HERMES-GIELIE/api/streaming.py

"""
Hermes Web UI -- SSE streaming engine and agent thread runner.
Includes Sprint 10 cancel support via CANCEL_FLAGS.
"""
import json
import logging
import os
import queue
import threading
import time
import traceback
from pathlib import Path

logger = logging.getLogger(__name__)

from api.config import (
    STREAMS, STREAMS_LOCK, CANCEL_FLAGS, AGENT_INSTANCES, CLI_TOOLSETS,
    LOCK, SESSIONS, SESSION_DIR,
    _get_session_agent_lock, _set_thread_env, _clear_thread_env,
    resolve_model_provider,
)
from api.helpers import redact_session_data

# Global lock for os.environ writes. Per-session locks (_agent_lock) prevent
# concurrent runs of the SAME session, but two DIFFERENT sessions can still
# interleave their os.environ writes. This global lock serializes the env
# save/restore around the entire agent run.
_ENV_LOCK = threading.Lock()

# Lazy import to avoid circular deps -- hermes-agent is on sys.path via api/config.py
try:
    from run_agent import AIAgent
except ImportError:
    AIAgent = None

def _get_ai_agent():
    """Return AIAgent class, retrying the import if the initial attempt failed.

    auto_install_agent_deps() in server.py may install missing packages after
    this module is first imported (common in Docker with a volume-mounted agent).
    Re-attempting the import here picks up the newly installed packages without
    requiring a server restart.
    """
    global AIAgent
    if AIAgent is None:
        try:
            from run_agent import AIAgent as _cls  # noqa: PLC0415
            AIAgent = _cls
        except ImportError:
            pass
    return AIAgent
from api.models import get_session, title_from
from api.workspace import set_last_workspace

# Fields that are safe to send to LLM provider APIs.
# Everything else (attachments, timestamp, _ts, etc.) is display-only
# metadata added by the webui and must be stripped before the API call.
_API_SAFE_MSG_KEYS = {'role', 'content', 'tool_calls', 'tool_call_id', 'name', 'refusal'}


def _sanitize_messages_for_api(messages):
    """Return a deep copy of messages with only API-safe fields.

    The webui stores extra metadata on messages (attachments, timestamp, _ts)
    for display purposes. Some providers (e.g. Z.AI/GLM) reject unknown fields
    instead of ignoring them, causing HTTP 400 errors on subsequent messages.
    """
    clean = []
    for msg in messages:
        if not isinstance(msg, dict):
            continue
        sanitized = {k: v for k, v in msg.items() if k in _API_SAFE_MSG_KEYS}
        if sanitized.get('role'):
            clean.append(sanitized)
    return clean


def _sse(handler, event, data):
    """Write one SSE event to the response stream."""
    payload = f"event: {event}\ndata: {json.dumps(data, ensure_ascii=False)}\n\n"
    handler.wfile.write(payload.encode('utf-8'))
    handler.wfile.flush()


def _run_agent_streaming(session_id, msg_text, model, workspace, stream_id, attachments=None):
    """Run agent in background thread, writing SSE events to STREAMS[stream_id]."""
    q = STREAMS.get(stream_id)
    if q is None:
        return

    # Sprint 10: create a cancel event for this stream
    cancel_event = threading.Event()
    with STREAMS_LOCK:
        CANCEL_FLAGS[stream_id] = cancel_event

    def put(event, data):
        # If cancelled, drop all further events except the cancel event itself
        if cancel_event.is_set() and event not in ('cancel', 'error'):
            return
        try:
            q.put_nowait((event, data))
        except Exception:
            logger.debug("Failed to put event to queue")

    try:
        s = get_session(session_id)
        s.workspace = str(Path(workspace).expanduser().resolve())
        s.model = model

        _agent_lock = _get_session_agent_lock(session_id)
        # TD1: set thread-local env context so concurrent sessions don't clobber globals
        # Check for pre-flight cancel (user cancelled before agent even started)
        if cancel_event.is_set():
            put('cancel', {'message': 'Cancelled before start'})
            return

        # Resolve profile home for this agent run (snapshot at start)
        try:
            from api.profiles import get_active_hermes_home
            _profile_home = str(get_active_hermes_home())
        except ImportError:
            _profile_home = os.environ.get('HERMES_HOME', '')

