This is a non-fatal issue that occurs during concurrent project close
when multiple nodes try to write their md5sum cache while the project
directory is being cleaned up.
- Expose optional 'fields' parameter to AI via tool description
- List all available node fields in the parameter description
- Mention inherited template_id in batch mode
- Batch mode now inherits top-level template_id as default per-node
- Both single and batch modes filter response to minimal fields by default
(node_id, name, node_type, status, console)
- Optional 'fields' parameter overrides the default field set
Dynamips node creation (e.g., Cisco 7200 with multiple adapters)
can exceed the previous 10-second timeout, causing MCP tools to
fail with Read timed out errors.
- Add class-level caches for loader and default RAM/NVRAM values
- When multiple IOU nodes use the same image, only the first one runs
the ld-linux --verify and iou-image -h subprocesses
- Subsequent nodes reuse cached results, saving ~2 subprocess calls per node
- Cache is populated only on successful subprocess execution to avoid
overwriting explicitly set ram/nvram values with stale cached defaults
The _iou_id_lock must cover _create_node() because get_next_application_id()
checks in-memory nodes (self._nodes), which are only registered after
_create_node() completes. Without this serialization, concurrent IOU
node creation produces duplicate application IDs.
- Narrow IOU lock scope to only cover application_id allocation,
allowing concurrent IOU node creation via Pool(concurrency=5)
- Parallelize link creation during project.open() using Pool(concurrency=5)
instead of sequential processing
- Add batch UDP port allocation endpoint on compute to allocate N ports
in a single HTTP call
- Pre-allocate UDP ports per compute before link creation during project
loading, reducing HTTP round-trips
- UDPLink.create() falls back to individual port allocation if no
pre-allocated port is available
_ jw t_username_var set in _resolve_token for both JWT and API key auth.
Passed to handlers via gns3_ctx['jwt_username']. No raw key exposure,
no fake-user fallback.
Dict comprehension overwrote earlier entries when the same device
appeared multiple times, causing all entries' outputs to collapse
into the last one. Now commands are appended for duplicate names.
config_tools_nornir expects config_commands, while
display_tools_nornir and vpcs_tools_netmiko expect commands.
Render template now uses the correct field name.
- Add optional 'template' param with Jinja2 syntax
- Each device entry can use 'vars' dict instead of 'config_commands'
- Template rendered per device, merged with existing commands
- Rendering errors returned inline for AI self-correction
- Each tool accepts either node_id (single) or node_ids (batch)
- Batch mode runs actions in parallel via ThreadPoolExecutor
- Useful for starting/stopping nodes by topology region
- node_create accepts nodes=[{template_id, x, y, name?}] for batch creation
- link_create accepts links=[{nodes, link_type?, filters?}] for batch creation
- Uses ThreadPoolExecutor for parallel REST API calls
- Max 10 concurrent workers per batch, backward compatible with single mode
REST API auth already supports gns3_ keys, so there's no need
to create a temporary 5-min JWT. The raw API key is passed
through as the Bearer token, eliminating token expiry issues.
Removing the soft-delete approach — revoked keys are now deleted
from the database entirely via DELETE endpoint. This prevents the
api_keys table from accumulating stale records.
_db_engine is not available when register_starlette_routes() is
called (it's set later during lifespan startup). Store the app
reference instead and access app.state._db_engine lazily.
