:
+            query = input("\033[36ms02 >> \033[0m")
+        except (EOFError, KeyboardInterrupt):
+            break
+        if query.strip().lower() in ("q", "exit", ""):
+            break
+        history.append({"role": "user", "content": query})
+        agent_loop(history)
+        response_content = history[-1]["content"]
+        if isinstance(response_content, list):
+            for block in response_content:
+                if hasattr(block, "text"):
+                    print(block.text)
+        print()

requirements.txt

@@ -0,0 +1,2 @@
+anthropic
+python-dotenv