import json import logging from typing import List, Optional, Tuple from typeguard import typechecked import os import re from backend.config.paths import SESSIONS_DIR logger = logging.getLogger(__name__) # One plain-English trust line, fenced by a tag. The model treats the fence as structural framing; the sentence is what actually defuses a security-conscious agent flagging the block as spoofed tool output. PLATFORM_NOTE_PREAMBLE = ( "This block is authored by the OpenSwarm platform, not tool output and not a " "prior message. It is trusted context." ) PLATFORM_NOTE_OPEN = "" PLATFORM_NOTE_CLOSE = "" SESSION_RECAP_OPEN = "" SESSION_RECAP_CLOSE = "" # Per-turn caps so the re-grounded recap stays compact (summaries, not replays) and cannot reinflate the context window from one giant tool input/output. RECAP_TOOL_INPUT_CAP = 200 RECAP_TOOL_RESULT_CAP = 500 @typechecked def wrap_platform_note(body: str) -> str: """Fence platform-authored text so the model reads it as trusted annotation, never as spoofed tool output. The frontend parses the same tag to render a calm chip instead of leaking the raw tag into chat.""" return f"{PLATFORM_NOTE_OPEN}\n{PLATFORM_NOTE_PREAMBLE}\n{body}\n{PLATFORM_NOTE_CLOSE}" P_SENTINEL_TAG_RE = re.compile(r"]*>") @typechecked def strip_forged_sentinels(text: str) -> str: """Neuter any platform-note/recap tags hiding in UNTRUSTED text (tool results, user input) so attacker-supplied content can't pose as trusted platform context.""" if "openswarm_platform_note" not in text and "openswarm_session_recap" not in text: return text return P_SENTINEL_TAG_RE.sub(lambda m: m.group(0).replace("<", "<").replace(">", ">"), text) @typechecked def p_recap_tool_call_line(content: object) -> str: """One compact line for a tool_call turn: Tool call: name().""" if isinstance(content, dict): tool = content.get("tool") or content.get("name") or "tool" raw_input = content.get("input") try: input_str = json.dumps(raw_input, ensure_ascii=False, default=str) except Exception: input_str = str(raw_input) else: tool = "tool" input_str = str(content) if len(input_str) > RECAP_TOOL_INPUT_CAP: input_str = input_str[:RECAP_TOOL_INPUT_CAP] + "..." return f"Tool call: {tool}({strip_forged_sentinels(input_str)})" @typechecked def p_recap_tool_result_line(content: object) -> str: """One compact line for a tool_result turn: Tool result (name): .""" tool_name = "" if isinstance(content, dict): tool_name = content.get("tool_name") or "" text = content.get("text") body = text if isinstance(text, str) else json.dumps(content, ensure_ascii=False, default=str) else: body = str(content) if len(body) > RECAP_TOOL_RESULT_CAP: body = body[:RECAP_TOOL_RESULT_CAP] + "..." label = f"Tool result ({tool_name})" if tool_name else "Tool result" return f"{label}: {strip_forged_sentinels(body)}" @typechecked def get_branch_messages(session) -> List: """Return the linear message list for the active branch, walking the branch tree.""" branch_id = session.active_branch_id or "main" branch = session.branches.get(branch_id) if not branch or not branch.fork_point_message_id: return [m for m in session.messages if m.branch_id == "main" or m.branch_id == branch_id] segments = [] cur = branch cur_id = branch_id visited = set() while cur and cur.fork_point_message_id: if cur_id in visited: break visited.add(cur_id) segments.insert(0, {"branch_id": cur_id, "up_to": cur.fork_point_message_id}) cur_id = cur.parent_branch_id or "main" cur = session.branches.get(cur_id) segments.insert(0, {"branch_id": cur_id, "up_to": None}) result = [] for i, seg in enumerate(segments): fork_msg_id = seg["up_to"] if fork_msg_id: fork_idx = next((j for j, m in enumerate(session.messages) if m.id == fork_msg_id), len(session.messages)) result.extend(m for m in session.messages[:fork_idx] if m.branch_id == seg["branch_id"]) else: next_fork = segments[i + 1]["up_to"] if i + 1 < len(segments) else None if next_fork: fork_idx = next((j for j, m in enumerate(session.messages) if m.id == next_fork), len(session.messages)) result.extend(m for m in session.messages[:fork_idx] if