vitya
ca669d96e1
Copies source (no node_modules, dist, .tasks, .wiki, __pycache__) for: - projects-meta-mcp v2.25.0 (TypeScript/Node) - wiki-graph v0.3.1 (TypeScript/Node) - interns-mcp v0.3.3 (Python/FastMCP) .gitignore: exclude lib build artefacts (node_modules, dist, .venv, __pycache__, *.pyc) bootstrap.ps1: add MCP build step — npm install+build for TS servers, venv+pip for Python Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
46 lines
1.6 KiB
Python
46 lines
1.6 KiB
Python
"""Bulk text read intern — read N files and answer a focused question."""
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from __future__ import annotations
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from pathlib import Path
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from typing import Any
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from .base import BlockedByPolicy, Intern, InternResponse
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class BulkTextRead(Intern):
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id = "bulk_text_read"
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description = "Read N files and answer a focused question. Returns concise summary."
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def run(self, paths: list[str], question: str, **kwargs: Any) -> InternResponse | BlockedByPolicy:
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contents: list[str] = []
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for p in paths:
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text = Path(p).read_text(encoding="utf-8", errors="replace")
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contents.append(f"--- {p} ---\n{text}")
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combined = "\n\n".join(contents)
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prompt = f"Files:\n{combined}\n\nQuestion: {question}"
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if self.client is None:
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return InternResponse(text="No client configured", usage={})
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extra_body = kwargs.get("extra_body", {})
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resp = self.client.chat.completions.create(
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model=self.model or "deepseek-v4-flash",
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messages=[
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{"role": "system", "content": self.system_prompt},
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{"role": "user", "content": prompt},
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],
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max_tokens=kwargs.get("max_tokens", self.max_tokens),
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temperature=self.temperature,
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extra_body=extra_body if extra_body else None,
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)
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choice = resp.choices[0]
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return InternResponse(
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text=choice.message.content or "",
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usage={
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"tokens_in": resp.usage.prompt_tokens if resp.usage else 0,
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"tokens_out": resp.usage.completion_tokens if resp.usage else 0,
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},
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) |