@ramarivera/coding-agent-langfuse

coding-agent-langfuse

Universal coding-agent Langfuse backfiller and OTLP exporter helpers.

It imports local histories from Codex, Claude Code, Grok, OpenCode, and Pi into Langfuse as session traces with child observations. LLM generations include Langfuse canonical usage_details and cost_details attributes so historical backfills participate in Langfuse model-usage and cost dashboards. Tool calls remain child spans under the same session.

Codex event_msg token_count rows are imported as cost-accounting generations when they include input/output/cache buckets for a known priced model. The importer preserves the original token snapshot in metadata and sends Langfuse canonical usage_details/cost_details derived from the bucketed usage. Total-only Codex snapshots and unknown/free-preview models stay non-billable to avoid inventing cost from ambiguous telemetry.

coding-agent-langfuse-backfill --agents codex,claude,grok,pi,opencode

Use the public Langfuse OTLP hostname for real imports from any host:

npx @ramarivera/coding-agent-langfuse@latest \
  --agents claude,codex,grok,pi,opencode \
  --endpoint https://langfuse.ai.roxasroot.net/otel/v1/traces \
  --state "$HOME/.local/state/coding-agent-langfuse/backfill-v6.json" \
  --batch-size 10

For a Langfuse endpoint that requires project API keys, pass Basic auth credentials as publicKey:secretKey or set LANGFUSE_BACKFILL_AUTH:

npx @ramarivera/coding-agent-langfuse@latest \
  --agents claude,codex,grok,pi,opencode \
  --endpoint http://127.0.0.1:3000/api/public/otel/v1/traces \
  --auth pk-lf-example:sk-lf-example

Run live incremental forwarding without putting inference behind a gateway:

npx @ramarivera/coding-agent-langfuse@latest \
  --agents codex \
  --endpoint https://langfuse.ai.roxasroot.net/otel/v1/traces \
  --state "$HOME/.local/state/coding-agent-langfuse/live-codex.json" \
  --batch-size 10 \
  --follow

The importer is fail-fast: the first failed OTLP POST stops the run, prints the real network cause, and preserves local state so reruns resume cleanly.

Project tags and metadata

Backfills and live followers can attach stable Langfuse dimensions based on the session cwd. Use this for client/workstream dashboards without guessing from host names or Windows paths in the Langfuse UI.

There are two config layers:

• Global host config: ~/.config/coding-agent-langfuse/path-tags.json
• Optional project-local overlays: every .langfuse-ca.json found while walking from the session cwd up to the scanned home directory

Global config uses path-prefix or Git-remote rules:

{
  "rules": [
    {
      "pathPrefix": "/Users/example/dev/acme",
      "gitRemoteIncludes": ["github.com/acme"],
      "tags": ["acme", "client:acme"],
      "metadata": {
        "project_group": "acme",
        "project_owner": "platform-team"
      },
      "projectName": "acme",
      "projectFolder": "acme"
    }
  ]
}

Use pathPrefix for stable checkout roots. Use gitRemoteIncludes for temporary agent worktrees, where the cwd may live under a random directory such as .codex/worktrees/<id>/repo but the Git remote still identifies the real project.

Project-local config is intentionally smaller and overrides/extends the matched global rule. Parent overlays are applied before child overlays, so a config at ~/work/client-a/.langfuse-ca.json can tag a whole workstream while nested repos add repo-specific fields:

{
  "tags": ["repo:portal"],
  "metadata": {
    "service": "portal"
  },
  "projectName": "acme-portal"
}

Matched values are emitted on root trace metadata, observation metadata, and top-level OTLP attributes such as project.tags, project.group, and project.owner. When the session cwd is inside a Git repository, the exporter also emits git.worktree.path, git.branch, and git.commit plus matching Langfuse metadata fields. The root span also sets langfuse.trace.tags, so Langfuse custom dashboards can filter/group by tags, metadata, branch, or worktree. Historical repair runs use the same OTLP builder as live follow mode, so rerunning with --force can backfill newly added tags and Git metadata for existing sessions.

Use a non-default global config path with:

npx @ramarivera/coding-agent-langfuse@latest \
  --path-tags-config "$HOME/.config/coding-agent-langfuse/path-tags.json"

Generated services keep their command small and rely on the package's default global config plus upward project-local discovery. Use --path-tags-config only for one-off CLI runs that need a non-default global config path.

Cost calculation

Backfill cost calculation follows Langfuse's OpenTelemetry mapping: generation spans receive langfuse.observation.usage_details and langfuse.observation.cost_details JSON attributes. If a source history already records a total cost, that recorded value wins. Otherwise, the importer calculates per-usage-type USD costs from a model catalog using rates in USD per 1M tokens.

By default, the importer refreshes model pricing from https://models.dev/api.json and caches it locally. The cache is used for both one-shot backfills and --follow services, so long-running collectors do not hit the network for every scan. The built-in catalog remains only as an offline fallback for known local models; explicit --cost-rates and --cost-rates-json overrides always win.