        _set_thread_env(
            TERMINAL_CWD=str(s.workspace),
            HERMES_EXEC_ASK='1',
            HERMES_SESSION_KEY=session_id,
            HERMES_HOME=_profile_home,
        )
        # Still set process-level env as fallback for tools that bypass thread-local
        # Acquire lock only for the env mutation, then release before the agent runs.
        # The finally block re-acquires to restore — keeping critical sections short
        # and preventing a deadlock where the restore would re-enter the same lock.
        with _ENV_LOCK:
            old_cwd = os.environ.get('TERMINAL_CWD')
            old_exec_ask = os.environ.get('HERMES_EXEC_ASK')
            old_session_key = os.environ.get('HERMES_SESSION_KEY')
            old_hermes_home = os.environ.get('HERMES_HOME')
            os.environ['TERMINAL_CWD'] = str(s.workspace)
            os.environ['HERMES_EXEC_ASK'] = '1'
            os.environ['HERMES_SESSION_KEY'] = session_id
            if _profile_home:
                os.environ['HERMES_HOME'] = _profile_home
        # Lock released — agent runs without holding it
        # Register a gateway-style notify callback so the approval system can
        # push the `approval` SSE event the moment a dangerous command is
        # detected, without waiting for the next on_tool() poll cycle.
        # Without this, the agent thread blocks inside the terminal tool
        # waiting for approval that the UI never knew to ask for, leaving
        # the chat stuck in "Thinking…" forever.
        _approval_registered = False
        _unreg_notify = None
        try:
            from tools.approval import (
                register_gateway_notify as _reg_notify,
                unregister_gateway_notify as _unreg_notify,
            )
            def _approval_notify_cb(approval_data):
                put('approval', approval_data)
            _reg_notify(session_id, _approval_notify_cb)
            _approval_registered = True
        except ImportError:
            logger.debug("Approval module not available, falling back to polling")

        try:
            _token_sent = False  # tracks whether any streamed tokens were sent

            def on_token(text):
                nonlocal _token_sent
                if text is None:
                    return  # end-of-stream sentinel
                _token_sent = True
                put('token', {'text': text})

            def on_reasoning(text):
                if text is None:
                    return
                put('reasoning', {'text': str(text)})

            def on_tool(*cb_args, **cb_kwargs):
                event_type = None
                name = None
                preview = None
                args = None

                if len(cb_args) >= 4:
                    event_type, name, preview, args = cb_args[:4]
                elif len(cb_args) == 3:
                    name, preview, args = cb_args
                    event_type = 'tool.started'
                elif len(cb_args) == 2:
                    event_type, name = cb_args
                elif len(cb_args) == 1:
                    name = cb_args[0]
                    event_type = 'tool.started'

                if event_type in ('reasoning.available', '_thinking'):
                    reason_text = preview if event_type == 'reasoning.available' else name
                    if reason_text:
                        put('reasoning', {'text': str(reason_text)})
                    return

                args_snap = {}
                if isinstance(args, dict):
                    for k, v in list(args.items())[:4]:
                        s2 = str(v)
                        args_snap[k] = s2[:120] + ('...' if len(s2) > 120 else '')

                if event_type in (None, 'tool.started'):
                    put('tool', {
                        'event_type': event_type or 'tool.started',
                        'name': name,
                        'preview': preview,
                        'args': args_snap,
                    })
                    # Fallback: poll for pending approval in case notify_cb wasn't
                    # registered (e.g. older approval module without gateway support).
                    try:
                        from tools.approval import has_pending as _has_pending, _pending, _lock
                        if _has_pending(session_id):
                            with _lock:
                                p = dict(_pending.get(session_id, {}))
                            if p:
                                put('approval', p)
                    except ImportError:
                        pass
                    return

                if event_type == 'tool.completed':
                    put('tool_complete', {
                        'event_type': event_type,
                        'name': name,
                        'preview': preview,
                        'args': args_snap,
                        'duration': cb_kwargs.get('duration'),
                        'is_error': bool(cb_kwargs.get('is_error', False)),
                    })
                    return

            _AIAgent = _get_ai_agent()
            if _AIAgent is None:
                raise ImportError("AIAgent not available -- check that hermes-agent is on sys.path")

            # Initialize SessionDB so session_search works in WebUI sessions
            _session_db = None
            try:
                from hermes_state import SessionDB
                _session_db = SessionDB()
            except Exception as _db_err:
                print(f"[webui] WARNING: SessionDB init failed — session_search will be unavailable: {_db_err}", flush=True)
            resolved_model, resolved_provider, resolved_base_url = resolve_model_provider(model)

