DATA
6de0bf9f5b
Vendored deer-flow upstream (bytedance/deer-flow) plus prompt-injection hardening: - New deerflow.security package: content_delimiter, html_cleaner, sanitizer (8 layers — invisible chars, control chars, symbols, NFC, PUA, tag chars, horizontal whitespace collapse with newline/tab preservation, length cap) - New deerflow.community.searx package: web_search, web_fetch, image_search backed by a private SearX instance, every external string sanitized and wrapped in <<<EXTERNAL_UNTRUSTED_CONTENT>>> delimiters - All native community web providers (ddg_search, tavily, exa, firecrawl, jina_ai, infoquest, image_search) replaced with hard-fail stubs that raise NativeWebToolDisabledError at import time, so a misconfigured tool.use path fails loud rather than silently falling back to unsanitized output - Native client back-doors (jina_client.py, infoquest_client.py) stubbed too - Native-tool tests quarantined under tests/_disabled_native/ (collect_ignore_glob via local conftest.py) - Sanitizer Layer 7 fix: only collapse horizontal whitespace, preserve newlines and tabs so list/table structure survives - Hardened runtime config.yaml references only the searx-backed tools - Factory overlay (backend/) kept in sync with deer-flow tree as a reference / source See HARDENING.md for the full audit trail and verification steps.
77 lines
2.1 KiB
Python
77 lines
2.1 KiB
Python
"""Step 1: LLM provider selection."""
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from __future__ import annotations
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from dataclasses import dataclass
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from wizard.providers import LLM_PROVIDERS, LLMProvider
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from wizard.ui import (
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ask_choice,
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ask_secret,
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ask_text,
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print_header,
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print_info,
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print_success,
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)
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@dataclass
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class LLMStepResult:
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provider: LLMProvider
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model_name: str
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api_key: str | None
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base_url: str | None = None
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def run_llm_step(step_label: str = "Step 1/3") -> LLMStepResult:
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print_header(f"{step_label} · Choose your LLM provider")
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options = [f"{p.display_name} ({p.description})" for p in LLM_PROVIDERS]
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idx = ask_choice("Enter choice", options)
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provider = LLM_PROVIDERS[idx]
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print()
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# Model selection (show list, default to first)
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if len(provider.models) > 1:
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print_info(f"Available models for {provider.display_name}:")
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model_idx = ask_choice("Select model", provider.models, default=0)
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model_name = provider.models[model_idx]
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else:
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model_name = provider.models[0]
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print()
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base_url: str | None = None
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if provider.name in {"openrouter", "vllm"}:
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base_url = provider.extra_config.get("base_url")
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if provider.name == "other":
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print_header(f"{step_label} · Connection details")
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base_url = ask_text("Base URL (e.g. https://api.openai.com/v1)", required=True)
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model_name = ask_text("Model name", default=provider.default_model)
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elif provider.auth_hint:
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print_header(f"{step_label} · Authentication")
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print_info(provider.auth_hint)
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api_key = None
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return LLMStepResult(
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provider=provider,
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model_name=model_name,
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api_key=api_key,
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base_url=base_url,
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)
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print_header(f"{step_label} · Enter your API Key")
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if provider.env_var:
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api_key = ask_secret(f"{provider.env_var}")
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else:
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api_key = None
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if api_key:
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print_success(f"Key will be saved to .env as {provider.env_var}")
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return LLMStepResult(
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provider=provider,
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model_name=model_name,
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api_key=api_key,
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base_url=base_url,
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)
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