mirror of
https://github.com/outbackdingo/optimclaw.git
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feat(gemini_oauth): full Gemini CLI OAuth integration with Cloud Code API (#1356)
* feat: integrate Gemini CLI OAuth with Cloud Code API
- Add gemini_oauth.rs: full OAuth flow with PKCE, token refresh,
and Cloud Code project discovery (loadCodeAssist + onboardUser)
- Route preview/gemini-3 models through cloudcode-pa.googleapis.com
with proper project ID injection in request payload
- Trigger OAuth login during onboarding wizard (not first chat message)
- Support manual redirect URL paste as fallback (tokio::select race)
- Parse 429 rate-limit errors with retry_after from Google response
- Add static model list: gemini-1.5/2.0/2.5/3.0/3.1 variants
- Add GeminiOauthConfig with default credentials path (~/.gemini/)
* feat(gemini): implement function calling, generationConfig, and update models
- Implement function calling support (functionDeclarations, functionResponse)
- Add functionCall SSE parsing and empty stream retry support
- Add generationConfig (temperature, maxOutputTokens)
- Add thinkingConfig for Gemini 3 and thinking models
- Add toolConfig (functionCallingConfig.mode)
- Fix .expect() panics with .ok_or_else()
- Restrict oauth credentials file permissions to 0600
- Update docs and FEATURE_PARITY.md
- Update wizard to current Gemini 3.1 and 2.5 models
* fix: address code review issues in gemini-cli OAuth integration
- Add cache_read_input_tokens/cache_creation_input_tokens fields (value 0)
- Implement manual Debug for OAuthCredential to redact tokens
- Fix hardcoded /tmp: use GeminiOauthConfig::default_credentials_path()
- Replace emoji output with plain text markers
- Propagate Client::builder() errors instead of silent fallback
- Use tokio::fs for all file I/O in CredentialManager (was std::fs)
- Use if let Some(ref pid) to avoid consuming credential.project_id
- Extract uses_cloud_code_api() helper; route by major version (gemini-2+)
- Concatenate multiple system messages into systemInstruction
- Include functionCall parts in assistant message conversion
- Add 401 retry loop with allow_retry flag for auth failures
- Remove biased from tokio::select! in OAuth callback handler
- Remove hardcoded context_length 1M; vary by model family
- Change GOOG_API_CLIENT from Node.js spoof to gl-rust/1.0.0
- Implement list_models() with static model list
- Move create_gemini_oauth_provider() before test module (clippy)
- Fix 9 additional clippy warnings (collapsible_if, map_or, needless_borrow)
- Run cargo fmt
* Add dedicated regression tests for Gemini OAuth fixes
* style: fix formatting in Gemini OAuth regression tests
* feat(gemini-oauth): implement code review v3 refinements
- Add force_refresh() for 401 retry (bypass timestamp check)
- Standardize Gemini model list across docs, wizard, and provider
- Restore gemini-3 check for thinkingConfig
- Redact sensitive tokens in GoogleTokenRefreshResponse Debug output
- Use dynamic version for GOOG_API_CLIENT
- Improve model_metadata() context length heuristics
- Use strip_prefix("data:") for safer SSE parsing
- Skip re-auth in wizard if keeping existing provider
* feat(gemini_oauth): full Cloud Code API integration with project discovery
- Register gemini_oauth as a dedicated backend in config/llm.rs (skip
registry fallback, preserve backend name, suppress unknown-backend warning)
- Fix app.rs credential guard to exclude backends with dedicated configs
(gemini_oauth, bedrock) from the provider.is_none() check
- Auto-discover Cloud Code project_id via loadCodeAssist when credentials
lack it (e.g. created by the original Gemini CLI)
- Persist discovered project_id to credentials file for subsequent runs
- Add safety settings (BLOCK_NONE), gated behind GEMINI_SAFETY_BLOCK_NONE env
- Add thinkingConfig: budget-based for Gemini 2.5, level-based for Gemini 3.x
(without includeThoughts to avoid empty responses from reasoning.rs stripping)
- Add thought signature injection for Gemini 3.x preview APIs
- Add history curation to filter invalid model outputs before re-sending
- Add extended generationConfig env vars (topP, topK, seed, penalties,
responseMimeType, responseJsonSchema, cachedContent)
- Add custom headers support via GEMINI_CLI_CUSTOM_HEADERS
- Add API key auth mode (GEMINI_API_KEY + GEMINI_API_KEY_AUTH_MECHANISM)
- Add SSE metadata extraction (modelVersion, credits, promptFeedback,
groundingMetadata, citationMetadata, cachedContentTokenCount)
- Add countTokens API support
- Add new models to wizard (gemini-3.1-pro-preview-customtools,
gemini-3-pro-preview, gemini-3.1-flash-lite-preview)
- Update docs/LLM_PROVIDERS.md with new models and routing rules
- Rewrite regression tests with comprehensive coverage (23 unit tests pass)
* fix: CI violations — add safety comment on expect, fix fmt
- Add '// safety: hardcoded literal' to regex .expect() to satisfy
the no-panic-in-prod CI check
- Fix cargo fmt whitespace in collapsible if-let chain
* fix: address PR review feedback from gemini-code-assist
- Fix parse_custom_headers to preserve commas in values by splitting
only on commas followed by a header-name:colon pattern (manual scan
