Agents-Flex vs BerriAI/litellm - GitHub
Side-by-side comparison · Updated October 2026
| Description | Agents-Flex is a powerful, open-source Java framework designed to simplify the development of AI applications by providing a structured and modular approach. It enables the creation of various AI applications, such as chatbots, image generation, embedding models, function calling, and Retrieval Augmented Generation (RAG) applications. The framework supports both synchronous and streaming APIs and offers features like LLM Connectors, prompt engineering capabilities, and memory management. It is compatible with JDK 8+, integrates with any framework, and includes advanced agent and chain orchestration capabilities, allowing developers to focus on unique project aspects while handling common tasks with ease. | LiteLLM is an AI gateway and Python SDK from Berrie AI Incorporated, published in the BerriAI GitHub repository. The SDK provides a common interface for model calls inside Python applications. The proxy gateway centralizes access for a team, with virtual keys, model routing, spend tracking, budgets and an administration interface. The official documentation lists support for more than 100 model providers. Supported endpoints and features vary by integration, so verify your model’s streaming, tool-calling, image, audio or embedding requirements. The router supports retries, fallbacks and load balancing; observability integrations can send request data to tools such as Langfuse, LangSmith and OpenTelemetry. LiteLLM also provides an MCP gateway. It can connect upstream servers using Streamable HTTP, SSE or stdio, expose tools through a fixed gateway endpoint, and scope access by key, team or organization. This requires configuring the upstream servers and authentication; the gateway does not automatically grant access to third-party tools. Agent-to-agent integrations are documented separately. The open-source offering has no software license fee for self-hosting. Code outside the enterprise directory is MIT-licensed, while enterprise code has separate terms. Enterprise pricing is quoted by annual gateway request capacity, deployment architecture and support needs, rather than a per-token license charge. Model-provider charges and infrastructure costs still apply. Enterprise adds controls and support such as SSO, SCIM, audit logs and service-level agreements. Compare New API for another self-hosted gateway with provider-channel management and usage accounting. Evaluate a representative workload, inspect request logging and secret handling, test budget and failure behavior, and decide whether SDK integration or a shared gateway best fits your application. |
| Category | AI Development Framework | Developer Tools |
| Rating | No reviews | No reviews |
| Pricing | Free | Open Source |
| Starting Price | Free | N/A |
| Plans |
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| Tags | JavaAI applicationschatbotsimage generationembedding models | AI gatewayPython SDKLLM routingMCP gatewayvirtual keys |
| Features | ||
| LLM Connectors supporting HTTP, SSE, and WebSockets. | ||
| Prompt engineering templates including FEW-SHOT, CRISPE, BROKE, and ICIO. | ||
| Flexible function calling with local and external service integration. | ||
| Comprehensive document processing tools for web, local, and database documents. | ||
| Advanced memory management systems for chat and execution contexts. | ||
| Embedding capabilities and support for multiple vector databases. | ||
| Agent and chain management for complex application scenarios. | ||
| Simple chat and history support for context-aware interactions. | ||
| Custom function definition and invocation through annotations. | ||
| Open-source availability with community contribution options. | ||
| Python SDK for direct application integration | ||
| Shared AI proxy gateway and administration UI | ||
| More than 100 documented model-provider integrations | ||
| Virtual keys, users, teams, budgets and rate limits | ||
| Spend tracking and observability integrations | ||
| Router retries, fallbacks and load balancing | ||
| MCP gateway for Streamable HTTP, SSE and stdio upstreams | ||
| Key, team and organization MCP permissions | ||
| Separate enterprise identity, audit and support features | ||
| View Agents-Flex | View BerriAI/litellm - GitHub | |
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