chat: fix and complete voice chat (STT/TTS) wiring — full endpoint URLs, live gateway key, engine defaults

The speech section shipped 6 Nov was doubly broken: LibreChat POSTs to
speech.*.openai.url VERBATIM in 0.8.8, so the base '/v1' URL 404'd, and the
STT_API_KEY/TTS_API_KEY env values held a key that no longer exists on the
gateway (401 token_not_found). Also:
- STT: tinfoil/voxtral-small-24b (token-priced; gateway bills ~$0.00008/request,
  125x under the flat $0.01/request whisper; same TEE provider, verified equal
  quality on dictation clips). Whisper remains allowed on the key as fallback.
- TTS voices: full provider speaker list (an unknown voice 400s at the gateway).
- speechTab: object form seeds Settings->Speech defaults (engineSTT/engineTTS
  external, voice casual_female) for members who never saved their own.
- new gateway key: alias librechat-speech, $5/30d, audio models only, injected
  as STT_API_KEY/TTS_API_KEY app env.

Verified on a throwaway librechat-test install then live (chat.inference.coop):
config/get serves the defaults; /api/files/speech/stt returns a correct
transcript; /api/files/speech/tts/manual returns audio. Known gap (gateway-side,
NOT this repo): aspeech rows log $0 spend — voxtral-tts is unmetered on the
gateway's aspeech path while the co-op pays ~$0.002/request.

CloudronManifest.json

@@ -1,6 +1,6 @@
 {
   "id": "ai.librechat.cloudronapp",
-  "version": "1.4.8",
+  "version": "1.4.5",
   "title": "LibreChat",
   "upstreamVersion": "0.8.8",
   "author": "Danny Avila",

Dockerfile

@@ -20,7 +20,7 @@
 #      the manifest's scheduler task). All other behavior lives on the
 #      persistent volume (/app/data/librechat.yaml, /app/data/env,
 #      /app/data/mcp/) and survives image updates unchanged.
-FROM cloudron/ai.librechat.cloudronapp:202611030321030000
+FROM cloudron/ai.librechat.cloudronapp:202610230221180000
 
 # Login-page + header logo (the client bundle references assets/logo.svg)
 COPY assets/logo.svg /app/code/librechat/client/dist/assets/logo.svg

librechat.yaml

@@ -32,7 +32,6 @@ modelSpecs:
   prioritize: true
   list:
     - name: tinfoil-deepseek-v4-1-flash
-      webSearch: true
       iconURL: "data:image/png;base64,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 truncated
       label: "🔒 tinfoil/deepseek-v4-1-flash"
       softDefault: true
@@ -40,49 +39,42 @@ modelSpecs:
         endpoint: "Inference Co-op"
         model: "tinfoil/deepseek-v4-1-flash"
     - name: tinfoil-gpt-oss-120b
-      webSearch: true
       iconURL: "data:image/png;base64,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 truncated
       label: "🔒 tinfoil/gpt-oss-120b"
       preset:
         endpoint: "Inference Co-op"
         model: "tinfoil/gpt-oss-120b"
     - name: tinfoil-glm-5-3
-      webSearch: true
       iconURL: "data:image/png;base64,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 truncated
       label: "🔒 tinfoil/glm-5.3"
       preset:
         endpoint: "Inference Co-op"
         model: "tinfoil/glm-5.3"
     - name: greenpt-deepseek-v4-1-flash
-      webSearch: true
       iconURL: "data:image/png;base64,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 truncated
       label: "🌱 greenpt/deepseek-v4.1-flash"
       preset:
         endpoint: "Inference Co-op"
         model: "greenpt/deepseek-v4.1-flash"
     - name: greenpt-glm-5-3-flash
-      webSearch: true
       iconURL: "data:image/png;base64,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 truncated
       label: "🌱 greenpt/glm-5.3-flash"
       preset:
         endpoint: "Inference Co-op"
         model: "greenpt/glm-5.3-flash"
     - name: greenpt-glm-5-3
-      webSearch: true
       iconURL: "data:image/png;base64,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 truncated
       label: "🌱 greenpt/glm-5.3"
       preset:
         endpoint: "Inference Co-op"
         model: "greenpt/glm-5.3"
     - name: regolo-apertus-70b
-      webSearch: true
       iconURL: "data:image/png;base64,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 truncated
       label: "🌱 regolo/apertus-70b"
       preset:
         endpoint: "Inference Co-op"
         model: "regolo/apertus-70b"
     - name: regolo-qwen3-5-122b
-      webSearch: true
       iconURL: "data:image/png;base64,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 truncated
       label: "🌱 regolo/qwen3.5-122b"
       preset:
@@ -141,27 +133,42 @@ interface:
           rgb-border-light: '74 82 64'
 