instead of simple split(','))
- Use matches! macro for backend exclusion check in app.rs
- Merge SSE metadata extraction into single pass (was iterating twice)
- Replace fragile substring-based context_length with explicit match
on known Gemini model IDs via gemini_context_length()
- Add missing models to regression test (8 models, not 5)
* fix: address Copilot PR review feedback
- Fix empty text part for assistant messages with tool calls
(curate_contents could drop entire model turn)
- Propagate cache_read/creation_input_tokens in complete_with_tools
- Log warning on save_credential failure instead of silently ignoring
- Fix doc comment to mention underscore in header name pattern
- Handle gemini-oauth (hyphen variant) in setup wizard display
- Fix docs: thinkingConfig uses thinkingBudget/thinkingLevel, not
includeThoughts
* fix: add missing allow_always field after staging merge
* fix(gemini_oauth): align header parser doc with implementation [skip-regression-check]
Update parse_custom_headers doc comments to include underscore in the
header-name character class, matching the actual implementation.
Also fix formatting from merge.
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
* fix(gemini_oauth): curate_contents per-part filtering and dead code removal
Fix curate_contents to filter invalid parts individually instead of
dropping entire model turn sequences. Previously a single empty text
part would discard all consecutive model turns including valid
functionCall parts, breaking the tool-call flow.
Also remove unused MID_STREAM_* constants.
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
* style(gemini_oauth): rustfmt formatting [skip-regression-check]
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
* fix(llm): support smart routing cheap model for gemini_oauth backend
Add explicit gemini_oauth handling in create_cheap_provider_for_backend()
to create a GeminiOauthProvider with the cheap model swapped in. Without
this, setting LLM_CHEAP_MODEL with gemini_oauth backend would fail with
a confusing "no registry provider config available" error.
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
* docs: add Gemini OAuth env vars to .env.example [skip-regression-check]
Document GEMINI_MODEL, GEMINI_CREDENTIALS_PATH, GEMINI_API_KEY, and
all extended generation config env vars in the example config file.
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
---------
Co-authored-by: [email protected] <[email protected]>
Co-authored-by: Claude Opus 4.6 (1M context) <[email protected]>
This commit is contained in:
Artem
+206
-103
@@ -1078,23 +1078,40 @@ impl SetupWizard {
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.map(|s| s.display_name().to_string())
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.unwrap_or_else(|| def.id.clone())
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} else {
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current.clone()
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match current.as_str() {
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"nearai" => "NEAR AI".to_string(),
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"gemini_oauth" | "gemini-oauth" => "Gemini API (OAuth)".to_string(),
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_ => {
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if let Some(def) = registry.find(¤t) {
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def.setup
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.as_ref()
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.map(|s| s.display_name().to_string())
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.unwrap_or_else(|| def.id.clone())
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} else {
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current.clone()
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}
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}
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}
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};
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print_info(&format!("Current provider: {}", display));
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println!();
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let is_known = current == "nearai"
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|| current == "bedrock"
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|| current == "gemini_oauth"
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|| current == "gemini-oauth"
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|| current == "openai_codex"
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|| registry.is_known(¤t);
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if is_known && confirm("Keep current provider?", true).map_err(SetupError::Io)? {
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if current == "bedrock" {
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// Keeping the existing Bedrock config — no need to re-run
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// the full setup flow (region, auth, cross-region).
