> ## Documentation Index > Fetch the complete documentation index at: https://candy-208aed2d-85.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # Configuration # Configuration (high-level) This document summarizes what to configure and where. ## Minimal configuration * Requester-only: set `LCPD_LND_*` (peer messaging / invoice payments) and run `lcpd-grpcd`. * Provider: also set `LCPD_PROVIDER_CONFIG_PATH` (YAML) and `LCPD_BACKEND` (for example `openai`). ## Environment variables (required/optional) ### go-lcpd (common) | Variable | Required | Purpose | | ----------------------------------------- | ----------------------------------: | ---------------------------------------------------------- | | `LCPD_LOG_LEVEL` | Optional | `debug`/`info`/`warn`, etc. | | `LCPD_BACKEND` | Effectively required for Provider | `openai` / `deterministic` / `disabled` | | `LCPD_OPENAI_API_KEY` or `OPENAI_API_KEY` | Required when `LCPD_BACKEND=openai` | OpenAI API key | | `LCPD_OPENAI_BASE_URL` | Optional | Base URL for an OpenAI-compatible API | | `LCPD_DETERMINISTIC_OUTPUT_BASE64` | Optional | Fixed output for the `deterministic` backend (dev/testing) | ### lnd integration (peer messaging / payments) | Variable | Required | Purpose | | ----------------------------------- | ---------------------: | -------------------------------------------------------------------------- | | `LCPD_LND_RPC_ADDR` | Required if using lnd | `host:port` | | `LCPD_LND_TLS_CERT_PATH` | Usually required | Path to `tls.cert` (if empty, verify with system roots) | | `LCPD_LND_ADMIN_MACAROON_PATH` | Recommended on mainnet | Admin macaroon (needed for payments/invoice ops) | | `LCPD_LND_MANIFEST_RESEND_INTERVAL` | Optional | Periodically re-send `lcp_manifest` to connected peers (unset/0s disables) | Typical default paths (adjust for your network and lnd setup): ```sh theme={null} export LCPD_LND_RPC_ADDR="localhost:10009" export LCPD_LND_TLS_CERT_PATH="$HOME/.lnd/tls.cert" export LCPD_LND_ADMIN_MACAROON_PATH="$HOME/.lnd/data/chain/bitcoin/mainnet/admin.macaroon" ``` ### Logging (privacy) `lcpd-grpcd` logs are intentionally designed to be diagnosable **without** persisting raw user content. * `LCPD_LOG_LEVEL` controls verbosity (`debug`, `info`, `warn`, `error`; default is `info`). * Logs MUST NOT contain raw prompts, raw model outputs, API keys, macaroons, or BOLT11 invoices. * Even with content redaction, logs still contain metadata (peer ids, job ids, prices, timings). Details: [Logging & privacy](/go-lcpd/docs/logging). ### Provider (YAML) | Variable | Required | Purpose | | --------------------------- | --------------------: | ---------------------------------------------------------------------------------------------- | | `LCPD_PROVIDER_CONFIG_PATH` | Required for Provider | Path to Provider YAML config (default: uses `config.yaml` in the current directory if present) | Provider configuration is YAML-first (`LCPD_PROVIDER_CONFIG_PATH`). Without YAML, Provider mode is disabled. Provider YAML details and examples are documented below in "Provider configuration (YAML)". ## Provider configuration (YAML) Provider behavior for `lcpd-grpcd` is configured via YAML only. * Pass the path via `LCPD_PROVIDER_CONFIG_PATH` * If unset, `config.yaml` in the current directory is used (if present) * If the file is empty or missing, defaults apply (Provider disabled, TTL=300s, `max_output_tokens=4096`, built-in price table, etc.) Sample with explicit defaults: `go-lcpd/config.yaml.sample` (copy to `go-lcpd/config.yaml`) ### Examples #### mainnet example ```yaml theme={null} enabled: true quote_ttl_seconds: 600 pricing: # Optional: load-based surge pricing, applied at quote-time only. # Multiplier = 1.0 + per_job_bps/10_000 * max(0, in_flight_jobs - threshold) in_flight_surge: threshold: 2 per_job_bps: 500 # +5% per job