docs: Add FAQ section for common questions about Airweave context retrieval

[meichuanyi]

Summary

This PR adds a comprehensive FAQ section to the README, covering common questions about Airweave:

Topics Covered

General:

• What is Airweave (context retrieval layer for AI agents)
• Difference from traditional RAG systems
• Where it fits in architecture

Getting Started:

• Quick start (Cloud-hosted vs Self-hosted)
• Docker setup instructions

Integrations:

• 50+ supported integrations (productivity, storage, communication, development, CRM, etc.)
• Adding new integrations

SDKs & CLI:

• Python SDK (pip install airweave-sdk)
• TypeScript SDK (npm install @airweave/sdk)
• CLI usage examples
• MCP support

Technical Details:

• Tech stack (React/FastAPI/PostgreSQL/Vespa/Temporal/Redis)
• Syncing mechanism (Temporal orchestration)
• Retrieval process (vector search + metadata filtering)

Performance & Scale:

• Multiple sources handling
• Large datasets management

Troubleshooting:

• Sync failure troubleshooting
• Search relevance issues
• Docker startup issues

Help & Resources:

• Documentation links
• Example notebooks
• Discord community
• GitHub issues

This FAQ helps new users understand Airweave's unified retrieval approach, get started quickly, and troubleshoot common issues.

---

Summary by cubic

Adds a focused FAQ to the README covering what Airweave is, where it fits, setup options (cloud vs self-hosted), supported integrations, and how to query via the SDKs (airweave-sdk, @airweave/sdk) and CLI (airweave-cli). Also includes MCP support, tech stack details, performance guidance, troubleshooting steps, and resource links to speed up onboarding.

^{Written for commit 52ed2cf. Summary will update on new commits.}

[cubic-dev-ai]

No issues found across 1 file