Coverage for core / constants.py: 89.6%
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1"""Module-level constants shared across HARTOS.
3This file is the single source of truth for literal values that were
4previously hardcoded in multiple modules. Before this file existed the
5channel registry, flask integration, dynamic agent registry, test
6fixtures, and example scripts each carried their own copy of
7``10077`` / ``8888`` with no mechanism to keep them in sync.
9Import from here instead of repeating literals:
11 from core.constants import DEFAULT_USER_ID, DEFAULT_PROMPT_ID
13Why these specific values:
14 DEFAULT_USER_ID = 10077 — the guest/unauthenticated Hevolve user
15 account used by channel adapters, test fixtures, and
16 standalone entry points that haven't resolved a real user yet.
17 Any real user_id comes from UserChannelBinding resolution,
18 JWT auth, or the frontend session — the default only fires
19 when every other source is empty.
20 DEFAULT_PROMPT_ID = 8888 — the pre-registered default agent prompt
21 that serves generic chat when no custom agent_id is provided.
22 Tests and the channel fallback path both point here so a
23 brand-new install answers chat requests out of the box.
24"""
26DEFAULT_USER_ID: int = 10077
27DEFAULT_PROMPT_ID: int = 8888
30# ──────────────────────────────────────────────────────────────────────
31# HIVE_DEPTH — maximum hop count for any cross-host task / hivemind /
32# federation propagation.
33#
34# The Hevolve topology is a strict 3-level pyramid:
35# flat (desktop) → regional (edge) → central (cloud)
36# A task submitted on a flat node may hop up to regional and up to
37# central (2 hops = 3 levels). Any propagation deeper is either a bug
38# (cycle) or an attempt to fan out beyond the published topology, and
39# the coordinator must reject it.
40#
41# Single source of truth — consumed by:
42# - integrations.distributed_agent.task_coordinator.submit_goal
43# (stamps initial hop=0, rejects context['hop'] > HIVE_DEPTH)
44# - integrations.distributed_agent.worker_loop (before re-dispatching
45# a claimed task to a deeper hive layer)
46#
47# Keep in sync with security.key_delegation.get_node_tier() which also
48# enumerates the same three tiers.
49# ──────────────────────────────────────────────────────────────────────
50HIVE_DEPTH: int = 3
53# ISO 639-1 → language name mapping.
54# Used by hart_intelligence_entry (system prompt), speculative_dispatcher
55# (draft language prompt), and _persist_language (validation).
56SUPPORTED_LANG_DICT = {
57 "ar": "Arabic", "bg": "Bulgarian", "zh": "Chinese",
58 "zh-cn": "Chinese (Simplified)", "nl": "Dutch", "fi": "Finnish",
59 "fr": "French", "de": "German", "el": "Greek", "he": "Hebrew",
60 "hu": "Hungarian", "is": "Icelandic", "id": "Indonesian",
61 "ko": "Korean", "lv": "Latvian", "ms": "Malay", "fa": "Persian",
62 "pl": "Polish", "pt": "Portuguese", "ro": "Romanian", "ru": "Russian",
63 "es": "Spanish", "sw": "Swahili", "sv": "Swedish", "th": "Thai",
64 "tr": "Turkish", "uk": "Ukrainian", "ur": "Urdu", "vi": "Vietnamese",
65 "cy": "Welsh", "hi": "Hindi", "bn": "Bengali", "ta": "Tamil",
66 "pa": "Punjabi", "gu": "Gujarati", "kn": "Kannada", "te": "Telugu",
67 "mr": "Marathi", "ml": "Malayalam", "en": "English",
68 # Indian English — Indic-accented variant. Code preserved (NOT
69 # collapsed by `_normalize_lang` the way en-US is) because Nunba's
70 # TTS preference for en-IN routes to Indic Parler (ai4bharat,
71 # trained on All India Radio + Indic corpora) at position 1, while
72 # plain `en` keeps the chatterbox-first American/expressive ladder.
73 # See `Nunba/tts/tts_engine.py:_FALLBACK_LANG_ENGINE_PREFERENCE`.
