Pi Agent: First Chat

pi-agent chat "Hello, please introduce yourself"

Pi Agent v0.8.0
Provider: deepseek (deepseek-chat)

Hello! I'm Pi Agent, a lightweight AI agent framework. I can help you
answer questions, call tools, and execute tasks. Chatting with me is
like talking to an AI partner that can take action!

pi-agent chat --provider openai --model gpt-4o "Explain quantum entanglement"

pi-agent chat --skill code_review "Review this Python code"

from pi_agent import Agent

agent = Agent(name="hello")
response = agent.chat("Hello, Pi Agent!")
print(response)

from pi_agent import Agent

agent = Agent(name="tutor", system_prompt="You are a Python programming tutor")

r1 = agent.chat("What are list comprehensions?")
print(r1)

r2 = agent.chat("Give me a practical example")
print(r2)

r3 = agent.chat("What are the advantages over for loops?")
print(r3)

from pi_agent import Agent

agent = Agent(name="structured")
response = agent.chat(
    "List 5 programming languages with their names and invention years",
    response_format="json"
)

print(type(response))  # <class 'dict'>

messages = [
    {"role": "system", "content": "You are a coding assistant"},
    {"role": "user", "content": "What are decorators?"},
    {"role": "assistant", "content": "Decorators are..."},
    {"role": "user", "content": "Can you give an example?"}
]

from pi_agent import Agent

coder = Agent(
    name="coder",
    system_prompt="You are a Python expert. Respond concisely with code and key explanations only"
)

teacher = Agent(
    name="teacher",
    system_prompt="You are a patient programming teacher. Explain concepts with analogies and step-by-step breakdowns"
)

q = "What are generators?"

print("=== Coder ===")
print(coder.chat(q))

print("=== Teacher ===")
print(teacher.chat(q))

from pi_agent import Agent

agent = Agent(name="stream")
for chunk in agent.chat_stream("Write a poem about programming"):
    print(chunk, end="", flush=True)

from pi_agent import Agent

agent = Agent(name="meta")
response = agent.chat("1+1=?")

print(response.text)          # "2"
print(response.model)         # "deepseek-chat"
print(response.usage)         # {"prompt_tokens": 12, "completion_tokens": 3}
print(response.tool_calls)    # [] (يسجل إذا استُدعيت أدوات)
print(response.finish_reason) # "stop"