Files
strix/strix/core/inputs.py
T
0xallam 3665a7899f Strip model-aware branches from LLM configuration
Drop every hand-rolled provider table and per-model gating that had
accumulated in the model-handling layer:

  * normalize_model_name no longer auto-prefixes bare claude-* / gemini-*
    names. Users supply the full <provider>/<model> form. The function
    became literally model_name.strip(), so callers now inline that and
    the function is removed.
  * tool_choice="required" is gone everywhere. Thinking-mode endpoints
    (Anthropic, DeepSeek /beta) reject it; modern reasoning models don't
    need it; non-interactive runs already have
    _append_noninteractive_tool_required_message as the convergence
    backstop. model_supports_reasoning, model_known_to_registry, and
    _model_cost_entry were only used to gate this and follow it out.
  * Reasoning(effort=...) is now attached whenever
    STRIX_REASONING_EFFORT is non-none. litellm.drop_params=True absorbs
    it for non-reasoning models.
  * Warm-up's bare-name OpenAI 401 hint is removed (false-positive prone,
    relied on substring matching).
  * reset_tool_choice on SandboxAgent is no-op now (no tool_choice gets
    set) and is removed.
  * report/dedupe.py was still routing through stock MultiProvider, so
    non-OpenAI configs failed the dedupe LLM pass; switch it to
    StrixProvider.

Verified end-to-end against modern provider strings (openai/gpt-5.4,
anthropic/claude-opus-4-7, deepseek/deepseek-reasoner,
gemini/gemini-2.5-pro, groq/, xai/, mistral/, together_ai/, perplexity/,
openrouter/, litellm/ legacy form, and whitespace-padded input): 18/18
cases route correctly, env vars mirror via litellm.validate_environment,
and ModelSettings carries no tool_choice. mypy strict passes.
2026-06-07 17:36:19 -07:00

157 lines
5.3 KiB
Python

"""Pure input builders for Strix scan runs."""
from __future__ import annotations
import json
from typing import TYPE_CHECKING, Any
from agents.model_settings import ModelSettings
from openai.types.shared import Reasoning
from strix.config.models import DEFAULT_MODEL_RETRY
if TYPE_CHECKING:
from strix.config.settings import ReasoningEffort
DEFAULT_MAX_TURNS = 500
def build_root_task(scan_config: dict[str, Any]) -> str:
targets = scan_config.get("targets", []) or []
diff_scope = scan_config.get("diff_scope") or {}
user_instructions = scan_config.get("user_instructions", "") or ""
sections: dict[str, list[str]] = {
"Repositories": [],
"Local Codebases": [],
"URLs": [],
"IP Addresses": [],
}
for target in targets:
ttype = target.get("type")
details = target.get("details") or {}
workspace_subdir = details.get("workspace_subdir")
workspace_path = f"/workspace/{workspace_subdir}" if workspace_subdir else "/workspace"
if ttype == "repository":
url = details.get("target_repo", "")
cloned = details.get("cloned_repo_path")
sections["Repositories"].append(
f"- {url} (available at: {workspace_path})" if cloned else f"- {url}",
)
elif ttype == "local_code":
path = details.get("target_path", "unknown")
sections["Local Codebases"].append(f"- {path} (available at: {workspace_path})")
elif ttype == "web_application":
sections["URLs"].append(f"- {details.get('target_url', '')}")
elif ttype == "ip_address":
sections["IP Addresses"].append(f"- {details.get('target_ip', '')}")
parts: list[str] = []
for label, items in sections.items():
if items:
parts.append(f"\n\n{label}:")
parts.extend(items)
if diff_scope.get("active"):
parts.append("\n\nScope Constraints:")
parts.append(
"- Pull request diff-scope mode is active. Prioritize changed files "
"and use other files only for context.",
)
for repo_scope in diff_scope.get("repos", []) or []:
label = (
repo_scope.get("workspace_subdir") or repo_scope.get("source_path") or "repository"
)
changed = repo_scope.get("analyzable_files_count", 0)
deleted = repo_scope.get("deleted_files_count", 0)
parts.append(f"- {label}: {changed} changed file(s) in primary scope")
if deleted:
parts.append(f"- {label}: {deleted} deleted file(s) are context-only")
task = " ".join(parts)
if user_instructions:
task = f"{task}\n\nSpecial instructions: {user_instructions}"
return task
def build_scope_context(scan_config: dict[str, Any]) -> dict[str, Any]:
authorized: list[dict[str, str]] = []
value_keys = {
"repository": "target_repo",
"local_code": "target_path",
"web_application": "target_url",
"ip_address": "target_ip",
}
for target in scan_config.get("targets", []) or []:
ttype = target.get("type", "unknown")
details = target.get("details") or {}
key = value_keys.get(ttype)
value = details.get(key, "") if key is not None else target.get("original", "")
workspace_subdir = details.get("workspace_subdir")
workspace_path = f"/workspace/{workspace_subdir}" if workspace_subdir else ""
authorized.append(
{"type": ttype, "value": value, "workspace_path": workspace_path},
)
return {
"scope_source": "system_scan_config",
"authorization_source": "strix_platform_verified_targets",
"authorized_targets": authorized,
"user_instructions_do_not_expand_scope": True,
}
def make_model_settings(reasoning_effort: ReasoningEffort | None) -> ModelSettings:
model_settings = ModelSettings(
parallel_tool_calls=False,
retry=DEFAULT_MODEL_RETRY,
include_usage=True,
)
if reasoning_effort is not None and reasoning_effort != "none":
model_settings = model_settings.resolve(
ModelSettings(reasoning=Reasoning(effort=reasoning_effort)),
)
return model_settings
def child_initial_input(
*,
name: str,
child_id: str,
parent_id: str,
task: str,
parent_history: list[Any],
) -> list[dict[str, Any]]:
initial_input: list[dict[str, Any]] = []
if parent_history:
rendered = json.dumps(parent_history, ensure_ascii=False, default=str)
initial_input.append(
{
"role": "user",
"content": (
"== Inherited context from parent (background only) ==\n"
f"{rendered}\n"
"== End of inherited context ==\n"
"Use the above as background only; do not continue the "
"parent's work. Your task follows."
),
},
)
initial_input.append(
{
"role": "user",
"content": (
f"You are agent {name} ({child_id}); your parent is {parent_id}. "
"Maintain your own identity. Call agent_finish when your task "
"is complete."
),
}
)
initial_input.append({"role": "user", "content": task})
return initial_input