* feat: add --provider CLI flag for multi-provider support
Adds a --provider flag that maps friendly provider names to the
environment variables the codebase uses for provider detection.
No more manual env-var configuration — users can now simply run:
openclaude --provider openai --model gpt-4o
openclaude --provider gemini --model gemini-2.0-flash
openclaude --provider ollama --model llama3.2
openclaude --provider bedrock
openclaude --provider vertex
Implementation details:
- providerFlag.ts: core logic — maps provider names to env vars,
uses ??= so explicit env vars always win over the flag defaults
- providerFlag.test.ts: 18 tests covering all 7 providers,
error messages, model passthrough, and env-var precedence
- cli.tsx: early fast-path (mirrors --bare pattern) — sets env
vars before Commander option-building and module constants run
- main.tsx: adds --provider to Commander option chain for --help
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix: custom OPENAI_BASE_URL always wins over Codex model alias detection
When OPENAI_MODEL=gpt-5.4 (or gpt-5.4-mini) and a custom OPENAI_BASE_URL
is set (Azure, OpenRouter, etc), the transport was incorrectly forced to
codex_responses because gpt-5.4 is in CODEX_ALIAS_MODELS. This caused
requests to be sent with Codex auth instead of the user's API key,
resulting in 401 Unauthorized errors.
Fix: only use codex_responses when the base URL is explicitly the Codex
endpoint, OR when no custom base URL is set and the model is a Codex
alias. An explicit OPENAI_BASE_URL always takes priority over model-name
based Codex detection.
Verified locally: gpt-5.4 via OpenRouter now correctly shows
Provider=OpenRouter, Endpoint=https://openrouter.ai/api/v1 instead of
routing to chatgpt.com/backend-api/codex.
Fixes#200, #203
---------
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
React 19 requires `supportsMicrotasks: true` in the reconciler host
config so it can flush state updates from passive effects via
queueMicrotask. Without this, state updates triggered inside
useMcpConnectivityStatus were silently dropped, corrupting React's
internal executionContext and causing all keyboard input to freeze
after the "N MCP server(s) need auth" notification appeared.
Root cause (three-part fix):
1. reconciler.ts: declare supportsMicrotasks + scheduleMicrotask so
React 19 schedules passive-effect flushes correctly.
2. useMcpConnectivityStatus.tsx: wrap the MCP auth notification effect
in try/catch so any unexpected throw does not propagate into
flushPassiveEffects and permanently corrupt executionContext.
3. notifications.tsx: wrap addNotification, removeNotification, and
processQueue in try/catch for the same reason — these are called
from 12+ notification hooks across passive effects.
Also fixes a pre-existing test isolation bug in context.test.ts where
assigning `undefined` to process.env produced the string "undefined",
polluting the env for subsequent test files.
Resolves: #169, #205, #77
Images in the clipboard could fail to become pasted image attachments in OpenClaude. User-facing symptom: paste would detect that an image existed, but nothing would appear in the prompt, and bundled builds could also fail while converting BMP clipboard images into a format OpenClaude can send to the model.
Linux clipboard image paste had drifted between detection and extraction. checkImage accepted png/jpeg/jpg/gif/webp/bmp, but saveImage only tried image/png and image/bmp. When the clipboard advertised a JPEG, GIF, or WebP image, OpenClaude concluded that an image was present and then failed to write the temp screenshot file, so the paste path returned null and nothing was inserted into the prompt.
Bundled OpenClaude builds had a second failure mode. The build replaces image-processor-napi and sharp with explicit stub modules in bundled mode. getImageProcessor() treated those stubs as real processors, so BMP clipboard images reached sharp(imageBuffer).png() and then failed before they could be converted into a pasteable PNG for OpenClaude.
Keep the Linux clipboard commands generated from one MIME type list and reject __stub-marked image processors up front instead of failing in the middle of image paste.
The Gemini provider uses Google's OpenAI-compatible endpoint
(generativelanguage.googleapis.com/v1beta/openai) but the client
routing condition in client.ts only checked CLAUDE_CODE_USE_OPENAI
and CLAUDE_CODE_USE_GITHUB — CLAUDE_CODE_USE_GEMINI was missing.