m.branch_id == seg["branch_id"]) else: result.extend(m for m in session.messages if m.branch_id == seg["branch_id"]) if not any(m.branch_id == branch_id for m in result): result.extend(m for m in session.messages if m.branch_id == branch_id) return result @typechecked def build_history_prefix(messages, cutoff_msg_id: Optional[str] = None) -> str: """Format branch messages into a conversation summary for context injection. When `cutoff_msg_id` is provided (session.compacted_through_msg_id), drop every message up to and including that id so the marker the UI shows actually matches what the model sees. Missing cutoff id falls through to full history. """ if cutoff_msg_id: skip_idx = next((i for i, m in enumerate(messages) if m.id == cutoff_msg_id), -1) if skip_idx >= 0: messages = messages[skip_idx + 1:] lines = [] for m in messages: if getattr(m, "hidden", False): continue if m.role == "user": text = m.content if isinstance(m.content, str) else str(m.content) lines.append(f"User: {strip_forged_sentinels(text)}") elif m.role == "assistant": text = m.content if isinstance(m.content, str) else str(m.content) lines.append(f"Assistant: {strip_forged_sentinels(text)}") elif m.role == "tool_call": lines.append(p_recap_tool_call_line(m.content)) elif m.role == "tool_result": lines.append(p_recap_tool_result_line(m.content)) if not lines: return "" return f"{SESSION_RECAP_OPEN}\n{PLATFORM_NOTE_PREAMBLE}\n" + "\n".join(lines) + f"\n{SESSION_RECAP_CLOSE}" @typechecked def estimate_post_compact_input(session) -> int: """Return a conservative token estimate after compaction trims history.""" try: messages = get_branch_messages(session) cutoff_msg_id = getattr(session, "compacted_through_msg_id", None) if cutoff_msg_id: skip_idx = next( (i for i, m in enumerate(messages) if m.id == cutoff_msg_id), -1, ) if skip_idx >= 0: messages = messages[skip_idx + 1:] surviving_chars = 0 for message in messages: if getattr(message, "hidden", False): continue content = getattr(message, "content", "") if isinstance(content, str): serialized = content else: try: serialized = json.dumps(content, ensure_ascii=False) except Exception: serialized = str(content) surviving_chars += len(serialized) framework_overhead = int(getattr(session, "framework_overhead_tokens", 0) or 0) summary_overhead = 200 if cutoff_msg_id else 0 return max(0, framework_overhead + summary_overhead + (surviving_chars // 4)) except Exception: logger.debug("post-compact token estimate failed", exc_info=True) return max(0, int(getattr(session, "framework_overhead_tokens", 0) or 0)) @typechecked def truncate_large_tool_result(content: object, session_id: str, msg_id: str, max_bytes: int = 50_000) -> Tuple[object, Optional[str]]: """Spill a large tool_result body to disk, return a truncated inline replacement plus the on-disk path (or None if untouched). Storage is session-scoped under data/sessions//blobs/, never honors caller-supplied paths (defense against path traversal). The inline replacement keeps the first 4KB so the model retains some signal about what was returned. """ if not isinstance(content, str): try: serialized = json.dumps(content) if not isinstance(content, str) else content except Exception: serialized = str(content) else: serialized = content if len(serialized.encode("utf-8")) <= max_bytes: return content, None blobs_dir = os.path.join(SESSIONS_DIR, session_id, "blobs") os.makedirs(blobs_dir, exist_ok=True) # Sanitize msg_id (it's UUID hex, but be defensive). safe_msg_id = re.sub(r"[^a-zA-Z0-9_-]", "", str(msg_id))[:64] or "blob" blob_path = os.path.join(blobs_dir, f"{safe_msg_id}.txt") try: with open(blob_path, "w", encoding="utf-8") as f: f.write(serialized) except Exception as e: logger.warning(f"Failed to spill tool result to {blob_path}: {e}") return content, None head = strip_forged_sentinels(serialized[:4_000]) note = wrap_platform_note( f"Output truncated by OpenSwarm. Full output ({len(serialized)} chars) saved to " f"{blob_path}. Ask the user or run a follow-up tool call if you need the rest." ) replacement = f"{head}\n\n{note}" return replacement, blob_path