{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/4"}],"enrichment":{"capability":"A Python client for accessing LLMs through UiPath's infrastructure, supporting multiple backends (AgentHub, Orchestrator, LLMGateway) and providers (OpenAI, Google, Anthropic, AWS Bedrock, Fireworks AI, Azure AI) with optional LangChain integration.","skillfed_tags":["llm-client","uipath-integration","multi-provider"],"use_cases":["Route LLM requests through UiPath AgentHub for model discovery, routing, and tracing in RPA workflows.","Use LangChain-compatible chat models and embeddings within UiPath Orchestrator automation jobs.","Access multiple LLM providers (OpenAI, Google, Anthropic, AWS Bedrock) via a single unified client.","Integrate LLM capabilities into UiPath agent-based systems with automatic CLI-based authentication.","Send requests to LLMGateway backend with S2S authentication for enterprise multi-tenant deployments."],"what_it_does":"UiPath LLM Client is a Python library that wraps UiPath's LLM infrastructure, allowing you to send requests to multiple LLM providers (OpenAI, Google, Anthropic, AWS Bedrock, Fireworks AI, Azure AI) through UiPath's managed backends. It provides both a low-level HTTP client with built-in authentication, retry logic, and request handling, and a separate LangChain-compatible integration for chat models and embeddings. The package supports three backend modes: AgentHub (default, CLI-based authentication), Orchestrator (same auth as AgentHub but different routing), and LLMGateway (S2S authentication). You configure it via environment variables or direct instantiation, and it handles token refresh and endpoint selection automatically.\n\nThe client is designed for teams already using UiPath's platform infrastructure who want to integrate LLM capabilities without managing provider credentials directly. It abstracts away backend selection and authentication complexity, making it suitable for enterprise automation workflows, agent-based systems, and applications that need to route LLM requests through a centralized gateway.","worth_installing":"Yes, if you are already using UiPath's platform and need LLM integration. The package is actively maintained, has low install friction, and supports multiple backends and providers. However, verify the license terms first \u2014 the license status is unclear in the metadata, which is a blocker for some use cases. No known security vulnerabilities as of the latest scan."},"id":"uipath-llm-client","links":{"html":"https://skillfed.io/packages/uipath-llm-client","md":"https://skillfed.io/packages/uipath-llm-client.md","pypi":"https://pypi.org/project/uipath-llm-client/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-13","license_spdx":null,"license_treatment":"unclear","name":"uipath-llm-client","python_support":"supports_current","summary":"UiPath LLM Client"},"popularity":{"monthly_downloads":1144967,"position":4301,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"1.17.2"}