            # Resolve API key via Hermes runtime provider (matches gateway behaviour).
            # Pass the resolved provider so non-default providers get their own credentials.
            resolved_api_key = None
            try:
                from hermes_cli.runtime_provider import resolve_runtime_provider
                _rt = resolve_runtime_provider(requested=resolved_provider)
                resolved_api_key = _rt.get("api_key")
                if not resolved_provider:
                    resolved_provider = _rt.get("provider")
                if not resolved_base_url:
                    resolved_base_url = _rt.get("base_url")
            except Exception as _e:
                print(f"[webui] WARNING: resolve_runtime_provider failed: {_e}", flush=True)

            # Read per-profile config at call time (not module-level snapshot)
            from api.config import get_config as _get_config
            _cfg = _get_config()

            # Per-profile toolsets (fall back to module-level CLI_TOOLSETS)
            _pt = _cfg.get('platform_toolsets', {})
            _toolsets = _pt.get('cli', CLI_TOOLSETS) if isinstance(_pt, dict) else CLI_TOOLSETS

            # Fallback model from profile config (e.g. for rate-limit recovery)
            _fallback = _cfg.get('fallback_model') or None
            if _fallback:
                # Resolve the fallback through our provider logic too
                fb_model = _fallback.get('model', '')
                fb_provider = _fallback.get('provider', '')
                fb_base_url = _fallback.get('base_url')
                _fallback_resolved = {
                    'model': fb_model,
                    'provider': fb_provider,
                    'base_url': fb_base_url,
                }
            else:
                _fallback_resolved = None

            agent = _AIAgent(
                model=resolved_model,
                provider=resolved_provider,
                base_url=resolved_base_url,
                api_key=resolved_api_key,
                platform='cli',
                quiet_mode=True,
                enabled_toolsets=_toolsets,
                fallback_model=_fallback_resolved,
                session_id=session_id,
                session_db=_session_db,
                stream_delta_callback=on_token,
                reasoning_callback=on_reasoning,
                tool_progress_callback=on_tool,
            )

            # Store agent instance for cancel/interrupt propagation
            with STREAMS_LOCK:
                AGENT_INSTANCES[stream_id] = agent
                # Check if cancel was requested during agent initialization
                if stream_id in CANCEL_FLAGS and CANCEL_FLAGS[stream_id].is_set():
                    # Cancel arrived during agent creation - interrupt immediately
                    try:
                        agent.interrupt("Cancelled before start")
                    except Exception:
                        logger.debug("Failed to interrupt agent before start")
                    put('cancel', {'message': 'Cancelled by user'})
                    return

            # Prepend workspace context so the agent always knows which directory
            # to use for file operations, regardless of session age or AGENTS.md defaults.
            workspace_ctx = f"[Workspace: {s.workspace}]\n"
            workspace_system_msg = (
                f"Active workspace at session start: {s.workspace}\n"
                "Every user message is prefixed with [Workspace: /absolute/path] indicating the "
                "workspace the user has selected in the web UI at the time they sent that message. "
                "This tag is the single authoritative source of the active workspace and updates "
                "with every message. It overrides any prior workspace mentioned in this system "
                "prompt, memory, or conversation history. Always use the value from the most recent "
                "[Workspace: ...] tag as your default working directory for ALL file operations: "
                "write_file, read_file, search_files, terminal workdir, and patch. "
                "Never fall back to a hardcoded path when this tag is present."
            )
            # Resolve personality prompt from config.yaml agent.personalities
            # (matches hermes-agent CLI behavior — passes via ephemeral_system_prompt)
            _personality_prompt = None
            _pname = getattr(s, 'personality', None)
            if _pname:
                _agent_cfg = _cfg.get('agent', {})
                _personalities = _agent_cfg.get('personalities', {})
                if isinstance(_personalities, dict) and _pname in _personalities:
                    _pval = _personalities[_pname]
                    if isinstance(_pval, dict):
                        _parts = [_pval.get('system_prompt', '') or _pval.get('prompt', '')]
                        if _pval.get('tone'):
                            _parts.append(f'Tone: {_pval["tone"]}')
                        if _pval.get('style'):
                            _parts.append(f'Style: {_pval["style"]}')
                        _personality_prompt = '\n'.join(p for p in _parts if p)
                    else:
                        _personality_prompt = str(_pval)
            # Pass personality via ephemeral_system_prompt (agent's own mechanism)
            if _personality_prompt:
                agent.ephemeral_system_prompt = _personality_prompt
            result = agent.run_conversation(
                user_message=workspace_ctx + msg_text,
                system_message=workspace_system_msg,
                conversation_history=_sanitize_messages_for_api(s.messages),
                task_id=session_id,
                persist_user_message=msg_text,
            )
            s.messages = result.get('messages') or s.messages

