--- title: "agentscope vs haystack" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agentscope-ai-agentscope-vs-deepset-ai-haystack" tools: ["agentscope-ai-agentscope", "deepset-ai-haystack"] --- # agentscope vs haystack *GraphCanon updated Aug 16, 2026* ## Verdict Pick agentscope if agentscope is a Python-based development tool focused on creating transparent and trustworthy AI agents. It supports the creation of both single and multi-agent systems incorporating large language models into its design; pick haystack if haystack is an open-source AI orchestration framework for building context-engineered LLM applications. [agentscope](https://docs.agentscope.io/) reports 29k GitHub stars, 3.4k forks, and 354 open issues, last pushed Aug 14, 2026. [haystack](https://haystack.deepset.ai) has 26k stars, 3.0k forks, and 108 open issues, last pushed Aug 1, 2026. Figures are from public GitHub metadata via [agentscope's repository](https://github.com/agentscope-ai/agentscope) and [haystack's repository](https://github.com/deepset-ai/haystack). | | [agentscope](/tools/agentscope-ai-agentscope.md) | [haystack](/tools/deepset-ai-haystack.md) | | --- | --- | --- | | Tagline | Build and run agents you can see, understand and trust. | Open-source AI orchestration framework for building context-engineered LLM applications. | | Stars | 28,973 | 26,073 | | Forks | 3,367 | 2,972 | | Open issues | 354 | 108 | | Language | Python | Python | | Adopt for | agentscope is a Python-based development tool focused on creating transparent and trustworthy AI agents. It supports the creation of both single and multi-agent systems incorporating large language models into its design | Haystack is an open-source AI orchestration framework for building context-engineered LLM applications. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | AI Agents, LLM Frameworks | AI Agents, Data & Retrieval, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agentscope](/tools/agentscope-ai-agentscope.md) | [haystack](/tools/deepset-ai-haystack.md) | | --- | --- | --- | | Days since push | 2d | 0d | | Open issues (now) | 354 | 108 | | Stars delta | +1.0k (30d) | Unknown | | Open issues delta | +70 (30d) | Unknown | | Full report | [trust report](/tools/agentscope-ai-agentscope/trust.md) | [trust report](/tools/deepset-ai-haystack/trust.md) | ## Shared compatibility - **Python**: [agentscope](/tools/agentscope-ai-agentscope.md) - Python runtime; [haystack](/tools/deepset-ai-haystack.md) - Python runtime ## Decision facts: agentscope - **Adopt for:** agentscope is a Python-based development tool focused on creating transparent and trustworthy AI agents. It supports the creation of both single and multi-agent systems incorporating large language models into its design ## Decision facts: haystack - **Pricing:** freemium - Free and open-source under the Apache-2.0 license, but users have to manage their own infrastructure and resources. - **Requirements:** Min 4 GB RAM; Requires Docker - **Adopt for:** Haystack is an open-source AI orchestration framework for building context-engineered LLM applications. - **License detail:** Apache-2.0 ## Choose when ### Choose agentscope if… - Tags unique to agentscope: chatbot, llm, llm-agent, multi-agent. - - You need to develop AI agents where transparency and interpretability are critical. - More GitHub stars (29k vs 26k) - visibility, not fit. ### Choose haystack if… - Pricing: Free and open-source under the Apache-2.0 license, but users have to manage their own infrastructure and resources.. - Requirements: Min 4 GB RAM; Requires Docker. - Tags unique to haystack: agents, ai, gemini, generative-ai. - Also covers Data & Retrieval. - You need explicit control over retrieval, routing, memory, and generation within your LLM application pipelines. ## When NOT to use agentscope - - If your project does not benefit from the transparency features offered by agentscope, and less emphasis is placed on interpretability and more on specialized machine learning tasks without a need ## When NOT to use haystack - You require integration with specific proprietary tools or frameworks not supported by Haystack. - Your development team is not familiar with Python-based technologies, since Haystack primarily supports Python-based workflows. - You are looking for a completely managed service rather than an open-source framework that requires more hands-on configuration and customization. ## Common questions ### What is the difference between agentscope and haystack? agentscope: Build and run agents you can see, understand and trust.. haystack: Open-source AI orchestration framework for building context-engineered LLM applications.. See the comparison table for live GitHub stats and shared categories. ### When should I choose agentscope over haystack? Choose agentscope over haystack when Tags unique to agentscope: chatbot, llm, llm-agent, multi-agent; - You need to develop AI agents where transparency and interpretability are critical; More GitHub stars (29k vs 26k) - visibility, not fit. ### When should I choose haystack over agentscope? Choose haystack over agentscope when Pricing: Free and open-source under the Apache-2.0 license, but users have to manage their own infrastructure and resources.; Requirements: Min 4 GB RAM; Requires Docker; Tags unique to haystack: agents, ai, gemini, generative-ai; Also covers Data & Retrieval; You need explicit control over retrieval, routing, memory, and generation within your LLM application pipelines. ### When should I avoid agentscope? - If your project does not benefit from the transparency features offered by agentscope, and less emphasis is placed on interpretability and more on specialized machine learning tasks without a need ### When should I avoid haystack? You require integration with specific proprietary tools or frameworks not supported by Haystack. Your development team is not familiar with Python-based technologies, since Haystack primarily supports Python-based workflows. You are looking for a completely managed service rather than an open-source framework that requires more hands-on configuration and customization. ### Is agentscope or haystack more popular on GitHub? agentscope has more GitHub stars (28,973 vs 26,073). Stars measure visibility, not whether either tool fits your constraints. ### Are agentscope and haystack open source? Yes - both are open-source projects on GitHub (agentscope: Apache-2.0, haystack: Apache-2.0). ### Where can I find alternatives to agentscope or haystack? GraphCanon lists graph-backed alternatives at [agentscope alternatives](/tools/agentscope-ai-agentscope/alternatives) and [haystack alternatives](/tools/deepset-ai-haystack/alternatives) ([agentscope markdown twin](/tools/agentscope-ai-agentscope/alternatives.md), [haystack markdown twin](/tools/deepset-ai-haystack/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/agentscope-ai-agentscope-vs-deepset-ai-haystack.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agentscope or haystack? agentscope: Very active. haystack: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for agentscope and haystack? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agentscope trust report](/tools/agentscope-ai-agentscope/trust); [haystack trust report](/tools/deepset-ai-haystack/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=agentscope-ai-agentscope`](/api/graphcanon/graph?tool=agentscope-ai-agentscope) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_