Initial commit: hardened DeerFlow factory

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.

deer-flow/scripts/wizard/steps/llm.py

@@ -0,0 +1,76 @@
+"""Step 1: LLM provider selection."""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+
+from wizard.providers import LLM_PROVIDERS, LLMProvider
+from wizard.ui import (
+    ask_choice,
+    ask_secret,
+    ask_text,
+    print_header,
+    print_info,
+    print_success,
+)
+
+
+@dataclass
+class LLMStepResult:
+    provider: LLMProvider
+    model_name: str
+    api_key: str | None
+    base_url: str | None = None
+
+
+def run_llm_step(step_label: str = "Step 1/3") -> LLMStepResult:
+    print_header(f"{step_label} · Choose your LLM provider")
+
+    options = [f"{p.display_name}  ({p.description})" for p in LLM_PROVIDERS]
+    idx = ask_choice("Enter choice", options)
+    provider = LLM_PROVIDERS[idx]
+
+    print()
+
+    # Model selection (show list, default to first)
+    if len(provider.models) > 1:
+        print_info(f"Available models for {provider.display_name}:")
+        model_idx = ask_choice("Select model", provider.models, default=0)
+        model_name = provider.models[model_idx]
+    else:
+        model_name = provider.models[0]
+
+    print()
+    base_url: str | None = None
+    if provider.name in {"openrouter", "vllm"}:
+        base_url = provider.extra_config.get("base_url")
+    if provider.name == "other":
+        print_header(f"{step_label} · Connection details")
+        base_url = ask_text("Base URL (e.g. https://api.openai.com/v1)", required=True)
+        model_name = ask_text("Model name", default=provider.default_model)
+    elif provider.auth_hint:
+        print_header(f"{step_label} · Authentication")
+        print_info(provider.auth_hint)
+        api_key = None
+        return LLMStepResult(
+            provider=provider,
+            model_name=model_name,
+            api_key=api_key,
+            base_url=base_url,
+        )
+
+    print_header(f"{step_label} · Enter your API Key")
+    if provider.env_var:
+        api_key = ask_secret(f"{provider.env_var}")
+    else:
+        api_key = None
+
+    if api_key:
+        print_success(f"Key will be saved to .env as {provider.env_var}")
+
+    return LLMStepResult(
+        provider=provider,
+        model_name=model_name,
+        api_key=api_key,
+        base_url=base_url,
+    )