            # ── Detect silent agent failure (no assistant reply produced) ──
            # When the agent catches an auth/network error internally it may return
            # an empty final_response without raising — the stream would end with
            # a done event containing zero assistant messages, leaving the user with
            # no feedback. Emit an apperror so the client shows an inline error.
            _assistant_added = any(
                m.get('role') == 'assistant' and str(m.get('content') or '').strip()
                for m in (result.get('messages') or [])
            )
            # _token_sent tracks whether on_token() was called (any streamed text)
            if not _assistant_added and not _token_sent:
                _last_err = getattr(agent, '_last_error', None) or result.get('error') or ''
                _err_str = str(_last_err) if _last_err else ''
                _is_auth = (
                    '401' in _err_str
                    or (_last_err and 'AuthenticationError' in type(_last_err).__name__)
                    or 'authentication' in _err_str.lower()
                    or 'unauthorized' in _err_str.lower()
                    or 'invalid api key' in _err_str.lower()
                    or 'invalid_api_key' in _err_str.lower()
                )
                if _is_auth:
                    put('apperror', {
                        'message': _err_str or 'Authentication failed — check your API key.',
                        'type': 'auth_mismatch',
                        'hint': (
                            'The selected model may not be supported by your configured provider or '
                            'your API key is invalid. Run `hermes model` in your terminal to '
                            'update credentials, then restart the WebUI.'
                        ),
                    })
                else:
                    put('apperror', {
                        'message': _err_str or 'The agent returned no response. Check your API key and model selection.',
                        'type': 'no_response',
                        'hint': 'Verify your API key is valid and the selected model is available for your account.',
                    })
                return  # Don't emit done — the apperror already closes the stream on the client

            # ── Handle context compression side effects ──
            # If compression fired inside run_conversation, the agent may have
            # rotated its session_id. Detect and fix the mismatch so the WebUI
            # continues writing to the correct session file.
            _agent_sid = getattr(agent, 'session_id', None)
            _compressed = False
            if _agent_sid and _agent_sid != session_id:
                old_sid = session_id
                new_sid = _agent_sid
                # Rename the session file
                old_path = SESSION_DIR / f'{old_sid}.json'
                new_path = SESSION_DIR / f'{new_sid}.json'
                s.session_id = new_sid
                with LOCK:
                    if old_sid in SESSIONS:
                        SESSIONS[new_sid] = SESSIONS.pop(old_sid)
                if old_path.exists() and not new_path.exists():
                    try:
                        old_path.rename(new_path)
                    except OSError:
                        logger.debug("Failed to rename session file during compression")
                _compressed = True
            # Also detect compression via the result dict or compressor state
            if not _compressed:
                _compressor = getattr(agent, 'context_compressor', None)
                if _compressor and getattr(_compressor, 'compression_count', 0) > 0:
                    _compressed = True
            # Notify the frontend that compression happened
            if _compressed:
                put('compressed', {
                    'message': 'Context auto-compressed to continue the conversation',
                })