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print_info("Keeping existing AWS Bedrock configuration.");
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return Ok(());
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}
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if current == "gemini_oauth" || current == "gemini-oauth" {
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print_info("Keeping existing Gemini CLI OAuth configuration.");
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return Ok(());
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}
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if current == "openai_codex" {
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print_info("Keeping existing OpenAI Codex configuration.");
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return Ok(());
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@@ -1113,13 +1130,15 @@ impl SetupWizard {
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print_info("Select your inference provider:");
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println!();
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// Build menu: NearAI first, then OpenAI Codex, then registry providers, then Bedrock
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// Build menu: NearAI first, then Gemini OAuth, then OpenAI Codex, then registry providers, then Bedrock
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let selectable = registry.selectable();
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let mut options: Vec<String> = Vec::with_capacity(2 + selectable.len());
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let mut provider_ids: Vec<String> = Vec::with_capacity(2 + selectable.len());
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let mut options: Vec<String> = Vec::with_capacity(3 + selectable.len());
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let mut provider_ids: Vec<String> = Vec::with_capacity(3 + selectable.len());
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options.push("NEAR AI - multi-model access via NEAR account".to_string());
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provider_ids.push("nearai".to_string());
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options.push("Gemini CLI - Official Gemini API via Gemini CLI OAuth".to_string());
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provider_ids.push("gemini_oauth".to_string());
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options.push("OpenAI Codex - ChatGPT subscription (Plus/Pro/Max)".to_string());
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provider_ids.push("openai_codex".to_string());
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@@ -1147,6 +1166,8 @@ impl SetupWizard {
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if selected_id == "bedrock" {
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self.setup_bedrock().await?;
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} else if selected_id == "gemini_oauth" {
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self.setup_gemini_oauth().await?;
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} else {
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self.run_provider_setup(selected_id, ®istry).await?;
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}
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@@ -1795,6 +1816,40 @@ impl SetupWizard {
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Ok(())
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}
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async fn setup_gemini_oauth(&mut self) -> Result<(), SetupError> {
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self.settings.llm_backend = Some("gemini_oauth".to_string());
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print_info("Starting Gemini CLI OAuth authentication...");
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println!();
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let creds_path = crate::config::GeminiOauthConfig::default_credentials_path();
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let cred_manager =
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crate::llm::gemini_oauth::CredentialManager::new(&creds_path).map_err(|e| {
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SetupError::Config(format!(
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"Failed to initialize Gemini credential manager: {}",
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e
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))
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})?;
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match cred_manager.get_valid_credential().await {
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Ok(cred) => {
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print_success("Gemini CLI authentication successful!");
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if let Some(ref pid) = cred.project_id {
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print_info(&format!("Cloud Code project: {}", pid));
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}
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}
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Err(e) => {
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return Err(SetupError::Config(format!(
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"Gemini CLI authentication failed: {}. Please try again.",
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e
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)));
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}
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}
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println!();
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print_success("Gemini API configured via Gemini CLI");
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Ok(())
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}
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/// Step 4: Model selection.
