These docs are built from the langchain-parallel repo and have not been verified for accuracy by the LangChain team.
For issues, please open an issue in the langchain-parallel repo.
Refer to the docs for a high-level guide on how to use each module. These reference pages contain auto-generated API documentation for each module, focusing on the "what" rather than the "how" or "why" (i.e. no end-to-end tutorials or conceptual overviews).
Input schema for Parallel Extract Tool.
Parallel Extract Tool.
Input schema for ParallelWeb search tool.
Parallel Search tool with web research capabilities.
Settings for excerpt extraction.
Settings for full content extraction.
Fetch policy for cache vs live content.
Domain allow/deny lists and freshness floor for web research.
Webhook config for a Parallel monitor.
Manage scheduled web monitors via the Parallel Monitor API (alpha).
One BYOMCP server description for a Task Run.
Input schema for :class:ParallelTaskRunTool.
Run a single Parallel Task synchronously and return the structured result.
High-level Runnable for Parallel deep-research tasks.
Batch task runner backed by the Task Group API.
High-level Runnable for the structured-batch enrichment pattern.
LangChain retriever that returns Parallel Search results as Documents.
Webhook config for a FindAll run.
One boolean condition the API uses to filter candidates.
One entry in the FindAll exclude_list.
Input schema for :class:ParallelFindAllTool.
Run a Parallel FindAll discovery and return the matched candidates.
Parallel Web chat model integration.
Build a TaskSpecParam dict from pydantic classes / schemas / text.
Verify a Parallel webhook signature (Standard Webhooks scheme).
Extract citations, low-confidence fields, and interaction_id.
Retrieve the Parallel API key from argument or environment variables.
Returns a configured sync OpenAI client for the Chat API.
Returns a configured async OpenAI client for the Chat API.
Returns a configured sync Parallel SDK client.
Returns a configured async Parallel SDK client.
