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60 Commits

Author SHA1 Message Date
730d609f81 Relax Xcode signing identity matching
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TestFlight / testflight (push) Failing after 26s
2026-06-25 23:57:17 -07:00
137fce8558 Use passworded CI keychain
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TestFlight / testflight (push) Failing after 25s
2026-06-25 23:53:24 -07:00
3e6d3c6817 Use user keychain domain in CI
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TestFlight / testflight (push) Failing after 23s
2026-06-25 23:51:33 -07:00
100b51de12 Use explicit CI signing keychain
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TestFlight / testflight (push) Failing after 18s
2026-06-25 23:48:26 -07:00
23ee30a53a Simplify TestFlight CI signing
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TestFlight / testflight (push) Failing after 22s
2026-06-25 23:44:13 -07:00
0be2442ad0 Pass signing keychain to Xcode resolver
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TestFlight / testflight (push) Failing after 28s
2026-06-25 23:37:24 -07:00
c84ef8c242 Refresh CI key partition access before build
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TestFlight / testflight (push) Failing after 27s
2026-06-25 23:35:00 -07:00
98f96eda45 Let Xcode select Apple Distribution identity
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TestFlight / testflight (push) Failing after 25s
2026-06-25 23:32:38 -07:00
3904457c21 Use runner home for CI keychain preferences
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TestFlight / testflight (push) Failing after 24s
2026-06-25 23:30:46 -07:00
0fc2117a11 Set CI keychain as default for Xcode
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2026-06-25 23:28:58 -07:00
60469f05b5 Tolerate login keychain preference failure
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2026-06-25 23:27:13 -07:00
d834ed7931 Create CI login keychain when missing
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TestFlight / testflight (push) Failing after 19s
2026-06-25 23:25:42 -07:00
f98a002f52 Use explicit runner login keychain
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TestFlight / testflight (push) Failing after 17s
2026-06-25 23:23:13 -07:00
b0c0a2d55e Reset CI keychain search list
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TestFlight / testflight (push) Failing after 19s
2026-06-25 23:21:42 -07:00
3262f4ff80 Detect runner login keychain path
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TestFlight / testflight (push) Failing after 19s
2026-06-25 23:20:06 -07:00
585be09eb7 Target login keychain path for CI signing
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TestFlight / testflight (push) Failing after 19s
2026-06-25 23:18:01 -07:00
387896741c Use runner login keychain for CI signing
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TestFlight / testflight (push) Failing after 21s
2026-06-25 23:16:22 -07:00
f6a10af7a9 Use signing certificate identity hash
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TestFlight / testflight (push) Failing after 24s
2026-06-25 23:13:08 -07:00
8aab86e2a6 Avoid changing default keychain in CI
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2026-06-25 23:10:35 -07:00
eb4b233e33 Resolve CI signing keychain path
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TestFlight / testflight (push) Failing after 18s
2026-06-25 23:08:35 -07:00
cbd7a68e57 Make CI signing keychain visible to Xcode
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TestFlight / testflight (push) Failing after 21s
2026-06-25 23:06:00 -07:00
04c15e8f12 Use absolute iOS paths in Fastlane
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2026-06-25 22:50:30 -07:00
ca28ebc0a0 Use disposable match keychain in CI
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TestFlight / testflight (push) Failing after 16s
2026-06-25 22:48:59 -07:00
87787642b5 Preserve Ruby path for TestFlight workflow
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TestFlight / testflight (push) Failing after 22s
2026-06-25 22:46:14 -07:00
4124a31a34 Use Ruby 3.1 for TestFlight workflow
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TestFlight / testflight (push) Failing after 21s
2026-06-25 22:43:27 -07:00
a68f1e50ca Reset iOS TestFlight deployment
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TestFlight / testflight (push) Failing after 14s
2026-06-25 22:41:00 -07:00
272ad0bbf0 ios: pass signing settings to archive
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TestFlight Release / testflight (push) Failing after 17s
2026-06-25 22:19:25 -07:00
de7b448bc5 ios: avoid system default keychain writes
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TestFlight Release / testflight (push) Failing after 16s
2026-06-25 22:16:24 -07:00
3c7fc51fdb ios: set ci keychain in default domain
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TestFlight Release / testflight (push) Failing after 10s
2026-06-25 22:14:25 -07:00
0062f37b9f ios: sign with disposable login keychain
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TestFlight Release / testflight (push) Failing after 17s
2026-06-25 22:12:17 -07:00
0ae551615f ios: use signing identity fingerprint in ci
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TestFlight Release / testflight (push) Failing after 16s
2026-06-25 22:10:06 -07:00
88bef50ae7 ios: create named ci keychain in home
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2026-06-25 22:07:12 -07:00
0d069b4233 ios: create ci keychain by name
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TestFlight Release / testflight (push) Failing after 11s
2026-06-25 22:05:47 -07:00
60bbe077e8 ios: pass signing keychain to xcode
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TestFlight Release / testflight (push) Failing after 18s
2026-06-25 22:02:19 -07:00
0b09d5425b ios: handle empty ci keychain list
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TestFlight Release / testflight (push) Failing after 15s
2026-06-25 21:58:01 -07:00
c9a3015e35 ios: parse ci profile without keychain
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TestFlight Release / testflight (push) Failing after 9s
2026-06-25 21:56:19 -07:00
abd8a80daa ios: isolate ci signing keychains
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TestFlight Release / testflight (push) Failing after 8s
2026-06-25 21:52:17 -07:00
0f76ef91a9 ios: restore working ci p12 import
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TestFlight Release / testflight (push) Failing after 9s
2026-06-25 21:48:19 -07:00
72e2ffd898 ios: use temporary keychain path in ci
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TestFlight Release / testflight (push) Failing after 9s
2026-06-25 21:46:48 -07:00
4c610c89e1 ios: install ci profiles for xcode signing
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TestFlight Release / testflight (push) Failing after 9s
2026-06-25 21:44:42 -07:00
477921563f ios: remove invalid ci codesign path
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TestFlight Release / testflight (push) Failing after 18s
2026-06-25 21:36:37 -07:00
0fca0e93ec ios: grant ci key access to xcode tools
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TestFlight Release / testflight (push) Failing after 10s
2026-06-25 21:35:11 -07:00
f977f9943c ios: patch generated release signing settings
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TestFlight Release / testflight (push) Failing after 16s
2026-06-25 21:31:51 -07:00
f445730a41 ios: override iphoneos signing identity
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2026-06-25 21:29:35 -07:00
76cb808c33 ios: use disposable keychain as ci default
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TestFlight Release / testflight (push) Failing after 15s
2026-06-25 21:27:19 -07:00
e167bd983f ios: use generic xcode signing selector
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2026-06-25 21:25:13 -07:00
e4dd91564f ios: unlock signing keychain before build
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TestFlight Release / testflight (push) Failing after 17s
2026-06-25 21:20:31 -07:00
3bfde476a6 ios: use single identity signing p12
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TestFlight Release / testflight (push) Failing after 16s
2026-06-25 21:18:54 -07:00
b8676027db ios: trust Apple root in CI signing keychain
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2026-06-25 21:12:53 -07:00
d36d2c60a3 ios: install Apple WWDR intermediate in CI
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TestFlight Release / testflight (push) Failing after 18s
2026-06-25 21:11:01 -07:00
3d7031bb40 ios: avoid default keychain mutation in ci
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2026-06-25 21:08:32 -07:00
fa9b725c77 ios: expose signing keychain to xcodebuild
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TestFlight Release / testflight (push) Failing after 9s
2026-06-25 21:07:38 -07:00
a88987d08d ios: pin distribution signing identity
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TestFlight Release / testflight (push) Failing after 15s
2026-06-25 21:05:26 -07:00
e137ea1077 ios: bootstrap signing with existing certificate
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TestFlight Release / testflight (push) Failing after 17s
2026-06-25 21:03:43 -07:00
fad25d7f2b ios: configure api-key TestFlight signing 2026-06-25 20:51:01 -07:00
fb28508764 ios: ci: keychain cleanup 2026-06-25 20:35:39 -07:00
4365798f5e workflow: fix
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2026-06-25 20:21:39 -07:00
f232013e5a ios: ci: deploy via fastlane
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2026-06-25 19:30:58 -07:00
27c425f664 supposedly better tool call animation 2026-06-14 19:10:56 -07:00
297b053a91 big backend refactor 2026-06-13 12:02:22 -07:00
28 changed files with 2370 additions and 1284 deletions

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@@ -0,0 +1,70 @@
name: TestFlight
on:
workflow_dispatch:
push:
tags:
- "v*"
jobs:
testflight:
runs-on: xcode
defaults:
run:
shell: bash
steps:
- name: Checkout
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Setup Ruby
uses: ruby/setup-ruby@v1
with:
ruby-version: "3.1.7"
bundler-cache: true
working-directory: ios
- name: Install XcodeGen
run: |
set -euo pipefail
if ! command -v xcodegen >/dev/null 2>&1; then
brew install xcodegen
fi
- name: Prepare Runner Keychain
env:
HOME: /var/lib/act_runner
run: |
set -euo pipefail
mkdir -p "${HOME}/Library/Keychains"
login_keychain="${HOME}/Library/Keychains/login.keychain"
if [ ! -f "${login_keychain}-db" ]; then
security create-keychain -p "" "${login_keychain}"
fi
security unlock-keychain -p "" "${login_keychain}" 2>/dev/null || \
security unlock-keychain -p "sybil-ci-keychain-password" "${login_keychain}" 2>/dev/null || true
security default-keychain -d user -s "${login_keychain}"
security list-keychains -d user -s "${login_keychain}-db"
security delete-keychain "${HOME}/Library/Keychains/sybil_ci_keychain" >/dev/null 2>&1 || true
rm -f "${HOME}/Library/Keychains/sybil_ci_keychain" "${HOME}/Library/Keychains/sybil_ci_keychain-db"
- name: Upload to TestFlight
working-directory: ios
env:
HOME: /var/lib/act_runner
APP_STORE_CONNECT_KEY_ID: ${{ secrets.APP_STORE_CONNECT_KEY_ID }}
APP_STORE_CONNECT_ISSUER_ID: ${{ secrets.APP_STORE_CONNECT_ISSUER_ID }}
APP_STORE_CONNECT_KEY_CONTENT: ${{ secrets.APP_STORE_CONNECT_KEY_CONTENT }}
MATCH_PASSWORD: ${{ secrets.MATCH_PASSWORD }}
MATCH_GIT_URL: ${{ secrets.MATCH_GIT_URL }}
MATCH_GIT_BASIC_AUTHORIZATION: ${{ secrets.MATCH_GIT_BASIC_AUTHORIZATION }}
FASTLANE_SKIP_UPDATE_CHECK: "1"
FASTLANE_XCODEBUILD_SETTINGS_TIMEOUT: "120"
run: |
export PATH="/Users/runner/hostedtoolcache/Ruby/3.1.7/arm64/bin:${PATH}"
ruby --version
bundle exec fastlane ios beta

3
.gitignore vendored
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@@ -1,2 +1,3 @@
.env
ios/fastlane/README.md
ios/fastlane/report.xml

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@@ -56,7 +56,7 @@ Chat upload limits:
```
Behavior notes:
- Lists Sybil-managed chat tools that can be enabled for `openai` and `xai` chat completions.
- Lists Sybil-managed chat tools that can be enabled for `openai`, `anthropic`, and `xai` chat completions.
- Optional tools such as `codex_exec` and `shell_exec` appear only when enabled by server environment configuration.
## Active Runs
@@ -291,13 +291,14 @@ Behavior notes:
- Images are forwarded inline to providers as multimodal image parts. Use PNG or JPEG for cross-provider compatibility.
- Text files are forwarded as explicit text blocks rather than provider-managed file references. Large text attachments should already be truncated client-side before submission.
- For `openai`, backend calls OpenAI's Responses API and enables internal tool use with an internal system instruction.
- For `anthropic`, backend calls Anthropic's Messages API and enables internal tool use with Anthropic `tool_use`/`tool_result` content blocks.
- For `xai`, backend calls xAI's OpenAI-compatible Chat Completions API and enables internal tool use with the same internal system instruction.
- For `hermes-agent`, backend calls the configured Hermes Agent OpenAI-compatible Chat Completions API without adding Sybil-managed tool definitions; Hermes Agent handles its own tools server-side.
- For `openai`, image attachments are sent as Responses `input_image` items and text attachments are sent as `input_text` items.
- For `xai` and `hermes-agent`, image attachments are sent as Chat Completions content parts alongside text.
- For `openai`, Responses calls that can enter the server-managed tool loop use `store: true` so reasoning and function-call items can be passed between tool rounds.
- For `anthropic`, image attachments are sent as Messages API `image` blocks using base64 source data; text attachments are added as `text` blocks.
- Available Sybil-managed tool calls for `openai` and `xai`: `web_search` and `fetch_url`. When `CHAT_CODEX_TOOL_ENABLED=true`, `codex_exec` is also available. When `CHAT_SHELL_TOOL_ENABLED=true`, `shell_exec` is also available.
- Available Sybil-managed tool calls for `openai`, `anthropic`, and `xai`: `web_search` and `fetch_url`. When `CHAT_CODEX_TOOL_ENABLED=true`, `codex_exec` is also available. When `CHAT_SHELL_TOOL_ENABLED=true`, `shell_exec` is also available.
- `web_search` returns ranked results with per-result summaries/snippets. Its backend engine is selected by `CHAT_WEB_SEARCH_ENGINE` (`exa` default, or `searxng` with `SEARXNG_BASE_URL` set). SearXNG mode requires the instance to allow `format=json`.
- `fetch_url` fetches a URL with browser-like navigation headers and returns plaintext page content (HTML converted to text server-side).
- `codex_exec` delegates coding, shell, repository inspection, and other complex software tasks to a persistent remote Codex CLI workspace over SSH. The server runs `codex exec --dangerously-bypass-approvals-and-sandbox --skip-git-repo-check <non-interactive wrapped prompt>` on the configured devbox inside `CHAT_CODEX_REMOTE_WORKDIR`, with SSH stdin closed.
@@ -315,7 +316,6 @@ Behavior notes:
- `CHAT_CODEX_EXEC_TIMEOUT_MS=600000` (optional)
- `CHAT_SHELL_EXEC_TIMEOUT_MS=120000` (optional)
- When a tool call is executed, backend stores a chat `Message` with `role: "tool"` and tool metadata (`metadata.kind = "tool_call"`). Streaming requests emit an initiated SSE `tool_call` event before execution, then persist each completed or failed tool call as its terminal SSE `tool_call` event is emitted, then store the assistant output when the completion finishes.
- `anthropic` currently runs without server-managed tool calls.
## Searches

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@@ -171,19 +171,20 @@ Terminal tool-call event:
## Provider Streaming Behavior
- `openai`: backend uses OpenAI's Responses API and may execute internal function tool calls (`web_search`, `fetch_url`, optional `codex_exec`, and optional `shell_exec`) before producing final text.
- `anthropic`: backend uses Anthropic's Messages API and may execute the same internal tools with `tool_use`/`tool_result` content blocks before producing final text.
- `xai`: backend uses xAI's OpenAI-compatible Chat Completions API and may execute the same internal tool calls before producing final text.
- `fetch_url` sends browser-like navigation headers for outbound URL requests to reduce false 403s from sites that reject generic server clients.
- `hermes-agent`: backend uses the configured Hermes Agent OpenAI-compatible Chat Completions API. Sybil does not add its own tool definitions for this provider; Hermes Agent handles its own tools server-side. Custom Hermes stream events are normalized away unless they produce text deltas in this SSE contract.
- `openai`: image attachments are sent as Responses `input_image` items; text attachments are sent as `input_text` items.
- `xai` and `hermes-agent`: image attachments are sent as Chat Completions content parts; text attachments are inlined as text parts.
- `openai`: Responses calls that can enter the server-managed tool loop use `store: true` so reasoning and function-call items can be passed between tool rounds.
- `anthropic`: streamed via event stream; emits `delta` from `content_block_delta` with `text_delta`. Image attachments are sent as base64 `image` blocks and text attachments are appended as `text` blocks.
- `anthropic`: streamed via event stream; emits `delta` from `content_block_delta` with `text_delta`, and emits normalized `tool_call` SSE events when Anthropic `tool_use` blocks are executed. Image attachments are sent as base64 `image` blocks and text attachments are appended as `text` blocks.
- `web_search` uses `CHAT_WEB_SEARCH_ENGINE` (`exa` default, or `searxng` with `SEARXNG_BASE_URL` set). SearXNG mode requires the instance to allow `format=json`. This only affects chat-mode tool calls, not search-mode endpoints.
- `codex_exec` is available only when `CHAT_CODEX_TOOL_ENABLED=true`. It SSHes to `CHAT_CODEX_REMOTE_HOST`, creates/uses `CHAT_CODEX_REMOTE_WORKDIR`, and runs `codex exec --dangerously-bypass-approvals-and-sandbox --skip-git-repo-check <non-interactive wrapped prompt>` there with SSH stdin closed. Prefer `CHAT_CODEX_SSH_KEY_PATH` with a read-only mounted private key; `CHAT_CODEX_SSH_PRIVATE_KEY_B64` is also supported.
- `shell_exec` is available only when `CHAT_SHELL_TOOL_ENABLED=true`. It uses the same devbox SSH configuration, starts in `CHAT_CODEX_REMOTE_WORKDIR`, and runs non-interactive shell commands there with SSH stdin closed, not inside the Sybil server container.
- `CHAT_MAX_TOOL_ROUNDS` controls how many model/tool result cycles may occur before the backend returns a tool-call limit message; default is 100.
Tool-enabled streaming notes (`openai`/`xai`):
Tool-enabled streaming notes (`openai`/`anthropic`/`xai`):
- Stream still emits standard `meta`, `delta`, `done|error` events.
- Stream may emit `tool_call` events while tool calls are executed.
- `delta` events carry assistant text and are emitted incrementally for normal text rounds. The backend may buffer model-native text briefly while determining whether a provider round contains tool calls.