74 "en-IN": "English (Indian)",
75 "ja": "Japanese", "it": "Italian", "ne": "Nepali", "si": "Sinhala",
76 "or": "Odia", "as": "Assamese", "sd": "Sindhi", "ks": "Kashmiri",
77 "doi": "Dogri", "mni": "Manipuri", "sa": "Sanskrit", "kok": "Konkani",
78 "mai": "Maithili", "brx": "Bodo", "sat": "Santali",
79 # SEA Brahmi-derived scripts — added for NON_LATIN_SCRIPT_LANGS
80 # membership so the sub-1B draft-skip gate recognises them.
81 "km": "Khmer", "lo": "Lao", "my": "Burmese",
82 # Cyrillic / Greek — weaker but non-zero 0.8B coverage; listed so
83 # NON_LATIN_SCRIPT_LANGS assertion passes.
84 "sr": "Serbian",
85}
88# Indic-language ISO 639-1 codes (Brahmi-family scripts + Urdu/Sindhi
89# in Perso-Arabic). Subset used by TTS routing (Indic Parler) and by
90# NON_LATIN_SCRIPT_LANGS below. Single source for any code that needs
91# "is this an Indic language?" — previously duplicated as _INDIC_LANGS
92# in tts/tts_engine.py.
93INDIC_LANGS = frozenset({
94 "as", "bn", "brx", "doi", "gu", "hi", "kn", "kok", "mai",
95 "ml", "mni", "mr", "ne", "or", "pa", "sa", "sat", "sd", "ta",
96 "te", "ur",
97})
100# ISO 639-1 codes where sub-1B LLMs (the Qwen3.5-0.8B-class draft
101# model) produce Latin-transliterated output ("Vanakkam" instead of
102# native Tamil script) due to weak Unicode-script tokenizer coverage.
103#
104# Single source of truth — consumed by:
105# - integrations.agent_engine.speculative_dispatcher
106# (dispatch_draft_first skip-gate at runtime)
107# - integrations.service_tools.model_lifecycle
108# (on_lang_change subscriber — evicts draft on switch TO these)
109#
110# Derived from INDIC_LANGS plus the other non-Latin script families.
111# Do NOT inline a duplicate frozenset anywhere else — import this.
112NON_LATIN_SCRIPT_LANGS = INDIC_LANGS | frozenset({
113 # CJK
114 "zh", "ja", "ko",
115 # RTL (Arabic / Hebrew / Persian)
116 "ar", "he", "fa",
117 # Southeast Asian Brahmi-derived
118 "th", "lo", "km", "my",
119 # Cyrillic + Greek (historically included by HIE's inline
120 # _NON_LATIN_LANGS; kept here for parity + weaker 0.8B coverage)
121 "ru", "uk", "bg", "sr", "el",
122})
124# Invariant: every code in NON_LATIN_SCRIPT_LANGS must be a registered
125# language in SUPPORTED_LANG_DICT. Fails loud at import time on drift,
126# so adding a code to the set without registering its display name is
127# a build-time error, not a runtime mystery.
128assert NON_LATIN_SCRIPT_LANGS <= set(SUPPORTED_LANG_DICT), (
129 f"NON_LATIN_SCRIPT_LANGS has codes not in SUPPORTED_LANG_DICT: "
130 f"{NON_LATIN_SCRIPT_LANGS - set(SUPPORTED_LANG_DICT)}"
131)
134# ──────────────────────────────────────────────────────────────────────
135# GREETINGS — canonical, localized "first-run handshake" phrase per
136# language. Used by the TTS first-run handshake smoke test
137# (tts/tts_handshake.py) to synthesize a phrase the user actually hears
138# before the "Voice engine ready" banner flips.
139#
140# Single source of truth — replaces two historical parallel paths:
141# 1. tts/verified_synth._TEST_PHRASES (synthesis probe)
142# 2. the "ready to use" string that the React card heuristically
143# matched to flip isComplete before any audio had been produced.
144#
145# Contract:
146# * Keys are ISO 639-1 codes that appear in SUPPORTED_LANG_DICT.
147# * Values are phrases long enough to produce > MIN_AUDIO_BYTES
148# (~0.5s at 22kHz mono) on CPU synth in under 30 seconds.
