17 KiB
Audita Go Architecture
Scope and intent
This document describes:
- the current implemented Go architecture; and
- the intended final architecture for later rewrite phases.
Status labels are explicit so future engineers and LLM agents do not assume unimplemented behavior exists.
Current implementation status
Implemented today:
- Go CLI entrypoint and
audita processwiring. - Config defaults, env loading, CLI override precedence, and validation.
- Transcript and glossary parsing/validation.
- Deterministic transcript normalization.
- Deterministic token estimation and transcript chunking.
- Per-run diagnostics directory creation plus Phase 6 process-level artifacts.
- Process report JSON output with diagnostics artifact references.
- Framework foundation packages for contracts and proposal application.
- Production runner orchestration package with deterministic sequential module execution.
- Module-level report structures with applied/skipped change records.
- Runtime validator models and deterministic validators.
- Deterministic validator-chain execution in the runner with cardinality enforcement.
- Module-level validator decision/rejection reporting.
- Internal structured LLM client contract plus an
instructor-go-backed adapter package. - Bounded LLM scheduler/semaphore infrastructure with context-aware permit handling.
- Runtime primary/validation LLM effective-config resolution helpers with validation inheritance.
- Generic JSON prompt/response diagnostics writer primitives with secret redaction.
- LLM-backed validator models, prompt builders, batching, and runtime execution.
- Runner wiring for LLM validators via the internal structured LLM abstraction and scheduler hooks.
- LLM validator diagnostics artifacts and report-level decision metadata paths.
- Shared LLM proposal-generation helper with structured correction-set parsing.
- Deterministic proposal-index assignment and enriched proposal mapping for shared generation.
- Proposal-generation diagnostics artifacts with secret redaction.
- Production module registry scaffolding with known-key recognition and explicit unsupported/unimplemented errors.
Not implemented in CLI runtime path today:
- Real module execution pipeline (
glossary,homophones,spoken_word,grammar). - Real domain proposal prompts for production modules.
- End-to-end transcript polishing with real module behavior.
Phase sequencing note:
- Phase 9 LLM infrastructure is complete (structured client, scheduler, effective config resolution, diagnostics primitives);
- Phase 10 LLM-backed validator runtime integration is complete;
- Phase 11 shared proposal-generation framework and module-registry scaffolding are complete;
- next recommended phase is Phase 12 (grammar module).
Actual Go package layout
cmd/audita/
main.go
internal/cli/
run.go
internal/core/config/
config.go
env.go
flags.go
redaction.go
validation.go
internal/core/schema/
transcript.go
glossary.go
errors.go
internal/core/io/
files.go
internal/core/normalization/
normalize.go
tokens.go
internal/core/chunking/
sections.go
summary.go
tokens.go
internal/core/diagnostics/
run_dir.go
internal/core/reporting/
report.go
internal/framework/contracts/
contracts.go
internal/framework/proposals/
proposal.go
policy.go
preview.go
apply.go
internal/framework/runner/
runner.go
internal/framework/proposal_generation/
generate.go
internal/framework/modules/
registry.go
internal/framework/validators/
models.go
deterministic.go
llm_models.go
llm_prompt_builders.go
llm_batching.go
llm_validators.go
internal/framework/llm/
instructor_client.go
scheduler.go
effective_config.go
diagnostics.go
Current CLI behavior
Primary command:
audita process <transcript.json> --glossary <glossary.yaml> [flags]
Current runtime flow (internal/cli/run.go):
- Load config from env.
- Parse flags and apply CLI overrides.
- Validate transcript positional argument and required
--glossary. - Create per-run diagnostics directory.
- Read transcript and glossary files.
- Parse/validate transcript and glossary.
- Write source transcript artifacts.
- Normalize transcript.
- Write normalized transcript and normalization summary artifacts.
- Chunk normalized transcript and compute chunk summaries.
- Write chunking summary artifact.
- Optionally execute runner modules sequentially when a module factory is injected (tests currently use this path; production defaults still avoid real module execution).
- Output working transcript to
--outputfile or stdout. - Build process report (
phasecurrently set tophase11-proposal-generation-framework). - Optionally write
--report-json; always write run-dirreport.json. - Apply work-dir retention.
Important behavior details:
- Glossary is validated but not yet used for real correction module logic.
- Default production CLI behavior remains deterministic normalization/chunking output because no real module implementations are registered yet.
- No real LLM calls occur in the default production runtime path because no real modules are registered yet.
- Success path is generally quiet on stderr.
- Source IDs are preserved into a canonical transcript before normalization; normalization then reassigns output IDs sequentially from
1.
Implemented data contracts
Transcript input
Accepted top-level forms:
- bare JSON array of segments
- object with
segmentsarray
Source segment contract:
idoptional integerspeakernon-empty stringstartfinite non-negative numberendfinite non-negative number withend >= starttextnon-empty stringcategoriesoptional array of non-empty strings
Additional checks:
- duplicate explicit source IDs are rejected.
