BerriAI/litellm - GitHub vs Haptik

Side-by-side comparison · Updated October 2026

 BerriAI/litellm - GitHubBerriAI/litellm - GitHubHaptikHaptik
DescriptionLiteLLM 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.Haptik's AI Agents webinar, titled 'Future of Enterprise Automation', is scheduled for 24th July at 4 PM IST. The webinar will delve into the transformative potential of AI-driven agents in automating enterprise tasks and improving operational efficiency. Join industry experts as they discuss advancements, use cases, and best practices for integrating AI agents into business workflows to stay ahead of the competition.
CategoryDeveloper ToolsAI Assistant
RatingNo reviewsNo reviews
PricingOpen SourceFreemium
Starting PriceN/AFree
Plans—
  • Free — Free
Use Cases
  • Developers
  • Enterprises
  • Startups
  • Educational Institutions
  • Business professionals
  • IT leaders
  • AI enthusiasts
  • Project managers
Tags
AI gatewayPython SDKLLM routingMCP gatewayvirtual keys
AI AgentswebinarEnterprise Automationindustry expertsAI-driven agents
Features
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
Expert speakers
Latest advancements in AI
Best practices for AI integration
Real-world use cases
Interactive Q&A session
Free registration
Recorded session available
Strategic insights
Industry-specific examples
Future trends in enterprise automation
 View BerriAI/litellm - GitHubView Haptik

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