149# * English 'en' is the fallback when a requested lang is missing.
150#
151# Scope — only the languages that TTS backends actually ship support
152# for today. Do NOT bulk-add entries without verifying the engine
153# can synth them; a missing entry falls back to English, which is
154# preferable to synthesizing garbage.
155# ──────────────────────────────────────────────────────────────────────
156GREETINGS = {
157 # Core — every Nunba install can hit these via at least one engine.
158 "en": "Hey, I'm Nunba. Can you hear me?",
159 "ta": "வணக்கம், நான் நண்பா. என்னுடைய குரல் கேட்கிறதா?",
160 "hi": "नमस्ते, मैं नन्बा हूँ। क्या आप मुझे सुन सकते हैं?",
161 # Indic Parler cohort — its 21-language allowlist, minus the
162 # scripts we haven't hand-verified greetings for.
163 # Transliteration intent: the brand "Nunba" reads aloud as "Nan-baa"
164 # (rhymes with "Numba" the JIT lib). Indic scripts use "न + न" /
165 # "ன + ன" / equivalent so TTS synth renders the intended phonetics.
166 "bn": "হ্যালো, আমি নন্বা। আপনি কি আমাকে শুনতে পাচ্ছেন?",
167 "te": "హలో, నేను నన్బా. మీరు నన్ను వినగలరా?",
168 "ml": "ഹലോ, ഞാൻ നൻബ. എനിക്കു നിങ്ങൾ കേൾക്കാനാകുമോ?",
169 "kn": "ಹಲೋ, ನಾನು ನನ್ಬಾ. ನೀವು ನನ್ನನ್ನು ಕೇಳಬಹುದೆ?",
170 "mr": "नमस्कार, मी नन्बा. तुम्ही मला ऐकू शकता का?",
171 "gu": "નમસ્તે, હું નન્બા છું. શું તમે મને સાંભળી શકો છો?",
172 "pa": "ਸਤਿ ਸ੍ਰੀ ਅਕਾਲ, ਮੈਂ ਨਨਬਾ ਹਾਂ। ਕੀ ਤੁਸੀਂ ਮੈਨੂੰ ਸੁਣ ਸਕਦੇ ਹੋ?",
173 "ur": "ہیلو، میں نَنبا ہوں۔ کیا آپ مجھے سن سکتے ہیں؟",
174 # Chatterbox Multilingual + CosyVoice3 cohort
175 "zh": "你好,我是 Nunba。你能听到我吗?",
176 "ja": "こんにちは、私はNunbaです。聞こえますか?",
177 "ko": "안녕하세요, 저는 Nunba입니다. 제 목소리가 들리시나요?",
178 "fr": "Bonjour, je suis Nunba. Vous m'entendez ?",
179 "es": "Hola, soy Nunba. ¿Me escuchas?",
180 "de": "Hallo, ich bin Nunba. Kannst du mich hören?",
181 "it": "Ciao, sono Nunba. Mi senti?",
182 "ru": "Привет, я Nunba. Вы меня слышите?",
183 "pt": "Olá, eu sou o Nunba. Você consegue me ouvir?",
184}
187# Fallback phrase when the requested language isn't in GREETINGS.
188# Kept as a named constant (not a magic literal) so call sites read
189# clearly and tests can refer to it by name.
190GREETING_FALLBACK_LANG: str = "en"
193# ──────────────────────────────────────────────────────────────────────
194# Brand identity — used as the assistant's "Who am I?" sentence in
195# every English chat path that doesn't already carry a per-agent
196# persona. Single source of truth so HARTOS's draft prompt and Nunba's
197# fallback chat handler can never drift on the brand wording.
198#
199# Non-English paths get their identity through
200# core.agent_personality.get_regional_tone_prompt(lang) — which carries
201# the Nunba name natively in script (e.g. Tamil "நண்பா"). This
202# constant is for English (and any language with no regional-tone
203# entry).