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///
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/// Branches on the selected LLM backend and fetches models from the
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@@ -1818,109 +1873,157 @@ impl SetupWizard {
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let backend = self.settings.llm_backend.as_deref().unwrap_or("nearai");
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let registry = crate::llm::ProviderRegistry::load();
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if backend == "nearai" {
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// NEAR AI: use existing provider list_models()
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let fetched = self.fetch_nearai_models().await;
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let models = if fetched.is_empty() {
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crate::llm::default_models()
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} else {
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fetched.iter().map(|m| (m.clone(), m.clone())).collect()
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};
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self.select_from_model_list(&models)?;
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} else if let Some(def) = registry.find(backend) {
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let can_list = def
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.setup
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.as_ref()
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.map(|s| s.can_list_models())
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.unwrap_or(false);
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if can_list {
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// Try to fetch models from the provider's /v1/models endpoint
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let cached_key = self
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.llm_api_key
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.as_ref()
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.map(|k| k.expose_secret().to_string());
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let models = match backend {
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"anthropic" => fetch_anthropic_models(cached_key.as_deref()).await,
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"openai" => fetch_openai_models(cached_key.as_deref()).await,
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"ollama" => {
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let base_url = self
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.settings
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.ollama_base_url
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.as_deref()
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.or(def.default_base_url.as_deref())
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.unwrap_or("http://localhost:11434");
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let models = fetch_ollama_models(base_url).await;
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if models.is_empty() {
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print_info("No models found. Pull one first: ollama pull llama3");
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}
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models
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}
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_ => {
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// Generic OpenAI-compatible model listing
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let base_url = def.default_base_url.as_deref().unwrap_or("");
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fetch_openai_compatible_models(base_url, cached_key.as_deref()).await
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}
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};
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// Apply models_filter from setup hint (e.g., Groq "chat" filters non-chat models)
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let models =
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if let Some(filter) = def.setup.as_ref().and_then(|s| s.models_filter()) {
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let filter_lower = filter.to_lowercase();
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models
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.into_iter()
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.filter(|(id, _)| id.to_lowercase().contains(&filter_lower))
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.collect()
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} else {
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models
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};
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if models.is_empty() {
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// Fall back to manual entry
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let default = &def.default_model;
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let model_id = input(&format!("Model name (default: {default})"))
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.map_err(SetupError::Io)?;
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let model_id = if model_id.is_empty() {
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default.clone()
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} else {
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model_id
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};
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self.settings.selected_model = Some(model_id.clone());
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print_success(&format!("Selected {}", model_id));
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match backend {
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"nearai" => {
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// NEAR AI: use existing provider list_models()
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let fetched = self.fetch_nearai_models().await;
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let models = if fetched.is_empty() {
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crate::llm::default_models()
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} else {
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self.select_from_model_list(&models)?;
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}
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} else {
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// Manual model entry
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let default = &def.default_model;
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fetched.iter().map(|m| (m.clone(), m.clone())).collect()
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};
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self.select_from_model_list(&models)?;
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}
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"gemini_oauth" | "gemini-oauth" => {
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let default_models: Vec<(String, String)> = vec![
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(
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"gemini-3.1-pro-preview".into(),
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"Gemini 3.1 Pro (Latest, strongest reasoning)".into(),
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),
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(
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"gemini-3.1-pro-preview-customtools".into(),
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"Gemini 3.1 Pro Custom Tools (Enhanced tool use)".into(),
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),
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(
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"gemini-3-pro-preview".into(),
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"Gemini 3 Pro (Preview)".into(),
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),
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(
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"gemini-3-flash-preview".into(),
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"Gemini 3 Flash (Fast preview with thinking)".into(),
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),
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(
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"gemini-3.1-flash-lite-preview".into(),
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"Gemini 3.1 Flash Lite (Preview, lightweight)".into(),
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),
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(
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"gemini-2.5-pro".into(),
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"Gemini 2.5 Pro (Stable, strong reasoning)".into(),
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),
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(
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"gemini-2.5-flash".into(),