This caused every Gemini request to fall through to the Anthropic
client path. Since ANTHROPIC_API_KEY is not set when using Gemini,
the Anthropic SDK threw:
"Could not resolve authentication method. Expected either apiKey
or authToken to be set."
Fix: add CLAUDE_CODE_USE_GEMINI to the OpenAI shim routing condition
so Gemini requests correctly reach createOpenAIShimClient(), which
maps GEMINI_API_KEY → OPENAI_API_KEY and sets OPENAI_BASE_URL to
the Google endpoint.
Closes#176
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Previously getRateLimitResetDelayMs only read the Anthropic-specific
'anthropic-ratelimit-unified-reset' header (Unix timestamp), returning
null for every other provider. This meant OpenAI, GitHub, and Codex
users in persistent retry mode (CLAUDE_CODE_UNATTENDED_RETRY=1) always
fell back to dumb exponential backoff even when the server included an
exact reset time in the response headers.
This change makes the function provider-aware:
- firstParty (Anthropic): existing behaviour preserved — reads
'anthropic-ratelimit-unified-reset' Unix timestamp
- openai / codex / github: reads 'x-ratelimit-reset-requests' and
'x-ratelimit-reset-tokens' (OpenAI relative duration strings like
"1s", "6m0s", "1h30m0s"), picks the larger of the two so retries
don't fire before both token and request limits have reset
- bedrock / vertex / foundry / gemini: returns null (no standard
reset header for these providers)
Adds parseOpenAIDuration() as an exported helper to convert OpenAI's
duration format into milliseconds.
16 new tests covering all provider paths and edge cases.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Finding 1 [CRITICAL] — sessionRunner leaks full process.env to child
Extract buildChildEnv() with an explicit allowlist of safe OS/runtime vars.
Child process no longer inherits ANTHROPIC_API_KEY, OPENAI_API_KEY, DB
credentials, or any other secret present in the parent shell environment.
Only CLAUDE_CODE_* bridge vars, PATH, HOME, and standard OS env are passed.
Finding 2 [HIGH] — USER_TYPE=ant activatable by external users
Add isAntEmployee() -> false constant in src/utils/buildConfig.ts.
Replace all three direct process.env.USER_TYPE === 'ant' checks in
setup.ts and onChangeAppState.ts so no external user can activate
Anthropic-internal code paths (commit attribution, system prompt clearing,
dangerously-skip-permissions bypass) by setting USER_TYPE in their shell.
Finding 3 [HIGH] — memoryScan.ts unlimited directory walk
Add MAX_DEPTH=3 guard on readdir({ recursive: true }) results.
Deep or symlink-looped memory directories no longer cause an unbounded
blocking walk before the MAX_MEMORY_FILES cap takes effect.
Finding 5 [HIGH] — buildSdkUrl uses string.includes for protocol detection
Replace apiBaseUrl.includes('localhost') with new URL(apiBaseUrl).hostname
comparison so a remote URL containing 'localhost' in its path no longer
incorrectly gets ws:// (unencrypted) instead of wss://.
Finding 6 [HIGH] — upstream proxy writes unvalidated CA cert to disk
Add isValidPemContent() validation before writeFile in the CA cert download
path. A compromised proxy sending non-PEM data (HTML, JSON, scripts) is now
rejected before it can be appended to the system CA bundle.
Each fix is covered by new unit tests (25 tests across 5 new test files).
All 52 tests pass. Build verified clean on v0.1.7.
Fixes#42
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
WebSearch is currently disabled for all non-Anthropic providers (OpenAI
shim, DeepSeek, Ollama, etc.) because those providers have no native
search backend. This adds Firecrawl as a fallback that activates when
FIRECRAWL_API_KEY is set, unlocking web search for every model
openclaude supports.
WebFetch uses basic HTTP + Turndown for HTML-to-markdown conversion,
which fails silently on JS-rendered SPAs and bot-protected pages.
Firecrawl scrape replaces the fetch layer when FIRECRAWL_API_KEY is set,
returning clean markdown that handles dynamic content correctly.
Changes:
- WebSearchTool: add runFirecrawlSearch() using @mendable/firecrawl-js,
respects allowed_domains (post-filter) and blocked_domains (-site: operators),
includes result snippets alongside links. shouldUseFirecrawl() ensures
firstParty/Vertex/Foundry/Codex providers keep their native backends.