204#
205# Call sites:
206# - integrations/agent_engine/speculative_dispatcher.py
207# (HARTOS draft prompt persona_block default)
208# - Nunba/routes/hartos_backend_adapter.py
209# (cold-boot fallback chat system prompt)
210#
211# Phrasing intentionally short — every byte costs draft-prompt tokens
212# and Nunba is also a TTS-spoken name (the brand identity reads
213# naturally aloud). Per-site framing (privacy mention, language
214# directive, etc.) is added on top by the call site, not baked here.
215# ──────────────────────────────────────────────────────────────────────
216NUNBA_BRAND_IDENTITY: str = (
217 "You are Nunba, a friendly and helpful local AI assistant. "
218 "Hevolve.ai is the web cloud version of Nunba — same intelligence, "
219 "different deployment. With hive enabled, you crowdsource "
220 "intelligence from peer Nunba devices and Hevolve cloud nodes."
221)
224# Every GREETINGS key MUST be a registered language. Mirrors the
225# NON_LATIN_SCRIPT_LANGS invariant above — a missing display name for
226# a greeting-supported lang is a build-time error, not a runtime
227# "None" appearing in a banner.
228assert set(GREETINGS) <= set(SUPPORTED_LANG_DICT), (
229 f"GREETINGS has codes not in SUPPORTED_LANG_DICT: "
230 f"{set(GREETINGS) - set(SUPPORTED_LANG_DICT)}"
231)
232assert GREETING_FALLBACK_LANG in GREETINGS, (
233 f"GREETING_FALLBACK_LANG={GREETING_FALLBACK_LANG!r} is not in GREETINGS"
234)
237# ──────────────────────────────────────────────────────────────────────
238# VISION INTENT — keywords that indicate the user is asking Nunba to
239# use the camera / describe the scene / see them / read a screen.
240# When the draft 0.8B classifier flags a turn as `is_casual=True`, the
241# dispatcher short-circuits to the draft reply without loading the
242# LangChain tool registry — which means the `Visual_Context_Camera`
243# tool never runs even though the user clearly needs vision.
244#
245# This set is consulted in hart_intelligence_entry.dispatch path as a
246# safety net: if the message matches any pattern, we force the full
247# LangChain path so `parse_visual_context` is reachable.
248#
249# Single source of truth — do NOT inline a parallel regex anywhere.
250# Keep lower-cased; callers must lowercase the prompt before matching.
251# ──────────────────────────────────────────────────────────────────────
252import re as _vis_re
254VISION_INTENT_KEYWORDS: tuple = (
255 # direct camera / vision verbs
256 "see me", "see my", "see what", "look at me", "look at my",
257 "looking at me", "watch me", "watch my",
258 # describe-scene phrases
259 "what do you see", "what can you see", "what am i doing",
260 "what am i wearing", "what am i holding", "what's in front of",
261 "what is in front of", "what is on my", "what's on my",
262 "describe me", "describe what", "describe the scene",
263 "describe my", "describe this",
264 # camera-specific
265 "through my camera", "on my camera", "on the camera",
266 "via camera", "using camera", "use the camera", "use my camera",
267 "turn on camera", "turn on the camera", "start camera",
268 # visual modality
269 "can you see", "do you see", "are you seeing",
270 "visual context", "visual question", "video call",
271 # screen / ocr / read-what-is-shown
272 "read the screen", "read my screen", "what's on screen",
273 "what is on screen", "what does the screen show",
274)
276# Word-boundary regex compiled once. Matching uses `search` so partial
277# phrasings ("can you see what i'm wearing") hit.
278_VISION_PATTERN_SRC: str = r"\b(?:" + "|".join(
279 _vis_re.escape(kw) for kw in VISION_INTENT_KEYWORDS
280) + r")\b"
281VISION_INTENT_PATTERN = _vis_re.compile(_VISION_PATTERN_SRC, _vis_re.IGNORECASE)
284def prompt_needs_vision(prompt: str) -> bool:
285 """Return True if the prompt clearly requests a vision / camera
286 capability (i.e. should route through the LangChain tool path so
287 Visual_Context_Camera can fire) even if the draft classifier
288 flagged the turn casual.