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@@ -1,14 +1,18 @@
FASTLANE_APP_IDENTIFIER=net.buzzert.sybil2
FASTLANE_TEAM_ID=DQQH5H6GBD
FASTLANE_USER=you@example.com
FASTLANE_APPLE_APPLICATION_SPECIFIC_PASSWORD=xxxx-xxxx-xxxx-xxxx
FASTLANE_SKIP_UPDATE_CHECK=1
FASTLANE_HIDE_CHANGELOG=1
SYBIL_APP_STORE_APPLE_ID=6759442828
SYBIL_PROVIDER_PUBLIC_ID=c043d167-ad88-4036-84ea-76c223f1b1b2
SYBIL_PROVISIONING_PROFILE_SPECIFIER=Sybil AppStore CI
SYBIL_PROVISIONING_PROFILE_UUID=
SYBIL_CODE_SIGN_IDENTITY=Apple Distribution: James Magahern (DQQH5H6GBD)
SYBIL_XCODE_CODE_SIGN_IDENTITY=6B74B268C4761720FB2051D01D8BB3E47B55D9F5
SYBIL_EXPORT_SIGNING_CERTIFICATE=Apple Distribution
SYBIL_SIGNING_CERTIFICATE_ID=
SYBIL_SIGNING_KEYCHAIN=
# Optional App Store Connect API key settings for non-interactive upload and
# TestFlight build-number lookup.
# App Store Connect API key settings for TestFlight upload and signing setup.
APP_STORE_CONNECT_API_KEY_ID=
APP_STORE_CONNECT_API_ISSUER_ID=
APP_STORE_CONNECT_API_KEY_PATH=

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@@ -32,6 +32,12 @@ targets:
INFOPLIST_KEY_UILaunchScreen_Generation: YES
INFOPLIST_KEY_UISupportedInterfaceOrientations_iPhone: UIInterfaceOrientationPortrait
INFOPLIST_KEY_UISupportedInterfaceOrientations_iPad: UIInterfaceOrientationPortrait UIInterfaceOrientationPortraitUpsideDown UIInterfaceOrientationLandscapeLeft UIInterfaceOrientationLandscapeRight
configs:
Release:
CODE_SIGN_STYLE: Manual
CODE_SIGN_IDENTITY: Apple Distribution
"CODE_SIGN_IDENTITY[sdk=iphoneos*]": Apple Distribution
PROVISIONING_PROFILE_SPECIFIER: Sybil AppStore CI
schemes:
Sybil:

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@@ -1,3 +1,3 @@
source "https://rubygems.org"
gem "fastlane", "~> 2.227"
gem "fastlane"

231
ios/Gemfile.lock Normal file
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@@ -0,0 +1,231 @@
GEM
remote: https://rubygems.org/
specs:
CFPropertyList (3.0.9)
abbrev (0.1.2)
addressable (2.9.0)
public_suffix (>= 2.0.2, < 8.0)
artifactory (3.0.17)
atomos (0.1.3)
aws-eventstream (1.3.2)
aws-partitions (1.1109.0)
aws-sdk-core (3.224.1)
aws-eventstream (~> 1, >= 1.3.0)
aws-partitions (~> 1, >= 1.992.0)
aws-sigv4 (~> 1.9)
base64
jmespath (~> 1, >= 1.6.1)
logger
aws-sdk-kms (1.101.0)
aws-sdk-core (~> 3, >= 3.216.0)
aws-sigv4 (~> 1.5)
aws-sdk-s3 (1.188.0)
aws-sdk-core (~> 3, >= 3.224.1)
aws-sdk-kms (~> 1)
aws-sigv4 (~> 1.5)
aws-sigv4 (1.11.0)
aws-eventstream (~> 1, >= 1.0.2)
babosa (1.0.4)
base64 (0.2.0)
claide (1.1.0)
colored (1.2)
colored2 (3.1.2)
commander (4.6.0)
highline (~> 2.0.0)
csv (3.3.5)
declarative (0.0.20)
digest-crc (0.7.0)
rake (>= 12.0.0, < 14.0.0)
domain_name (0.5.20190701)
unf (>= 0.0.5, < 1.0.0)
dotenv (2.8.1)
emoji_regex (3.2.3)
excon (0.109.0)
faraday (1.10.6)
faraday-em_http (~> 1.0)
faraday-em_synchrony (~> 1.0)
faraday-excon (~> 1.1)
faraday-httpclient (~> 1.0)
faraday-multipart (~> 1.0)
faraday-net_http (~> 1.0)
faraday-net_http_persistent (~> 1.0)
faraday-patron (~> 1.0)
faraday-rack (~> 1.0)
faraday-retry (~> 1.0)
ruby2_keywords (>= 0.0.4)
faraday-cookie_jar (0.0.8)
faraday (>= 0.8.0)
http-cookie (>= 1.0.0)
faraday-em_http (1.0.0)
faraday-em_synchrony (1.0.1)
faraday-excon (1.1.0)
faraday-httpclient (1.0.1)
faraday-multipart (1.2.0)
multipart-post (~> 2.0)
faraday-net_http (1.0.2)
faraday-net_http_persistent (1.2.0)
faraday-patron (1.0.0)
faraday-rack (1.0.0)
faraday-retry (1.0.4)
faraday_middleware (1.2.1)
faraday (~> 1.0)
fastimage (2.4.1)
fastlane (2.230.0)
CFPropertyList (>= 2.3, < 4.0.0)
abbrev (~> 0.1.2)
addressable (>= 2.8, < 3.0.0)
artifactory (~> 3.0)
aws-sdk-s3 (~> 1.0)
babosa (>= 1.0.3, < 2.0.0)
base64 (~> 0.2.0)
bundler (>= 1.12.0, < 3.0.0)
colored (~> 1.2)
commander (~> 4.6)
csv (~> 3.3)
dotenv (>= 2.1.1, < 3.0.0)
emoji_regex (>= 0.1, < 4.0)
excon (>= 0.71.0, < 1.0.0)
faraday (~> 1.0)
faraday-cookie_jar (~> 0.0.6)
faraday_middleware (~> 1.0)
fastimage (>= 2.1.0, < 3.0.0)
fastlane-sirp (>= 1.0.0)
gh_inspector (>= 1.1.2, < 2.0.0)
google-apis-androidpublisher_v3 (~> 0.3)
google-apis-playcustomapp_v1 (~> 0.1)
google-cloud-env (>= 1.6.0, < 2.0.0)
google-cloud-storage (~> 1.31)
highline (~> 2.0)
http-cookie (~> 1.0.5)
json (< 3.0.0)
jwt (>= 2.1.0, < 3)
logger (>= 1.6, < 2.0)
mini_magick (>= 4.9.4, < 5.0.0)
multipart-post (>= 2.0.0, < 3.0.0)
mutex_m (~> 0.3.0)
naturally (~> 2.2)
nkf (~> 0.2.0)
optparse (>= 0.1.1, < 1.0.0)
plist (>= 3.1.0, < 4.0.0)
rubyzip (>= 2.0.0, < 3.0.0)
security (= 0.1.5)
simctl (~> 1.6.3)
terminal-notifier (>= 2.0.0, < 3.0.0)
terminal-table (~> 3)
tty-screen (>= 0.6.3, < 1.0.0)
tty-spinner (>= 0.8.0, < 1.0.0)
word_wrap (~> 1.0.0)
xcodeproj (>= 1.13.0, < 2.0.0)
xcpretty (~> 0.4.1)
xcpretty-travis-formatter (>= 0.0.3, < 2.0.0)
fastlane-sirp (1.1.0)
gh_inspector (1.1.3)
google-apis-androidpublisher_v3 (0.54.0)
google-apis-core (>= 0.11.0, < 2.a)
google-apis-core (0.11.3)
addressable (~> 2.5, >= 2.5.1)
googleauth (>= 0.16.2, < 2.a)
httpclient (>= 2.8.1, < 3.a)
mini_mime (~> 1.0)
representable (~> 3.0)
retriable (>= 2.0, < 4.a)
rexml
google-apis-iamcredentials_v1 (0.17.0)
google-apis-core (>= 0.11.0, < 2.a)
google-apis-playcustomapp_v1 (0.13.0)
google-apis-core (>= 0.11.0, < 2.a)
google-apis-storage_v1 (0.29.0)
google-apis-core (>= 0.11.0, < 2.a)
google-cloud-core (1.6.1)
google-cloud-env (>= 1.0, < 3.a)
google-cloud-errors (~> 1.0)
google-cloud-env (1.6.0)
faraday (>= 0.17.3, < 3.0)
google-cloud-errors (1.3.1)
google-cloud-storage (1.45.0)
addressable (~> 2.8)
digest-crc (~> 0.4)
google-apis-iamcredentials_v1 (~> 0.1)
google-apis-storage_v1 (~> 0.29.0)
google-cloud-core (~> 1.6)
googleauth (>= 0.16.2, < 2.a)
mini_mime (~> 1.0)
googleauth (1.8.1)
faraday (>= 0.17.3, < 3.a)
jwt (>= 1.4, < 3.0)
multi_json (~> 1.11)
os (>= 0.9, < 2.0)
signet (>= 0.16, < 2.a)
highline (2.0.3)
http-cookie (1.0.8)
domain_name (~> 0.5)
httpclient (2.9.0)
mutex_m
jmespath (1.6.2)
json (2.7.6)
jwt (2.10.3)
base64
logger (1.7.0)
mini_magick (4.13.2)
mini_mime (1.1.5)
multi_json (1.15.0)
multipart-post (2.4.1)
mutex_m (0.3.0)
nanaimo (0.4.0)
naturally (2.3.0)
nkf (0.2.0)
optparse (0.8.1)
os (1.1.4)
plist (3.7.2)
public_suffix (5.1.1)
rake (13.4.2)
representable (3.2.0)
declarative (< 0.1.0)
trailblazer-option (>= 0.1.1, < 0.2.0)
uber (< 0.2.0)
retriable (3.8.0)
rexml (3.4.4)
rouge (3.28.0)
ruby2_keywords (0.0.5)
rubyzip (2.4.1)
security (0.1.5)
signet (0.18.0)
addressable (~> 2.8)
faraday (>= 0.17.5, < 3.a)
jwt (>= 1.5, < 3.0)
multi_json (~> 1.10)
simctl (1.6.10)
CFPropertyList
naturally
terminal-notifier (2.0.0)
terminal-table (3.0.2)
unicode-display_width (>= 1.1.1, < 3)
trailblazer-option (0.1.2)
tty-cursor (0.7.1)
tty-screen (0.8.2)
tty-spinner (0.9.3)
tty-cursor (~> 0.7)
uber (0.1.0)
unf (0.2.0)
unicode-display_width (2.6.0)
word_wrap (1.0.0)
xcodeproj (1.27.0)
CFPropertyList (>= 2.3.3, < 4.0)
atomos (~> 0.1.3)
claide (>= 1.0.2, < 2.0)
colored2 (~> 3.1)
nanaimo (~> 0.4.0)
rexml (>= 3.3.6, < 4.0)
xcpretty (0.4.1)
rouge (~> 3.28.0)
xcpretty-travis-formatter (1.0.1)
xcpretty (~> 0.2, >= 0.0.7)
PLATFORMS
ruby
DEPENDENCIES
fastlane
BUNDLED WITH
2.5.23

View File

@@ -9,10 +9,23 @@ struct SybilChatTranscriptView: View {
var bottomContentInset: CGFloat = 0
var bottomPinRequestID: Int = 0
@State private var hasTrackedToolCallMessages = false
@State private var knownToolCallMessageIDs: Set<String> = []
private let bottomAnchorID = "sybil-chat-transcript-bottom-anchor"
private var renderItems: [TranscriptRenderItem] {
buildTranscriptRenderItems(from: messages)
}
private var toolCallMessageIDs: Set<String> {
Set(messages.compactMap { $0.toolCallMetadata == nil ? nil : $0.id })
}
private var enteringToolCallMessageIDs: Set<String> {
guard hasTrackedToolCallMessages else { return [] }
return toolCallMessageIDs.subtracting(knownToolCallMessageIDs)
}
private var toolCallMessageIDSignature: String {
toolCallMessageIDs.sorted().joined(separator: "|")
}
var body: some View {
ScrollViewReader { proxy in
@@ -31,7 +44,11 @@ struct SybilChatTranscriptView: View {
MessageBubble(message: message, isSending: isSending)
.frame(maxWidth: .infinity)
case let .toolGroup(id, messages):
ToolCallStackView(groupID: id, messages: messages)
ToolCallStackView(
groupID: id,
messages: messages,
entryAnimationIDs: enteringToolCallMessageIDs
)
.frame(maxWidth: .infinity)
.id(id)
}
@@ -48,8 +65,12 @@ struct SybilChatTranscriptView: View {
.frame(maxWidth: .infinity, alignment: .leading)
.scrollDismissesKeyboard(.interactively)
.onAppear {
syncKnownToolCallMessageIDs()
scrollToBottom(with: proxy, animated: false)
}
.onChange(of: toolCallMessageIDSignature) { _, _ in
syncKnownToolCallMessageIDs()
}
.onChange(of: bottomPinRequestID) { _, _ in
scrollToBottom(with: proxy, animated: true)
}
@@ -67,6 +88,12 @@ struct SybilChatTranscriptView: View {
action()
}
}
private func syncKnownToolCallMessageIDs() {
guard !toolCallMessageIDs.isEmpty else { return }
knownToolCallMessageIDs.formUnion(toolCallMessageIDs)
hasTrackedToolCallMessages = true
}
}
enum TranscriptRenderItem: Identifiable {
@@ -216,6 +243,7 @@ private struct ToolCallStackView: View {
var groupID: String
var messages: [Message]
var entryAnimationIDs: Set<String>
@Environment(\.accessibilityReduceMotion) private var reduceMotion
@State private var isExpanded = false
@@ -262,8 +290,14 @@ private struct ToolCallStackView: View {
let layout = layout(for: index)
let depth = messages.count - index - 1
let isHidden = !isExpanded && depth >= visibleCollapsedLimit
let shouldAnimateEntry = entryAnimationIDs.contains(message.id) && !isHidden
ToolCallStackCard(message: message, cardHeight: cardHeight, compactLayout: true)
ToolCallStackCard(
message: message,
cardHeight: cardHeight,
compactLayout: true,
animateEntry: shouldAnimateEntry
)
.frame(width: cardWidth, height: cardHeight, alignment: .topLeading)
.scaleEffect(layout.scale, anchor: .topLeading)
.opacity(layout.opacity)
@@ -362,10 +396,16 @@ private struct ToolCallStackCard: View {
var message: Message
var cardHeight: CGFloat
var compactLayout: Bool
var animateEntry: Bool
@Environment(\.accessibilityReduceMotion) private var reduceMotion
@State private var entryAnimationArmed = false
@State private var didEnter = false
private var isPreparingEntry: Bool {
(animateEntry || entryAnimationArmed) && !didEnter
}
var body: some View {
Group {
if let metadata = message.toolCallMetadata {
@@ -378,12 +418,17 @@ private struct ToolCallStackCard: View {
}
}
.frame(height: cardHeight, alignment: .top)
.scaleEffect(didEnter ? 1 : 1.025, anchor: .topLeading)
.offset(y: didEnter ? 0 : -8)
.rotation3DEffect(.degrees(didEnter ? 0 : 3), axis: (x: 1, y: 0, z: 0), anchor: .top)
.opacity(didEnter ? 1 : 0.72)
.scaleEffect(isPreparingEntry ? 1.025 : 1, anchor: .topLeading)
.offset(y: isPreparingEntry ? -8 : 0)
.rotation3DEffect(.degrees(isPreparingEntry ? 3 : 0), axis: (x: 1, y: 0, z: 0), anchor: .top)
.opacity(isPreparingEntry ? 0.72 : 1)
.onAppear {
guard !didEnter else { return }
guard !didEnter, !entryAnimationArmed else { return }
guard animateEntry else {
didEnter = true
return
}
entryAnimationArmed = true
if reduceMotion {
didEnter = true
} else {

View File

@@ -179,8 +179,8 @@ enum SybilTheme {
static var toolCallGradient: LinearGradient {
LinearGradient(
colors: [
Color(red: 0.01, green: 0.15, blue: 0.17).opacity(0.70),
Color(red: 0.03, green: 0.09, blue: 0.15).opacity(0.78)
Color(red: 0.01, green: 0.15, blue: 0.17),
Color(red: 0.03, green: 0.09, blue: 0.15)
],
startPoint: .leading,
endPoint: .trailing
@@ -190,8 +190,8 @@ enum SybilTheme {
static var runningToolCallGradient: LinearGradient {
LinearGradient(
colors: [
Color(red: 0.30, green: 0.19, blue: 0.04).opacity(0.72),
Color(red: 0.09, green: 0.05, blue: 0.17).opacity(0.78)
Color(red: 0.30, green: 0.19, blue: 0.04),
Color(red: 0.09, green: 0.05, blue: 0.17)
],
startPoint: .leading,
endPoint: .trailing
@@ -201,8 +201,8 @@ enum SybilTheme {
static var failedToolCallGradient: LinearGradient {
LinearGradient(
colors: [
danger.opacity(0.18),
Color(red: 0.15, green: 0.03, blue: 0.07).opacity(0.72)
Color(red: 0.27, green: 0.04, blue: 0.10),
Color(red: 0.15, green: 0.03, blue: 0.07)
],
startPoint: .leading,
endPoint: .trailing

View File

@@ -1,9 +0,0 @@
require "dotenv"
Dotenv.load(File.expand_path("../.env", __dir__))
app_identifier(ENV.fetch("FASTLANE_APP_IDENTIFIER", "net.buzzert.sybil2"))
team_id(ENV.fetch("FASTLANE_TEAM_ID", "DQQH5H6GBD"))
apple_id(ENV["FASTLANE_USER"]) if ENV["FASTLANE_USER"].to_s.strip.length.positive?
itc_team_id(ENV["FASTLANE_ITC_TEAM_ID"]) if ENV["FASTLANE_ITC_TEAM_ID"].to_s.strip.length.positive?

View File

@@ -1,177 +1,205 @@
require "dotenv"
require "open3"
require "fileutils"
require "shellwords"
require "yaml"
Dotenv.load(File.expand_path("../.env", __dir__))
default_platform(:ios)
APP_IDENTIFIER = ENV.fetch("FASTLANE_APP_IDENTIFIER", "net.buzzert.sybil2")
TEAM_ID = ENV.fetch("FASTLANE_TEAM_ID", "DQQH5H6GBD")
APP_STORE_APPLE_ID = ENV.fetch("SYBIL_APP_STORE_APPLE_ID", "6759442828")
PROVIDER_PUBLIC_ID = ENV.fetch("SYBIL_PROVIDER_PUBLIC_ID", "c043d167-ad88-4036-84ea-76c223f1b1b2")
APP_IDENTIFIER = "net.buzzert.sybil2"
SCHEME = "Sybil"
TEAM_ID = "DQQH5H6GBD"
PROFILE_NAME = "Sybil AppStore CI"
SIGNING_IDENTITY = "Apple Distribution: James Magahern (DQQH5H6GBD)"
CI_KEYCHAIN_NAME = "sybil_ci_keychain"
CI_KEYCHAIN_PASSWORD = "sybil-ci-keychain-password"
IOS_ROOT = File.expand_path("..", __dir__)
PROJECT_FILE = File.join(IOS_ROOT, "Sybil.xcodeproj")
PROJECT_SPEC = File.join(IOS_ROOT, "project.yml")
APP_SPEC = File.join(IOS_ROOT, "Apps/Sybil/project.yml")
SCHEME = "Sybil"
TARGET = "SybilApp"
CI_KEYCHAIN_PATH = File.join(File.expand_path("~/Library/Keychains"), CI_KEYCHAIN_NAME)
CI_KEYCHAIN_DB_PATH = "#{CI_KEYCHAIN_PATH}-db"
LOGIN_KEYCHAIN_PATH = File.expand_path("~/Library/Keychains/login.keychain")
LOGIN_KEYCHAIN_DB_PATH = "#{LOGIN_KEYCHAIN_PATH}-db"
def present?(value)
!value.to_s.strip.empty?
end
def capture(command)
stdout, stderr, status = Open3.capture3(command)
return stdout.strip if status.success?
def release_version
tag = ENV["SYBIL_VERSION_TAG"].to_s
tag = ENV["GITHUB_REF_NAME"].to_s if !present?(tag)
tag = ENV["GITHUB_REF"].to_s.sub(%r{\Arefs/tags/}, "") if !present?(tag)
tag = sh("git describe --tags --abbrev=0").strip if !present?(tag)
version = tag.sub(%r{\Arelease/}, "").sub(/\Av/, "")
UI.user_error!("Command failed: #{command}\n#{stderr.strip}")
end
def app_project_settings
YAML.safe_load(File.read(APP_SPEC)).fetch("targets").fetch(TARGET).fetch("settings").fetch("base")
end
def local_marketing_version
app_project_settings.fetch("MARKETING_VERSION").to_s
end
def local_build_number
app_project_settings.fetch("CURRENT_PROJECT_VERSION").to_i
end
def normalize_version_tag(tag)
version = tag.to_s.strip.sub(/\Av/, "")
unless version.match?(/\A\d+\.\d+(\.\d+)?\z/)
UI.user_error!("Release tag #{tag.inspect} must look like v1.10 or v1.10.0")
unless version.match?(/\A\d+\.\d+\.\d+\z/)
UI.user_error!("Release tag must look like v1.2.3; got #{tag.inspect}")
end
version
end
def release_version
tag = ENV["SYBIL_VERSION_TAG"]
tag = capture("git describe --tags --abbrev=0") unless present?(tag)
normalize_version_tag(tag)
def ci?
present?(ENV["CI"])
end
def xcode_build_setting(key, value)
"#{key}=#{value.to_s.shellescape}"
end
def app_store_connect_key_options
key_id = ENV["APP_STORE_CONNECT_API_KEY_ID"]
issuer_id = ENV["APP_STORE_CONNECT_API_ISSUER_ID"]
return nil unless present?(key_id) && present?(issuer_id)
key_path = ENV["APP_STORE_CONNECT_API_KEY_PATH"]
key_content = ENV["APP_STORE_CONNECT_API_KEY_CONTENT"]
if present?(key_path)
{
key_id: key_id,
issuer_id: issuer_id,
key_filepath: key_path
}
elsif present?(key_content)
{
key_id: key_id,
issuer_id: issuer_id,
key_content: key_content,
is_key_content_base64: ENV["APP_STORE_CONNECT_API_KEY_CONTENT_BASE64"].to_s == "true"
}
end
def ci_keychain_path
File.file?(CI_KEYCHAIN_DB_PATH) ? CI_KEYCHAIN_DB_PATH : CI_KEYCHAIN_PATH
end
platform :ios do
desc "Show the version Fastlane will stamp into the next TestFlight archive"
lane :version do
UI.message("Git tag version: #{release_version}")
UI.message("Checked-in app version: #{local_marketing_version}")
UI.message("Checked-in build number: #{local_build_number}")
private_lane :app_store_api_key do
app_store_connect_api_key(
key_id: ENV.fetch("APP_STORE_CONNECT_KEY_ID"),
issuer_id: ENV.fetch("APP_STORE_CONNECT_ISSUER_ID"),
key_content: ENV.fetch("APP_STORE_CONNECT_KEY_CONTENT"),
is_key_content_base64: true
)
end
desc "Build Sybil and upload it to TestFlight"
private_lane :setup_ci_signing do
next unless ci?
