BeamWeaver

v0.1.5 Feature

This release adds 2 notable features for engineering teams evaluating rollout.

Published 28d AI Agents & Assistants

✓ No known CVEs patched

✓ No known CVEs patched in this version

Topics

ai-agents deepagents elixir harness human-in-the-loop langchain

+4 more

langgraph-alternative llm observability distributed-tracing

Summary

AI summary

Added first-class prompt caching options for OpenAI, xAI/Grok, and updated trace handling to preserve cache keys.

Full changelog

Added a dedicated prompt-caching guide and runnable example covering stable
cache-key construction, provider-specific cache controls, and cache-hit
inspection across OpenAI, xAI/Grok, Anthropic, Moonshot/Kimi, Gemini, and
Z.ai.
Added first-class OpenAI Responses and Chat Completions prompt_cache_key and
prompt_cache_retention model options, while keeping per-call overrides.
Added xAI/Grok cache routing support: Responses accepts prompt_cache_key,
and Chat Completions accepts x_grok_conv_id, which BeamWeaver sends as the
x-grok-conv-id header.

Model traces now preserve provider-specific invocation parameters from the
checked-in profile registry, including cache keys and cache-routing options,
while still omitting client configuration and secrets.
Redaction now keeps token counts and generation limits such as
max_output_tokens, budget_tokens, and *_token_count fields so cache and
usage telemetry remain inspectable.

OpenAI Responses prompt_cache_key now respects first-class model options
ahead of model_kwargs, while per-call options continue to take precedence.
xAI requests now merge per-call headers with default headers and let per-call
x_grok_conv_id override the model-level conversation/cache routing header.

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