290 Cheap regex match — safe to call on every draft fall-through path.
291 """
292 if not prompt:
293 return False
294 try:
295 return bool(VISION_INTENT_PATTERN.search(prompt))
296 except Exception:
297 return False
300# ──────────────────────────────────────────────────────────────────────
301# ENCOUNTER_TOPICS — WAMP topic namespace for the P2P encounter feature
302# (BLE rotating-pubkey discovery → autonomous sighting correlation →
303# avatar-only mutual-like swipe → icebreaker agent → map overlay).
304#
305# Full design in Claude-memory: project_encounter_icebreaker.md.
306#
307# Single source of truth — consumed by:
308# - integrations.social.encounter_api (publish on swipe/match)
309# - integrations.agent_engine.goal_seeding (encounter_icebreaker_agent
310# subscribes to 'match' topic)
311# - Nunba desktop wamp_router + landing-page crossbarWorker
312# - Hevolve_React_Native AutobahnConnectionManager (subscribes to
313# per-user 'sighting' and 'icebreaker' private topics)
314#
315# Per-user privacy scoping: 'sighting', 'swipe', 'icebreaker' are
316# always prefixed with the user_id by the publisher; 'match' publishes
317# TWO events (one per participant) so one user's subscription never
318# leaks the other's pubkey outside the matched pair.
319#
320# Do NOT inline duplicate topic strings; import from here.
321# ──────────────────────────────────────────────────────────────────────
322ENCOUNTER_TOPIC_SIGHTING: str = 'com.hevolve.encounter.sighting'
323ENCOUNTER_TOPIC_SWIPE: str = 'com.hevolve.encounter.swipe'
324ENCOUNTER_TOPIC_MATCH: str = 'com.hevolve.encounter.match'
325ENCOUNTER_TOPIC_ICEBREAKER: str = 'com.hevolve.encounter.icebreaker'
327ENCOUNTER_TOPICS: tuple = (
328 ENCOUNTER_TOPIC_SIGHTING,
329 ENCOUNTER_TOPIC_SWIPE,
330 ENCOUNTER_TOPIC_MATCH,
331 ENCOUNTER_TOPIC_ICEBREAKER,
332)
334# Invariant: all encounter topics share the canonical 'com.hevolve.
335# encounter.' prefix so crossbar ACL rules + log grepping are uniform.
336# A topic outside this prefix would not be scoped by the existing
337# WAMP router authorization (wamp_router.py _handle_publish per-topic
338# authorization, Task #301), so drift here is a security regression.
339_ENCOUNTER_PREFIX = 'com.hevolve.encounter.'
340assert all(t.startswith(_ENCOUNTER_PREFIX) for t in ENCOUNTER_TOPICS), (
341 f"ENCOUNTER_TOPICS must all share prefix {_ENCOUNTER_PREFIX!r}: "
342 f"{[t for t in ENCOUNTER_TOPICS if not t.startswith(_ENCOUNTER_PREFIX)]}"
343)
346# ──────────────────────────────────────────────────────────────────────
347# ENCOUNTER feature tunables — physical-world sighting correlation.
348# A beacon is treated as a SIGHTING (autonomous pairing of the real
349# person in front of the user with their rotating pubkey) only when
350# ALL three conditions hold together. Loosening any one of these
351# degrades to random-pairs-in-a-crowd; tightening any one degrades to
352# never-fires. Values tuned for phone-in-hand, face-to-face scenario.
353# Pocket-mode (low motion detected on both devices) relaxes compass
354# tolerance to ±90° per BleSightingDetector rules.
355#
356# Consumed by:
357# - Hevolve_React_Native BleSightingDetector (Kotlin port of same)
358# - integrations.social.encounter_api.ENCOUNTER_SIGHTING_RULES
359# - tests.unit.test_sighting_correlation
360# ──────────────────────────────────────────────────────────────────────
361ENCOUNTER_SIGHTING_RSSI_PEAK_DBM: int = -55 # ~1.5m line-of-sight
362ENCOUNTER_SIGHTING_MIN_DWELL_SEC: int = 3 # both parties slowed/stopped
363ENCOUNTER_SIGHTING_COMPASS_TOL_DEG: int = 30 # devices facing within cone
364ENCOUNTER_PUBKEY_ROTATION_SEC: int = 15 * 60 # 15 min / relaunch / geo-shift
365ENCOUNTER_DISCOVERABLE_TTL_SEC: int = 4 * 60 * 60 # 4h auto-off
366ENCOUNTER_DISCOVERABLE_MAX_TOGGLES_24H: int = 6
367ENCOUNTER_SIGHTING_EXPIRES_SEC: int = 24 * 60 * 60 # swipe grace window
368ENCOUNTER_MATCH_WINDOW_SEC: int = 5 * 60 # both sightings must be
369 # within this window to match
370ENCOUNTER_DRAFT_MAX_CHARS: int = 220 # icebreaker length cap
373# ──────────────────────────────────────────────────────────────────────
374# CHAT_TOPICS — WAMP topic namespace for cross-device chat mirroring
375# (U1-U8 workstream, task ledger #389).