FileUtils.mkdir_p(File.dirname(CI_KEYCHAIN_PATH))
sh("security delete-keychain #{CI_KEYCHAIN_PATH.shellescape} || true", log: false)
FileUtils.rm_f(CI_KEYCHAIN_PATH)
FileUtils.rm_f(CI_KEYCHAIN_DB_PATH)
create_keychain(
path: CI_KEYCHAIN_PATH,
password: CI_KEYCHAIN_PASSWORD,
default_keychain: false,
unlock: true,
timeout: 3600,
lock_when_sleeps: true,
add_to_search_list: false
)
sh("security default-keychain -d user -s #{CI_KEYCHAIN_PATH.shellescape}", log: false)
sh("security list-keychains -d user -s #{ci_keychain_path.shellescape}", log: false)
sh("security list-keychains -d dynamic -s #{ci_keychain_path.shellescape} || true", log: false)
sh("security list-keychains -d common -s #{ci_keychain_path.shellescape} || true", log: false)
ENV["MATCH_KEYCHAIN_NAME"] = CI_KEYCHAIN_PATH
ENV["MATCH_KEYCHAIN_PASSWORD"] = CI_KEYCHAIN_PASSWORD
ENV["MATCH_READONLY"] = "true"
end
private_lane :cleanup_ci_signing do
next unless ci?
if File.file?(LOGIN_KEYCHAIN_DB_PATH) || File.file?(LOGIN_KEYCHAIN_PATH)
sh("security default-keychain -d user -s #{LOGIN_KEYCHAIN_PATH.shellescape} || true", log: false)
sh("security list-keychains -d user -s #{LOGIN_KEYCHAIN_DB_PATH.shellescape} || true", log: false)
end
sh("security delete-keychain #{ci_keychain_path.shellescape} || true", log: false)
FileUtils.rm_f(CI_KEYCHAIN_PATH)
FileUtils.rm_f(CI_KEYCHAIN_DB_PATH)
rescue => error
UI.message("Unable to delete temporary CI keychain: #{error.message}")
ensure
ENV.delete("MATCH_KEYCHAIN_NAME")
ENV.delete("MATCH_KEYCHAIN_PASSWORD")
ENV.delete("MATCH_READONLY")
end
private_lane :sync_signing do |options|
match_options = {
type: "appstore",
readonly: options.fetch(:readonly),
app_identifier: APP_IDENTIFIER,
team_id: TEAM_ID,
profile_name: PROFILE_NAME,
git_url: ENV.fetch("MATCH_GIT_URL"),
git_branch: "master",
git_full_name: "Sybil Release Bot",
git_user_email: "james.magahern@me.com",
api_key: options.fetch(:api_key)
}
match_options[:keychain_name] = ENV["MATCH_KEYCHAIN_NAME"] if present?(ENV["MATCH_KEYCHAIN_NAME"])
match_options[:keychain_password] = ENV["MATCH_KEYCHAIN_PASSWORD"] if ENV.key?("MATCH_KEYCHAIN_PASSWORD")
match(match_options)
end
private_lane :verify_ci_signing do
next unless ci?
if File.file?(ci_keychain_path)
password = ENV.fetch("MATCH_KEYCHAIN_PASSWORD", "")
sh("security unlock-keychain -p #{password.shellescape} #{ci_keychain_path.shellescape}", log: false)
sh("security set-key-partition-list -S apple-tool:,apple:,codesign: -s -k #{password.shellescape} #{ci_keychain_path.shellescape}", log: false)
end
identities = sh("security find-identity -v -p codesigning #{ci_keychain_path.shellescape}", log: false)
UI.message(identities)
unless identities.include?(SIGNING_IDENTITY)
UI.user_error!("The CI keychain search list does not contain #{SIGNING_IDENTITY}")
end
end
desc "Create or update match signing assets"
lane :setup_signing do
sync_signing(api_key: app_store_api_key, readonly: false)
end
desc "Build and upload to TestFlight"
lane :beta do
version = release_version
build_number = ENV["SYBIL_BUILD_NUMBER"].to_s
api_key = nil
setup_ci_signing
if app_store_connect_key_options
api_key = app_store_connect_api_key(app_store_connect_key_options)
end
unless present?(build_number)
build_number = (local_build_number + 1).to_s
if api_key
begin
latest = latest_testflight_build_number(
app_identifier: APP_IDENTIFIER,
version: version,
api_key: api_key,
initial_build_number: local_build_number
).to_i
build_number = [latest + 1, local_build_number + 1].max.to_s
rescue StandardError => e
UI.important("Could not look up TestFlight build number: #{e.message}")
UI.important("Using checked-in build number + 1: #{build_number}")
end
end
end
UI.user_error!("Build number must be a positive integer") unless build_number.match?(/\A[1-9]\d*\z/)
api_key = app_store_api_key
sh("xcodegen --spec #{PROJECT_SPEC.shellescape}")
xcode_args = [
"-allowProvisioningUpdates",
xcode_build_setting("MARKETING_VERSION", version),
xcode_build_setting("CURRENT_PROJECT_VERSION", build_number)
].join(" ")
increment_version_number(
version_number: release_version,
xcodeproj: PROJECT_FILE
)
ipa_path = build_app(
latest_build_number = latest_testflight_build_number(
app_identifier: APP_IDENTIFIER,
api_key: api_key,
initial_build_number: 0
)
increment_build_number(
build_number: latest_build_number + 1,
xcodeproj: PROJECT_FILE
)
sync_signing(api_key: api_key, readonly: true)
verify_ci_signing
xcargs = [
"DEVELOPMENT_TEAM=#{TEAM_ID.shellescape}",
"CODE_SIGN_STYLE=Manual",
"CODE_SIGN_IDENTITY=Apple\\ Distribution",
"PROVISIONING_PROFILE_SPECIFIER=#{PROFILE_NAME.shellescape}"
]
if ci?
xcargs << "CODE_SIGN_KEYCHAIN=#{ci_keychain_path.shellescape}"
xcargs << "OTHER_CODE_SIGN_FLAGS=#{("--keychain #{ci_keychain_path}").shellescape}"
end
build_app(
project: PROJECT_FILE,
scheme: SCHEME,
clean: true,
sdk: "iphoneos",
export_method: "app-store",
output_directory: File.join(IOS_ROOT, "build/fastlane"),
output_name: "Sybil-#{version}-#{build_number}.ipa",
xcargs: xcode_args,
export_xcargs: "-allowProvisioningUpdates",
codesigning_identity: "Apple Distribution",
xcargs: xcargs.join(" "),
export_options: {
method: "app-store-connect",
destination: "export",
signingStyle: "automatic",
signingStyle: "manual",
teamID: TEAM_ID,
manageAppVersionAndBuildNumber: false,
uploadSymbols: true,
stripSwiftSymbols: true
provisioningProfiles: {
APP_IDENTIFIER => PROFILE_NAME
}
}
)
ipa_path ||= lane_context[SharedValues::IPA_OUTPUT_PATH]
UI.user_error!("IPA export failed; no IPA path was returned") unless present?(ipa_path) && File.exist?(ipa_path)
password = ENV["FASTLANE_APPLE_APPLICATION_SPECIFIC_PASSWORD"]
UI.user_error!("FASTLANE_USER is required for altool upload") unless present?(ENV["FASTLANE_USER"])
UI.user_error!("FASTLANE_APPLE_APPLICATION_SPECIFIC_PASSWORD is required for altool upload") unless present?(password)
UI.user_error!("SYBIL_APP_STORE_APPLE_ID is required for altool upload") unless present?(APP_STORE_APPLE_ID)
UI.user_error!("SYBIL_PROVIDER_PUBLIC_ID is required for altool upload") unless present?(PROVIDER_PUBLIC_ID)
ENV["ITMS_TRANSPORTER_PASSWORD"] = password
sh([
"xcrun altool",
"--upload-package #{ipa_path.shellescape}",
"--platform ios",
"--apple-id #{APP_STORE_APPLE_ID.shellescape}",
"--bundle-id #{APP_IDENTIFIER.shellescape}",
"--bundle-version #{build_number.shellescape}",
"--bundle-short-version-string #{version.shellescape}",
"--provider-public-id #{PROVIDER_PUBLIC_ID.shellescape}",
"--username #{ENV.fetch("FASTLANE_USER").shellescape}",
"--password @env:ITMS_TRANSPORTER_PASSWORD",
"--show-progress"
].join(" "))
upload_to_testflight(
api_key: api_key,
skip_waiting_for_build_processing: true
)
ensure
cleanup_ci_signing
end
end

View File

@@ -1,40 +0,0 @@
fastlane documentation
----
# Installation
Make sure you have the latest version of the Xcode command line tools installed:
```sh
xcode-select --install
```
For _fastlane_ installation instructions, see [Installing _fastlane_](https://docs.fastlane.tools/#installing-fastlane)
# Available Actions
## iOS
### ios version
```sh
[bundle exec] fastlane ios version
```
Show the version Fastlane will stamp into the next TestFlight archive
### ios beta
```sh
[bundle exec] fastlane ios beta
```
Build Sybil and upload it to TestFlight
----
This README.md is auto-generated and will be re-generated every time [_fastlane_](https://fastlane.tools) is run.
More information about _fastlane_ can be found on [fastlane.tools](https://fastlane.tools).
The documentation of _fastlane_ can be found on [docs.fastlane.tools](https://docs.fastlane.tools).

View File

@@ -4,20 +4,14 @@ import os from "node:os";
import path from "node:path";
import { promisify } from "node:util";
import { convert as htmlToText } from "html-to-text";
import type OpenAI from "openai";
import { z } from "zod";
import { buildBrowserLikeNavigationHeaders } from "../browser-fetch-headers.js";
import { env } from "../env.js";
import { exaClient } from "../search/exa.js";
import { searchSearxng } from "../search/searxng.js";
import {
buildOpenAIConversationMessage,
buildOpenAIResponsesInputMessage,
buildSystemPromptAugmentationMessage,
} from "./message-content.js";
import type { ChatMessage } from "./types.js";
const MAX_TOOL_ROUNDS = env.CHAT_MAX_TOOL_ROUNDS;
export const MAX_TOOL_ROUNDS = env.CHAT_MAX_TOOL_ROUNDS;
const DEFAULT_WEB_RESULTS = 5;
const MAX_WEB_RESULTS = 10;
const DEFAULT_FETCH_MAX_CHARACTERS = 12_000;
@@ -30,7 +24,7 @@ const MAX_SHELL_COMMAND_CHARACTERS = 20_000;
const DEFAULT_SHELL_MAX_OUTPUT_CHARACTERS = 24_000;
const MAX_SHELL_MAX_OUTPUT_CHARACTERS = 80_000;
const REMOTE_EXEC_MAX_BUFFER_BYTES = 1_000_000;
const MAX_DANGLING_TOOL_INTENT_RETRIES = 1;
export const MAX_DANGLING_TOOL_INTENT_RETRIES = 1;
const execFileAsync = promisify(execFile);
@@ -220,7 +214,7 @@ function getEnabledToolSet(params: Pick<ToolAwareCompletionParams, "enabledTools
return new Set(normalizeEnabledChatTools(params.enabledTools));
}
function getEnabledChatTools(params: Pick<ToolAwareCompletionParams, "enabledTools">) {
export function getEnabledChatTools(params: Pick<ToolAwareCompletionParams, "enabledTools">) {
const enabled = getEnabledToolSet(params);
return CHAT_TOOLS.filter((tool) => {
const name = getToolName(tool);
@@ -228,19 +222,6 @@ function getEnabledChatTools(params: Pick<ToolAwareCompletionParams, "enabledToo
});
}
function toResponsesChatTools(tools: any[]) {
return tools.map((tool) => {
if (tool?.type !== "function") return tool;
return {
type: "function",
name: tool.function.name,
description: tool.function.description,
parameters: tool.function.parameters,
strict: false,
};
});
}
export const CHAT_TOOL_SYSTEM_PROMPT =
"You can use tools to gather up-to-date web information when needed. " +
"Use web_search for discovery and recent facts, and fetch_url to read the full content of a specific page. " +
@@ -254,18 +235,18 @@ export const CHAT_TOOL_SYSTEM_PROMPT =
: "") +
"Do not fabricate tool outputs; reason only from provided tool results.";
type ToolRunOutcome = {
export type ToolRunOutcome = {
ok: boolean;
[key: string]: unknown;
};
type ToolAwareUsage = {
export type ToolAwareUsage = {
inputTokens?: number;
outputTokens?: number;
totalTokens?: number;
};
type ToolAwareCompletionResult = {
export type ToolAwareCompletionResult = {
text: string;
usage?: ToolAwareUsage;
raw: unknown;
@@ -277,8 +258,8 @@ export type ToolAwareStreamingEvent =
| { type: "tool_call"; event: ToolExecutionEvent }
| { type: "done"; result: ToolAwareCompletionResult };
type ToolAwareCompletionParams = {
client: OpenAI;
export type ToolAwareCompletionParams = {
client: any;
model: string;
messages: ChatMessage[];
enabledTools?: string[];
@@ -440,7 +421,7 @@ function extractHtmlTitle(html: string) {
);
}
function buildChatToolSystemPrompt(params: Pick<ToolAwareCompletionParams, "enabledTools">) {
export function buildChatToolSystemPrompt(params: Pick<ToolAwareCompletionParams, "enabledTools">) {
const enabled = getEnabledToolSet(params);
return (
"You can use tools to gather up-to-date web information when needed. " +
@@ -458,22 +439,6 @@ function buildChatToolSystemPrompt(params: Pick<ToolAwareCompletionParams, "enab
);
}
function normalizeIncomingMessages(messages: ChatMessage[], userLocation?: string, params: Pick<ToolAwareCompletionParams, "enabledTools"> = {}) {
const normalized = messages.map((message) => buildOpenAIConversationMessage(message));
return [{ role: "system", content: buildChatToolSystemPrompt(params) }, buildSystemPromptAugmentationMessage(userLocation), ...normalized];
}
function normalizePlainIncomingMessages(messages: ChatMessage[], userLocation?: string) {
return [buildSystemPromptAugmentationMessage(userLocation), ...messages.map((message) => buildOpenAIConversationMessage(message))];
}
function normalizeIncomingResponsesInput(messages: ChatMessage[], userLocation?: string, params: Pick<ToolAwareCompletionParams, "enabledTools"> = {}) {
const normalized = messages.map((message) => buildOpenAIResponsesInputMessage(message));
return [{ role: "system", content: buildChatToolSystemPrompt(params) }, buildSystemPromptAugmentationMessage(userLocation), ...normalized];
}
async function runExaWebSearchTool(args: WebSearchArgs): Promise<ToolRunOutcome> {
const exa = exaClient();
const response = await exa.search(args.query, {
@@ -842,7 +807,7 @@ async function executeTool(name: string, args: unknown): Promise<ToolRunOutcome>
return { ok: false, error: `Unknown tool: ${name}` };
}
function parseToolArgs(raw: unknown) {
export function parseToolArgs(raw: unknown) {
if (typeof raw !== "string") return {};
const trimmed = raw.trim();
if (!trimmed) return {};
@@ -871,7 +836,7 @@ function buildEventArgs(name: string, args: Record<string, unknown>) {
return args;
}
function looksLikeDanglingToolIntent(text: string) {
export function looksLikeDanglingToolIntent(text: string) {
const normalized = text
.toLowerCase()
.replace(/[`*_>#-]/g, " ")
@@ -887,7 +852,7 @@ function looksLikeDanglingToolIntent(text: string) {
);
}
function appendDanglingToolIntentCorrection(conversation: any[], text: string) {
export function appendDanglingToolIntentCorrection(conversation: any[], text: string) {
conversation.push({ role: "assistant", content: text });
conversation.push({
role: "system",
@@ -896,7 +861,7 @@ function appendDanglingToolIntentCorrection(conversation: any[], text: string) {
});
}
function mergeUsage(acc: Required<ToolAwareUsage>, usage: any) {
export function mergeUsage(acc: Required<ToolAwareUsage>, usage: any) {
if (!usage) return false;
acc.inputTokens += usage.prompt_tokens ?? 0;
acc.outputTokens += usage.completion_tokens ?? 0;
@@ -904,79 +869,19 @@ function mergeUsage(acc: Required<ToolAwareUsage>, usage: any) {
return true;
}
function mergeResponsesUsage(acc: Required<ToolAwareUsage>, usage: any) {
if (!usage) return false;
acc.inputTokens += usage.input_tokens ?? 0;
acc.outputTokens += usage.output_tokens ?? 0;
acc.totalTokens += usage.total_tokens ?? 0;
return true;
}
function getResponseOutputItems(response: any) {
return Array.isArray(response?.output) ? response.output : [];
}
function extractResponsesText(response: any, fallback = "") {
if (typeof response?.output_text === "string") return response.output_text;
const parts: string[] = [];
for (const item of getResponseOutputItems(response)) {
if (item?.type !== "message" || !Array.isArray(item.content)) continue;
for (const content of item.content) {
if (content?.type === "output_text" && typeof content.text === "string") {
parts.push(content.text);
} else if (content?.type === "refusal" && typeof content.refusal === "string") {
parts.push(content.refusal);
}
}
}
return parts.join("") || fallback;
}
function extractChatCompletionContent(message: any) {
if (typeof message?.content === "string") return message.content;
if (!Array.isArray(message?.content)) return "";
return message.content
.map((part: any) => {
if (typeof part === "string") return part;
if (typeof part?.text === "string") return part.text;
if (typeof part?.content === "string") return part.content;
return "";
})
.join("");
}
function getUnstreamedText(finalText: string, streamedText: string) {
export function getUnstreamedText(finalText: string, streamedText: string) {
if (!finalText) return "";
if (!streamedText) return finalText;
return finalText.startsWith(streamedText) ? finalText.slice(streamedText.length) : "";
}
function getResponseFailureMessage(response: any) {
if (response?.status !== "failed" && response?.status !== "incomplete") return null;
const errorMessage = typeof response?.error?.message === "string" ? response.error.message : null;
const incompleteReason = typeof response?.incomplete_details?.reason === "string" ? response.incomplete_details.reason : null;
return errorMessage ?? (incompleteReason ? `Response incomplete: ${incompleteReason}` : `Response ${response.status}.`);
}
function normalizeResponsesToolCalls(outputItems: any[], round: number): NormalizedToolCall[] {
return outputItems
.filter((item) => item?.type === "function_call")
.map((call: any, index: number) => ({
id: call.call_id ?? call.id ?? `tool_call_${round}_${index}`,
name: call.name ?? "unknown_tool",
arguments: call.arguments ?? "{}",
}));
}
type NormalizedToolCall = {
export type NormalizedToolCall = {
id: string;
name: string;
arguments: string;
};
function normalizeModelToolCalls(toolCalls: any[], round: number): NormalizedToolCall[] {
export function normalizeModelToolCalls(toolCalls: any[], round: number): NormalizedToolCall[] {
return toolCalls.map((call: any, index: number) => ({
id: call?.id ?? `tool_call_${round}_${index}`,
name: call?.function?.name ?? "unknown_tool",
@@ -984,7 +889,7 @@ function normalizeModelToolCalls(toolCalls: any[], round: number): NormalizedToo
}));
}
type PreparedToolCallExecution = {
export type PreparedToolCallExecution = {
startedAtMs: number;
startedAt: string;
parsedArgs: Record<string, unknown>;
@@ -992,7 +897,7 @@ type PreparedToolCallExecution = {
parseError?: unknown;
};
function prepareToolCallExecution(call: NormalizedToolCall): { event: ToolExecutionEvent; execution: PreparedToolCallExecution } {
export function prepareToolCallExecution(call: NormalizedToolCall): { event: ToolExecutionEvent; execution: PreparedToolCallExecution } {
const startedAtMs = Date.now();
const startedAt = new Date(startedAtMs).toISOString();
let parsedArgs: Record<string, unknown> = {};
@@ -1024,7 +929,7 @@ function prepareToolCallExecution(call: NormalizedToolCall): { event: ToolExecut
};
}
async function executeToolCallAndBuildEvent(
export async function executeToolCallAndBuildEvent(
call: NormalizedToolCall,
execution: PreparedToolCallExecution,
params: ToolAwareCompletionParams
@@ -1068,488 +973,3 @@ async function executeToolCallAndBuildEvent(
return { event, toolResult };
}
export async function runToolAwareOpenAIChat(params: ToolAwareCompletionParams): Promise<ToolAwareCompletionResult> {
const enabledTools = getEnabledChatTools(params);
const input: any[] = normalizeIncomingResponsesInput(params.messages, params.userLocation, params);
const rawResponses: unknown[] = [];
const toolEvents: ToolExecutionEvent[] = [];
const usageAcc: Required<ToolAwareUsage> = { inputTokens: 0, outputTokens: 0, totalTokens: 0 };
let sawUsage = false;
let totalToolCalls = 0;
let danglingToolIntentRetries = 0;
for (let round = 0; round < MAX_TOOL_ROUNDS; round += 1) {
const response = await params.client.responses.create({
model: params.model,
input,
temperature: params.temperature,
max_output_tokens: params.maxTokens,
tools: toResponsesChatTools(enabledTools),
tool_choice: "auto",
parallel_tool_calls: true,
// Tool loops pass response output items back as input; reasoning items need persistence.
