LLMR 0.8.10

A bug-fix release; all changes are backward compatible.

• llm_hash() no longer depends on the collation locale, so the same object hashes identically on every machine; hashes recorded under the C locale are unchanged.
• Constant prompts (no {column} reference) now fill every row; previously rows 2..n were sent with NA content and rejected by providers.
• llm_mutate() appends its generated columns again (instead of moving them to the front), and .before/.after now work on the embedding, structured, tag, and row-batched paths.
• llm_usage() and llm_failures() work on llm_mutate_structured() and llm_mutate_tags() results; config-side and log-side request hashes agree after provider parameter renames.
• Streaming no longer errors for providers outside the built-in table and now applies the req_builder hook and the request timeout. Assorted smaller fixes; see the commit log.

LLMR 0.8.9

• Additive helpers for the agent layer: call_llm_par(.request_hash =), llm_add_request_hash(), llm_log_active(), llm_tool_signature(), and llm_uuid().
• llm_agreement() gains ordinal and interval Krippendorff’s alpha (metric =); the nominal default is unchanged.

LLMR 0.8.8

• Bundled example data anes_2024_personas: 100 participant profiles derived from the ANES 2024 public release, the shared persona dataset of the LLMR family.
• Persona-frame contract helpers: llm_persona_split(), llm_persona_overview(), llm_persona_dictionary(), llm_persona_demographic_fields(), llm_validate_persona_frame().

LLMR 0.8.7

• transcript_as_messages() and ensure_alternating_messages(): build a provider-safe, role-flipped message array from a multi-speaker transcript (own turns become assistant, others become labeled user turns).

LLMR 0.8.6

• Row-packing controls renamed (.batch_size -> .rows_per_prompt, and kin); the word “batch” is now reserved for the asynchronous provider Batch API.
• llm_log_read(): parse a JSONL audit log into records plus a per-record manifest with record and request hashes.
• llm_request_hash() canonicalizes message shape and keys on all generation parameters, so a logged call and its config hash identically.
• Added the shared reset() generic.

LLMR 0.8.5

• Provenance helpers: llm_response_record() (one-row response contract; a failed call is a row, never a dropped call) and llm_request_hash() (stable identity for a call).

LLMR 0.8.4

• Added the shared S3 generics diagnostics() and report(), implemented by the LLMR method packages.

LLMR 0.8.3

• Provider Batch APIs at roughly half price: llm_batch_submit(), llm_batch_status(), llm_batch_fetch(), llm_batch_cancel() (OpenAI, Groq, Anthropic, Gemini).
• Audit log for reproducible research (llm_log_enable()), a draft methods paragraph (llm_methods_text()), and replication with agreement statistics (llm_replicate(), llm_agreement()).
• Native tool calling (llm_tool(), call_llm_tools()) and streaming (call_llm_stream()).
• Token log-probabilities (llm_logprobs()), canonical seed, model_version and thinking on every response, prompt caching, and cost estimates from a user-supplied price_table.
• One shared request builder for the nine OpenAI-compatible providers, with full multimodal, structured-output, tools, and hooks parity.

LLMR 0.8.0

• llm_preview(): render exactly what a call would send, and flag problems, without any API call.
• llm_usage() and llm_failures(): outcome counts, token totals, and per-row failure listings for any result frame.
• Missing token usage is reported as NA, not 0; a bare environment-variable name passed as api_key is always treated as a reference.
• New “LLMR in 5 minutes” quickstart vignette, runnable on an open-weight model.

LLMR 0.7.2

• Retry and error-classification fixes (provider errors containing braces, typed re-raise after exhausted retries).
• llm_par_resume() re-runs only the failed rows; JSON array recovery and embedding-dimension fixes.

LLMR 0.7.1

• Row batching for generative calls: pack several rows into one request, with fault-tolerant recovery for dropped, reordered, or truncated rows.

LLMR 0.7.0

• Soft structured output via XML-like tags: .tags on llm_mutate(), plus llm_mutate_tags(), llm_fn_tags(), and the tag parsers.
• Four new providers (Xiaomi, Alibaba/Qwen, Zhipu, Moonshot) and Gemini on Vertex AI.

LLMR 0.6.3

• Ollama provider (local generative and embedding models); stable embedding column names.

LLMR 0.6.2

• llm_mutate() shorthand (answer = "{question}") and .structured = TRUE.

LLMR 0.6.1

• Fixed a bug affecting Anthropic calls.

LLMR 0.6.0

• call_llm() returns an llmr_response object; as.character(x) extracts the text.
• Secure API-key handling, structured JSON output, and multi-column injection in llm_mutate().