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@promptbook/vercel

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Promptbook: Turn your company's scattered knowledge into AI ready books

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import type { ChatPromptResult } from '../../execution/PromptResult'; import type { Prompt } from '../../types/Prompt'; import type { string_agent_hash, string_agent_name } from '../../types/typeAliases'; import { Agent } from './Agent'; import type { RemoteAgentOptions } from './RemoteAgentOptions'; /** * Represents one AI Agent * * Note: [🦖] There are several different things in Promptbook: * - `Agent` - which represents an AI Agent with its source, memories, actions, etc. Agent is a higher-level abstraction which is internally using: * - `LlmExecutionTools` - which wraps one or more LLM models and provides an interface to execute them * - `AgentLlmExecutionTools` - which is a specific implementation of `LlmExecutionTools` that wraps another LlmExecutionTools and applies agent-specific system prompts and requirements * - `OpenAiAssistantExecutionTools` - which is a specific implementation of `LlmExecutionTools` for OpenAI models with assistant capabilities, recommended for usage in `Agent` or `AgentLlmExecutionTools` * - `RemoteAgent` - which is an `Agent` that connects to a Promptbook Agents Server * * @public exported from `@promptbook/core` */ export declare class RemoteAgent extends Agent { static connect(options: RemoteAgentOptions): Promise<RemoteAgent>; /** * The source of the agent */ private agentUrl; private _remoteAgentName; private _remoteAgentHash; private constructor(); get agentName(): string_agent_name; get agentHash(): string_agent_hash; /** * Calls the agent on agents remote server */ callChatModel(prompt: Prompt): Promise<ChatPromptResult>; /** * Calls the agent on agents remote server with streaming */ callChatModelStream(prompt: Prompt, onProgress: (chunk: ChatPromptResult) => void): Promise<ChatPromptResult>; } /** * TODO: [🧠][😰]Agent is not working with the parameters, should it be? * TODO: !!! Agent on remote server */