store: true,
} as any);
rawResponses.push(response);
sawUsage = mergeResponsesUsage(usageAcc, response?.usage) || sawUsage;
const failureMessage = getResponseFailureMessage(response);
if (failureMessage) {
throw new Error(failureMessage);
}
const outputItems = getResponseOutputItems(response);
const normalizedToolCalls = normalizeResponsesToolCalls(outputItems, round);
if (!normalizedToolCalls.length) {
const text = extractResponsesText(response);
if (danglingToolIntentRetries < MAX_DANGLING_TOOL_INTENT_RETRIES && looksLikeDanglingToolIntent(text)) {
danglingToolIntentRetries += 1;
appendDanglingToolIntentCorrection(input, text);
continue;
}
return {
text,
usage: sawUsage ? usageAcc : undefined,
raw: { responses: rawResponses, toolCallsUsed: totalToolCalls, api: "responses" },
toolEvents,
};
}
totalToolCalls += normalizedToolCalls.length;
input.push(...outputItems);
for (const call of normalizedToolCalls) {
const { execution } = prepareToolCallExecution(call);
const { event, toolResult } = await executeToolCallAndBuildEvent(call, execution, params);
toolEvents.push(event);
input.push({
type: "function_call_output",
call_id: call.id,
output: JSON.stringify(toolResult),
});
}
}
return {
text: "I reached the tool-call limit while gathering information. Please narrow the request and try again.",
usage: sawUsage ? usageAcc : undefined,
raw: { responses: rawResponses, toolCallsUsed: totalToolCalls, toolCallLimitReached: true, api: "responses" },
toolEvents,
};
}
export async function runToolAwareChatCompletions(params: ToolAwareCompletionParams): Promise<ToolAwareCompletionResult> {
const enabledTools = getEnabledChatTools(params);
const conversation: any[] = normalizeIncomingMessages(params.messages, params.userLocation, params);
const rawResponses: unknown[] = [];
const toolEvents: ToolExecutionEvent[] = [];
const usageAcc: Required<ToolAwareUsage> = { inputTokens: 0, outputTokens: 0, totalTokens: 0 };
let sawUsage = false;
let totalToolCalls = 0;
let danglingToolIntentRetries = 0;
for (let round = 0; round < MAX_TOOL_ROUNDS; round += 1) {
const completion = await params.client.chat.completions.create({
model: params.model,
messages: conversation,
temperature: params.temperature,
max_tokens: params.maxTokens,
tools: enabledTools,
tool_choice: "auto",
} as any);
rawResponses.push(completion);
sawUsage = mergeUsage(usageAcc, completion?.usage) || sawUsage;
const message = completion?.choices?.[0]?.message;
if (!message) {
return {
text: "",
usage: sawUsage ? usageAcc : undefined,
raw: { responses: rawResponses, toolCallsUsed: totalToolCalls, missingMessage: true },
toolEvents,
};
}
const toolCalls = Array.isArray(message.tool_calls) ? message.tool_calls : [];
if (!toolCalls.length) {
const text = typeof message.content === "string" ? message.content : "";
if (danglingToolIntentRetries < MAX_DANGLING_TOOL_INTENT_RETRIES && looksLikeDanglingToolIntent(text)) {
danglingToolIntentRetries += 1;
appendDanglingToolIntentCorrection(conversation, text);
continue;
}
return {
text,
usage: sawUsage ? usageAcc : undefined,
raw: { responses: rawResponses, toolCallsUsed: totalToolCalls },
toolEvents,
};
}
const normalizedToolCalls = normalizeModelToolCalls(toolCalls, round);
totalToolCalls += normalizedToolCalls.length;
const assistantToolCallMessage: any = {
role: "assistant",
tool_calls: normalizedToolCalls.map((call) => ({
id: call.id,
type: "function",
function: {
name: call.name,
arguments: call.arguments,
},
})),
};
if (typeof message.content === "string" && message.content.length) {
assistantToolCallMessage.content = message.content;
}
conversation.push(assistantToolCallMessage);
for (const call of normalizedToolCalls) {
const { execution } = prepareToolCallExecution(call);
const { event, toolResult } = await executeToolCallAndBuildEvent(call, execution, params);
toolEvents.push(event);
conversation.push({
role: "tool",
tool_call_id: call.id,
content: JSON.stringify(toolResult),
});
}
}
return {
text: "I reached the tool-call limit while gathering information. Please narrow the request and try again.",
usage: sawUsage ? usageAcc : undefined,
raw: { responses: rawResponses, toolCallsUsed: totalToolCalls, toolCallLimitReached: true },
toolEvents,
};
}
export async function runPlainChatCompletions(params: ToolAwareCompletionParams): Promise<ToolAwareCompletionResult> {
const completion = await params.client.chat.completions.create({
model: params.model,
messages: normalizePlainIncomingMessages(params.messages, params.userLocation),
temperature: params.temperature,
max_tokens: params.maxTokens,
} as any);
const usageAcc: Required<ToolAwareUsage> = { inputTokens: 0, outputTokens: 0, totalTokens: 0 };
const sawUsage = mergeUsage(usageAcc, completion?.usage);
const message = completion?.choices?.[0]?.message;
return {
text: extractChatCompletionContent(message),
usage: sawUsage ? usageAcc : undefined,
raw: { response: completion, api: "chat.completions" },
toolEvents: [],
};
}
export async function* runToolAwareOpenAIChatStream(
params: ToolAwareCompletionParams
): AsyncGenerator<ToolAwareStreamingEvent> {
const enabledTools = getEnabledChatTools(params);
const input: any[] = normalizeIncomingResponsesInput(params.messages, params.userLocation, params);
const rawResponses: unknown[] = [];
const toolEvents: ToolExecutionEvent[] = [];
const usageAcc: Required<ToolAwareUsage> = { inputTokens: 0, outputTokens: 0, totalTokens: 0 };
let sawUsage = false;
let totalToolCalls = 0;
let danglingToolIntentRetries = 0;
for (let round = 0; round < MAX_TOOL_ROUNDS; round += 1) {
const stream = await params.client.responses.create({
model: params.model,
input,
temperature: params.temperature,
max_output_tokens: params.maxTokens,
tools: toResponsesChatTools(enabledTools),
tool_choice: "auto",
parallel_tool_calls: true,
// Tool loops pass response output items back as input; reasoning items need persistence.
store: true,
stream: true,
} as any);
let roundText = "";
let streamedRoundText = "";
let roundHasToolCalls = false;
let canStreamRoundText = false;
let completedResponse: any | null = null;
const completedOutputItems: any[] = [];
for await (const event of stream as any as AsyncIterable<any>) {
rawResponses.push(event);
if (event?.type === "response.output_text.delta" && typeof event.delta === "string") {
roundText += event.delta;
if (canStreamRoundText && !roundHasToolCalls && event.delta.length) {
streamedRoundText += event.delta;
yield { type: "delta", text: event.delta };
}
} else if (event?.type === "response.output_item.added" && event.item) {
if (event.item.type === "function_call") {
roundHasToolCalls = true;
canStreamRoundText = false;
} else if (event.item.type === "message" && !roundHasToolCalls) {
canStreamRoundText = true;
}
} else if (event?.type === "response.output_item.done" && event.item) {
completedOutputItems[event.output_index ?? completedOutputItems.length] = event.item;
if (event.item.type === "function_call") {
roundHasToolCalls = true;
canStreamRoundText = false;
}
} else if (event?.type === "response.completed") {
completedResponse = event.response;
sawUsage = mergeResponsesUsage(usageAcc, event.response?.usage) || sawUsage;
} else if (event?.type === "response.failed" || event?.type === "response.incomplete") {
completedResponse = event.response;
sawUsage = mergeResponsesUsage(usageAcc, event.response?.usage) || sawUsage;
} else if (event?.type === "error") {
throw new Error(event.message ?? "OpenAI Responses stream failed.");
}
}
const failureMessage = getResponseFailureMessage(completedResponse);
if (failureMessage) {
throw new Error(failureMessage);
}
const outputItems = getResponseOutputItems(completedResponse);
const responseOutputItems = outputItems.length ? outputItems : completedOutputItems.filter(Boolean);
const normalizedToolCalls = normalizeResponsesToolCalls(responseOutputItems, round);
if (!normalizedToolCalls.length) {
const text = extractResponsesText(completedResponse, roundText);
if (
!streamedRoundText &&
danglingToolIntentRetries < MAX_DANGLING_TOOL_INTENT_RETRIES &&
looksLikeDanglingToolIntent(text)
) {
danglingToolIntentRetries += 1;
appendDanglingToolIntentCorrection(input, text);
continue;
}
const unstreamedText = getUnstreamedText(text, streamedRoundText);
if (unstreamedText) {
yield { type: "delta", text: unstreamedText };
}
yield {
type: "done",
result: {
text,
usage: sawUsage ? usageAcc : undefined,
raw: { streamed: true, responses: rawResponses, toolCallsUsed: totalToolCalls, api: "responses" },
toolEvents,
},
};
return;
}
totalToolCalls += normalizedToolCalls.length;
input.push(...responseOutputItems);
for (const call of normalizedToolCalls) {
const { event: initiatedEvent, execution } = prepareToolCallExecution(call);
yield { type: "tool_call", event: initiatedEvent };
const { event, toolResult } = await executeToolCallAndBuildEvent(call, execution, params);
toolEvents.push(event);
yield { type: "tool_call", event };
input.push({
type: "function_call_output",
call_id: call.id,
output: JSON.stringify(toolResult),
});
}
}
yield {
type: "done",
result: {
text: "I reached the tool-call limit while gathering information. Please narrow the request and try again.",
usage: sawUsage ? usageAcc : undefined,
raw: { streamed: true, responses: rawResponses, toolCallsUsed: totalToolCalls, toolCallLimitReached: true, api: "responses" },
toolEvents,
},
};
}
export async function* runToolAwareChatCompletionsStream(
params: ToolAwareCompletionParams
): AsyncGenerator<ToolAwareStreamingEvent> {
const enabledTools = getEnabledChatTools(params);
const conversation: any[] = normalizeIncomingMessages(params.messages, params.userLocation, params);
const rawResponses: unknown[] = [];
const toolEvents: ToolExecutionEvent[] = [];
const usageAcc: Required<ToolAwareUsage> = { inputTokens: 0, outputTokens: 0, totalTokens: 0 };
let sawUsage = false;
let totalToolCalls = 0;
let danglingToolIntentRetries = 0;
for (let round = 0; round < MAX_TOOL_ROUNDS; round += 1) {
const stream = await params.client.chat.completions.create({
model: params.model,
messages: conversation,
temperature: params.temperature,
max_tokens: params.maxTokens,
tools: enabledTools,
tool_choice: "auto",
stream: true,
stream_options: { include_usage: true },
} as any);
let roundText = "";
let streamedRoundText = "";
let roundHasToolCalls = false;
const roundToolCalls = new Map<number, { id?: string; name?: string; arguments: string }>();
for await (const chunk of stream as any as AsyncIterable<any>) {
rawResponses.push(chunk);
sawUsage = mergeUsage(usageAcc, chunk?.usage) || sawUsage;
const choice = chunk?.choices?.[0];
const deltaText = choice?.delta?.content ?? "";
if (typeof deltaText === "string" && deltaText.length) {
roundText += deltaText;
if (!roundHasToolCalls) {
streamedRoundText += deltaText;
yield { type: "delta", text: deltaText };
}
}
const deltaToolCalls = Array.isArray(choice?.delta?.tool_calls) ? choice.delta.tool_calls : [];
if (deltaToolCalls.length) {
roundHasToolCalls = true;
}
for (const toolCall of deltaToolCalls) {
const idx = typeof toolCall?.index === "number" ? toolCall.index : 0;
const entry = roundToolCalls.get(idx) ?? { arguments: "" };
if (typeof toolCall?.id === "string" && toolCall.id.length) {
entry.id = toolCall.id;
}
if (typeof toolCall?.function?.name === "string" && toolCall.function.name.length) {
entry.name = toolCall.function.name;
}
if (typeof toolCall?.function?.arguments === "string" && toolCall.function.arguments.length) {
entry.arguments += toolCall.function.arguments;
}
roundToolCalls.set(idx, entry);
}
}
const normalizedToolCalls: NormalizedToolCall[] = [...roundToolCalls.entries()]
.sort((a, b) => a[0] - b[0])
.map(([_, call], index) => ({
id: call.id ?? `tool_call_${round}_${index}`,
name: call.name ?? "unknown_tool",
arguments: call.arguments || "{}",
}));
if (!normalizedToolCalls.length) {
if (
!streamedRoundText &&
danglingToolIntentRetries < MAX_DANGLING_TOOL_INTENT_RETRIES &&
looksLikeDanglingToolIntent(roundText)
) {
danglingToolIntentRetries += 1;
appendDanglingToolIntentCorrection(conversation, roundText);
continue;
}
const unstreamedText = getUnstreamedText(roundText, streamedRoundText);
if (unstreamedText) {
yield { type: "delta", text: unstreamedText };
}
yield {
type: "done",
result: {
text: roundText,
usage: sawUsage ? usageAcc : undefined,
raw: { streamed: true, responses: rawResponses, toolCallsUsed: totalToolCalls },
toolEvents,
},
};
return;
}
totalToolCalls += normalizedToolCalls.length;
const assistantToolCallMessage: any = {
role: "assistant",
tool_calls: normalizedToolCalls.map((call) => ({
id: call.id,
type: "function",
function: {
name: call.name,
arguments: call.arguments,
},
})),
};
if (roundText) {
assistantToolCallMessage.content = roundText;
}
conversation.push(assistantToolCallMessage);
for (const call of normalizedToolCalls) {
const { event: initiatedEvent, execution } = prepareToolCallExecution(call);
yield { type: "tool_call", event: initiatedEvent };
const { event, toolResult } = await executeToolCallAndBuildEvent(call, execution, params);
toolEvents.push(event);
yield { type: "tool_call", event };
conversation.push({
role: "tool",
tool_call_id: call.id,
content: JSON.stringify(toolResult),
});
}
}
yield {
type: "done",
result: {
text: "I reached the tool-call limit while gathering information. Please narrow the request and try again.",
usage: sawUsage ? usageAcc : undefined,
raw: { streamed: true, responses: rawResponses, toolCallsUsed: totalToolCalls, toolCallLimitReached: true },
toolEvents,
},
};
}
export async function* runPlainChatCompletionsStream(
params: ToolAwareCompletionParams
): AsyncGenerator<ToolAwareStreamingEvent> {
const rawResponses: unknown[] = [];
const usageAcc: Required<ToolAwareUsage> = { inputTokens: 0, outputTokens: 0, totalTokens: 0 };
let sawUsage = false;
let text = "";
const stream = await params.client.chat.completions.create({
model: params.model,
messages: normalizePlainIncomingMessages(params.messages, params.userLocation),
temperature: params.temperature,
max_tokens: params.maxTokens,
stream: true,
} as any);
for await (const chunk of stream as any as AsyncIterable<any>) {
rawResponses.push(chunk);
sawUsage = mergeUsage(usageAcc, chunk?.usage) || sawUsage;
const deltaText = chunk?.choices?.[0]?.delta?.content ?? "";
if (typeof deltaText === "string" && deltaText.length) {
text += deltaText;
yield { type: "delta", text: deltaText };
}
}
yield {
type: "done",
result: {
text,
usage: sawUsage ? usageAcc : undefined,
raw: { streamed: true, responses: rawResponses, api: "chat.completions" },
toolEvents: [],
},
};
}

View File

@@ -18,21 +18,21 @@ function escapeAttribute(value: string) {
return value.replace(/"/g, "&quot;");
}
function getImageAttachments(message: ChatMessage) {
export function getImageAttachments(message: ChatMessage) {
return (message.attachments ?? []).filter((attachment): attachment is ChatImageAttachment => attachment.kind === "image");
}
function getTextAttachments(message: ChatMessage) {
export function getTextAttachments(message: ChatMessage) {
return (message.attachments ?? []).filter((attachment): attachment is ChatTextAttachment => attachment.kind === "text");
}
function buildImageSummaryText(attachments: ChatImageAttachment[]) {
export function buildImageSummaryText(attachments: ChatImageAttachment[]) {
if (!attachments.length) return null;
const label = attachments.length === 1 ? "Attached image" : "Attached images";
return `${label}: ${attachments.map((attachment) => attachment.filename).join(", ")}.`;
}
function buildTextAttachmentPrompt(attachment: ChatTextAttachment) {
export function buildTextAttachmentPrompt(attachment: ChatTextAttachment) {
const truncationNote = attachment.truncated ? ' truncated="true"' : "";
return [
`Attached text file: ${attachment.filename}${attachment.truncated ? " (content truncated)" : ""}`,
@@ -42,83 +42,7 @@ function buildTextAttachmentPrompt(attachment: ChatTextAttachment) {
].join("\n");
}
function toOpenAIContent(message: ChatMessage) {
const imageAttachments = getImageAttachments(message);
const textAttachments = getTextAttachments(message);
if (!imageAttachments.length && !textAttachments.length) {
return message.content;
}
const parts: Array<Record<string, unknown>> = [];
for (const attachment of imageAttachments) {
parts.push({
type: "image_url",
image_url: {
url: attachment.dataUrl,
detail: "auto",
},
});
}
const imageSummary = buildImageSummaryText(imageAttachments);
if (imageSummary) {
parts.push({ type: "text", text: imageSummary });
}
for (const attachment of textAttachments) {
parts.push({ type: "text", text: buildTextAttachmentPrompt(attachment) });
}
if (message.content.trim()) {
parts.push({ type: "text", text: message.content });
}
if (parts.length === 1 && parts[0]?.type === "text" && typeof parts[0].text === "string") {
return parts[0].text;
}
return parts;
}
function toOpenAIResponsesContent(message: ChatMessage) {
const imageAttachments = getImageAttachments(message);
const textAttachments = getTextAttachments(message);
if (!imageAttachments.length && !textAttachments.length) {
return message.content;
}
const parts: Array<Record<string, unknown>> = [];
for (const attachment of imageAttachments) {
parts.push({
type: "input_image",
image_url: attachment.dataUrl,
detail: "auto",
});
}
const imageSummary = buildImageSummaryText(imageAttachments);
if (imageSummary) {
parts.push({ type: "input_text", text: imageSummary });
}
for (const attachment of textAttachments) {
parts.push({ type: "input_text", text: buildTextAttachmentPrompt(attachment) });
}
if (message.content.trim()) {
parts.push({ type: "input_text", text: message.content });
}
if (parts.length === 1 && parts[0]?.type === "input_text" && typeof parts[0].text === "string") {
return parts[0].text;
}
return parts;
}
function parseImageDataUrl(attachment: ChatImageAttachment) {
export function parseImageDataUrl(attachment: ChatImageAttachment) {
const match = attachment.dataUrl.match(/^data:(image\/(?:png|jpeg));base64,([a-z0-9+/=\s]+)$/i);
if (!match) {
throw new Error(`Invalid image attachment data URL for '${attachment.filename}'.`);
@@ -135,83 +59,6 @@ function parseImageDataUrl(attachment: ChatImageAttachment) {
};
}
function toAnthropicContent(message: ChatMessage) {
const imageAttachments = getImageAttachments(message);
const textAttachments = getTextAttachments(message);
if (!imageAttachments.length && !textAttachments.length) {
return message.content;
}
const blocks: Array<Record<string, unknown>> = [];
for (const attachment of imageAttachments) {
const source = parseImageDataUrl(attachment);
blocks.push({
type: "image",
source: {
type: "base64",
media_type: source.mediaType,
data: source.data,
},
});
}
const imageSummary = buildImageSummaryText(imageAttachments);
if (imageSummary) {
blocks.push({ type: "text", text: imageSummary });
}
for (const attachment of textAttachments) {
blocks.push({ type: "text", text: buildTextAttachmentPrompt(attachment) });
}
if (message.content.trim()) {
blocks.push({ type: "text", text: message.content });
}
if (blocks.length === 1 && blocks[0]?.type === "text" && typeof blocks[0].text === "string") {
return blocks[0].text;
}
return blocks;
}