            # Stamp 'timestamp' on any messages that don't have one yet
            _now = time.time()
            for _m in s.messages:
                if isinstance(_m, dict) and not _m.get('timestamp') and not _m.get('_ts'):
                    _m['timestamp'] = int(_now)
            # Only auto-generate title when still default; preserves user renames
            if s.title == 'Untitled' or s.title == 'New Chat' or not s.title:
                s.title = title_from(s.messages, s.title)
            # Read token/cost usage from the agent object (if available)
            input_tokens = getattr(agent, 'session_prompt_tokens', 0) or 0
            output_tokens = getattr(agent, 'session_completion_tokens', 0) or 0
            estimated_cost = getattr(agent, 'session_estimated_cost_usd', None)
            s.input_tokens = (s.input_tokens or 0) + input_tokens
            s.output_tokens = (s.output_tokens or 0) + output_tokens
            if estimated_cost:
                s.estimated_cost = (s.estimated_cost or 0) + estimated_cost
            # Extract tool call metadata grouped by assistant message index
            # Each tool call gets assistant_msg_idx so the client can render
            # cards inline with the assistant bubble that triggered them.
            tool_calls = []
            pending_names = {}   # tool_call_id -> name
            pending_args = {}    # tool_call_id -> args dict
            pending_asst_idx = {} # tool_call_id -> index in s.messages
            for msg_idx, m in enumerate(s.messages):
                if m.get('role') == 'assistant':
                    c = m.get('content', '')
                    # Anthropic format: content is a list with type=tool_use blocks
                    if isinstance(c, list):
                        for p in c:
                            if isinstance(p, dict) and p.get('type') == 'tool_use':
                                tid = p.get('id', '')
                                pending_names[tid] = p.get('name', '')
                                pending_args[tid] = p.get('input', {})
                                pending_asst_idx[tid] = msg_idx
                    # OpenAI format: tool_calls as top-level field on the message
                    for tc in m.get('tool_calls', []):
                        if not isinstance(tc, dict):
                            continue
                        tid = tc.get('id', '') or tc.get('call_id', '')
                        fn = tc.get('function', {})
                        name = fn.get('name', '')
                        try:
                            import json as _j
                            args = _j.loads(fn.get('arguments', '{}') or '{}')
                        except Exception:
                            args = {}
                        if tid and name:
                            pending_names[tid] = name
                            pending_args[tid] = args
                            pending_asst_idx[tid] = msg_idx
                elif m.get('role') == 'tool':
                    tid = m.get('tool_call_id') or m.get('tool_use_id', '')
                    name = pending_names.get(tid, '')
                    if not name or name == 'tool':
                        continue  # skip unresolvable tool entries
                    asst_idx = pending_asst_idx.get(tid, -1)
                    args = pending_args.get(tid, {})
                    raw = str(m.get('content', ''))
                    try:
                        rd = json.loads(raw)
                        snippet = str(rd.get('output') or rd.get('result') or rd.get('error') or raw)[:200]
                    except Exception:
                        snippet = raw[:200]
                    # Truncate args values for storage
                    args_snap = {}
                    if isinstance(args, dict):
                        for k, v in list(args.items())[:6]:
                            s2 = str(v)
                            args_snap[k] = s2[:120] + ('...' if len(s2) > 120 else '')
                    tool_calls.append({
                        'name': name, 'snippet': snippet, 'tid': tid,
                        'assistant_msg_idx': asst_idx, 'args': args_snap,
                    })
            s.tool_calls = tool_calls
            s.active_stream_id = None
            s.pending_user_message = None
            s.pending_attachments = []
            s.pending_started_at = None
            # Tag the matching user message with attachment filenames for display on reload
            # Only tag a user message whose content relates to this turn's text
            # (msg_text is the full message including the [Attached files: ...] suffix)
            if attachments:
                for m in reversed(s.messages):
                    if m.get('role') == 'user':
                        content = str(m.get('content', ''))
                        # Match if content is part of the sent message or vice-versa
                        base_text = msg_text.split('\n\n[Attached files:')[0].strip()
                        if base_text[:60] in content or content[:60] in msg_text:
                            m['attachments'] = attachments
                            break
            s.save()
            # Sync to state.db for /insights (opt-in setting)
            try:
                from api.config import load_settings as _load_settings
                if _load_settings().get('sync_to_insights'):
                    from api.state_sync import sync_session_usage
                    sync_session_usage(
                        session_id=s.session_id,
                        input_tokens=s.input_tokens or 0,
                        output_tokens=s.output_tokens or 0,
                        estimated_cost=s.estimated_cost,
                        model=model,
                        title=s.title,
                        message_count=len(s.messages),
                    )
            except Exception:
                logger.debug("Failed to sync session to insights")
            usage = {'input_tokens': input_tokens, 'output_tokens': output_tokens, 'estimated_cost': estimated_cost}
            # Include context window data from the agent's compressor for the UI indicator
            _cc = getattr(agent, 'context_compressor', None)
            if _cc:
                usage['context_length'] = getattr(_cc, 'context_length', 0) or 0
                usage['threshold_tokens'] = getattr(_cc, 'threshold_tokens', 0) or 0
                usage['last_prompt_tokens'] = getattr(_cc, 'last_prompt_tokens', 0) or 0
            raw_session = s.compact() | {'messages': s.messages, 'tool_calls': tool_calls}
            put('done', {'session': redact_session_data(raw_session), 'usage': usage})
        finally:
            # Unregister the gateway approval callback and unblock any threads
            # still waiting on approval (e.g. stream cancelled mid-approval).
            if _approval_registered and _unreg_notify is not None:
                try:
                    _unreg_notify(session_id)
                except Exception:
                    logger.debug("Failed to unregister approval callback")
            with _ENV_LOCK:
                if old_cwd is None: os.environ.pop('TERMINAL_CWD', None)
                else: os.environ['TERMINAL_CWD'] = old_cwd
                if old_exec_ask is None: os.environ.pop('HERMES_EXEC_ASK', None)
                else: os.environ['HERMES_EXEC_ASK'] = old_exec_ask
                if old_session_key is None: os.environ.pop('HERMES_SESSION_KEY', None)
                else: os.environ['HERMES_SESSION_KEY'] = old_session_key
                if old_hermes_home is None: os.environ.pop('HERMES_HOME', None)
                else: os.environ['HERMES_HOME'] = old_hermes_home

