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https://github.com/furyhawk/home_stack.git
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furyhawk
027468cb5a
- Implemented a brand validation script to check content against brand guidelines including colors, fonts, tone, and messaging. - Created a comprehensive financial modeling suite with DCF analysis, sensitivity testing, Monte Carlo simulations, and scenario planning. - Added scripts for DCF modeling and sensitivity analysis, including detailed documentation for usage and input requirements. - Included example usage for both brand validation and financial modeling to demonstrate functionality.
54 lines
2.6 KiB
Python
54 lines
2.6 KiB
Python
import logfire
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from pydantic_ai import Agent
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from pydantic_ai.capabilities import MCP, WebSearch
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from pydantic_ai.models.openai import OpenAIChatModel
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from pydantic_ai.providers.openai import OpenAIProvider
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from pydantic_ai_harness import CodeMode
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# See https://ai.pydantic.dev/logfire/ for setup details.
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logfire.configure()
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logfire.instrument_pydantic_ai()
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model = OpenAIChatModel(
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"llama",
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provider=OpenAIProvider(base_url="http://localhost:8011/v1"),
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)
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agent = Agent(
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model,
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capabilities=[
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# Wraps every tool into a single run_code tool, sandboxed by Monty
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# (https://github.com/pydantic/monty -- pulled in by the [code-mode] extra).
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# The model writes Python that calls multiple tools with loops, conditionals,
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# asyncio.gather, and local filtering -- one model round-trip for N tool calls.
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CodeMode(),
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# Connect to any MCP server -- here, the open-source Hacker News server
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# (https://github.com/cyanheads/hn-mcp-server). native=False forces the
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# local MCP toolset so CodeMode can wrap the tools; without it,
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# providers that natively support MCP server connectors execute the tools
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# server-side and bypass the sandbox.
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MCP('https://hn.caseyjhand.com/mcp', native=False),
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# Provider-adaptive web search; native=False routes through the local
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# DuckDuckGo fallback (the [duckduckgo] extra above) so CodeMode can batch
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# web searches alongside the HN calls in a single run_code.
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WebSearch(native=False),
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],
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)
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result = agent.run_sync(
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"Across the top, best, and 'show HN' Hacker News feeds, find the most-discussed "
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"story with at least 100 points. Pull its comment thread, its submitter's profile, "
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"and any web coverage. Summarize what you find in one paragraph."
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)
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print(result.output)
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"""
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The most-discussed HN story across top/best/show clearing 100 points is "Vibe coding
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and agentic engineering are getting closer than I'd like" by Simon Willison (748 points,
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853 comments, on the Best feed), submitted by long-time HNer e12e. The piece argues
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that the two modes Willison once kept mentally separate -- throwaway "vibe coding" and
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disciplined "agentic engineering" -- are blurring, since agents like Claude Code now
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reliably handle non-trivial tasks like "build a JSON API endpoint that runs a SQL query"
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with tests and docs on the first pass. The HN thread is unusually substantive, with
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commenters debating whether LLMs created or merely *exposed* sloppy engineering
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practices and warning of a "normalization of deviance" as engineers stop reviewing diffs.
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""" |