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"Gemini 2.5 Flash (Fast, good quality)".into(),
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),
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(
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"gemini-2.5-flash-lite".into(),
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"Gemini 2.5 Flash Lite (Fastest, lightweight)".into(),
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),
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];
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self.select_from_model_list(&default_models)?;
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}
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"bedrock" => {
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let model_id =
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input(&format!("Model name (default: {default})")).map_err(SetupError::Io)?;
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let model_id = if model_id.is_empty() {
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default.clone()
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} else {
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model_id
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};
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input("Bedrock model ID (e.g., anthropic.claude-v3-sonnet-20240229-v1:0)")
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.map_err(SetupError::Io)?;
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if model_id.is_empty() {
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return Err(SetupError::Config("Model ID is required".to_string()));
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}
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self.settings.selected_model = Some(model_id.clone());
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print_success(&format!("Selected {}", model_id));
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}
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} else if backend == "bedrock" {
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let model_id = input("Bedrock model ID (e.g., anthropic.claude-opus-4-6-v1)")
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.map_err(SetupError::Io)?;
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if model_id.is_empty() {
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return Err(SetupError::Config("Model ID is required".to_string()));
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_ => {
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if let Some(def) = registry.find(backend) {
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let can_list = def
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.setup
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.as_ref()
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.map(|s| s.can_list_models())
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.unwrap_or(false);
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|
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if can_list {
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// Try to fetch models from the provider's /v1/models endpoint
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let cached_key = self
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.llm_api_key
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.as_ref()
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.map(|k| k.expose_secret().to_string());
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let models = match backend {
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"anthropic" => fetch_anthropic_models(cached_key.as_deref()).await,
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"openai" => fetch_openai_models(cached_key.as_deref()).await,
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"ollama" => {
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let base_url = self
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.settings
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.ollama_base_url
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.as_deref()
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.or(def.default_base_url.as_deref())
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.unwrap_or("http://localhost:11434");
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let models = fetch_ollama_models(base_url).await;
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if models.is_empty() {
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print_info(
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"No models found. Pull one first: ollama pull llama3",
|
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);
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}
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models
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}
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_ => {
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// Generic OpenAI-compatible model listing
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let base_url = def.default_base_url.as_deref().unwrap_or("");
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fetch_openai_compatible_models(base_url, cached_key.as_deref())
|
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.await
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}
|
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};
|
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|
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// Apply models_filter from setup hint
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let models = if let Some(filter) =
|
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def.setup.as_ref().and_then(|s| s.models_filter())
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{
|
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let filter_lower = filter.to_lowercase();
|
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models
|
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.into_iter()
|
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.filter(|(id, _)| id.to_lowercase().contains(&filter_lower))
|
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.collect()
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} else {
|
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models
|
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};
|
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|
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if models.is_empty() {
|
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// Fall back to manual entry
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let default = &def.default_model;
|
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let model_id = input(&format!("Model name (default: {default})"))
|
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.map_err(SetupError::Io)?;
|
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let model_id = if model_id.is_empty() {
|
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default.clone()
|
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} else {
|
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model_id
|
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};
|
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self.settings.selected_model = Some(model_id.clone());
|
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print_success(&format!("Selected {}", model_id));
|
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} else {
|
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self.select_from_model_list(&models)?;
|
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}
|
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} else {
|
||||
// Manual model entry
|
||||
let default = &def.default_model;
|
||||
let model_id = input(&format!("Model name (default: {default})"))
|
||||
.map_err(SetupError::Io)?;
|
||||
let model_id = if model_id.is_empty() {
|
||||
default.clone()
|
||||
} else {
|
||||
model_id
|
||||
};
|
||||
self.settings.selected_model = Some(model_id.clone());
|
||||
print_success(&format!("Selected {}", model_id));
|
||||
}
|
||||
} else {
|
||||
// Unknown provider, manual entry
|
||||
let model_id = input("Model name (e.g., meta-llama/Llama-3-8b-chat-hf)")
|
||||
.map_err(SetupError::Io)?;
|
||||
if model_id.is_empty() {
|
||||
return Err(SetupError::Config("Model name is required".to_string()));
|
||||
}
|
||||
self.settings.selected_model = Some(model_id.clone());
|
||||
print_success(&format!("Selected {}", model_id));
|
||||
}
|
||||
}
|
||||
self.settings.selected_model = Some(model_id.clone());
|
||||
print_success(&format!("Selected {}", model_id));
|
||||
} else {
|
||||
// Unknown provider, manual entry
|
||||
let model_id = input("Model name (e.g., meta-llama/Llama-3-8b-chat-hf)")
|
||||
.map_err(SetupError::Io)?;
|
||||
if model_id.is_empty() {
|
||||
return Err(SetupError::Config("Model name is required".to_string()));
|
||||
}
|
||||
self.settings.selected_model = Some(model_id.clone());
|
||||
print_success(&format!("Selected {}", model_id));
|
||||
}
|
||||
|
||||
Ok(())
|
||||
|
||||
Reference in New Issue
Block a user