- WebFetchTool: add scrapeWithFirecrawl(), drops into the existing
applyPromptToMarkdown() pipeline so prompt processing is unchanged.
- Remove "Web search is only available in the US" restriction from
prompt when Firecrawl is active (it works globally).
1. errors.ts: Add getCustomOffSwitchMessage() that returns a
provider-neutral message for 3P users instead of the hardcoded
"Opus is experiencing high load, please use /model to switch to
Sonnet" which is misleading for OpenAI/Gemini/Ollama users.
The original constant is preserved for backward-compatible string
matching in error handlers.
2. Onboarding.tsx: Skip the "approve API key" step when a 3P provider
is active. Previously, having ANTHROPIC_API_KEY in the environment
(e.g., from a previous Anthropic setup) triggered an irrelevant
Anthropic key approval UI even when using Gemini or OpenAI.
1. cli/update.ts: Block the update command for third-party providers.
The update mechanism downloads from Anthropic's GCS bucket, which
would silently replace the OpenClaude build (with the OpenAI shim)
with the upstream Claude Code binary (without it). Now shows an
actionable message directing users to rebuild from source.
2. codexShim.ts: Filter thinking blocks from assistant history, matching
the openaiShim behavior. Without this, thinking blocks were included
as plain text in assistant messages for the Codex transport but
excluded for the OpenAI transport — causing inconsistent history
when switching providers mid-session.
Three targeted fixes:
1. Replace Math.random() with crypto.randomUUID() for message and tool
call IDs in both openaiShim.ts and codexShim.ts. Math.random() is
not cryptographically secure and predictable in seeded environments.
2. Anchor Azure endpoint detection to parsed hostname instead of raw
URL regex. Adds support for Azure AI Foundry (services.ai.azure.com)
alongside existing cognitiveservices and openai Azure endpoints.
Prevents SSRF-style bypass via path segments.
3. Surface content safety filter blocks to the user. When Gemini or
Azure returns finish_reason 'content_filter' or 'safety', emit a
visible text block '[Content blocked by provider safety filter]'
instead of silently returning empty/truncated content with
stop_reason 'end_turn'. Applied to both streaming and non-streaming.
Two fixes in openaiContextWindows.ts:
1. Sort lookup keys by length descending in lookupByModel() so the most
specific prefix always wins. Without this, 'gpt-4-turbo-preview'
could match 'gpt-4' (8k) instead of 'gpt-4-turbo' (128k) depending
on V8's object key iteration order.
2. Update Llama 3.1/3.2/3.3 context windows from 8,192 to 128,000.
These models support 128k context natively (Meta official specs).
The previous 8k value was Ollama's default num_ctx, not the model's
actual capability, causing premature auto-compact warnings.
Two fixes for issue #133 where setting ANTHROPIC_API_KEY=dummy alongside
CLAUDE_CODE_USE_GEMINI=1 causes "Invalid API key" errors:
1. auth.ts: In the CI branch of getAnthropicApiKeyWithSource(), the
ANTHROPIC_API_KEY value was returned without checking isUsing3PServices().
A dummy key leaked into the Anthropic key resolution pipeline even when
Gemini was the active provider. Now guards with isUsing3PServices().
2. errors.ts: The x-api-key error handler surfaced "Invalid API key" for
any provider. Added getAPIProvider() === 'firstParty' guard so 3P users
see the real underlying error instead of a misleading auth message.
Note: The cli.tsx Gemini validation fix (originally part of this PR) was
independently implemented in PR #121 and is already on main.
OpenAI returns cached token counts in usage.prompt_tokens_details.cached_tokens
but the shim hardcoded cache_read_input_tokens to 0. This made prompt
caching invisible to the cost tracker and session summary even when
OpenAI's automatic caching was actively reducing costs.
Changes:
- Extend OpenAIStreamChunk usage interface with prompt_tokens_details
- Map cached_tokens to cache_read_input_tokens in convertChunkUsage()
- Same fix in _convertNonStreamingResponse() for non-streaming path
- cache_creation_input_tokens remains 0 (OpenAI auto-caching has no
creation cost — it is free and automatic)