376#
377# chat.new — a new assistant or user message was persisted. Payload
378# carries the full ChatMessage row (seq, msg_id, user_id,
379# agent_id, role, content, request_id, lang, device_id,
380# attachments, created_at). Every device subscribed to the
381# per-user topic mirrors the row into its local view.
382# chat.ack — a subscriber ACKs receipt up to seq=N. Used by the server
383# to decide when a message can be evicted from the hot cache
384# (the durable row stays in the DB for cursor-pull replay).
385#
386# Per-user scoping: publisher MUST suffix the user_id so a subscriber
387# can ONLY see their own messages. Enforced by Nunba's wamp_router
388# _handle_publish per-topic authorization (Task #301).
389#
390# Do NOT inline duplicate topic strings; import from here.
391# ──────────────────────────────────────────────────────────────────────
392CHAT_TOPIC_NEW: str = 'com.hertzai.hevolve.chat.new'
393CHAT_TOPIC_ACK: str = 'com.hertzai.hevolve.chat.ack'
395CHAT_TOPICS: tuple = (
396 CHAT_TOPIC_NEW,
397 CHAT_TOPIC_ACK,
398)
400# Invariant mirrors ENCOUNTER_TOPICS: shared prefix = uniform ACL. The
401# existing chat-reply topic 'com.hertzai.hevolve.chat.{user_id}' at
402# hart_intelligence_entry.py:2174,4211 uses the same prefix — per-user
403# suffixing happens at publish-time, not at constant-definition time.
404_CHAT_PREFIX = 'com.hertzai.hevolve.chat.'
405assert all(t.startswith(_CHAT_PREFIX) for t in CHAT_TOPICS), (
406 f"CHAT_TOPICS must all share prefix {_CHAT_PREFIX!r}: "
407 f"{[t for t in CHAT_TOPICS if not t.startswith(_CHAT_PREFIX)]}"
408)
410# Cursor-pull tunables — bound the worst-case pull size so a freshly-
411# restored device doesn't stall on a 10k-message replay, and so a
412# malicious cursor=0 pull can't exfiltrate the whole table.
413CHAT_CURSOR_PULL_MAX_ROWS: int = 500
414CHAT_CURSOR_PULL_MAX_BYTES: int = 2 * 1024 * 1024 # 2 MB body cap
417# Chat-hot-path stage strings (#508) — single i18n site, consumed by
418# publish_chat_stage(). Keep values ≤ 60 chars (UI bubble truncates).
419CHAT_STAGE_TEXTS: dict = {
420 'loading_context': 'Loading your context…',
421 'loading_memory': 'Recalling our recent chat…',
422 'loading_tools': 'Preparing tools…',
423 'thinking': 'Thinking…',
424 'generating': 'Generating a response…',
425 'finalizing': 'Finalizing the answer…',
426 # Generic fallback used by _with_tool_logging — callers pass
427 # text=TOOL_LABELS.get(name, 'Running {name}…') for the real text.
428 'tool_call': 'Running a tool…',
429}
430CHAT_STAGES: frozenset = frozenset(CHAT_STAGE_TEXTS)
433# Per-tool human-readable labels for tool_call stage emits (#508). Static
434# entries cover the hardcoded tools in get_tools(is_first=True) + canonical
435# provider/builtin tools. Dynamic tool registries (skills, service_tools,
436# providers, Tier-2 goal-aware) should call register_tool_label() at the
437# point of Tool() construction so their tools also get a friendly label.