    except Exception as e:
        print('[webui] stream error:\n' + traceback.format_exc(), flush=True)
        if s is not None:
            s.active_stream_id = None
            s.pending_user_message = None
            s.pending_attachments = []
            s.pending_started_at = None
            try:
                s.save()
            except Exception:
                pass
        err_str = str(e)
        # Detect rate limit errors specifically so the client can show a helpful card
        # rather than the generic "Connection lost" message
        is_rate_limit = 'rate limit' in err_str.lower() or '429' in err_str or 'RateLimitError' in type(e).__name__
        is_auth_error = (
            '401' in err_str
            or 'AuthenticationError' in type(e).__name__
            or 'authentication' in err_str.lower()
            or 'unauthorized' in err_str.lower()
            or 'invalid api key' in err_str.lower()
            or 'no cookie auth credentials' in err_str.lower()
        )
        if is_rate_limit:
            put('apperror', {
                'message': err_str,
                'type': 'rate_limit',
                'hint': 'Rate limit reached. The fallback model (if configured) was also exhausted. Try again in a moment.',
            })
        elif is_auth_error:
            put('apperror', {
                'message': err_str,
                'type': 'auth_mismatch',
                'hint': (
                    'The selected model may not be supported by your configured provider. '
                    'Run `hermes model` in your terminal to switch providers, then restart the WebUI.'
                ),
            })
        else:
            put('apperror', {'message': err_str, 'type': 'error'})
    finally:
        _clear_thread_env()  # TD1: always clear thread-local context
        with STREAMS_LOCK:
            STREAMS.pop(stream_id, None)
            CANCEL_FLAGS.pop(stream_id, None)
            AGENT_INSTANCES.pop(stream_id, None)  # Clean up agent instance reference

# ============================================================
# SECTION: HTTP Request Handler
# do_GET: read-only API endpoints + SSE stream + static HTML
# do_POST: mutating endpoints (session CRUD, chat, upload, approval)
# Routing is a flat if/elif chain. See ARCHITECTURE.md section 4.1.
# ============================================================


def cancel_stream(stream_id: str) -> bool:
    """Signal an in-flight stream to cancel. Returns True if the stream existed."""
    with STREAMS_LOCK:
        if stream_id not in STREAMS:
            return False

        # Set WebUI layer cancel flag
        flag = CANCEL_FLAGS.get(stream_id)
        if flag:
            flag.set()

        # Interrupt the AIAgent instance to stop tool execution
        agent = AGENT_INSTANCES.get(stream_id)
        if agent:
            try:
                agent.interrupt("Cancelled by user")
            except Exception as e:
                # Log but don't block the cancel flow
                import logging
                logging.getLogger(__name__).debug(
                    f"Failed to interrupt agent for stream {stream_id}: {e}"
                )
        else:
            # Agent not yet stored - cancel_event flag will be checked by agent thread
            import logging
            logging.getLogger(__name__).debug(
                f"Cancel requested for stream {stream_id} before agent ready - "
                f"cancel_event flag set, will be checked on agent startup"
            )

        # Put a cancel sentinel into the queue so the SSE handler wakes up
        q = STREAMS.get(stream_id)
        if q:
            try:
                q.put_nowait(('cancel', {'message': 'Cancelled by user'}))
            except Exception:
                logger.debug("Failed to put cancel event to queue")
    return True