* feat: add devcontainer for local setup
* feat: add local install hook
* feat: add devcontainer based setup docs
* feat: use uv in api/Dockerfile
* fix: fix CI scripts
* fix: fix post job cleanup step
* feat: add MiniMax provider support (Chat + TTS)
- Add MiniMax LLM provider using OpenAI-compatible API
- Models: MiniMax-M2.7, MiniMax-M2.7-highspeed
- Default base URL: https://api.minimax.io/v1
- Uses MINIMAX_API_KEY for authentication
- Add MiniMax TTS provider using Pipecat's MiniMaxHttpTTSService
- Models: speech-2.8-hd (default), speech-2.8-turbo
- 6 built-in voices
- Requires group_id configuration
- Add unit tests for both providers
* fix(minimax): validator, temperature, session cleanup, reasoning filter
- check_validity.py: wire MiniMax into _validator_map and enforce
group_id at save time. Without this, saving a config with a valid
key was rejected.
- registry.py: surface temperature on the LLM config (gt=0; MiniMax
rejects 0) and base_url on the TTS config
- service_factory.py:
* Plumb temperature through create_llm_service
* Normalize TTS base_url to include /t2a_v2 — pipecat appends only
?GroupId=... to the URL.
* Use the new MiniMaxLLMService (from pipecat) to strip
<think>...</think> reasoning that MiniMax-M2.7 emits inline in
delta.content (otherwise it leaks straight to TTS).
* Use MiniMaxOwnedSessionTTSService so the per-instance aiohttp
session gets closed in cleanup() instead of leaking sockets/FDs.
- minimax_tts.py: small wrapper around MiniMaxHttpTTSService that owns
the session it was handed (pipecat's caller-owns-session API
conflicts with the ftory's per-instance pattern).
- pipecat submodule: bumps to a commit that adds MiniMaxLLMService — a
thin OpenAILLMService subclass with the streaming <think> filter
(mirrors NvidiaLLMService's pattern for NIM reasoning models).
- Tests updated/added for all of the above.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: octo-patch <octo-patch@github.com>
Co-authored-by: Sabiha Khan <sabihak89@gmail.com>
Closes three known advisories in python-multipart, all reachable
from the FastAPI multipart form-parser used across the API
(transcribe_audio, knowledge_base uploads, presigned upload flows):
- GHSA-wp53-j4wj-2cfg (HIGH, CWE-22) — arbitrary file write via
non-default configuration. Fixed in 0.0.22.
- GHSA-pp6c-gr5w-3c5g (HIGH, CWE-400) — DoS via unbounded multipart
part headers. Fixed in 0.0.27.
- GHSA-mj87-hwqh-73pj (MOD, CWE-400) — DoS via large multipart
preamble or epilogue. Fixed in 0.0.26.
0.0.27 is a patch-level bump within the same 0.0.x line, no API
changes; fastapi==0.135.3 only requires python-multipart>=0.0.7 so
the upper bound is unaffected.
Detected by Aeon + osv-scanner.
Co-authored-by: aeonframework <aeon@aaronjmars.com>
The MCP `instructions` hint is static and baked into the client prompt,
while tool names, signatures, and error codes are discovered dynamically
via tools/list. The two had drifted: instructions restated stale
signatures and an error-code enum that omitted schema_validation and
trigger_path_conflict.
- Trim instructions.py to tool names + call order; stop restating
signatures and error codes the dynamic surface already carries.
- Document each tool's full error_code contract in the save_workflow and
create_workflow docstrings (the descriptions shipped via tools/list).
- Add test_mcp_instructions_drift.py: every tool named in the guide must
be registered, and every error_code a tool returns must appear in its
description.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* feat(mcp): add search_docs tool over Mintlify docs corpus
Closes#295. The docs at https://docs.dograh.com promise "Search the
Dograh docs for how to configure a TURN server" as an MCP example
prompt, but no search_docs tool exists in the MCP server — agents can
list workspace resources but cannot search the documentation.
This adds a dependency-free, in-process keyword search over the
`docs/` tree shipped into the API image (`COPY ./docs ./docs`):
- New `api/mcp_server/tools/docs_search.py` — async `search_docs(query,
limit=10)` with weighted scoring (path > title > body), a 25-result
hard cap, snippet extraction around the first term hit, and graceful
empty-list degradation when docs aren't on disk. `DOGRAH_DOCS_PATH`
env var overrides location discovery for non-Docker layouts.
- Registered in `api/mcp_server/server.py` alongside the other tools,
keeping the existing list-alphabetical convention.
- `api/tests/test_mcp_docs_search.py` — 18 unit tests covering the
pure helpers (tokenizer, frontmatter stripping, title extraction,
scoring weights, URL building) and end-to-end ranking, limit
clamping, empty-corpus degradation, and input-validation errors.