438# Unknown tools fall back to "Running {name}…" at the emit site.
439# Keep values <= 60 chars (UI bubble truncates).
440TOOL_LABELS: dict = {
441 # Memory + history
442 'FULL_HISTORY': 'Searching your message history…',
443 'recall_memory': 'Recalling memories…',
444 'remember_memory': 'Saving to memory…',
445 # Computation + web
446 'Calculator': 'Calculating…',
447 'google-search': 'Searching the web…',
448 # Vision / camera
449 'Visual_Context_Camera': 'Looking through camera…',
450 'Visual_Context_Watcher': 'Setting up a visual watcher…',
451 'Request_Camera_Access': 'Requesting camera access…',
452 'Image_Inference_Tool': 'Analyzing the image…',
453 'Animate_Character': 'Animating your character…',
454 # Media generation
455 'Generate_Image': 'Generating an image…',
456 'Text to image': 'Generating an image from text…',
457 # Channels + invites + rooms
458 'Connect_Channel': 'Connecting channel…',
459 'Invite_Friend': 'Generating an invite link…',
460 'Join_External_Room': 'Joining the room…',
461 # Agent + planning
462 'Agentic_Router': 'Planning the next steps…',
463 'Create_Agent': 'Starting agent creation…',
464 # System / OS
465 'Shell_Command': 'Running a command…',
466 'Computer_Action': 'Acting on your screen…',
467 'Computer_Screenshot': 'Taking a screenshot…',
468 'Request_Screen_Access': 'Requesting screen access…',
469 # Cloud expert
470 'Cloud_LLM': 'Consulting the cloud expert…',
471 # Navigation + UX
472 'Navigate_App': 'Opening the requested page…',
473 'List_Pending_Actions': 'Listing pending actions…',
474 # Data extraction + user lookup
475 'Data_Extraction_From_URL': 'Extracting data from URL…',
476 'User_details_tool': 'Looking up user details…',
477 'OpenAPI_Specification': 'Calling the OpenAPI service…',
478 # Resource requests + self-improvement
479 'Request_Resource': 'Requesting a resource…',
480 'Suggest_Share_Worthy_Content': 'Finding share-worthy content…',
481 'Observe_User_Experience': 'Recording an observation…',
482 'Self_Critique_And_Enhance': 'Reflecting on past suggestions…',
483 # ── reuse_recipe.py inner tools (autogen function_map names) ──
484 # #509 — added here (canonical static home) instead of being
485 # dynamically register_tool_label()-ed at reuse_recipe import time.
486 'txt2img': 'Generating an image…',
487 'img2txt': 'Reading the image…',
488 'save_data_in_memory': 'Saving to memory…',
489 'get_saved_metadata': 'Listing saved memory…',
490 'get_data_by_key': 'Recalling from memory…',
491 'get_user_id': 'Looking up your user id…',
492 'get_prompt_id': 'Looking up your prompt id…',
493 'Generate_video': 'Generating a video…',
494 'get_user_uploaded_file': 'Fetching your uploaded file…',
495 'get_user_camera_inp': 'Reading from your camera…',
496 'get_chat_history': 'Reading recent chat history…',
497 'search_visual_history': 'Searching your visual history…',
498 'register_visual_watcher': 'Registering a visual watcher…',
499 'search_long_term_memory': 'Searching long-term memory…',
500 'save_to_long_term_memory': 'Saving to long-term memory…',
501 'create_scheduled_jobs': 'Scheduling a task…',
502 'send_message_to_user': 'Sending you a message…',
503 'send_presynthesized_video_to_user': 'Sending a video to you…',
504 'send_message_in_seconds': 'Scheduling a message…',
505 'consult_expert': 'Consulting the cloud expert…',
506 'get_user_camera_inp_by_mins': 'Reading camera history…',
507 'execute_windows_or_android_command': 'Running a system command…',
508 'google_search': 'Searching the web…',
509 'create_new_agent': 'Starting agent creation…',
510 'update_persona': 'Updating role/persona in DB…',
511 # ── journey_engine.py + outreach_crm_tools.py (autogen tools) ──
512 # #509 — moved from inline _journey_ui_labels / _outreach_ui_labels
513 # dicts at the call site so register_labeled_function picks them up
514 # via TOOL_LABELS.get(name, …) without per-site dups.
