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agent_alpha/agent_a.py
T

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Python

import logfire
from pydantic_ai.models.openai import OpenAIResponsesModel
from pydantic_ai.providers.openai import OpenAIProvider
from pydantic_ai import Agent
from pydantic_ai.capabilities import MCP, Thinking, ToolSearch, WebSearch
from pydantic_ai_harness import CodeMode
# Community packages, alphabetical:
from pydantic_ai_backends import ConsoleCapability
from pydantic_ai_shields import CostTracking, InputGuard, SecretRedaction, ToolGuard
from pydantic_ai_skills import SkillsCapability
from pydantic_ai_summarization import ContextManagerCapability
from pydantic_ai_todo import TodoCapability
from pydantic_deep import MemoryCapability, StuckLoopDetection
from pydantic_deep.deps import DeepAgentDeps
from subagents_pydantic_ai import SubAgentCapability, SubAgentConfig
# See https://ai.pydantic.dev/logfire/ for setup details.
logfire.configure()
logfire.instrument_pydantic_ai()
model = OpenAIResponsesModel(
"llama",
provider=OpenAIProvider(base_url="http://localhost:8011/v1"),
)
agent = Agent(
model,
capabilities=[
# --- Tool execution & discovery ---
# Wraps every tool into a single run_code, sandboxed by Monty.
CodeMode(),
# Progressive tool discovery for large tool sets; discovered tools fold into run_code.
ToolSearch(),
# --- Reasoning ---
# Provider-adaptive thinking; uses native extended thinking on supporting models.
Thinking(effort="xhigh"),
# --- Context management ---
# Sliding window + LLM compaction. By @vstorm-co:
# https://github.com/vstorm-co/summarization-pydantic-ai
# Pydantic AI also ships `AnthropicCompaction` and `OpenAICompaction` for
# provider-native compaction.
ContextManagerCapability(max_tokens=100_000),
# --- Tools ---
# Connect to any MCP server -- here, the open-source Hacker News server
# (https://github.com/cyanheads/hn-mcp-server).
MCP("https://hn.caseyjhand.com/mcp"),
# Provider-adaptive web search; falls back to a local DuckDuckGo implementation.
WebSearch(),
# Filesystem + shell. By @vstorm-co: https://github.com/vstorm-co/pydantic-ai-backend
ConsoleCapability(),
# --- Memory & persistence ---
# Persistent ./MEMORY.md per agent name. By @vstorm-co:
# https://github.com/vstorm-co/pydantic-deepagents
MemoryCapability(agent_name="harness-example"),
# --- Orchestration ---
# Agent skills (Anthropic's spec) by @DougTrajano:
# https://github.com/DougTrajano/pydantic-ai-skills
# @vstorm-co's pydantic-deep also offers skills loading; the two have different
# spec footprints (Doug's is closer to programmatic skills).
SkillsCapability(directories=["./skills"]),
# Spawn sub-agents with their own toolsets and instructions. By @vstorm-co:
# https://github.com/vstorm-co/subagents-pydantic-ai
SubAgentCapability(
subagents=[
SubAgentConfig(
name="researcher",
description="Deep research on a topic",
instructions="You are a thorough research assistant.",
),
]
),
# Track tasks and subtasks; in-memory by default, AsyncPostgresStorage available.
# By @vstorm-co: https://github.com/vstorm-co/pydantic-ai-todo
TodoCapability(enable_subtasks=True),
# --- Safety & reliability ---
# The next four are by @vstorm-co: https://github.com/vstorm-co/pydantic-ai-shields
# Per-run cost cap with a callback hook.
CostTracking(budget_usd=5.0),
# Reject prompts that look like prompt-injection attempts.
InputGuard(guard=lambda p: "ignore previous instructions" not in p.lower()),
# Block or require approval per tool name.
ToolGuard(blocked=["rm"], require_approval=["write_file"]),
# Detect API keys/tokens in tool I/O and redact before they reach the model.
SecretRedaction(),
# Bail out if the agent gets stuck calling the same tools in a loop.
# By @vstorm-co: https://github.com/vstorm-co/pydantic-deepagents
StuckLoopDetection(),
],
)
async def main() -> None:
deps = DeepAgentDeps()
result = await agent.run(
"What are your skills.",
# "Find the latest HN stories about AI, pull their comment threads, and summarize the discussions.",
deps=deps,
)
print(result.output)
if __name__ == "__main__":
import asyncio
asyncio.run(main())