export function buildOpenAIConversationMessage(message: ChatMessage) {
if (message.role === "tool") {
const name = message.name?.trim() || "tool";
return {
role: "user",
content: `Tool output (${name}):\n${message.content}`,
};
}
const out: Record<string, unknown> = {
role: message.role,
content: toOpenAIContent(message),
};
if (message.name && (message.role === "assistant" || message.role === "user")) {
out.name = message.name;
}
return out;
}
export function buildOpenAIResponsesInputMessage(message: ChatMessage) {
if (message.role === "tool") {
const name = message.name?.trim() || "tool";
return {
role: "user",
content: `Tool output (${name}):\n${message.content}`,
};
}
return {
role: message.role,
content: toOpenAIResponsesContent(message),
};
}
export function buildSystemPromptAugmentationMessage(userLocation?: string) {
return {
role: "system",
@@ -219,34 +66,12 @@ export function buildSystemPromptAugmentationMessage(userLocation?: string) {
};
}
const ANTHROPIC_NO_SERVER_TOOLS_PROMPT =
"This Anthropic backend path does not have server-managed tool calls. Do not claim to run shell commands, Codex tasks, web searches, or fetch URLs. If the user asks for tool execution, explain that they should switch to OpenAI or xAI in this app for tool-enabled chat.";
export function getAnthropicSystemPrompt(messages: ChatMessage[], userLocation?: string) {
return [ANTHROPIC_NO_SERVER_TOOLS_PROMPT, buildSystemPromptAugmentation(userLocation), messages.find((message) => message.role === "system")?.content]
export function buildTopLevelSystemPrompt(messages: ChatMessage[], userLocation?: string, toolSystemPrompt?: string) {
return [toolSystemPrompt, buildSystemPromptAugmentation(userLocation), messages.find((message) => message.role === "system")?.content]
.filter(Boolean)
.join("\n\n");
}
export function buildAnthropicConversationMessage(message: ChatMessage) {
if (message.role === "system") {
throw new Error("System messages must be handled separately for Anthropic.");
}
if (message.role === "tool") {
const name = message.name?.trim() || "tool";
return {
role: "user",
content: `Tool output (${name}):\n${message.content}`,
};
}
return {
role: message.role === "assistant" ? "assistant" : "user",
content: toAnthropicContent(message),
};
}
export function buildComparableAttachments(input: unknown): ChatAttachment[] {
if (!Array.isArray(input)) return [];

View File

@@ -1,6 +1,9 @@
import type { FastifyBaseLogger } from "fastify";
import { env } from "../env.js";
import { anthropicClient, hermesAgentClient, isHermesAgentConfigured, openaiClient, xaiClient } from "./providers.js";
import {
fetchProviderCatalogModels,
getProviderCatalogFallbackModels,
listModelCatalogProviders,
} from "./provider-adapters.js";
import type { Provider } from "./types.js";
export type ProviderModelSnapshot = {
@@ -11,35 +14,13 @@ export type ProviderModelSnapshot = {
export type ModelCatalogSnapshot = Partial<Record<Provider, ProviderModelSnapshot>>;
const baseProviders: Provider[] = ["openai", "anthropic", "xai"];
const MODEL_FETCH_TIMEOUT_MS = 15000;
const MODEL_CATALOG_REFRESH_INTERVAL_MS = 24 * 60 * 60 * 1000;
const modelCatalog: ModelCatalogSnapshot = {
openai: { models: [], loadedAt: null, error: null },
anthropic: { models: [], loadedAt: null, error: null },
xai: { models: [], loadedAt: null, error: null },
};
const modelCatalog: ModelCatalogSnapshot = {};
let catalogRefreshPromise: Promise<void> | null = null;
function getCatalogProviders(): Provider[] {
return isHermesAgentConfigured() ? [...baseProviders, "hermes-agent"] : baseProviders;
}
function uniqSorted(models: string[]) {
return [...new Set(models.map((value) => value.trim()).filter(Boolean))].sort((a, b) => a.localeCompare(b));
}
function isLikelyOpenAIResponsesModel(model: string) {
const id = model.toLowerCase();
if (id.includes("embedding") || id.includes("moderation")) return false;
if (id.includes("audio") || id.includes("realtime") || id.includes("transcribe") || id.includes("tts")) return false;
if (id.includes("image") || id.includes("dall-e") || id.includes("sora")) return false;
if (id.includes("search") || id.includes("computer-use")) return false;
return /^(gpt-|o\d|chatgpt-)/.test(id);
}
async function withTimeout<T>(promise: Promise<T>, timeoutMs: number, label: string) {
let timeoutId: NodeJS.Timeout | null = null;
try {
@@ -56,31 +37,9 @@ async function withTimeout<T>(promise: Promise<T>, timeoutMs: number, label: str
}
}
async function fetchProviderModels(provider: Provider) {
if (provider === "openai") {
const page = await openaiClient().models.list();
return uniqSorted(page.data.map((model) => model.id).filter(isLikelyOpenAIResponsesModel));
}
if (provider === "anthropic") {
const page = await anthropicClient().models.list({ limit: 200 });
return uniqSorted(page.data.map((model) => model.id));
}
if (provider === "xai") {
const page = await xaiClient().models.list();
return uniqSorted(page.data.map((model) => model.id));
}
const page = await hermesAgentClient().models.list();
const models = page.data.map((model) => model.id);
if (env.HERMES_AGENT_MODEL) models.push(env.HERMES_AGENT_MODEL);
return uniqSorted(models);
}
async function refreshProviderModels(provider: Provider, logger?: FastifyBaseLogger) {
try {
const models = await withTimeout(fetchProviderModels(provider), MODEL_FETCH_TIMEOUT_MS, `${provider} model fetch`);
const models = await withTimeout(fetchProviderCatalogModels(provider), MODEL_FETCH_TIMEOUT_MS, `${provider} model fetch`);
modelCatalog[provider] = {
models,
loadedAt: new Date().toISOString(),
@@ -90,7 +49,7 @@ async function refreshProviderModels(provider: Provider, logger?: FastifyBaseLog
} catch (err: any) {
const message = err?.message ?? String(err);
const previous = modelCatalog[provider];
const fallbackModels = provider === "hermes-agent" && env.HERMES_AGENT_MODEL ? [env.HERMES_AGENT_MODEL] : [];
const fallbackModels = getProviderCatalogFallbackModels(provider);
modelCatalog[provider] = {
models: previous?.models.length ? previous.models : fallbackModels,
loadedAt: previous?.loadedAt ?? null,
@@ -103,7 +62,7 @@ async function refreshProviderModels(provider: Provider, logger?: FastifyBaseLog
export async function refreshModelCatalog(logger?: FastifyBaseLogger) {
if (catalogRefreshPromise) return catalogRefreshPromise;
catalogRefreshPromise = Promise.all(getCatalogProviders().map((provider) => refreshProviderModels(provider, logger)))
catalogRefreshPromise = Promise.all(listModelCatalogProviders().map((provider) => refreshProviderModels(provider, logger)))
.then(() => undefined)
.finally(() => {
catalogRefreshPromise = null;
@@ -129,7 +88,7 @@ export function startModelCatalogRefreshLoop(logger?: FastifyBaseLogger) {
export function getModelCatalogSnapshot(): ModelCatalogSnapshot {
const snapshot: ModelCatalogSnapshot = {};
for (const provider of getCatalogProviders()) {
for (const provider of listModelCatalogProviders()) {
const entry = modelCatalog[provider] ?? { models: [], loadedAt: null, error: null };
snapshot[provider] = {
models: [...entry.models],

View File

@@ -1,8 +1,7 @@
import { performance } from "node:perf_hooks";
import { prisma } from "../db.js";
import { anthropicClient, hermesAgentClient, openaiClient, xaiClient } from "./providers.js";
import { buildToolLogMessageData, normalizeEnabledChatTools, runPlainChatCompletions, runToolAwareChatCompletions, runToolAwareOpenAIChat } from "./chat-tools.js";
import { buildAnthropicConversationMessage, getAnthropicSystemPrompt } from "./message-content.js";
import { buildToolLogMessageData } from "./chat-tools.js";
import { getProviderChatAdapter } from "./provider-adapters.js";
import { toPrismaProvider } from "./provider-ids.js";
import type { MultiplexRequest, MultiplexResponse, Provider } from "./types.js";
@@ -47,97 +46,24 @@ export async function runMultiplex(req: MultiplexRequest): Promise<MultiplexResp
let usage: MultiplexResponse["usage"] | undefined;
let raw: unknown;
let toolMessages: ReturnType<typeof buildToolLogMessageData>[] = [];
const enabledTools = normalizeEnabledChatTools(req.enabledTools);
if (req.provider === "openai" && enabledTools.length > 0) {
const client = openaiClient();
const r = await runToolAwareOpenAIChat({
client,
const adapter = getProviderChatAdapter(req.provider);
const r = await adapter.complete({
model: req.model,
messages: req.messages,
enabledTools: req.enabledTools,
userLocation: req.userLocation,
temperature: req.temperature,
maxTokens: req.maxTokens,
logContext: {
provider: req.provider,
model: req.model,
messages: req.messages,
enabledTools,
userLocation: req.userLocation,
temperature: req.temperature,
maxTokens: req.maxTokens,
logContext: {
provider: req.provider,
model: req.model,
chatId,
},
});
raw = r.raw;
outText = r.text;
usage = r.usage;
toolMessages = r.toolEvents.map((event) => buildToolLogMessageData(call.chatId, event));
} else if (req.provider === "xai" && enabledTools.length > 0) {
const client = xaiClient();
const r = await runToolAwareChatCompletions({
client,
model: req.model,
messages: req.messages,
enabledTools,
userLocation: req.userLocation,
temperature: req.temperature,
maxTokens: req.maxTokens,
logContext: {
provider: req.provider,
model: req.model,
chatId,
},
});
raw = r.raw;
outText = r.text;
usage = r.usage;
toolMessages = r.toolEvents.map((event) => buildToolLogMessageData(call.chatId, event));
} else if (req.provider === "openai" || req.provider === "xai" || req.provider === "hermes-agent") {
const client = req.provider === "openai" ? openaiClient() : req.provider === "xai" ? xaiClient() : hermesAgentClient();
const r = await runPlainChatCompletions({
client,
model: req.model,
messages: req.messages,
userLocation: req.userLocation,
temperature: req.temperature,
maxTokens: req.maxTokens,
logContext: {
provider: req.provider,
model: req.model,
chatId,
},
});
raw = r.raw;
outText = r.text;
usage = r.usage;
} else if (req.provider === "anthropic") {
const client = anthropicClient();
const system = getAnthropicSystemPrompt(req.messages, req.userLocation);
const msgs = req.messages.filter((message) => message.role !== "system").map((message) => buildAnthropicConversationMessage(message));
const r = await client.messages.create({
model: req.model,
system,
max_tokens: req.maxTokens ?? 1024,
temperature: req.temperature,
messages: msgs as any,
});
raw = r;
outText = r.content
.map((c: any) => (c.type === "text" ? c.text : ""))
.join("")
.trim();
// Anthropic usage (SDK typing varies by version)
const ru: any = (r as any).usage;
if (ru) {
usage = {
inputTokens: ru.input_tokens,
outputTokens: ru.output_tokens,
totalTokens: (ru.input_tokens ?? 0) + (ru.output_tokens ?? 0),
};
}
} else {
throw new Error(`unknown provider: ${req.provider}`);
}
chatId,
},
});
raw = r.raw;
outText = r.text;
usage = r.usage;
toolMessages = r.toolEvents.map((event) => buildToolLogMessageData(call.chatId, event));
const latencyMs = Math.round(performance.now() - t0);

View File

@@ -0,0 +1,386 @@
import {
appendDanglingToolIntentCorrection,
buildChatToolSystemPrompt,
executeToolCallAndBuildEvent,
getEnabledChatTools,
getUnstreamedText,
looksLikeDanglingToolIntent,
MAX_DANGLING_TOOL_INTENT_RETRIES,
MAX_TOOL_ROUNDS,
mergeUsage,
normalizeModelToolCalls,
prepareToolCallExecution,
type NormalizedToolCall,
type ToolAwareCompletionParams,
type ToolAwareCompletionResult,
type ToolAwareStreamingEvent,
type ToolExecutionEvent,
} from "../chat-tools.js";
import {
buildImageSummaryText,
buildSystemPromptAugmentationMessage,
buildTextAttachmentPrompt,
getImageAttachments,
getTextAttachments,
} from "../message-content.js";
import type { ChatMessage } from "../types.js";
function toContentParts(message: ChatMessage) {
const imageAttachments = getImageAttachments(message);
const textAttachments = getTextAttachments(message);
if (!imageAttachments.length && !textAttachments.length) {
return message.content;
}
const parts: Array<Record<string, unknown>> = [];
for (const attachment of imageAttachments) {
parts.push({
type: "image_url",
image_url: {
url: attachment.dataUrl,
detail: "auto",
},
});
}
const imageSummary = buildImageSummaryText(imageAttachments);
if (imageSummary) {
parts.push({ type: "text", text: imageSummary });
}
for (const attachment of textAttachments) {
parts.push({ type: "text", text: buildTextAttachmentPrompt(attachment) });
}
if (message.content.trim()) {
parts.push({ type: "text", text: message.content });
}
if (parts.length === 1 && parts[0]?.type === "text" && typeof parts[0].text === "string") {
return parts[0].text;
}
return parts;
}
function buildConversationMessage(message: ChatMessage) {
if (message.role === "tool") {
const name = message.name?.trim() || "tool";
return {
role: "user",
content: `Tool output (${name}):\n${message.content}`,
};
}
const out: Record<string, unknown> = {
role: message.role,
content: toContentParts(message),
};
if (message.name && (message.role === "assistant" || message.role === "user")) {
out.name = message.name;
}
return out;
}
function normalizeMessages(messages: ChatMessage[], userLocation?: string, params: Pick<ToolAwareCompletionParams, "enabledTools"> = {}) {
const normalized = messages.map((message) => buildConversationMessage(message));
return [{ role: "system", content: buildChatToolSystemPrompt(params) }, buildSystemPromptAugmentationMessage(userLocation), ...normalized];
}
function normalizePlainMessages(messages: ChatMessage[], userLocation?: string) {
return [buildSystemPromptAugmentationMessage(userLocation), ...messages.map((message) => buildConversationMessage(message))];
}
function extractContent(message: any) {
if (typeof message?.content === "string") return message.content;
if (!Array.isArray(message?.content)) return "";
return message.content
.map((part: any) => {
if (typeof part === "string") return part;
if (typeof part?.text === "string") return part.text;
if (typeof part?.content === "string") return part.content;
return "";
})
.join("");
}
export async function completeWithChatCompletionsApi(params: ToolAwareCompletionParams): Promise<ToolAwareCompletionResult> {
const enabledTools = getEnabledChatTools(params);
if (!enabledTools.length) {
const completion = await params.client.chat.completions.create({
model: params.model,
messages: normalizePlainMessages(params.messages, params.userLocation),
temperature: params.temperature,
max_tokens: params.maxTokens,
} as any);
const usageAcc: Required<NonNullable<ToolAwareCompletionResult["usage"]>> = { inputTokens: 0, outputTokens: 0, totalTokens: 0 };
const sawUsage = mergeUsage(usageAcc, completion?.usage);
const message = completion?.choices?.[0]?.message;
return {
text: extractContent(message),
usage: sawUsage ? usageAcc : undefined,
raw: { response: completion, api: "chat.completions" },
toolEvents: [],
};
}
const conversation: any[] = normalizeMessages(params.messages, params.userLocation, params);
const rawResponses: unknown[] = [];
const toolEvents: ToolExecutionEvent[] = [];
const usageAcc: Required<NonNullable<ToolAwareCompletionResult["usage"]>> = { inputTokens: 0, outputTokens: 0, totalTokens: 0 };
let sawUsage = false;
let totalToolCalls = 0;
let danglingToolIntentRetries = 0;
for (let round = 0; round < MAX_TOOL_ROUNDS; round += 1) {
const completion = await params.client.chat.completions.create({
model: params.model,
messages: conversation,
temperature: params.temperature,
max_tokens: params.maxTokens,
tools: enabledTools,
tool_choice: "auto",
} as any);
rawResponses.push(completion);
sawUsage = mergeUsage(usageAcc, completion?.usage) || sawUsage;
const message = completion?.choices?.[0]?.message;
if (!message) {
return {
text: "",
usage: sawUsage ? usageAcc : undefined,
raw: { responses: rawResponses, toolCallsUsed: totalToolCalls, missingMessage: true },
toolEvents,
};
}
const toolCalls = Array.isArray(message.tool_calls) ? message.tool_calls : [];
if (!toolCalls.length) {
const text = typeof message.content === "string" ? message.content : "";
if (danglingToolIntentRetries < MAX_DANGLING_TOOL_INTENT_RETRIES && looksLikeDanglingToolIntent(text)) {
danglingToolIntentRetries += 1;
appendDanglingToolIntentCorrection(conversation, text);
continue;
}
return {
text,
usage: sawUsage ? usageAcc : undefined,
raw: { responses: rawResponses, toolCallsUsed: totalToolCalls },
toolEvents,
};
}
const normalizedToolCalls = normalizeModelToolCalls(toolCalls, round);
totalToolCalls += normalizedToolCalls.length;
const assistantToolCallMessage: any = {
role: "assistant",
tool_calls: normalizedToolCalls.map((call) => ({
id: call.id,
type: "function",
function: {
name: call.name,
arguments: call.arguments,
},
})),
};
if (typeof message.content === "string" && message.content.length) {
assistantToolCallMessage.content = message.content;
}
conversation.push(assistantToolCallMessage);
for (const call of normalizedToolCalls) {
const { execution } = prepareToolCallExecution(call);
const { event, toolResult } = await executeToolCallAndBuildEvent(call, execution, params);
toolEvents.push(event);
conversation.push({
role: "tool",
tool_call_id: call.id,
content: JSON.stringify(toolResult),
});
}
}
return {
text: "I reached the tool-call limit while gathering information. Please narrow the request and try again.",
usage: sawUsage ? usageAcc : undefined,
raw: { responses: rawResponses, toolCallsUsed: totalToolCalls, toolCallLimitReached: true },
toolEvents,
};
}
export async function* streamWithChatCompletionsApi(params: ToolAwareCompletionParams): AsyncGenerator<ToolAwareStreamingEvent> {
const enabledTools = getEnabledChatTools(params);
if (!enabledTools.length) {
const rawResponses: unknown[] = [];
const usageAcc: Required<NonNullable<ToolAwareCompletionResult["usage"]>> = { inputTokens: 0, outputTokens: 0, totalTokens: 0 };
let sawUsage = false;
let text = "";
const stream = await params.client.chat.completions.create({
model: params.model,
messages: normalizePlainMessages(params.messages, params.userLocation),
temperature: params.temperature,
max_tokens: params.maxTokens,
stream: true,
} as any);
for await (const chunk of stream as any as AsyncIterable<any>) {
rawResponses.push(chunk);
sawUsage = mergeUsage(usageAcc, chunk?.usage) || sawUsage;
const deltaText = chunk?.choices?.[0]?.delta?.content ?? "";
if (typeof deltaText === "string" && deltaText.length) {
text += deltaText;
yield { type: "delta", text: deltaText };
}
}
yield {
type: "done",
result: {
text,
usage: sawUsage ? usageAcc : undefined,
raw: { streamed: true, responses: rawResponses, api: "chat.completions" },
toolEvents: [],
},
};
return;
}
const conversation: any[] = normalizeMessages(params.messages, params.userLocation, params);
const rawResponses: unknown[] = [];
const toolEvents: ToolExecutionEvent[] = [];
const usageAcc: Required<NonNullable<ToolAwareCompletionResult["usage"]>> = { inputTokens: 0, outputTokens: 0, totalTokens: 0 };
let sawUsage = false;
let totalToolCalls = 0;
let danglingToolIntentRetries = 0;
for (let round = 0; round < MAX_TOOL_ROUNDS; round += 1) {
const stream = await params.client.chat.completions.create({
model: params.model,
messages: conversation,
temperature: params.temperature,
max_tokens: params.maxTokens,
tools: enabledTools,