515 'view_journey_pipeline': 'Reviewing journey pipeline…',
516 'advance_prospect_stage': 'Advancing prospect stage…',
517 'run_journey_tick': 'Running journey tick…',
518 'send_prospect_message': 'Sending prospect message…',
519 'create_prospect': 'Creating CRM prospect…',
520 'send_outreach_email': 'Sending outreach email…',
521 'create_followup_sequence': 'Scheduling follow-up sequence…',
522 'check_pending_followups': 'Checking pending follow-ups…',
523 'move_prospect_stage': 'Moving prospect to next stage…',
524 'get_pipeline_status': 'Loading pipeline status…',
525 'list_sent_emails': 'Listing sent emails…',
526 # ── system_introspect_tool.py — duplicate-of-truth from
527 # _INTROSPECT_LABELS pulled into the canonical dict so the
528 # static names live in one place (the module still keeps its
529 # own dict for the LangChain `labeled_tool` call sites). ──
530 'get_gpu_tier': 'Checking GPU tier…',
531 'list_running_models': 'Looking up active models…',
532 'get_tts_status': 'Checking TTS engine status…',
533 'get_tier_thresholds': 'Reading tier thresholds…',
534 'get_boot_decision': 'Reading boot rationale…',
535 'get_system_health': 'Checking system health…',
536 'list_decisions': 'Listing recorded decisions…',
537 'explain_decision': 'Explaining a system decision…',
538 # ── core/agent_tools.py @log_tool_execution-decorated functions
539 # (the 28 "canonical" core tools shared by create_recipe +
540 # reuse_recipe via register_core_tools). These are *autogen
541 # function_map* names — snake_case — and are SEPARATE names from
542 # their similarly-named LangChain Tool() literals above (e.g.,
543 # `text_2_image` (autogen) vs `Generate_Image` / `Text to image`
544 # (LangChain). Same verb, same UX, registered both ways. A
545 # follow-up task will canonicalize the names; for now we list
546 # them all so the lookup never misses. ──
547 'text_2_image': 'Generating an image…',
548 'data_extraction_from_url': 'Extracting data from URL…',
549 'device_control': 'Acting on your device…',
550 'get_user_details': 'Looking up user details…',
551 'observe_user_experience': 'Recording an observation…',
552 'request_resource': 'Requesting a resource…',
553 'self_critique_and_enhance': 'Reflecting on past suggestions…',
554 'suggest_share_worthy_content': 'Finding share-worthy content…',
555 # ── integrations/channels/agent_tools.py @log_tool_execution funcs
556 # (channel-adapter tools shared by both create + reuse). ──
557 'register_channel': 'Registering a channel…',
558 'send_to_channel': 'Sending to a channel…',
559 'send_install_link': 'Sending an install link…',
560 'list_channels': 'Listing your channels…',
561 'get_channel_context': 'Reading channel context…',
562 'reconnect_channel': 'Reconnecting channel…',
563 'disconnect_channel': 'Disconnecting channel…',
564 # ── integrations/providers/agent_tools.py labeled_tool() literals
565 # that the prior pass missed (casing drift from Generate_video). ──
566 'Generate_Video': 'Generating a video…',
567 'List_AI_Providers': 'Listing AI providers…',
568 'Provider_Leaderboard': 'Loading provider leaderboard…',
569}
572def register_tool_label(name: str, label: str) -> None:
573 """Register a UI label for a tool name. Used by dynamic tool registries
574 (integrations.skills, integrations.service_tools, integrations.providers,
575 Tier-2 goal-aware tool packs) to supply human-readable status text next
576 to where they construct Tool() objects. Idempotent — overwrites prior
577 entry for the same name so a registry can refine its labels over time.
579 Tools that don't register a label fall back to the generic
580 'Running {name}…' template at the emit site in
581 hart_intelligence_entry._with_tool_logging.
582 """
583 if not name or not label:
584 return
585 TOOL_LABELS[str(name)] = str(label)[:60]