DeepAgent + live chat

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))

from shipit_agent.deep import DEEP_AGENT_PROMPT, DeepAgent, Goal, create_deep_agent
from shipit_agent.rag import RAG, HashingEmbedder

from examples.run_multi_tool_agent import build_llm_from_env

llm = build_llm_from_env("bedrock")

llm

print(DEEP_AGENT_PROMPT[:1000], "...")

agent = DeepAgent(llm=llm)
deep_tool_names = sorted({t.name for t in agent.tools})
print(f"{len(deep_tool_names)} tools wired:")
for name in deep_tool_names:
    print(f"  · {name}")

full = DeepAgent.with_builtins(llm=llm)
names = {t.name for t in full.tools}
print(f"{len(names)} tools when use_builtins=True")
deep_only = {
    "plan_task",
    "decompose_problem",
    "workspace_files",
    "sub_agent",
    "synthesize_evidence",
    "decision_matrix",
    "verify_output",
}
print("all 7 deep tools present:", deep_only <= names)

def get_weather(city: str) -> str:
    """Get weather for a given city."""
    return f"It's always sunny in {city}!"


weather_agent = create_deep_agent(
    tools=[get_weather],
    llm=llm,
    system_prompt="You are a helpful weather assistant.",
)
print("tools:", sorted(t.name for t in weather_agent.tools))
assert "get_weather" in {t.name for t in weather_agent.tools}
print("weather_agent is a DeepAgent:", isinstance(weather_agent, DeepAgent))

rag = RAG.default(embedder=HashingEmbedder(dimension=512))
rag.index_text("Shipit supports Python 3.10+.", source="readme.md")
rag.index_text("DeepAgent ships seven tools by default.", source="changelog.md")

powerful = DeepAgent.with_builtins(
    llm=llm,
    rag=rag,  # auto-cited grounded answers
    verify=True,  # verifier runs after every answer
    reflect=False,  # set True to enable self-critique
    max_iterations=20,
    parallel_tool_execution=True,
    context_window_tokens=200_000,
)
print("verify =", powerful.verify)
print("rag attached =", powerful.rag is not None)
print(
    "inner agent has rag_search =",
    any(t.name == "rag_search" for t in powerful.agent.tools),
)
print("max_iterations =", powerful.agent.max_iterations)

result = powerful.run("What Python version does Shipit support?")
print("output:", result.output[:200])
print("verification verdict present:", "verification" in result.metadata)
if "verification" in result.metadata:
    print("verification text:", result.metadata["verification"]["text"][:200])

goal_agent = DeepAgent(
    llm=llm,
    goal=Goal(
        objective="Say hello and confirm Python version.",
        success_criteria=["greeting", "mentions python"],
        max_steps=2,
    ),
    rag=rag,
)
result = goal_agent.run("What Python version does Shipit support?")
print("goal_status =", result.goal_status)
print("criteria_met =", result.criteria_met)
print("steps_taken =", result.steps_taken)

chat = powerful.chat(session_id="demo-1")

# First turn — streaming
for event in chat.stream("What Python version do we support?"):
    if event.type in (
        "run_started",
        "tool_called",
        "tool_completed",
        "rag_sources",
        "run_completed",
    ):
        print(f"  · [{event.type}] {event.message[:80]}")

# Second turn — blocking
result = chat.send("And what about deep agent features?")
print()
print("answer:", result.output[:200])
print()
print("history length:", len(chat.history()))

from shipit_agent.chat_cli import ChatREPL

repl = ChatREPL(
    llm=llm,
    agent_type="deep",
    use_builtins=False,
    quiet=True,
)

scripted = iter(["/agents", "/tools", "/info", "hello there", "/history", "/exit"])
log = []


def in_fn(_):
    return next(scripted)


def out(*a, **k):
    log.append(" ".join(str(x) for x in a))


exit_code = repl.run(input_fn=in_fn, output=out)
print("exit_code =", exit_code)
print()
print("--- captured log (first 25 lines) ---")
for line in log[:25]:
    print(line)

from shipit_agent.chat_cli import AGENT_TYPES, ChatREPL, make_agent

print("All agent types you can switch to:")
for t in AGENT_TYPES:
    a = make_agent(t, llm=llm, use_builtins=False)
    print(f"  · {t:12s} → {a.__class__.__name__}")