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SDKs and frameworks

Clients and adapters that put Remiq’s context in front of your model. Each one is one call to /v1/context before the model call; your model and its key stay yours.

Clients

Language	File	Use
Python	`prism_client.py`	`p = Prism(key, url)`, then `p.add(text, user=...)` and `p.context(query, user=...)`. One file, standard library only
TypeScript	`sdk-ts/prism.ts`	The same calls, typed answers, no dependencies (global `fetch`)

Frameworks

Framework	Adapter	What it does
LangChain	`adapters/langchain_prism.py`	`PrismRetriever(prism=p, user="alice").invoke(question)` returns the cited records as Documents; `with_prism(your_chat_model, p, user="alice")` puts the context in front of your model
LlamaIndex	`adapters/llamaindex_prism.py`	`PrismRetriever(p, user="alice").retrieve(question)` returns the cited records, best first
OpenAI Agents SDK	`adapters/openai_agents_prism.py`	`Agent(..., tools=prism_tools(p, user="alice"))`: remember and get context as function tools
Claude Agent SDK	`adapters/claude_agent_prism.py`	`ClaudeAgentOptions(mcp_servers={"prism": prism_mcp_server(p, user="alice")})`: Remiq as MCP tools in your agent
Claude memory tool	`adapters/anthropic_memory.py`	A backend for Anthropic’s memory tool: what Claude writes under `/memories` becomes searchable, permissioned records. Your Anthropic key stays with you
Vercel AI SDK	`sdk-ts/adapters/vercel.ts`	`wrapLanguageModel({ model, middleware: prismMiddleware(p, { user }) })`: one context call before each model call
Voice (LiveKit, Pipecat)	`adapters/livekit_prism.py`, `adapters/pipecat_prism.py`	One context call per spoken turn; the user’s words are saved in the background