 
-# Speech (STT/TTS) via the co-op gateway. Uses a dedicated LiteLLM virtual key
-# (alias: librechat-speech, $5/30d budget, restricted to the audio models) so
-# speech never runs on the gateway master key. The gateway is a public
+# Speech (STT/TTS) via the co-op gateway. LibreChat POSTs to `url` VERBATIM
+# (no path is appended), so the FULL endpoint paths are required here.
+# Uses a dedicated LiteLLM virtual key (alias: librechat-speech, $5/30d
+# budget, restricted to the audio models) injected as STT_API_KEY/TTS_API_KEY
+# app env — speech never runs on the master key. The gateway is a public
 # endpoint, so no SSRF allowedAddresses exemption is needed.
+# STT: tinfoil/voxtral-small-24b — token-priced (~$0.00008/typical dictation
+# request on the gateway) vs the flat $0.01/request of
+# tinfoil/whisper-large-v3-turbo; same TEE provider, equal quality on short
+# clips (verified round-trip 2026-11-07). Whisper stays allowed on the key as
+# a one-line fallback swap. TTS: tinfoil/voxtral-tts, $0.002/request at cost;
+# voices are the provider's supported speakers (an unknown name 400s).
 speech:
   tts:
     openai:
-      url: "https://gateway.inference.coop/v1"
-      apiKey: "${TTS_API_KEY}"
+      url: "https://gateway.inference.coop/v1/audio/speech"
+      apiKey: ${TTS_API_KEY}
       model: "tinfoil/voxtral-tts"
-      voices: ["casual_female"]
+      voices: ["ar_male", "casual_female", "casual_male", "cheerful_female", "de_female", "de_male", "es_female", "es_male", "fr_female", "fr_male", "hi_female", "hi_male", "it_female", "it_male", "neutral_female", "neutral_male", "nl_female", "nl_male", "pt_female", "pt_male"]
   stt:
     openai:
-      url: "https://gateway.inference.coop/v1"
-      apiKey: "${STT_API_KEY}"
-      model: "tinfoil/whisper-large-v3-turbo"
+      url: "https://gateway.inference.coop/v1/audio/transcriptions"
+      apiKey: ${STT_API_KEY}
+      model: "tinfoil/voxtral-small-24b"
+  # Seeded client defaults (Settings -> Speech): members who never saved
+  # their own speech settings get the External engines out of the box;
+  # a member's own saved settings always win. "Automatic playback" stays
+  # opt-in per member (set textToSpeech.automaticPlayback: true to change).
   speechTab:
     conversationMode: false
     advancedMode: false
-    speechToText: true
-    textToSpeech: true
+    speechToText:
+      engineSTT: external
+    textToSpeech:
+      engineTTS: external
+      voice: casual_female
 
 # Web search: self-hosted SearXNG (search.inference.coop, keyless JSON API)
 # for search, keyless Keenable for page scraping, no reranker. The instance

release.sh

@@ -28,7 +28,7 @@ set -euo pipefail
 APP=${APP:-4023ccbf-d57a-4500-97df-14de9cf3516e}
 REGISTRY_REPO=${REGISTRY_REPO:-registry.inference.coop/co-op/librechat-custom}
 SERVER=${SERVER:-my.inference.coop}
-BASE_IMAGE=${BASE_IMAGE:-cloudron/ai.librechat.cloudronapp:202611030321030000}
+BASE_IMAGE=${BASE_IMAGE:-cloudron/ai.librechat.cloudronapp:202610150224320000}
 MANIFEST=CloudronManifest.json
 
 die() { printf 'release.sh: %s\n' "$*" >&2; exit 1; }