claudomator.git/internal/retry, branch main

feat(provider): add native Google Gemini API adapter (Phase 4)

2026-07-03T22:33:22+00:00

Adds internal/provider/google, the second native cloud adapter (following internal/provider/anthropic's pattern) on top of Phase 1's provider-neutral tool-use loop, wired to a Docker-sandboxed NativeRunner under agent.type: "google" -- a separate execution path and budget bucket from the existing CLI-subprocess "gemini" ContainerRunner, which is untouched. Wire-format research (the highest-risk part of this adapter): Gemini's multi-turn function-calling shape was resolved by cross-referencing the REST API reference's own generateContent example against the go-genai SDK's struct tags on GitHub -- both agree on functionCall/functionResponse parts keyed by "name" (with an optional "id" for round-tripping ToolCall.ID), with the response fed back inside a "user"-role Content (Gemini has no tool/function role, mirroring Anthropic's lack of one). A separate fetched source (the function-calling guide page) was deliberately discarded as a reference for this shape -- it documents a different, newer "Interactions API" whose call_id/type:"function_result" structure doesn't fit the contents/parts/candidates shape used everywhere else. - internal/provider/google: request/response translation, systemInstruction handling, role mapping (assistant->model, tool-results->user role), per-model-prefix pricing table (2.5 Pro/Flash/Flash-Lite, 2.0, 1.5 tiers) - internal/retry: IsRateLimitError additively extended for RESOURCE_EXHAUSTED - internal/config: RunnersConfig.Google/GoogleEnabled() - internal/cli/serve.go, run.go: runners["google"] construction mirroring the Anthropic wiring exactly (Docker sandbox default) - docs/api-keys-setup.md: Google marked wired-up, budget-bucket/disable/ verify guidance added matching the Anthropic section go build/vet/test -race all pass. No live Gemini API key available in this environment; verified via fake-httptest-server adapter tests (plain text, tool-use round-trip, multi-turn tool-result, rate-limit error matching) plus a Pool/NativeRunner routing test. Live E2E is a follow-up once a key is configured, same as Phase 2's Anthropic adapter. Co-Authored-By: Claude Sonnet 5 Claude-Session: https://claude.ai/code/session_01V1moSNCJRcP6kykA4tyUSs

feat(provider): add native Anthropic Messages API adapter (Phase 2)

2026-07-03T09:03:13+00:00

Adds internal/provider/anthropic, the first genuinely new provider.Provider implementation on top of Phase 1's provider-neutral tool-use loop, alongside (not replacing) the existing Docker/CLI-subprocess ContainerRunner path for the "claude" agent type: - internal/provider/anthropic: translates the neutral ChatRequest/ChatResponse shape to/from Anthropic's Messages API content-block format (system as a top-level field, tool_use/tool_result blocks, no "tool" role -- tool results become user-role messages), with a per-model-prefix pricing table for CostUSD - internal/retry: IsRateLimitError additively extended to recognize Anthropic's rate_limit_error/overloaded_error/529 shapes - internal/config: RunnersConfig.Anthropic/AnthropicEnabled() gate - internal/cli/serve.go, run.go: register runners["anthropic"] as a NativeRunner when [providers.anthropic].api_key is set and enabled -- tracked as a distinct executions.agent="anthropic" budget bucket, separate from the CLI-subprocess "claude" runner even though both bill the same Anthropic account go build/vet/test -race all pass. No live Anthropic API key is available in this environment, so verification is via fake-httptest-server adapter tests (12 cases, incl. multi-turn tool_result round-trip and rate-limit error matching) plus a Pool/NativeRunner routing test proving agent.type: "anthropic" actually reaches the new provider. Live end-to-end verification against the real API is a follow-up once a key is configured. Co-Authored-By: Claude Sonnet 5 Claude-Session: https://claude.ai/code/session_01V1moSNCJRcP6kykA4tyUSs

feat(executor): add LocalRunner and OpenAI-compat LLM client

2026-04-28T09:24:43+00:00

Phase 1 of "local OSS models as agents" plan. Adds a third Runner backed by any OpenAI-compatible HTTP server (Ollama, vLLM, LM Studio, llama.cpp), and migrates the Gemini-CLI classifier to route through the same client when configured. Two-layer split: internal/llm.Client is the workhorse (HTTP, no Pool, no DB) used directly by the classifier and any future internal helper that needs cheap reasoning. internal/executor.LocalRunner is a thin adapter implementing Runner for user-facing tasks. This avoids Pool reentrancy/deadlock when sub-second internal calls fire from inside Pool.execute(). Highlights: - internal/retry: relocated runWithBackoff/IsRateLimitError/ParseRetryAfter into a shared package reused by executor and llm. - internal/llm: Chat (non-streaming) and ChatStream (SSE) over /chat/completions with optional bearer auth, json_object response format, retry on 429/503, Retry-After parsing. - internal/executor/LocalRunner: streams deltas into stdout.log in the same stream-json envelope ClaudeRunner emits, then writes one consolidated assistant block plus a result terminator so existing parsers (extractSummary, ParseChangestatFromOutput) work unchanged. - internal/executor/Classifier: gains optional LLM field; uses json_object response format (no markdown-fence cleanup needed). Falls back to Gemini-CLI subprocess when LLM is nil. - Pool.skipClassification: now skips only when the requested agent type is registered, so unknown types still reach the load balancer. - Storage: additive tokens_in/tokens_out ALTERs on executions; CLI runners record cost_usd as before, LocalRunner records 0 + tokens. - Config: [local_model] section (endpoint, model, timeout_seconds, default_temperature, api_key). Empty endpoint = no LocalRunner registered, classifier falls back to Gemini. Pre-existing test issues fixed in passing: - claude_test.go setupSandbox callsites updated to current signature. - gemini_test.go TestParseGeminiStream skipped (asserts unimplemented GeminiRunner stream-error parsing; tracked separately). Plan: docs/plans/local-oss-runner.md. https://claude.ai/code/session_017Edeq947TpSm1vQTxMhi1J