tool_choice: "auto",
stream: true,
stream_options: { include_usage: true },
} as any);
let roundText = "";
let streamedRoundText = "";
let roundHasToolCalls = false;
const roundToolCalls = new Map<number, { id?: string; name?: string; arguments: string }>();
for await (const chunk of stream as any as AsyncIterable<any>) {
rawResponses.push(chunk);
sawUsage = mergeUsage(usageAcc, chunk?.usage) || sawUsage;
const choice = chunk?.choices?.[0];
const deltaText = choice?.delta?.content ?? "";
if (typeof deltaText === "string" && deltaText.length) {
roundText += deltaText;
if (!roundHasToolCalls) {
streamedRoundText += deltaText;
yield { type: "delta", text: deltaText };
}
}
const deltaToolCalls = Array.isArray(choice?.delta?.tool_calls) ? choice.delta.tool_calls : [];
if (deltaToolCalls.length) {
roundHasToolCalls = true;
}
for (const toolCall of deltaToolCalls) {
const idx = typeof toolCall?.index === "number" ? toolCall.index : 0;
const entry = roundToolCalls.get(idx) ?? { arguments: "" };
if (typeof toolCall?.id === "string" && toolCall.id.length) {
entry.id = toolCall.id;
}
if (typeof toolCall?.function?.name === "string" && toolCall.function.name.length) {
entry.name = toolCall.function.name;
}
if (typeof toolCall?.function?.arguments === "string" && toolCall.function.arguments.length) {
entry.arguments += toolCall.function.arguments;
}
roundToolCalls.set(idx, entry);
}
}
const normalizedToolCalls: NormalizedToolCall[] = [...roundToolCalls.entries()]
.sort((a, b) => a[0] - b[0])
.map(([_, call], index) => ({
id: call.id ?? `tool_call_${round}_${index}`,
name: call.name ?? "unknown_tool",
arguments: call.arguments || "{}",
}));
if (!normalizedToolCalls.length) {
if (!streamedRoundText && danglingToolIntentRetries < MAX_DANGLING_TOOL_INTENT_RETRIES && looksLikeDanglingToolIntent(roundText)) {
danglingToolIntentRetries += 1;
appendDanglingToolIntentCorrection(conversation, roundText);
continue;
}
const unstreamedText = getUnstreamedText(roundText, streamedRoundText);
if (unstreamedText) {
yield { type: "delta", text: unstreamedText };
}
yield {
type: "done",
result: {
text: roundText,
usage: sawUsage ? usageAcc : undefined,
raw: { streamed: true, responses: rawResponses, toolCallsUsed: totalToolCalls },
toolEvents,
},
};
return;
}
totalToolCalls += normalizedToolCalls.length;
const assistantToolCallMessage: any = {
role: "assistant",
tool_calls: normalizedToolCalls.map((call) => ({
id: call.id,
type: "function",
function: {
name: call.name,
arguments: call.arguments,
},
})),
};
if (roundText) {
assistantToolCallMessage.content = roundText;
}
conversation.push(assistantToolCallMessage);
for (const call of normalizedToolCalls) {
const { event: initiatedEvent, execution } = prepareToolCallExecution(call);
yield { type: "tool_call", event: initiatedEvent };
const { event, toolResult } = await executeToolCallAndBuildEvent(call, execution, params);
toolEvents.push(event);
yield { type: "tool_call", event };
conversation.push({
role: "tool",
tool_call_id: call.id,
content: JSON.stringify(toolResult),
});
}
}
yield {
type: "done",
result: {
text: "I reached the tool-call limit while gathering information. Please narrow the request and try again.",
usage: sawUsage ? usageAcc : undefined,
raw: { streamed: true, responses: rawResponses, toolCallsUsed: totalToolCalls, toolCallLimitReached: true },
toolEvents,
},
};
}

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import {
buildChatToolSystemPrompt,
executeToolCallAndBuildEvent,
getEnabledChatTools,
looksLikeDanglingToolIntent,
MAX_DANGLING_TOOL_INTENT_RETRIES,
MAX_TOOL_ROUNDS,
parseToolArgs,
prepareToolCallExecution,
type NormalizedToolCall,
type ToolAwareCompletionParams,
type ToolAwareCompletionResult,
type ToolAwareStreamingEvent,
type ToolAwareUsage,
type ToolExecutionEvent,
type ToolRunOutcome,
} from "../chat-tools.js";
import {
buildImageSummaryText,
buildTextAttachmentPrompt,
buildTopLevelSystemPrompt,
getImageAttachments,
getTextAttachments,
parseImageDataUrl,
} from "../message-content.js";
import type { ChatMessage } from "../types.js";
const INTERNAL_CORRECTION =
"Internal correction: the previous assistant message claimed it would run a tool, but no tool call was made. If the task needs an available tool, call it now. Otherwise provide the final answer directly without saying you will run a tool.";
function toTools(tools: any[]) {
return tools
.map((tool) => {
if (tool?.type !== "function") return null;
return {
name: tool.function.name,
description: tool.function.description,
input_schema: tool.function.parameters,
};
})
.filter(Boolean);
}
function toContentBlocks(message: ChatMessage) {
const imageAttachments = getImageAttachments(message);
const textAttachments = getTextAttachments(message);
if (!imageAttachments.length && !textAttachments.length) {
return message.content;
}
const blocks: Array<Record<string, unknown>> = [];
for (const attachment of imageAttachments) {
const source = parseImageDataUrl(attachment);
blocks.push({
type: "image",
source: {
type: "base64",
media_type: source.mediaType,
data: source.data,
},
});
}
const imageSummary = buildImageSummaryText(imageAttachments);
if (imageSummary) {
blocks.push({ type: "text", text: imageSummary });
}
for (const attachment of textAttachments) {
blocks.push({ type: "text", text: buildTextAttachmentPrompt(attachment) });
}
if (message.content.trim()) {
blocks.push({ type: "text", text: message.content });
}
if (blocks.length === 1 && blocks[0]?.type === "text" && typeof blocks[0].text === "string") {
return blocks[0].text;
}
return blocks;
}
function buildConversationMessage(message: ChatMessage) {
if (message.role === "system") {
throw new Error("System messages must be handled separately for top-level-system protocols.");
}
if (message.role === "tool") {
const name = message.name?.trim() || "tool";
return {
role: "user",
content: `Tool output (${name}):\n${message.content}`,
};
}
return {
role: message.role === "assistant" ? "assistant" : "user",
content: toContentBlocks(message),
};
}
function buildBaseMessages(params: ToolAwareCompletionParams) {
return params.messages.filter((message) => message.role !== "system").map((message) => buildConversationMessage(message));
}
function stringifyToolInput(input: unknown) {
if (typeof input === "string") return input;
try {
return JSON.stringify(input ?? {});
} catch {
return "{}";
}
}
function normalizeToolCalls(content: any[], round: number): NormalizedToolCall[] {
return content
.filter((item) => item?.type === "tool_use")
.map((call: any, index: number) => ({
id: call?.id ?? `tool_call_${round}_${index}`,
name: call?.name ?? "unknown_tool",
arguments: stringifyToolInput(call?.input),
}));
}
function extractText(response: any) {
if (!Array.isArray(response?.content)) return "";
return response.content
.map((content: any) => (content?.type === "text" && typeof content.text === "string" ? content.text : ""))
.join("")
.trim();
}
function buildToolResultBlock(call: NormalizedToolCall, toolResult: ToolRunOutcome) {
return {
type: "tool_result",
tool_use_id: call.id,
content: JSON.stringify(toolResult),
is_error: !toolResult.ok,
};
}
function appendCorrection(conversation: any[], text: string) {
conversation.push({ role: "assistant", content: text });
conversation.push({
role: "user",
content: INTERNAL_CORRECTION,
});
}
function mergeUsage(acc: Required<ToolAwareUsage>, usage: any) {
if (!usage) return false;
const inputTokens = usage.input_tokens ?? 0;
const outputTokens = usage.output_tokens ?? 0;
acc.inputTokens += inputTokens;
acc.outputTokens += outputTokens;
acc.totalTokens += inputTokens + outputTokens;
return true;
}
export async function completeWithMessagesApi(params: ToolAwareCompletionParams): Promise<ToolAwareCompletionResult> {
const enabledTools = getEnabledChatTools(params);
if (!enabledTools.length) {
const response = await params.client.messages.create({
model: params.model,
system: buildTopLevelSystemPrompt(params.messages, params.userLocation),
max_tokens: params.maxTokens ?? 1024,
temperature: params.temperature,
messages: buildBaseMessages(params),
} as any);
const usageAcc: Required<ToolAwareUsage> = { inputTokens: 0, outputTokens: 0, totalTokens: 0 };
const sawUsage = mergeUsage(usageAcc, response?.usage);
return {
text: extractText(response),
usage: sawUsage ? usageAcc : undefined,
raw: { response, api: "messages" },
toolEvents: [],
};
}
const conversation: any[] = buildBaseMessages(params);
const rawResponses: unknown[] = [];
const toolEvents: ToolExecutionEvent[] = [];
const usageAcc: Required<ToolAwareUsage> = { inputTokens: 0, outputTokens: 0, totalTokens: 0 };
let sawUsage = false;
let totalToolCalls = 0;
let danglingToolIntentRetries = 0;
for (let round = 0; round < MAX_TOOL_ROUNDS; round += 1) {
const response = await params.client.messages.create({
model: params.model,
system: buildTopLevelSystemPrompt(params.messages, params.userLocation, buildChatToolSystemPrompt(params)),
max_tokens: params.maxTokens ?? 1024,
temperature: params.temperature,
messages: conversation,
tools: toTools(enabledTools),
tool_choice: { type: "auto" },
} as any);
rawResponses.push(response);
sawUsage = mergeUsage(usageAcc, response?.usage) || sawUsage;
const content = Array.isArray(response?.content) ? response.content : [];
const normalizedToolCalls = normalizeToolCalls(content, round);
if (!normalizedToolCalls.length) {
const text = extractText(response);
if (danglingToolIntentRetries < MAX_DANGLING_TOOL_INTENT_RETRIES && looksLikeDanglingToolIntent(text)) {
danglingToolIntentRetries += 1;
appendCorrection(conversation, text);
continue;
}
return {
text,
usage: sawUsage ? usageAcc : undefined,
raw: { responses: rawResponses, toolCallsUsed: totalToolCalls, api: "messages" },
toolEvents,
};
}
totalToolCalls += normalizedToolCalls.length;
conversation.push({
role: "assistant",
content,
});
const toolResultBlocks: any[] = [];
for (const call of normalizedToolCalls) {
const { execution } = prepareToolCallExecution(call);
const { event, toolResult } = await executeToolCallAndBuildEvent(call, execution, params);
toolEvents.push(event);
toolResultBlocks.push(buildToolResultBlock(call, toolResult));
}
conversation.push({
role: "user",
content: toolResultBlocks,
});
}
return {
text: "I reached the tool-call limit while gathering information. Please narrow the request and try again.",
usage: sawUsage ? usageAcc : undefined,
raw: { responses: rawResponses, toolCallsUsed: totalToolCalls, toolCallLimitReached: true, api: "messages" },
toolEvents,
};
}
export async function* streamWithMessagesApi(params: ToolAwareCompletionParams): AsyncGenerator<ToolAwareStreamingEvent> {
const enabledTools = getEnabledChatTools(params);
if (!enabledTools.length) {
const rawResponses: unknown[] = [];
const usageAcc: Required<ToolAwareUsage> = { inputTokens: 0, outputTokens: 0, totalTokens: 0 };
let sawUsage = false;
let roundInputTokens = 0;
let roundOutputTokens = 0;
let text = "";
const stream = await params.client.messages.create({
model: params.model,
system: buildTopLevelSystemPrompt(params.messages, params.userLocation),
max_tokens: params.maxTokens ?? 1024,
temperature: params.temperature,
messages: buildBaseMessages(params),
stream: true,
} as any);
for await (const ev of stream as any as AsyncIterable<any>) {
rawResponses.push(ev);
if (ev?.type === "message_start" && ev?.message?.usage) {
roundInputTokens = ev.message.usage.input_tokens ?? roundInputTokens;
sawUsage = true;
}
if (ev?.type === "content_block_delta" && ev?.delta?.type === "text_delta") {
const delta = ev.delta.text ?? "";
if (delta) {
text += delta;
yield { type: "delta", text: delta };
}
}
if (ev?.type === "message_delta" && ev.usage) {
roundInputTokens = ev.usage.input_tokens ?? roundInputTokens;
roundOutputTokens = ev.usage.output_tokens ?? roundOutputTokens;
sawUsage = true;
}
}
if (sawUsage) {
usageAcc.inputTokens += roundInputTokens;
usageAcc.outputTokens += roundOutputTokens;
usageAcc.totalTokens += roundInputTokens + roundOutputTokens;
}
yield {
type: "done",
result: {
text,
usage: sawUsage ? usageAcc : undefined,
raw: { streamed: true, responses: rawResponses, toolCallsUsed: 0, api: "messages" },
toolEvents: [],
},
};
return;
}
const conversation: any[] = buildBaseMessages(params);
const rawResponses: unknown[] = [];
const toolEvents: ToolExecutionEvent[] = [];
const usageAcc: Required<ToolAwareUsage> = { inputTokens: 0, outputTokens: 0, totalTokens: 0 };
let sawUsage = false;
let totalToolCalls = 0;
let danglingToolIntentRetries = 0;
for (let round = 0; round < MAX_TOOL_ROUNDS; round += 1) {
const stream = await params.client.messages.create({
model: params.model,
system: buildTopLevelSystemPrompt(params.messages, params.userLocation, buildChatToolSystemPrompt(params)),
max_tokens: params.maxTokens ?? 1024,
temperature: params.temperature,
messages: conversation,
tools: toTools(enabledTools),
tool_choice: { type: "auto" },
stream: true,
} as any);
const contentByIndex = new Map<number, any>();
const toolArgumentByIndex = new Map<number, string>();
let roundText = "";
let roundHasToolCalls = false;
let roundInputTokens = 0;
let roundOutputTokens = 0;
let sawRoundUsage = false;
for await (const ev of stream as any as AsyncIterable<any>) {
rawResponses.push(ev);
if (ev?.type === "message_start" && ev?.message?.usage) {
roundInputTokens = ev.message.usage.input_tokens ?? roundInputTokens;
sawRoundUsage = true;
}
if (ev?.type === "content_block_start" && typeof ev.index === "number") {
const block = ev.content_block ?? {};
if (block.type === "tool_use") {
roundHasToolCalls = true;
contentByIndex.set(ev.index, {
type: "tool_use",
id: block.id,
name: block.name,
input: block.input ?? {},
});
toolArgumentByIndex.set(ev.index, "");
} else if (block.type === "text") {
contentByIndex.set(ev.index, {
type: "text",
text: typeof block.text === "string" ? block.text : "",
});
} else if (block.type) {
contentByIndex.set(ev.index, block);
}
}
if (ev?.type === "content_block_delta" && typeof ev.index === "number") {
if (ev.delta?.type === "text_delta") {
const delta = typeof ev.delta.text === "string" ? ev.delta.text : "";
if (delta) {
const block = contentByIndex.get(ev.index) ?? { type: "text", text: "" };
if (block.type === "text") {
block.text = `${typeof block.text === "string" ? block.text : ""}${delta}`;
contentByIndex.set(ev.index, block);
}
roundText += delta;
}
} else if (ev.delta?.type === "input_json_delta") {
roundHasToolCalls = true;
const partialJson = typeof ev.delta.partial_json === "string" ? ev.delta.partial_json : "";
toolArgumentByIndex.set(ev.index, `${toolArgumentByIndex.get(ev.index) ?? ""}${partialJson}`);
}
}
if (ev?.type === "content_block_stop" && typeof ev.index === "number") {
const block = contentByIndex.get(ev.index);
if (block?.type === "tool_use") {
const rawArguments = toolArgumentByIndex.get(ev.index) || stringifyToolInput(block.input);
try {
block.input = parseToolArgs(rawArguments);
} catch {
block.input = {};
}
contentByIndex.set(ev.index, block);
}
}
if (ev?.type === "message_delta" && ev.usage) {
roundInputTokens = ev.usage.input_tokens ?? roundInputTokens;
roundOutputTokens = ev.usage.output_tokens ?? roundOutputTokens;
sawRoundUsage = true;
}
}
if (sawRoundUsage) {
usageAcc.inputTokens += roundInputTokens;
usageAcc.outputTokens += roundOutputTokens;
usageAcc.totalTokens += roundInputTokens + roundOutputTokens;
sawUsage = true;
}
const indexedContent = [...contentByIndex.entries()].sort((a, b) => a[0] - b[0]);
const assistantContent = indexedContent.map(([, block]) => block);
const normalizedToolCalls: NormalizedToolCall[] = indexedContent
.filter(([, block]) => block?.type === "tool_use")
.map(([index, block], callIndex) => ({
id: block.id ?? `tool_call_${round}_${callIndex}`,
name: block.name ?? "unknown_tool",
arguments: toolArgumentByIndex.get(index) || stringifyToolInput(block.input),
}));
if (!normalizedToolCalls.length) {
if (danglingToolIntentRetries < MAX_DANGLING_TOOL_INTENT_RETRIES && looksLikeDanglingToolIntent(roundText)) {
danglingToolIntentRetries += 1;
appendCorrection(conversation, roundText);
continue;
}
if (roundText) {
yield { type: "delta", text: roundText };
}
yield {
type: "done",
result: {
text: roundText,
usage: sawUsage ? usageAcc : undefined,
raw: { streamed: true, responses: rawResponses, toolCallsUsed: totalToolCalls, api: "messages" },
toolEvents,
},
};
return;
}
totalToolCalls += normalizedToolCalls.length;
conversation.push({
role: "assistant",
content: assistantContent,
});
const toolResultBlocks: any[] = [];
for (const call of normalizedToolCalls) {
const { event: initiatedEvent, execution } = prepareToolCallExecution(call);
yield { type: "tool_call", event: initiatedEvent };
const { event, toolResult } = await executeToolCallAndBuildEvent(call, execution, params);
toolEvents.push(event);
yield { type: "tool_call", event };
toolResultBlocks.push(buildToolResultBlock(call, toolResult));
}
conversation.push({
role: "user",
content: toolResultBlocks,
});
}
yield {
type: "done",
result: {
text: "I reached the tool-call limit while gathering information. Please narrow the request and try again.",
usage: sawUsage ? usageAcc : undefined,
raw: { streamed: true, responses: rawResponses, toolCallsUsed: totalToolCalls, toolCallLimitReached: true, api: "messages" },
toolEvents,
},
};
}

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import {
appendDanglingToolIntentCorrection,
buildChatToolSystemPrompt,
executeToolCallAndBuildEvent,
getEnabledChatTools,
getUnstreamedText,
looksLikeDanglingToolIntent,
MAX_DANGLING_TOOL_INTENT_RETRIES,
MAX_TOOL_ROUNDS,
prepareToolCallExecution,
type NormalizedToolCall,
type ToolAwareCompletionParams,
type ToolAwareCompletionResult,
type ToolAwareStreamingEvent,
type ToolAwareUsage,
type ToolExecutionEvent,
} from "../chat-tools.js";
import {
buildImageSummaryText,
buildSystemPromptAugmentationMessage,
buildTextAttachmentPrompt,
getImageAttachments,
getTextAttachments,
} from "../message-content.js";
import type { ChatMessage } from "../types.js";
function toResponsesTools(tools: any[]) {
return tools.map((tool) => {
if (tool?.type !== "function") return tool;
return {
type: "function",
name: tool.function.name,
description: tool.function.description,
parameters: tool.function.parameters,
strict: false,
};
});
}
function toContentParts(message: ChatMessage) {
const imageAttachments = getImageAttachments(message);
const textAttachments = getTextAttachments(message);
if (!imageAttachments.length && !textAttachments.length) {
return message.content;
}
const parts: Array<Record<string, unknown>> = [];
for (const attachment of imageAttachments) {
parts.push({
type: "input_image",
image_url: attachment.dataUrl,
detail: "auto",
});
}
const imageSummary = buildImageSummaryText(imageAttachments);
if (imageSummary) {
parts.push({ type: "input_text", text: imageSummary });
}
for (const attachment of textAttachments) {
parts.push({ type: "input_text", text: buildTextAttachmentPrompt(attachment) });
}
if (message.content.trim()) {
parts.push({ type: "input_text", text: message.content });
}
if (parts.length === 1 && parts[0]?.type === "input_text" && typeof parts[0].text === "string") {