Control the pricing cache with:

npx @ramarivera/coding-agent-langfuse@latest \
  --models-dev-cache "$HOME/.cache/coding-agent-langfuse/models-dev-v1.json" \
  --models-dev-ttl-ms 86400000

Use --models-dev to force-enable the cache if an environment disabled it. Use --no-models-dev or CODING_AGENT_LANGFUSE_MODELS_DEV=0 for fully static offline pricing. Advanced deployments can set --models-dev-url, CODING_AGENT_LANGFUSE_MODELS_DEV_CACHE, CODING_AGENT_LANGFUSE_MODELS_DEV_TTL_MS, or CODING_AGENT_LANGFUSE_MODELS_DEV_FETCH_TIMEOUT_MS.

When a billable generation source only records a total token count without input/output/cache breakdown, the importer charges that total at the model input rate and marks the cost source as calculated_total_as_input. Codex token-count snapshots are the exception: they are charged only when the snapshot has explicit input/output/cache buckets. Codex reasoning tokens are kept in metadata, but not charged separately because Codex token-count output totals already include reasoning tokens.

Use an override only when you intentionally want a different accounting policy:

npx @ramarivera/coding-agent-langfuse@latest \
  --agents codex \
  --cost-rates-json '{"gpt-5.5":{"input":1,"output":2,"cacheRead":0.1,"cacheWrite":0}}'

You can also keep the policy in a JSON file and pass --cost-rates PATH, or set CODING_AGENT_LANGFUSE_COST_RATES_PATH / CODING_AGENT_LANGFUSE_COST_RATES_JSON for both manual backfills and generated services. A file can be either a direct model map or { "rates": { ... } }:

{
  "rates": {
    "gpt-5.5": {
      "input": 1,
      "output": 2,
      "cacheRead": 0.1,
      "cacheWrite": 0,
      "cacheWrite5m": 0,
      "cacheWrite1h": 0
    }
  }
}

Follow as a host service

Install a live follower directly from npm. The generated service keeps inference outside any gateway: agents keep calling their normal providers, while this tool tails local histories and posts Langfuse OTLP traces.

Preview the service without touching the host:

npx @ramarivera/coding-agent-langfuse@latest service print \
  --platform linux \
  --agents codex,pi \
  --endpoint https://langfuse.ai.roxasroot.net/otel/v1/traces

Install and start it on the current host:

npx @ramarivera/coding-agent-langfuse@latest service install \
  --agents codex,pi \
  --endpoint https://langfuse.ai.roxasroot.net/otel/v1/traces

The service installer supports:

• macOS: LaunchAgent under ~/Library/LaunchAgents
• Linux: systemd user unit under ~/.config/systemd/user
• Windows: scheduled task installer script under %APPDATA%\\coding-agent-langfuse

Use --dry-run to print the exact file and commands, --no-start to only write the service file, service status to inspect the platform registration, and service uninstall to remove it.

npx @ramarivera/coding-agent-langfuse@latest service status \
  --agents codex,pi

The Windows path intentionally uses a per-user Scheduled Task for the default npx workflow. A true Windows SCM service needs an installed wrapper or native service binary; raw sc.exe is not a good fit for a transient npm command.

The generated services are package-manager agnostic. By default the installer uses npx through the service PATH (/usr/bin/env npx on macOS and Linux) with a conservative cross-platform PATH. Use --npx-path and --path when a host keeps Node.js somewhere outside the normal npm/Homebrew/system locations, including nvm, fnm, Volta, asdf, mise, or another shell manager.

The public API exposes serviceCreators for macOS LaunchAgent, Linux systemd user units, and Windows Scheduled Task scripts, plus agentProcessors for Claude Code, Codex, Grok, OpenCode, and Pi. These registries are the extension points for adding another host service target or coding-agent history reader without adding more platform or agent conditionals to the CLI internals.

Backfill windows

Backfill only a timeframe when repairing a host or replaying a recent window:

npx @ramarivera/coding-agent-langfuse@latest \
  --agents claude,codex,grok,pi,opencode \
  --since 2026-05-31T00:00:00Z \
  --until 2026-06-01T00:00:00Z \
  --endpoint https://langfuse.ai.roxasroot.net/otel/v1/traces

Deduplication is state-file based and keyed by importer state identity, agent, session id, and source record id. Reuse the same --state path for normal incremental runs.

For an intentional repair replay, add --force to resend the selected window even when the state file says those events were already sent:

npx @ramarivera/coding-agent-langfuse@latest \
  --agents claude,codex,grok,pi,opencode \
  --since 2026-05-01T00:00:00Z \
  --until 2026-06-01T00:00:00Z \
  --force \
  --endpoint https://langfuse.ai.roxasroot.net/otel/v1/traces

The Langfuse trace/span IDs intentionally stay pinned to the original pre-cost identity, while the state-file key can advance with importer payload changes. That lets cost repairs replace historical zero-cost rows instead of creating a new duplicate identity for the same source event.

Verification

The test suite covers parser behavior for all supported agents and exercises the CLI against a local OTLP collector.

npm run check
npm test
npm run test:e2e
npm run test:e2e:langfuse

The e2e suite verifies:

• Codex full session traces with messages, reasoning, tool calls, tool results, usage details, and cost details
• Follow mode picking up newly written Codex events
• One CLI run posting reconstructable traces for Claude Code, Codex, Grok, OpenCode, and Pi
• A Docker-backed mini Langfuse import that queries the public observations API and verifies usage/cost fields for sanitized multi-agent sessions, including Claude Code Opus 4.7 and Opus 4.8 cache accounting
• Service plan generation for Linux systemd user units, macOS LaunchAgents, and Windows Scheduled Tasks