langcache
This skill should be used when the user asks to "enable semantic caching", "cache LLM responses", "reduce API costs", "speed up AI responses", "configure LangCache", "search the semantic cache", "store responses in cache", or mentions Redis LangCache, semantic similarity caching, or LLM response caching. Provides integration with Redis LangCache managed service for semantic caching of prompts and responses.
Why use this skill?
Integrate Redis LangCache into OpenClaw to enable semantic caching. Reduce latency and LLM API costs by serving similar queries from cache.
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/manvinder01/openclaw-langcacheWhat This Skill Does
The LangCache skill for OpenClaw integrates the Redis LangCache managed service to provide high-performance semantic caching for LLM-powered workflows. Unlike traditional key-value caches that rely on exact string matches, semantic caching interprets the meaning of user prompts. By using vector similarity search, the skill retrieves relevant previous responses when a new query is semantically equivalent to one already processed. This significantly reduces latency for repetitive user queries, lowers API consumption costs for LLM providers, and improves the overall responsiveness of your AI agents.
Installation
To install this skill, use the standard OpenClaw CLI tool. Ensure you have your Redis LangCache credentials ready before proceeding. Run the following command in your terminal:
clawhub install openclaw/skills/skills/manvinder01/openclaw-langcache
After installation, you must configure your environment variables by adding the LANGCACHE_HOST, LANGCACHE_CACHE_ID, and LANGCACHE_API_KEY to your ~/.openclaw/secrets.env file. Without these, the skill cannot authenticate with the managed service.
Use Cases
This skill is ideal for any agent that handles repetitive inquiries. Use it for building a documentation FAQ bot where users ask variations of the same "how-to" questions, or for customer support agents that use standardized reply templates. It is also highly effective for development teams who query the same technical documentation or internal knowledge base repeatedly, allowing the agent to provide instant answers without querying the LLM again.
Example Prompts
- "Enable semantic caching for my current session to reduce latency and API costs."
- "Search the semantic cache to see if there is an existing explanation for how the OpenClaw configuration file works."
- "Configure LangCache with my API key and cache ID so the agent stops re-generating the same technical support replies."
Tips & Limitations
To get the most out of LangCache, always set an appropriate similarity threshold. While the default is 0.90, you may need to adjust it for specific use cases: use higher thresholds (0.95+) for strict technical answers and lower thresholds (0.85) for stylistic or creative variations. Note that certain sensitive data or dynamic information that changes per user should never be cached. Always verify the cache policy before implementation to ensure that real-time data remains accurate and isn't being served from stale cached entries.
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Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-manvinder01-openclaw-langcache": {
"enabled": true,
"auto_update": true
}
}
}Tags(AI)
Flags: external-api, network-access