return parts[0].text;
}
return parts;
}
function buildInputMessage(message: ChatMessage) {
if (message.role === "tool") {
const name = message.name?.trim() || "tool";
return {
role: "user",
content: `Tool output (${name}):\n${message.content}`,
};
}
return {
role: message.role,
content: toContentParts(message),
};
}
function normalizeInput(messages: ChatMessage[], userLocation?: string, params: Pick<ToolAwareCompletionParams, "enabledTools"> = {}) {
const normalized = messages.map((message) => buildInputMessage(message));
return [{ role: "system", content: buildChatToolSystemPrompt(params) }, buildSystemPromptAugmentationMessage(userLocation), ...normalized];
}
function mergeUsage(acc: Required<ToolAwareUsage>, usage: any) {
if (!usage) return false;
acc.inputTokens += usage.input_tokens ?? 0;
acc.outputTokens += usage.output_tokens ?? 0;
acc.totalTokens += usage.total_tokens ?? 0;
return true;
}
function getOutputItems(response: any) {
return Array.isArray(response?.output) ? response.output : [];
}
function extractText(response: any, fallback = "") {
if (typeof response?.output_text === "string") return response.output_text;
const parts: string[] = [];
for (const item of getOutputItems(response)) {
if (item?.type !== "message" || !Array.isArray(item.content)) continue;
for (const content of item.content) {
if (content?.type === "output_text" && typeof content.text === "string") {
parts.push(content.text);
} else if (content?.type === "refusal" && typeof content.refusal === "string") {
parts.push(content.refusal);
}
}
}
return parts.join("") || fallback;
}
function getFailureMessage(response: any) {
if (response?.status !== "failed" && response?.status !== "incomplete") return null;
const errorMessage = typeof response?.error?.message === "string" ? response.error.message : null;
const incompleteReason = typeof response?.incomplete_details?.reason === "string" ? response.incomplete_details.reason : null;
return errorMessage ?? (incompleteReason ? `Response incomplete: ${incompleteReason}` : `Response ${response.status}.`);
}
function normalizeToolCalls(outputItems: any[], round: number): NormalizedToolCall[] {
return outputItems
.filter((item) => item?.type === "function_call")
.map((call: any, index: number) => ({
id: call.call_id ?? call.id ?? `tool_call_${round}_${index}`,
name: call.name ?? "unknown_tool",
arguments: call.arguments ?? "{}",
}));
}
export async function completeWithResponsesApi(params: ToolAwareCompletionParams): Promise<ToolAwareCompletionResult> {
const enabledTools = getEnabledChatTools(params);
const input: any[] = normalizeInput(params.messages, params.userLocation, params);
const rawResponses: unknown[] = [];
const toolEvents: ToolExecutionEvent[] = [];
const usageAcc: Required<ToolAwareUsage> = { inputTokens: 0, outputTokens: 0, totalTokens: 0 };
let sawUsage = false;
let totalToolCalls = 0;
let danglingToolIntentRetries = 0;
for (let round = 0; round < MAX_TOOL_ROUNDS; round += 1) {
const response = await params.client.responses.create({
model: params.model,
input,
temperature: params.temperature,
max_output_tokens: params.maxTokens,
tools: toResponsesTools(enabledTools),
tool_choice: "auto",
parallel_tool_calls: true,
store: true,
} as any);
rawResponses.push(response);
sawUsage = mergeUsage(usageAcc, response?.usage) || sawUsage;
const failureMessage = getFailureMessage(response);
if (failureMessage) {
throw new Error(failureMessage);
}
const outputItems = getOutputItems(response);
const normalizedToolCalls = normalizeToolCalls(outputItems, round);
if (!normalizedToolCalls.length) {
const text = extractText(response);
if (danglingToolIntentRetries < MAX_DANGLING_TOOL_INTENT_RETRIES && looksLikeDanglingToolIntent(text)) {
danglingToolIntentRetries += 1;
appendDanglingToolIntentCorrection(input, text);
continue;
}
return {
text,
usage: sawUsage ? usageAcc : undefined,
raw: { responses: rawResponses, toolCallsUsed: totalToolCalls, api: "responses" },
toolEvents,
};
}
totalToolCalls += normalizedToolCalls.length;
input.push(...outputItems);
for (const call of normalizedToolCalls) {
const { execution } = prepareToolCallExecution(call);
const { event, toolResult } = await executeToolCallAndBuildEvent(call, execution, params);
toolEvents.push(event);
input.push({
type: "function_call_output",
call_id: call.id,
output: JSON.stringify(toolResult),
});
}
}
return {
text: "I reached the tool-call limit while gathering information. Please narrow the request and try again.",
usage: sawUsage ? usageAcc : undefined,
raw: { responses: rawResponses, toolCallsUsed: totalToolCalls, toolCallLimitReached: true, api: "responses" },
toolEvents,
};
}
export async function* streamWithResponsesApi(params: ToolAwareCompletionParams): AsyncGenerator<ToolAwareStreamingEvent> {
const enabledTools = getEnabledChatTools(params);
const input: any[] = normalizeInput(params.messages, params.userLocation, params);
const rawResponses: unknown[] = [];
const toolEvents: ToolExecutionEvent[] = [];
const usageAcc: Required<ToolAwareUsage> = { inputTokens: 0, outputTokens: 0, totalTokens: 0 };
let sawUsage = false;
let totalToolCalls = 0;
let danglingToolIntentRetries = 0;
for (let round = 0; round < MAX_TOOL_ROUNDS; round += 1) {
const stream = await params.client.responses.create({
model: params.model,
input,
temperature: params.temperature,
max_output_tokens: params.maxTokens,
tools: toResponsesTools(enabledTools),
tool_choice: "auto",
parallel_tool_calls: true,
store: true,
stream: true,
} as any);
let roundText = "";
let streamedRoundText = "";
let roundHasToolCalls = false;
let canStreamRoundText = false;
let completedResponse: any | null = null;
const completedOutputItems: any[] = [];
for await (const event of stream as any as AsyncIterable<any>) {
rawResponses.push(event);
if (event?.type === "response.output_text.delta" && typeof event.delta === "string") {
roundText += event.delta;
if (canStreamRoundText && !roundHasToolCalls && event.delta.length) {
streamedRoundText += event.delta;
yield { type: "delta", text: event.delta };
}
} else if (event?.type === "response.output_item.added" && event.item) {
if (event.item.type === "function_call") {
roundHasToolCalls = true;
canStreamRoundText = false;
} else if (event.item.type === "message" && !roundHasToolCalls) {
canStreamRoundText = true;
}
} else if (event?.type === "response.output_item.done" && event.item) {
completedOutputItems[event.output_index ?? completedOutputItems.length] = event.item;
if (event.item.type === "function_call") {
roundHasToolCalls = true;
canStreamRoundText = false;
}
} else if (event?.type === "response.completed") {
completedResponse = event.response;
sawUsage = mergeUsage(usageAcc, event.response?.usage) || sawUsage;
} else if (event?.type === "response.failed" || event?.type === "response.incomplete") {
completedResponse = event.response;
sawUsage = mergeUsage(usageAcc, event.response?.usage) || sawUsage;
} else if (event?.type === "error") {
throw new Error(event.message ?? "Responses stream failed.");
}
}
const failureMessage = getFailureMessage(completedResponse);
if (failureMessage) {
throw new Error(failureMessage);
}
const outputItems = getOutputItems(completedResponse);
const responseOutputItems = outputItems.length ? outputItems : completedOutputItems.filter(Boolean);
const normalizedToolCalls = normalizeToolCalls(responseOutputItems, round);
if (!normalizedToolCalls.length) {
const text = extractText(completedResponse, roundText);
if (!streamedRoundText && danglingToolIntentRetries < MAX_DANGLING_TOOL_INTENT_RETRIES && looksLikeDanglingToolIntent(text)) {
danglingToolIntentRetries += 1;
appendDanglingToolIntentCorrection(input, text);
continue;
}
const unstreamedText = getUnstreamedText(text, streamedRoundText);
if (unstreamedText) {
yield { type: "delta", text: unstreamedText };
}
yield {
type: "done",
result: {
text,
usage: sawUsage ? usageAcc : undefined,
raw: { streamed: true, responses: rawResponses, toolCallsUsed: totalToolCalls, api: "responses" },
toolEvents,
},
};
return;
}
totalToolCalls += normalizedToolCalls.length;
input.push(...responseOutputItems);
for (const call of normalizedToolCalls) {
const { event: initiatedEvent, execution } = prepareToolCallExecution(call);
yield { type: "tool_call", event: initiatedEvent };
const { event, toolResult } = await executeToolCallAndBuildEvent(call, execution, params);
toolEvents.push(event);
yield { type: "tool_call", event };
input.push({
type: "function_call_output",
call_id: call.id,
output: JSON.stringify(toolResult),
});
}
}
yield {
type: "done",
result: {
text: "I reached the tool-call limit while gathering information. Please narrow the request and try again.",
usage: sawUsage ? usageAcc : undefined,
raw: { streamed: true, responses: rawResponses, toolCallsUsed: totalToolCalls, toolCallLimitReached: true, api: "responses" },
toolEvents,
},
};
}

View File

@@ -0,0 +1,217 @@
import {
normalizeEnabledChatTools,
type ToolAwareCompletionParams,
type ToolAwareCompletionResult,
type ToolAwareStreamingEvent,
} from "./chat-tools.js";
import { completeWithChatCompletionsApi, streamWithChatCompletionsApi } from "./protocols/chat-completions-api.js";
import { completeWithMessagesApi, streamWithMessagesApi } from "./protocols/messages-api.js";
import { completeWithResponsesApi, streamWithResponsesApi } from "./protocols/responses-api.js";
import { env } from "../env.js";
import { anthropicClient, hermesAgentClient, isHermesAgentConfigured, openaiClient, xaiClient } from "./providers.js";
import type { ChatMessage, Provider } from "./types.js";
type ProviderAdapterParams = {
model: string;
messages: ChatMessage[];
enabledTools?: string[];
userLocation?: string;
temperature?: number;
maxTokens?: number;
logContext?: ToolAwareCompletionParams["logContext"];
};
export type ProviderChatAdapter = {
provider: Provider;
complete(params: ProviderAdapterParams): Promise<ToolAwareCompletionResult>;
stream(params: ProviderAdapterParams): AsyncGenerator<ToolAwareStreamingEvent>;
};
type ChatProtocolId = "chat-completions" | "messages" | "responses";
type ChatProtocol = {
id: ChatProtocolId;
complete(params: ToolAwareCompletionParams): Promise<ToolAwareCompletionResult>;
stream(params: ToolAwareCompletionParams): AsyncGenerator<ToolAwareStreamingEvent>;
};
type ModelCatalogSpec = {
enabled?: () => boolean;
fetchModels(client: any): Promise<string[]>;
fallbackModels?: () => string[];
};
type ProviderBackendSpec = {
createClient: () => any;
plainProtocol: ChatProtocol;
toolProtocol?: ChatProtocol;
managedTools?: boolean;
modelCatalog?: ModelCatalogSpec;
};
const chatCompletionsProtocol: ChatProtocol = {
id: "chat-completions",
complete: completeWithChatCompletionsApi,
stream: streamWithChatCompletionsApi,
};
const messagesProtocol: ChatProtocol = {
id: "messages",
complete: completeWithMessagesApi,
stream: streamWithMessagesApi,
};
const responsesProtocol: ChatProtocol = {
id: "responses",
complete: completeWithResponsesApi,
stream: streamWithResponsesApi,
};
function uniqSorted(values: string[]) {
return [...new Set(values.map((value) => value.trim()).filter(Boolean))].sort((a, b) => a.localeCompare(b));
}
function modelIdsFromListResponse(page: any) {
return Array.isArray(page?.data)
? page.data.map((model: any) => model?.id).filter((id: unknown): id is string => typeof id === "string")
: [];
}
function isLikelyResponsesApiModel(model: string) {
const id = model.toLowerCase();
if (id.includes("embedding") || id.includes("moderation")) return false;
if (id.includes("audio") || id.includes("realtime") || id.includes("transcribe") || id.includes("tts")) return false;
if (id.includes("image") || id.includes("dall-e") || id.includes("sora")) return false;
if (id.includes("search") || id.includes("computer-use")) return false;
return /^(gpt-|o\d|chatgpt-)/.test(id);
}
function withClient(params: ProviderAdapterParams, client: any, enabledTools?: string[]): ToolAwareCompletionParams {
return {
client,
model: params.model,
messages: params.messages,
enabledTools,
userLocation: params.userLocation,
temperature: params.temperature,
maxTokens: params.maxTokens,
logContext: params.logContext,
};
}
function selectChatProtocol(spec: ProviderBackendSpec, params: Pick<ProviderAdapterParams, "enabledTools">) {
const enabledTools = normalizeEnabledChatTools(params.enabledTools);
const useManagedTools = spec.managedTools === true && spec.toolProtocol && enabledTools.length > 0;
return {
protocol: useManagedTools ? spec.toolProtocol! : spec.plainProtocol,
enabledTools: useManagedTools ? enabledTools : [],
managedTools: Boolean(useManagedTools),
};
}
function createProviderChatAdapter(provider: Provider, spec: ProviderBackendSpec): ProviderChatAdapter {
return {
provider,
complete(params) {
const selected = selectChatProtocol(spec, params);
return selected.protocol.complete(withClient(params, spec.createClient(), selected.enabledTools));
},
stream(params) {
const selected = selectChatProtocol(spec, params);
return selected.protocol.stream(withClient(params, spec.createClient(), selected.enabledTools));
},
};
}
const backendSpecs: Record<Provider, ProviderBackendSpec> = {
openai: {
createClient: openaiClient,
plainProtocol: chatCompletionsProtocol,
toolProtocol: responsesProtocol,
managedTools: true,
modelCatalog: {
async fetchModels(client) {
const page = await client.models.list();
return modelIdsFromListResponse(page).filter(isLikelyResponsesApiModel);
},
},
},
anthropic: {
createClient: anthropicClient,
plainProtocol: messagesProtocol,
toolProtocol: messagesProtocol,
managedTools: true,
modelCatalog: {
async fetchModels(client) {
const page = await client.models.list({ limit: 200 });
return modelIdsFromListResponse(page);
},
},
},
xai: {
createClient: xaiClient,
plainProtocol: chatCompletionsProtocol,
toolProtocol: chatCompletionsProtocol,
managedTools: true,
modelCatalog: {
async fetchModels(client) {
const page = await client.models.list();
return modelIdsFromListResponse(page);
},
},
},
"hermes-agent": {
createClient: hermesAgentClient,
plainProtocol: chatCompletionsProtocol,
managedTools: false,
modelCatalog: {
enabled: isHermesAgentConfigured,
async fetchModels(client) {
const page = await client.models.list();
const models = modelIdsFromListResponse(page);
if (env.HERMES_AGENT_MODEL) models.push(env.HERMES_AGENT_MODEL);
return models;
},
fallbackModels() {
return env.HERMES_AGENT_MODEL ? [env.HERMES_AGENT_MODEL] : [];
},
},
},
};
const providerChatAdapters: Record<Provider, ProviderChatAdapter> = Object.fromEntries(
Object.entries(backendSpecs).map(([provider, spec]) => [provider, createProviderChatAdapter(provider as Provider, spec)])
) as Record<Provider, ProviderChatAdapter>;
export function getProviderChatAdapter(provider: Provider) {
return providerChatAdapters[provider];
}
export function describeProviderChatBackend(provider: Provider, enabledTools?: string[]) {
const selected = selectChatProtocol(backendSpecs[provider], { enabledTools });
return {
provider,
protocol: selected.protocol.id,
managedTools: selected.managedTools,
enabledTools: selected.enabledTools,
};
}
export function listModelCatalogProviders(): Provider[] {
return (Object.entries(backendSpecs) as [Provider, ProviderBackendSpec][])
.filter(([, spec]) => {
const catalog = spec.modelCatalog;
return catalog !== undefined && catalog.enabled?.() !== false;
})
.map(([provider]) => provider);
}
export async function fetchProviderCatalogModels(provider: Provider) {
const spec = backendSpecs[provider].modelCatalog;
if (!spec) return [];
return uniqSorted(await spec.fetchModels(backendSpecs[provider].createClient()));
}
export function getProviderCatalogFallbackModels(provider: Provider) {
return uniqSorted(backendSpecs[provider].modelCatalog?.fallbackModels?.() ?? []);
}

View File

@@ -2,15 +2,28 @@ import type { Provider } from "./types.js";
type PrismaProvider = Exclude<Provider, "hermes-agent"> | "hermes_agent";
const apiToPrismaProvider = {
openai: "openai",
anthropic: "anthropic",
xai: "xai",
"hermes-agent": "hermes_agent",
} as const satisfies Record<Provider, PrismaProvider>;
const prismaToApiProvider = {
openai: "openai",
anthropic: "anthropic",
xai: "xai",
hermes_agent: "hermes-agent",
"hermes-agent": "hermes-agent",
} as const satisfies Record<PrismaProvider | "hermes-agent", Provider>;
export function toPrismaProvider(provider: Provider): PrismaProvider {
return provider === "hermes-agent" ? "hermes_agent" : provider;
return apiToPrismaProvider[provider];
}
export function fromPrismaProvider(provider: unknown): Provider | null {
if (provider === null || provider === undefined) return null;
if (provider === "hermes_agent" || provider === "hermes-agent") return "hermes-agent";
if (provider === "openai" || provider === "anthropic" || provider === "xai") return provider;
return null;
return prismaToApiProvider[provider as keyof typeof prismaToApiProvider] ?? null;
}
export function serializeProviderFields<T extends Record<string, any>>(value: T): T {

View File

@@ -1,15 +1,10 @@
import { performance } from "node:perf_hooks";
import { prisma } from "../db.js";
import { anthropicClient, hermesAgentClient, openaiClient, xaiClient } from "./providers.js";
import {
buildToolLogMessageData,
normalizeEnabledChatTools,
runPlainChatCompletionsStream,
runToolAwareChatCompletionsStream,
runToolAwareOpenAIChatStream,
type ToolExecutionEvent,
} from "./chat-tools.js";
import { buildAnthropicConversationMessage, getAnthropicSystemPrompt } from "./message-content.js";
import { getProviderChatAdapter } from "./provider-adapters.js";
import { toPrismaProvider } from "./provider-ids.js";
import type { MultiplexRequest, Provider } from "./types.js";
@@ -75,119 +70,48 @@ export async function* runMultiplexStream(req: MultiplexRequest): AsyncGenerator
let raw: unknown = { streamed: true };
try {
if (req.provider === "openai" || req.provider === "xai" || req.provider === "hermes-agent") {
const client = req.provider === "openai" ? openaiClient() : req.provider === "xai" ? xaiClient() : hermesAgentClient();
const enabledTools = normalizeEnabledChatTools(req.enabledTools);
const streamEvents =
req.provider === "openai" && enabledTools.length > 0
? runToolAwareOpenAIChatStream({
client,
model: req.model,
messages: req.messages,
enabledTools,
userLocation: req.userLocation,
temperature: req.temperature,
maxTokens: req.maxTokens,
logContext: {
provider: req.provider,
model: req.model,
chatId: chatId ?? undefined,
},
})
: req.provider === "hermes-agent" || enabledTools.length === 0
? runPlainChatCompletionsStream({
client,
model: req.model,
messages: req.messages,
userLocation: req.userLocation,
temperature: req.temperature,
maxTokens: req.maxTokens,
logContext: {
provider: req.provider,
model: req.model,
chatId: chatId ?? undefined,
},
})
: runToolAwareChatCompletionsStream({
client,
model: req.model,
messages: req.messages,
enabledTools,
userLocation: req.userLocation,
temperature: req.temperature,
maxTokens: req.maxTokens,
logContext: {
provider: req.provider,
model: req.model,
chatId: chatId ?? undefined,
},
});
for await (const ev of streamEvents) {
if (ev.type === "delta") {
text += ev.text;
yield { type: "delta", text: ev.text };
continue;