above threshold max_multiplier_bps: 30000 # 3.0x cap llm: max_output_tokens: 4096 models: gpt-5.2: # Optional: per-model override for max output tokens. # max_output_tokens: 4096 # Required: pricing (msat per 1M tokens). price: input_msat_per_mtok: 1750000 cached_input_msat_per_mtok: 175000 output_msat_per_mtok: 14000000 ``` #### regtest example ```yaml theme={null} enabled: true quote_ttl_seconds: 60 llm: max_output_tokens: 512 models: gpt-5.2: max_output_tokens: 512 price: input_msat_per_mtok: 1 output_msat_per_mtok: 1 ``` ### Model naming * `model` is the OpenAI model ID. * It appears in: * `openai_chat_completions_v1_params_tlvs.model` on the wire (in `params_bytes`) * the OpenAI request JSON (`request_json.model`) carried in the input stream bytes * gRPC `LCPManifest.supported_tasks[].openai_chat_completions_v1.model` (model advertising) * The Provider uses `model` for allowlisting, pricing, and routing to the compute backend. ### Field reference * `enabled`: Enables Provider mode. If `false`, rejects quote/cancel and does not create invoices. * `quote_ttl_seconds`: Quote and invoice TTL in seconds. Default is 300s. * `pricing.in_flight_surge`: Optional load-based surge pricing, computed from the current in-flight job count at quote time. * `threshold`: Number of in-flight jobs before surge applies. * `per_job_bps`: Additive multiplier per job above `threshold` (basis points; 10,000 = 1.0x). If `0`, surge is disabled. * `max_multiplier_bps`: Caps the total multiplier in basis points. If `0`, a safe default cap is used. * `llm.max_output_tokens`: Provider-wide default for output token limits, used for quote-time estimation and request validation. Default is 4096. * `llm.models`: Map of allowed/advertised `openai.chat_completions.v1` model IDs. If empty, accepts any `model` but does not advertise `supported_tasks`. * `max_output_tokens`: Optional per-model override (must be > 0). * `price`: Required per-model pricing (msat per 1M tokens). `input_msat_per_mtok` and `output_msat_per_mtok` are required; `cached_input_msat_per_mtok` is optional. ### Default price table If YAML is not provided, a built-in price table is used (msat per 1M tokens): * `gpt-5.2`: input 1,750,000 / cached 175,000 / output 14,000,000 ### Quote → Execute flow (`openai.chat_completions.v1`) 1. Validate the QuoteRequest and check the model is allowed. 2. Receive and validate the input stream as OpenAI request JSON bytes (`request_json.model`, `request_json.messages`, `request_json.stream=false`). 3. Determine `max_output_tokens` for quote-time estimation: * Start from `llm.max_output_tokens` (and optional per-model override). * If the request sets an output-token cap (`max_completion_tokens` / `max_tokens` / `max_output_tokens`), it must be `<=` the Provider max, and that value is used for estimation. 4. Estimate token usage via `UsageEstimator` (`approx.v1`: `ceil(len(bytes)/4)`). 5. Compute price in msat via `QuotePrice(model, estimate, cached=0, price_table)` and apply optional `pricing.in_flight_surge`, then embed it into TermsHash / invoice binding. 6. After payment settles, execute the passthrough request in the backend, stream the result (`lcp_stream_*`), and finalize with `lcp_result`. ## Backend notes * `openai`: calls an external API (billing / rate limits / network dependency). * Uses the OpenAI-compatible Chat Completions API (`POST /v1/chat/completions`). * Sends the raw request body bytes from the LCP input stream as-is (non-streaming). * Returns the raw OpenAI-compatible response body bytes as-is (non-streaming JSON). * `deterministic`: fixed-output backend for development (no external API). * `disabled`: does not execute (useful for Requester-only mode). ## Related docs * gRPC dev CLI: `cli.md` * mainnet walkthrough: `quickstart-mainnet.md` * regtest walkthrough: `regtest.md`