ai-framework
LlamaIndex
Data framework for LLMs — RAG-first with LlamaCloud + LlamaParse
OSS data framework for LLM apps. RAG-first design. LlamaParse (best-in-class PDF parser), LlamaCloud (managed indexing + parsing). Python + TypeScript.
Pricing
| Tier | Price | Notes |
|---|---|---|
| OSS (MIT) | Free | MIT-licensed core. Python + TypeScript. Free forever. |
| LlamaCloud — Free | Free | Free tier of LlamaCloud. 1,000 pages/day via LlamaParse. Basic indexing. |
| LlamaCloud — Paid | Free | Pay-per-page parsing + usage-based indexing. $0.003 per page (Fast mode). |
| LlamaCloud Enterprise | Custom | Custom. SSO, SOC2, higher rate limits, private index hosting. |
Limits
| Tier | Metric | Value | Notes |
|---|---|---|---|
| — | integrations count | 300+ integrations (LLMs, vector stores, loaders, tools) | Integrations |
| — | languages | Python (primary) + TypeScript | SDK languages |
| — | llm provider neutral | Works with OpenAI, Anthropic, Mistral, local models, etc. | LLM neutrality |
| — | parse complex rate | $0.03 per page (Complex multimodal) | Parse Complex |
| — | parse fast rate | $0.003 per page (Fast mode) | LlamaParse Fast |
| — | parse premium rate | $0.015 per page (Premium — tables, math, complex layouts) | LlamaParse Premium |
| — | primary focus | RAG + structured extraction + agentic retrieval | Design focus |
| — | supported formats | PDF, DOCX, PPTX, XLSX, HTML, images (OCR) | LlamaParse formats |
Features
- Agents — Agent patterns: ReAct, function-calling, multi-agent workflows.
- Document Readers — 200+ readers for PDF, web, Google Drive, SharePoint, Notion, S3, Slack.
- Evaluations — Built-in eval framework: faithfulness, context precision/recall.
- LlamaCloud — Managed indexing + retrieval platform. File connectors, auto-chunking, retrieval API. · docs
- LlamaExtract — Schema-based structured extraction from unstructured docs.
- LlamaHub — Community marketplace of readers, tools, prompts. · docs
- LlamaParse — Best-in-class PDF + complex document parser. Tables, math, layout preserved. · docs
- Multimodal — Image + text models, image retrieval.
- Node Parsers — Document chunkers: token, sentence, semantic, hierarchical.
- Observability (OpenLLMetry) — OTel-based tracing baked in.
- Property Graph — Graph-based RAG (knowledge graphs from unstructured data).
- Query Engines — Retrieval + response synthesis combos — router, sub-question, tree, etc.
- RAG — End-to-end RAG patterns: ingest → index → retrieve → synthesize.
- Tools — 50+ pre-built tool integrations.
- Vector Store Integrations — 50+ vector DB integrations.
- Workflows — Event-driven agent workflows (AgentWorkflow). · docs
Developer interfaces
| Slug | Name | Kind | Version |
|---|---|---|---|
| llamacloud | LlamaCloud API | rest | v1 |
| mcp | LlamaIndex MCP | mcp | — |
| sdk-python | llama-index (Python) | sdk | 0.12.x |
| sdk-ts | llamaindex (TS) | sdk | 0.9.x |
| llamaparse | LlamaParse API | rest | v1 |
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