Transcript output
Current output uses schema.TranscriptToJSON and is a bare JSON array of normalized segments:
id,speaker,start,end,text, optionalcategories.
Glossary input
YAML with glossary entries. Required fields per entry:
name,category,summary
Optional:
aliases,plural
Implemented config/env/flag behavior
Precedence:
- defaults (
config.Default()) - environment (
config.LoadFromEnv()) - CLI flags (
ApplyCLIOverrides)
Implemented config surfaces include:
- module list
- primary and validation LLM settings
- section token controls and target sections
- confidence thresholds
- normalization controls
- work-dir and retention mode
Current caveat:
- LLM/module-related settings are mostly infrastructure-only today; default runtime path does not execute real modules.
Implemented structured LLM infrastructure
internal/framework/contracts now defines a typed structured-completion contract:
StructuredLLMClient.CompleteStructured(ctx, req, out)- caller-owned typed decode target via
outpointer.
internal/framework/llm provides InstructorClient, an internal adapter over github.com/jxnl/instructor-go:
- configurable
base_url, model, optional API key, retries, mode, HTTP client, and request timeout; - OpenAI-compatible endpoint behavior (for example OpenAI/OpenRouter/local-compatible base URLs);
- default mode is JSON mode (
ModeJSON), with optional tool-call mode (ModeToolCall); - request message translation from
contracts.LLMMessageto chat-completions messages; - response metadata mapping (provider/model/token usage) into Audita-owned response types;
- API-key redaction in adapter-returned errors.
Current runtime boundary:
- the default CLI runtime path still does not instantiate real production modules, so no default end-to-end LLM polishing occurs.
- LLM calls are exercised only when test/injected modules and validators are provided.
internal/framework/llm also provides:
- a bounded
Schedulerfor controlled concurrent LLM calls with reliable permit release; - primary/validation effective-config resolution helpers, including validation inheritance fallback to primary settings;
- generic interaction diagnostics primitives that write machine-readable JSON artifacts for request metadata, request payload, response payload, and optional error payload with secret redaction.
Implemented normalization behavior
Normalization (internal/core/normalization) currently:
- sorts by segment start time;
- merges adjacent same-speaker segments when constraints pass;
- uses gap-based joiners:
- gap
< ellipsis_gap-> single space join - gap
>= ellipsis_gap->...join
- gap
- enforces merged duration and token-limit constraints;
- reassigns output IDs sequentially from
1; - returns
NormalizationSummarywith merge and skip counters.
Note: merged categories are concatenated (not deduplicated).
Implemented chunking behavior
Chunking (internal/core/chunking) currently provides:
- deterministic heuristic token estimation;
- contiguous sectioning with section metadata;
- max/min section token validation;
- optional
target_sectionshandling with target-aware merge/split logic; - summary and detailed summary generation.
Current behavior details:
- if a single segment exceeds max tokens, it is emitted as its own section (not hard-failed);
- section balancing is deterministic but heuristic.
Implemented proposal/replacement infrastructure
internal/framework/proposals provides deterministic foundation logic:
CorrectionProposalandEnrichedCorrectionProposalmodels;- replacement policies:
require_unique,replace_all; - safe preview (
PreviewProposalForSegment) with stable skip reasons; - deterministic apply (
ApplyProposals) in ascendingproposal_indexorder; - applied/skipped change records suitable for reporting.
internal/framework/contracts provides interfaces and run-spec metadata scaffolding, including deterministic repeated module instance naming (ResolveModuleRunSpecs).
These primitives are wired into the production runner and report model. Real module implementations are still pending.
Implemented validator runtime infrastructure
internal/framework/validators provides deterministic validator infrastructure:
- runtime validation request/result models;
- stable validator reason codes;
- cardinality enforcement for validator decisions:
- missing proposal indexes fail
- duplicate proposal indexes fail
- unknown proposal indexes fail
- deterministic validators:
- confidence threshold by module key/config threshold
- original-text presence against current working transcript
- non-empty corrected text
- identical/no-effect rejection
- conservative protected glossary-term guard for non-glossary modules
internal/framework/runner executes validator chains in order for each module and applies only validator-approved proposals.
Validator rejections are reported distinctly from proposal-application skips.
Implemented LLM-backed validator infrastructure
internal/framework/validators now includes LLM-backed validator support:
- typed request/response models for structured LLM validation;
- prompt builders for:
- spoken-form plausibility
- meaning reversal detection
- editorial review
- grammar review
- spoken-word review
- deterministic batching by
validation_max_prompt_tokens; - strict cardinality validation of structured LLM decisions (missing/duplicate/unknown indexes fail);
- safe failure behavior for malformed/invalid structured responses.
internal/framework/runner wires LLM validators into existing validator chains using:
- the internal structured LLM client abstraction (
contracts.StructuredLLMClient); - bounded scheduler hooks for validator call execution;
- diagnostics writer hooks for machine-readable prompt/response artifacts with secret redaction.