}
if (ev.type === "tool_call") {
if (ev.event.status !== "initiated" && shouldPersist && chatId) {
const toolMessage = buildToolLogMessageData(chatId, ev.event);
await prisma.message.create({
data: {
chatId: toolMessage.chatId,
role: toolMessage.role as any,
content: toolMessage.content,
name: toolMessage.name,
metadata: toolMessage.metadata as any,
},
});
}
yield { type: "tool_call", event: ev.event };
continue;
}
raw = ev.result.raw;
usage = ev.result.usage;
text = ev.result.text;
}
} else if (req.provider === "anthropic") {
const client = anthropicClient();
const system = getAnthropicSystemPrompt(req.messages, req.userLocation);
const msgs = req.messages.filter((message) => message.role !== "system").map((message) => buildAnthropicConversationMessage(message));
const stream = await client.messages.create({
const adapter = getProviderChatAdapter(req.provider);
const streamEvents = adapter.stream({
model: req.model,
messages: req.messages,
enabledTools: req.enabledTools,
userLocation: req.userLocation,
temperature: req.temperature,
maxTokens: req.maxTokens,
logContext: {
provider: req.provider,
model: req.model,
system,
max_tokens: req.maxTokens ?? 1024,
temperature: req.temperature,
messages: msgs as any,
stream: true,
});
chatId: chatId ?? undefined,
},
});
for await (const ev of stream as any as AsyncIterable<any>) {
// Anthropic streaming events include content_block_delta with text_delta
if (ev?.type === "content_block_delta" && ev?.delta?.type === "text_delta") {
const delta = ev.delta.text ?? "";
if (delta) {
text += delta;
yield { type: "delta", text: delta };
}
}
// capture usage if present on message_delta
if (ev?.type === "message_delta" && ev?.usage) {
usage = {
inputTokens: ev.usage.input_tokens,
outputTokens: ev.usage.output_tokens,
totalTokens:
(ev.usage.input_tokens ?? 0) + (ev.usage.output_tokens ?? 0),
};
}
// some streams end with message_stop
for await (const ev of streamEvents) {
if (ev.type === "delta") {
text += ev.text;
yield { type: "delta", text: ev.text };
continue;
}
raw = { streamed: true, provider: "anthropic" };
} else {
throw new Error(`unknown provider: ${req.provider}`);
if (ev.type === "tool_call") {
if (ev.event.status !== "initiated" && shouldPersist && chatId) {
const toolMessage = buildToolLogMessageData(chatId, ev.event);
await prisma.message.create({
data: {
chatId: toolMessage.chatId,
role: toolMessage.role as any,
content: toolMessage.content,
name: toolMessage.name,
metadata: toolMessage.metadata as any,
},
});
}
yield { type: "tool_call", event: ev.event };
continue;
}
raw = ev.result.raw;
usage = ev.result.usage;
text = ev.result.text;
}
const latencyMs = Math.round(performance.now() - t0);

View File

@@ -1,12 +1,9 @@
import assert from "node:assert/strict";
import test from "node:test";
import {
runPlainChatCompletionsStream,
runToolAwareChatCompletions,
runToolAwareChatCompletionsStream,
runToolAwareOpenAIChatStream,
type ToolAwareStreamingEvent,
} from "../src/llm/chat-tools.js";
import { type ToolAwareStreamingEvent } from "../src/llm/chat-tools.js";
import { completeWithChatCompletionsApi, streamWithChatCompletionsApi } from "../src/llm/protocols/chat-completions-api.js";
import { completeWithMessagesApi, streamWithMessagesApi } from "../src/llm/protocols/messages-api.js";
import { streamWithResponsesApi } from "../src/llm/protocols/responses-api.js";
async function* streamFrom(events: any[]) {
for (const event of events) {
@@ -23,7 +20,7 @@ async function collectEvents(iterable: AsyncIterable<ToolAwareStreamingEvent>) {
return events;
}
test("OpenAI Responses stream emits text deltas as they arrive", async () => {
test("Responses API stream emits text deltas as they arrive", async () => {
const outputMessage = {
id: "msg_1",
type: "message",
@@ -53,7 +50,7 @@ test("OpenAI Responses stream emits text deltas as they arrive", async () => {
};
const events = await collectEvents(
runToolAwareOpenAIChatStream({
streamWithResponsesApi({
client: client as any,
model: "gpt-test",
messages: [{ role: "user", content: "Say hello" }],
@@ -71,7 +68,7 @@ test("OpenAI Responses stream emits text deltas as they arrive", async () => {
assert.equal(events.at(-1)?.type === "done" ? events.at(-1)?.result.text : null, "Hello");
});
test("OpenAI-compatible Chat Completions stream emits text deltas as they arrive", async () => {
test("Chat Completions API stream emits text deltas as they arrive", async () => {
const client = {
chat: {
completions: {
@@ -90,7 +87,7 @@ test("OpenAI-compatible Chat Completions stream emits text deltas as they arrive
};
const events = await collectEvents(
runToolAwareChatCompletionsStream({
streamWithChatCompletionsApi({
client: client as any,
model: "grok-test",
messages: [{ role: "user", content: "Say hello" }],
@@ -125,10 +122,11 @@ test("plain Chat Completions stream does not send Sybil-managed tools", async ()
};
const events = await collectEvents(
runPlainChatCompletionsStream({
streamWithChatCompletionsApi({
client: client as any,
model: "hermes-agent",
messages: [{ role: "user", content: "Say hi" }],
enabledTools: [],
})
);
@@ -189,7 +187,7 @@ test("fetch_url sends browser-like navigation headers", async () => {
},
};
const result = await runToolAwareChatCompletions({
const result = await completeWithChatCompletionsApi({
client: client as any,
model: "grok-test",
messages: [{ role: "user", content: "Fetch CPI PDF" }],
@@ -215,7 +213,81 @@ test("fetch_url sends browser-like navigation headers", async () => {
}
});
test("OpenAI-compatible Chat Completions stream emits initiated and terminal tool call updates", async () => {
test("Messages API executes tool_use blocks and sends tool_result follow-up", async () => {
const originalFetch = globalThis.fetch;
const fetchCalls: Array<{ input: RequestInfo | URL; init?: RequestInit }> = [];
globalThis.fetch = (async (input: RequestInfo | URL, init?: RequestInit) => {
fetchCalls.push({ input, init });
return new Response("<!doctype html><title>Example</title><main>Tool result body</main>", {
status: 200,
headers: { "content-type": "text/html; charset=utf-8" },
});
}) as typeof fetch;
try {
const requestBodies: any[] = [];
const client = {
messages: {
create: async (body: any) => {
requestBodies.push(body);
if (requestBodies.length === 1) {
return {
content: [
{
type: "tool_use",
id: "toolu_1",
name: "fetch_url",
input: { url: "https://example.com/article" },
},
],
usage: { input_tokens: 3, output_tokens: 2 },
};
}
return {
content: [{ type: "text", text: "Fetched" }],
usage: { input_tokens: 5, output_tokens: 1 },
};
},
},
};
const result = await completeWithMessagesApi({
client: client as any,
model: "claude-test",
messages: [{ role: "user", content: "Fetch the article" }],
});
assert.equal(result.text, "Fetched");
assert.equal(fetchCalls.length, 1);
assert.equal(String(fetchCalls[0]?.input), "https://example.com/article");
assert.equal(requestBodies.length, 2);
assert.equal(requestBodies[0]?.model, "claude-test");
assert.equal(requestBodies[0]?.tool_choice?.type, "auto");
const fetchTool = requestBodies[0]?.tools?.find((tool: any) => tool.name === "fetch_url");
assert.equal(fetchTool?.input_schema?.type, "object");
assert.equal(fetchTool?.input_schema?.properties?.url?.type, "string");
const secondMessages = requestBodies[1]?.messages ?? [];
assert.equal(secondMessages.at(-2)?.role, "assistant");
assert.equal(secondMessages.at(-2)?.content?.[0]?.type, "tool_use");
assert.equal(secondMessages.at(-1)?.role, "user");
const toolResult = secondMessages.at(-1)?.content?.[0];
assert.equal(toolResult?.type, "tool_result");
assert.equal(toolResult?.tool_use_id, "toolu_1");
assert.equal(toolResult?.is_error, false);
assert.equal(JSON.parse(toolResult?.content ?? "{}").ok, true);
assert.equal(result.toolEvents[0]?.toolCallId, "toolu_1");
assert.equal(result.toolEvents[0]?.status, "completed");
assert.equal(result.usage?.inputTokens, 8);
assert.equal(result.usage?.outputTokens, 3);
assert.equal(result.usage?.totalTokens, 11);
} finally {
globalThis.fetch = originalFetch;
}
});
test("Chat Completions API stream emits initiated and terminal tool call updates", async () => {
let requestCount = 0;
const client = {
chat: {
@@ -256,7 +328,7 @@ test("OpenAI-compatible Chat Completions stream emits initiated and terminal too
};
const events = await collectEvents(
runToolAwareChatCompletionsStream({
streamWithChatCompletionsApi({
client: client as any,
model: "grok-test",
messages: [{ role: "user", content: "Use a tool" }],
@@ -280,3 +352,122 @@ test("OpenAI-compatible Chat Completions stream emits initiated and terminal too
assert.equal(typeof toolEvents[1]?.durationMs, "number");
assert.equal(events.at(-1)?.type === "done" ? events.at(-1)?.result.text : null, "Done");
});
test("Messages API stream emits initiated and terminal tool call updates", async () => {
let requestCount = 0;
const requestBodies: any[] = [];
const client = {
messages: {
create: async (body: any) => {
requestCount += 1;
requestBodies.push(body);
if (requestCount === 1) {
return streamFrom([
{
type: "message_start",
message: {
usage: { input_tokens: 3, output_tokens: 0 },
},
},
{
type: "content_block_start",
index: 0,
content_block: { type: "text", text: "" },
},
{
type: "content_block_delta",
index: 0,
delta: { type: "text_delta", text: "I'll check that." },
},
{ type: "content_block_stop", index: 0 },
{
type: "content_block_start",
index: 1,
content_block: {
type: "tool_use",
id: "toolu_1",
name: "unknown_tool",
input: {},
},
},
{
type: "content_block_delta",
index: 1,
delta: { type: "input_json_delta", partial_json: "{\"query\":\"current weather\"}" },
},
{ type: "content_block_stop", index: 1 },
{
type: "message_delta",
delta: { stop_reason: "tool_use", stop_sequence: null },
usage: { output_tokens: 2 },
},
{ type: "message_stop" },
]);
}
return streamFrom([
{
type: "message_start",
message: {
usage: { input_tokens: 4, output_tokens: 0 },
},
},
{
type: "content_block_start",
index: 0,
content_block: { type: "text", text: "" },
},
{
type: "content_block_delta",
index: 0,
delta: { type: "text_delta", text: "Done" },
},
{ type: "content_block_stop", index: 0 },
{
type: "message_delta",
delta: { stop_reason: "end_turn", stop_sequence: null },
usage: { output_tokens: 1 },
},
{ type: "message_stop" },
]);
},
},
};
const events = await collectEvents(
streamWithMessagesApi({
client: client as any,
model: "claude-test",
messages: [{ role: "user", content: "Use a tool" }],
})
);
assert.deepEqual(
events.map((event) => event.type),
["tool_call", "tool_call", "delta", "done"]
);
assert.equal(requestBodies[0]?.stream, true);
assert.equal(requestBodies[0]?.tools?.some((tool: any) => tool.name === "fetch_url"), true);
const secondMessages = requestBodies[1]?.messages ?? [];
assert.equal(secondMessages.at(-2)?.role, "assistant");
assert.equal(secondMessages.at(-2)?.content?.[0]?.type, "text");
assert.equal(secondMessages.at(-2)?.content?.[0]?.text, "I'll check that.");
assert.equal(secondMessages.at(-2)?.content?.[1]?.type, "tool_use");
assert.deepEqual(secondMessages.at(-2)?.content?.[1]?.input, { query: "current weather" });
const toolResult = secondMessages.at(-1)?.content?.[0];
assert.equal(toolResult?.type, "tool_result");
assert.equal(toolResult?.tool_use_id, "toolu_1");
assert.equal(toolResult?.is_error, true);
assert.match(JSON.parse(toolResult?.content ?? "{}").error ?? "", /Unknown tool: unknown_tool/);
const toolEvents = events.flatMap((event) => (event.type === "tool_call" ? [event.event] : []));
assert.equal(toolEvents[0]?.toolCallId, "toolu_1");
assert.equal(toolEvents[0]?.status, "initiated");
assert.equal(toolEvents[1]?.toolCallId, "toolu_1");
assert.equal(toolEvents[1]?.status, "failed");
assert.match(toolEvents[1]?.error ?? "", /Unknown tool: unknown_tool/);
assert.equal(events.at(-1)?.type === "done" ? events.at(-1)?.result.text : null, "Done");
assert.equal(events.at(-1)?.type === "done" ? events.at(-1)?.result.usage?.inputTokens : null, 7);
assert.equal(events.at(-1)?.type === "done" ? events.at(-1)?.result.usage?.outputTokens : null, 3);
});

View File

@@ -1,6 +1,6 @@
import assert from "node:assert/strict";
import test from "node:test";
import { buildSystemPromptAugmentation, getAnthropicSystemPrompt } from "../src/llm/message-content.js";
import { buildSystemPromptAugmentation, buildTopLevelSystemPrompt } from "../src/llm/message-content.js";
test("system prompt augmentation includes date and default location", () => {
const prompt = buildSystemPromptAugmentation(undefined, new Date("2026-05-24T15:30:00Z"));
@@ -14,8 +14,8 @@ test("system prompt augmentation uses provided user location", () => {
assert.equal(prompt, "Current date: 2026-05-24.\nUser location: New York, NY.");
});
test("Anthropic system prompt includes runtime context with existing system messages", () => {
const prompt = getAnthropicSystemPrompt(
test("top-level system prompt includes runtime context with existing system messages", () => {
const prompt = buildTopLevelSystemPrompt(
[{ role: "system", content: "Use concise answers." }],
"Los Angeles, CA"
);

View File

@@ -0,0 +1,36 @@
import assert from "node:assert/strict";
import test from "node:test";
import { describeProviderChatBackend } from "../src/llm/provider-adapters.js";
test("provider backend registry selects chat protocol and managed-tool mode", () => {
assert.deepEqual(describeProviderChatBackend("openai", []), {
provider: "openai",
protocol: "chat-completions",
managedTools: false,
enabledTools: [],
});
assert.deepEqual(describeProviderChatBackend("openai", ["web_search"]), {
provider: "openai",
protocol: "responses",
managedTools: true,
enabledTools: ["web_search"],
});
assert.deepEqual(describeProviderChatBackend("anthropic", ["web_search"]), {
provider: "anthropic",
protocol: "messages",
managedTools: true,
enabledTools: ["web_search"],
});
assert.deepEqual(describeProviderChatBackend("xai", ["web_search"]), {
provider: "xai",
protocol: "chat-completions",
managedTools: true,
enabledTools: ["web_search"],
});
assert.deepEqual(describeProviderChatBackend("hermes-agent", ["web_search"]), {
provider: "hermes-agent",
protocol: "chat-completions",
managedTools: false,
enabledTools: [],
});
});

View File

@@ -1,5 +1,5 @@
import { useMemo, useRef, useState } from "preact/hooks";
import type { JSX } from "preact";
import { useEffect, useMemo, useRef, useState } from "preact/hooks";
import type { ComponentChildren, JSX } from "preact";
import { cn } from "@/lib/utils";
import { ChatAttachmentList } from "@/components/chat/chat-attachment-list";
import { getMessageAttachments, type Message } from "@/lib/api";
@@ -142,6 +142,14 @@ function buildMessageRenderItems(messages: Message[]) {
return items;
}
function getToolCallMessageIDs(messages: Message[]) {
const ids = new Set<string>();
for (const message of messages) {
if (message.role === "tool" && asToolLogMetadata(message.metadata)) ids.add(message.id);
}
return ids;
}
function getToolStackHeight(messageCount: number, expanded: boolean) {
const visibleCount = Math.min(messageCount, COLLAPSED_TOOL_STACK_LIMIT);
return expanded
@@ -246,10 +254,10 @@ function ToolCallCard({
className={cn(
"inline-flex min-w-0 items-start gap-3 overflow-hidden rounded-xl border px-3 py-2.5 shadow-[inset_0_1px_0_hsl(180_100%_88%_/_0.06)]",
isFailed
? "border-rose-400/34 bg-[linear-gradient(90deg,hsl(350_72%_44%_/_0.18),hsl(342_66%_9%_/_0.72))]"
? "border-rose-400/44 bg-[linear-gradient(90deg,hsl(350_64%_20%),hsl(342_58%_9%))]"
: isInitiated
? "border-amber-300/34 bg-[linear-gradient(90deg,hsl(43_74%_30%_/_0.34),hsl(260_48%_13%_/_0.74))]"
: "border-cyan-400/34 bg-[linear-gradient(90deg,hsl(184_89%_21%_/_0.70),hsl(208_66%_12%_/_0.78))]",
? "border-amber-300/44 bg-[linear-gradient(90deg,hsl(43_72%_20%),hsl(260_48%_13%))]"
: "border-cyan-400/44 bg-[linear-gradient(90deg,hsl(184_82%_14%),hsl(208_66%_10%))]",
className
)}
style={style}
@@ -280,15 +288,40 @@ function ToolCallCard({
);
}
function ToolCallStackCardSurface({
messageID,
animateEntry,
isHidden,
children,
}: {
messageID: string;
animateEntry: boolean;
isHidden: boolean;
children: ComponentChildren;
}) {
const [shouldAnimateEntry] = useState(() => animateEntry);
return (
<div
className={cn("tool-call-stack-card-surface", shouldAnimateEntry && !isHidden && "tool-call-stack-card-enter")}
data-tool-stack-card-id={messageID}
>
{children}
</div>
);
}
function ToolCallStack({
groupKey,
messages,
expanded,
entryMessageIDs,
onToggle,
}: {
groupKey: string;
messages: Message[];
expanded: boolean;
entryMessageIDs: Set<string>;
onToggle: (groupKey: string) => void;
}) {
const hiddenCount = Math.max(0, messages.length - COLLAPSED_TOOL_STACK_LIMIT);
@@ -324,6 +357,7 @@ function ToolCallStack({
{messages.map((message, index) => {
const depth = messages.length - index - 1;
const isHidden = !expanded && depth >= COLLAPSED_TOOL_STACK_LIMIT;
const shouldAnimateEntry = entryMessageIDs.has(message.id) && !isHidden;
return (
<div
key={message.id}
@@ -335,12 +369,9 @@ function ToolCallStack({
style={getToolStackStyle(index, messages.length, expanded, motionDirection)}
aria-hidden={isHidden ? "true" : undefined}
>
<div
className={cn("tool-call-stack-card-surface", !isHidden && "tool-call-stack-card-enter")}
data-tool-stack-card-id={message.id}
>
<ToolCallStackCardSurface messageID={message.id} animateEntry={shouldAnimateEntry} isHidden={isHidden}>
<ToolCallCard message={message} className="tool-call-stack-card-glass w-full max-w-full" />
</div>
</ToolCallStackCardSurface>
</div>
);
})}
@@ -367,8 +398,26 @@ function ToolCallStack({
export function ChatMessagesPanel({ messages, isLoading, isSending }: Props) {
const hasPendingAssistant = messages.some((message) => message.id.startsWith("temp-assistant-") && message.content.trim().length === 0);
const renderItems = useMemo(() => buildMessageRenderItems(messages), [messages]);
const toolCallMessageIDs = useMemo(() => getToolCallMessageIDs(messages), [messages]);
const seenToolCallMessageIDsRef = useRef<Set<string> | null>(null);
const entryToolCallMessageIDs = useMemo(() => {
const seenIDs = seenToolCallMessageIDsRef.current;
if (!seenIDs) return new Set<string>();
const entryIDs = new Set<string>();
for (const id of toolCallMessageIDs) {
if (!seenIDs.has(id)) entryIDs.add(id);
}
return entryIDs;
}, [toolCallMessageIDs]);
const [expandedToolGroups, setExpandedToolGroups] = useState<Set<string>>(() => new Set());
useEffect(() => {
if (!toolCallMessageIDs.size) return;
const seenIDs = seenToolCallMessageIDsRef.current ?? new Set<string>();
for (const id of toolCallMessageIDs) seenIDs.add(id);
seenToolCallMessageIDsRef.current = seenIDs;
}, [toolCallMessageIDs]);
const toggleToolGroup = (groupKey: string) => {
setExpandedToolGroups((current) => {
const next = new Set(current);
@@ -390,6 +439,7 @@ export function ChatMessagesPanel({ messages, isLoading, isSending }: Props) {
groupKey={item.key}
messages={item.messages}
expanded={expandedToolGroups.has(item.key)}
entryMessageIDs={entryToolCallMessageIDs}
onToggle={toggleToolGroup}
/>
);

View File

@@ -177,7 +177,7 @@ textarea {
}
.tool-call-stack-card-glass {
backdrop-filter: blur(10px);
backdrop-filter: none;
}
.tool-call-stack-card-enter {