Mocks `authenticate_mcp_request` to avoid the DB dependency,
mirroring `test_mcp_save_workflow.py`.
Implementation notes:
- The docs corpus is ~100 files / ~140k LoC, so a per-call scan runs
well under 50 ms; avoiding a vector index / embedding backend keeps
the tool zero-dependency and works for fully offline self-hosted
deployments.
- Authentication is required for consistency with the other MCP tools
(and to route through the existing rate-limit middleware), even
though docs are not org-scoped data.
- Title/path matches deliberately outweigh body matches so a page
whose subject IS the query term outranks one that merely mentions
it incidentally.
* feat: improve docs search
---------
Co-authored-by: Abhishek Kumar <abhishek@a6k.me>
* Add tuner integration
* bump pipecat version
* chore: update pipecat submodule to match upstream and use tuner-pipecat-sdk 0.2.0
Update pipecat submodule from 0.0.109.dev23 to 13e98d0d9 (the exact commit
upstream dograh-hq/dograh uses after v1.30.1). This installs pipecat-ai as
1.1.0.post277 via setuptools_scm, satisfying tuner-pipecat-sdk 0.2.0's
pipecat-ai>=1.0.0 requirement.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* wire tuner
* feat: refactor integrations into self contained packages
* chore: simplify ensure_public_access_token
* fix: remove NodeSpec and make DTOs the source of truth
* feat: send relevant signal to mcp using to_mcp_dict
* fix: fix tests
* cleanup: remove nango integrations
* feat: add agents.md for integrations
---------
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: Abhishek Kumar <abhishek@a6k.me>
* Resolve an issue with direct socket connections using the wrong event data.
* Resolve the formatting issus in the provider file
* chore: fix import ordering with ruff
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: Nir Simionovich <nirs@cloudonix.io>
Co-authored-by: Abhishek Kumar <abhishek@a6k.me>
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix(ari): pre-register ext channel id and defer bridge to its StasisStart
Two race conditions in the inbound ARI flow could leave a call silent:
1. Bridging both channels immediately after creating the ext media leg
raced against the ext channel entering the Stasis application; slow
chan_websocket handshakes produced "Channel not in Stasis application"
422 errors on addChannel.
2. Asterisk could fire StasisStart for the ext channel before the
externalMedia POST response returned, so _is_ext_channel returned
False and the event was dropped as an unknown outbound call.
Fixes:
- Generate the ext channel id as dograh-ext-<uuid> client-side and pass
it to Asterisk via the channelId query param. Mark the ext channel,
set its channel->run mapping, register the pending bridge entry, and
persist gathered_context.ext_channel_id all before the POST.
- Defer the bridge to a new _complete_bridge_after_ext_ready handler
triggered by the ext channel's own StasisStart. Both channels are
guaranteed in Stasis by then, so addChannel cannot 422.
- On POST failure or channelId mismatch, roll back the pending entry
and ERROR loudly.
* fix: replace in-memory dict with redis storage
* feat: configurable ElevenLabs base URL for Data Residency (#269)
Adds a `base_url` field to `ElevenlabsTTSConfiguration` so users on an
ElevenLabs Data Residency plan (EU, etc.) can point Dograh at the
regional endpoint instead of the hardcoded global one. Defaults to
`https://api.elevenlabs.io`, preserving existing behaviour. The
service factory rewrites the HTTP scheme to WSS when constructing the
WebSocket TTS service.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix: fix drift
---------
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* feat: inline rename of workflow on the editor page
Add a pencil icon next to the workflow name in
WorkflowEditorHeader.tsx. Clicking it swaps the <h1> for an inline
<Input> that saves on Enter or Blur, cancels on Esc, validates
empty/whitespace input, skips no-op renames, rolls back on API
error, and guards against double-submit. Reuses
saveWorkflowConfigurations (the existing rename path used by the
Settings page) — no parallel API call.
Closes https://github.com/dograh-hq/dograh/issues/252.
* refactor: collapse rename state and remove silent config fallback
- WorkflowEditorHeader: replace (isEditingName, nameDraft, nameError,
isRenaming) with a single discriminated-union state. Error and saving
were mutually exclusive and both meaningless in display mode; the
union makes the bad combinations unrepresentable and structurally
prevents the Enter -> disable-input -> blur -> re-fire race that the
original code only guarded against by convention.
- RenderWorkflow: drop the `?? DEFAULT_WORKFLOW_CONFIGURATIONS` fallback
in renameWorkflow. In normal flow the store is initialized before the
header renders, but if it ever weren't, the fallback would silently
overwrite the server-side config with defaults. Throw instead so the
header's existing catch surfaces a toast.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: Abhishek Kumar <abhishek@a6k.me>
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