Implemented shared proposal-generation infrastructure
internal/framework/proposal_generation provides a reusable, prompt-agnostic helper for future real modules:
- structured request model including module key/instance, replacement policy, working transcript context, optional section metadata, glossary, config, and diagnostics context;
- structured correction-set response model (
corrections) mapped into existingproposals.CorrectionProposalandproposals.EnrichedCorrectionProposalmodels; - deterministic proposal-index assignment through a caller-provided
start_index; - structured LLM calls through
contracts.StructuredLLMClientonly (no direct provider calls); - optional bounded execution through scheduler hooks (
contracts.LLMScheduler); - prompt/response diagnostics artifact writing via the generic
internal/framework/llmdiagnostics primitives with redaction of API keys/secrets.
This helper only produces candidate proposals; validator-chain execution and proposal application remain runner responsibilities.
Implemented production module-registry scaffolding
internal/framework/modules now provides a production registry scaffold:
- recognizes intended module keys:
glossaryhomophonesspoken_wordgrammar
- supports explicit constructor registration with dependency injection for:
- run spec
- config
- glossary
- proposal/validation structured LLM clients
- proposal/validation schedulers
- diagnostics directory context
- returns explicit errors for unknown keys (
unsupported_module) and recognized-but-unimplemented keys (unimplemented_module).
No real production correction modules are registered yet.
Reports and diagnostics (implemented)
Current per-run artifacts include:
source-transcript.jsonsource-transcript-parsed.jsonnormalized-transcript.jsonnormalization-summary.jsonchunking-summary.jsoninvocation.jsoneffective-config.json(redacted credentials)report.jsonerror.logon failure
--report-json writes a separate report file when requested.
Current process reports include diagnostics metadata references for:
- diagnostics directory path;
- source transcript artifact path;
- parsed source transcript artifact path;
- normalized transcript artifact path;
- normalization summary artifact path;
- chunking summary artifact path;
- invocation metadata artifact path;
- redacted effective-config artifact path;
- error-log artifact path on failure.
Current process reports also include:
- module-level results (when runner modules execute), including applied/skipped proposal changes;
- run-level module summary totals and failed module instance metadata.
- module-level validator decisions and validator rejections.
- optional decision-level diagnostic artifact paths for validator LLM interactions when available.
Retention modes implemented in ApplyRetention:
always: keep all run directories.never: keep successful run directories.auto: keep failed runs and successful runs with skipped corrections.- failed runs are always retained.
Current runtime note:
- real module execution is not implemented yet, so normal successful runs generally have no skipped corrections and
autotypically removes clean successful run directories.
Intentionally deferred to module/LLM phases:
- real domain proposal prompts and production module implementations remain tied to later module phases.
Current tests and quality posture
Implemented tests currently cover:
- CLI argument handling and behavior (
internal/cli/run_test.go) - subprocess stdout/stderr and exit-code behavior (
cmd/audita/main_integration_test.go) - config/env/override validation (
internal/core/config/*_test.go) - transcript and glossary schema validation (
internal/core/schema/*_test.go) - deterministic normalization (
internal/core/normalization/*_test.go) - deterministic chunking and summaries (
internal/core/chunking/*_test.go) - proposal preview/apply semantics (
internal/framework/proposals/*_test.go) - contracts/foundation composition tests (
internal/framework/contracts/*_test.go) - runner sequencing and failure behavior with deterministic fake modules (
internal/framework/runner/*_test.go) - CLI runner integration through injected fake module factories (
internal/cli/run_test.go) - validator models, cardinality enforcement, and deterministic validators (
internal/framework/validators/*_test.go) - LLM-backed validator batching, prompt builders, structured-response safety, scheduler hooks, and diagnostics redaction (
internal/framework/validators/*_test.go,internal/framework/runner/*_test.go) - shared proposal-generation request/response parsing, deterministic indexing, scheduler hooks, and diagnostics redaction (
internal/framework/proposal_generation/*_test.go,internal/framework/runner/*_test.go) - production module-registry known-key recognition and unsupported/unimplemented error behavior (
internal/framework/modules/*_test.go,internal/cli/run_test.go)
Not covered yet (because not implemented): real production module implementations and full transcript-polishing runtime behavior.
Intended final architecture (not yet implemented)
The intended end-state still matches the rewrite plan:
- sequential module pipeline over a mutable working transcript
- real module implementations (
glossary,homophones,spoken_word,grammar) - structured LLM proposal generation
- deterministic and LLM validators
- validator cardinality enforcement in pipeline execution
- proposal application integrated per module stage
- prompt/response diagnostics for LLM/module stages
Until those phases are implemented, documentation and external descriptions should treat the current Go CLI as deterministic preprocessing/reporting infrastructure, not a full LLM transcript polisher.