The shipit CLI & Power Tools Test Drive

from pathlib import Path
import sys
ROOT = Path.cwd().resolve().parent if Path.cwd().name == "notebooks" else Path.cwd().resolve()
if str(ROOT) not in sys.path:
    sys.path.insert(0, str(ROOT))
print("setup OK")

from shipit_agent.cli import main

print("── shipit models ──")
main(["models"])
print()
print("── shipit run (echo provider, JSON) ──")
main(["run", "hello from the notebook", "--provider", "echo", "--json"])

import subprocess, tempfile
from shipit_agent.tools import GitOpsTool
from shipit_agent.tools.base import ToolContext

repo = Path(tempfile.mkdtemp(prefix="shipit_git_"))
for argv in (["init","-q"], ["config","user.email","[email]"],
             ["config","user.name","Notebook"]):
    subprocess.run(["git", *argv], cwd=repo, check=True, capture_output=True)
(repo / "app.py").write_text("def greet():\n    return 'hello'\n")

git = GitOpsTool(root_dir=repo)
ctx = ToolContext(prompt="", system_prompt="", state={})
git.run(ctx, action="add")
print(git.run(ctx, action="commit", message="feat: greet").text.splitlines()[0])
(repo / "app.py").write_text("def greet():\n    return 'hello world'\n")
print(git.run(ctx, action="diff").text[:300])
print()
print("push gated:", git.run(ctx, action="push").text[:60])

import json as _json
from shipit_agent.tools import NotebookEditTool

nb_path = repo / "analysis.ipynb"
nb_path.write_text(_json.dumps({"cells":[
    {"cell_type":"markdown","metadata":{},"source":"# Analysis"},
    {"cell_type":"code","metadata":{},"execution_count":1,
     "source":"x = 1","outputs":[]}],
    "metadata":{},"nbformat":4,"nbformat_minor":5}))

nbt = NotebookEditTool(root_dir=repo)
print(nbt.run(ctx, path="analysis.ipynb", action="list").text)
nbt.run(ctx, path="analysis.ipynb", action="edit", index=1, source="x = 42")
nbt.run(ctx, path="analysis.ipynb", action="add", source="print(x)")
print()
print(nbt.run(ctx, path="analysis.ipynb", action="list").text)

from shipit_agent import Agent, FunctionTool, format_activity
from shipit_agent.llms.base import LLMResponse

class TextCallLLM:
    def __init__(self): self.turn = 0
    def complete(self, *, messages, tools=None, **_):
        self.turn += 1
        if self.turn == 1:
            return LLMResponse(content=(
                'I will add them.\n<tool_call>{"name": "add", '
                '"arguments": {"a": 2, "b": 3}}</tool_call>'))
        return LLMResponse(content="The sum is 5.")

def add(a: int, b: int, **_): return str(a + b)

agent = Agent(llm=TextCallLLM(),
              tools=[FunctionTool.from_callable(add, name="add")],
              auto_use_skills=False)
result = agent.run("2+3?")
print("healed:", any(e.type == "tool_call_healed" for e in result.events))
print(format_activity(result))

from shipit_agent.llms.base import ToolCall

class StallingLLM:
    def __init__(self): self.turn = 0
    def complete(self, *, messages, tools=None, **_):
        self.turn += 1
        if self.turn == 1:
            return LLMResponse(content="Let me use the add tool for this.")
        if self.turn == 2:
            return LLMResponse(tool_calls=[ToolCall(name="add", arguments={"a":2,"b":3})])
        return LLMResponse(content="The sum is 5.")

agent = Agent(llm=StallingLLM(),
              tools=[FunctionTool.from_callable(add, name="add")],
              auto_use_skills=False, max_iterations=6)
result = agent.run("2+3?")
nudges = [e for e in result.events if e.type == "tool_call_healed" and e.payload.get("nudge")]
print(f"nudged {len(nudges)}× → final: {result.output}")

import json as _json, urllib.request
from shipit_agent.serve import AgentServer

class EchoLLM:
    def complete(self, *, messages, **_):
        last = [m for m in messages if (m.get("role") if isinstance(m, dict) else m.role) == "user"][-1]
        text = last.get("content") if isinstance(last, dict) else last.content
        return LLMResponse(content=f"agent says: {text}")

srv = AgentServer(Agent(llm=EchoLLM(), auto_use_skills=False),
                  model_name="shipit-nb", api_key="demo")
port = srv.start(port=0)
req = urllib.request.Request(
    f"http://127.0.0.1:{port}/v1/chat/completions",
    data=_json.dumps({"messages":[{"role":"user","content":"ping"}]}).encode(),
    headers={"Content-Type":"application/json","Authorization":"Bearer demo"})
with urllib.request.urlopen(req) as resp:
    print(_json.loads(resp.read())["choices"][0]["message"]["content"])
srv.stop()
print("(any OpenAI SDK can do the same — base_url =", f"http://127.0.0.1:{port}/v1)")