{"data":{"node":{"slug":"deepset-ai-haystack","name":"haystack","tagline":"Open-source AI orchestration framework for building context-engineered LLM applications.","github_url":"https://github.com/deepset-ai/haystack","owner":"deepset-ai","repo":"haystack","owner_avatar_url":"https://avatars.githubusercontent.com/u/51827949?v=4","primary_language":"Python","stars":26073,"forks":2972,"topics":["agent","agents","ai","gemini","generative-ai","gpt-4","information-retrieval","large-language-models","llm","machine-learning","nlp","orchestration","python","pytorch","question-answering","rag","retrieval-augmented-generation","semantic-search","summarization","transformers"],"archived":false,"github_pushed_at":"2026-08-01T03:06:32+00:00","maintenance_label":"Very active","url":"https://www.graphcanon.com/tools/deepset-ai-haystack","markdown_url":"https://www.graphcanon.com/tools/deepset-ai-haystack.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/deepset-ai-haystack","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=deepset-ai-haystack"},"categories":[{"slug":"ai-agents","name":"AI Agents","url":"https://www.graphcanon.com/categories/ai-agents","markdown_url":"https://www.graphcanon.com/categories/ai-agents.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/ai-agents"},{"slug":"data-retrieval","name":"Data & Retrieval","url":"https://www.graphcanon.com/categories/data-retrieval","markdown_url":"https://www.graphcanon.com/categories/data-retrieval.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/data-retrieval"},{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"}],"tags":[{"slug":"agent","name":"agent"},{"slug":"agents","name":"agents"},{"slug":"ai","name":"ai"},{"slug":"gemini","name":"gemini"},{"slug":"generative-ai","name":"generative-ai"},{"slug":"gpt-4","name":"gpt-4"},{"slug":"information-retrieval","name":"information-retrieval"},{"slug":"large-language-models","name":"large language models"}],"edges":[{"type":"related","direction":"out","explanation":"ECC is a performance optimization system for agents, which can be related to the orchestration role of Haystack in agent workflow development.","successor_context":null,"tool":{"slug":"affaan-m-ecc","name":"ECC","tagline":"The agent harness performance optimization system for AI agents","github_url":"https://github.com/affaan-m/ECC","owner":"affaan-m","repo":"ECC","owner_avatar_url":"https://avatars.githubusercontent.com/u/124439313?v=4","primary_language":"JavaScript","stars":240297,"forks":36463,"topics":["ai-agents","anthropic","claude","claude-code","developer-tools","llm","mcp","productivity"],"archived":false,"github_pushed_at":"2026-08-15T20:02:53+00:00","maintenance_label":"Very active","stars_delta_30d":9964,"url":"https://www.graphcanon.com/tools/affaan-m-ecc","markdown_url":"https://www.graphcanon.com/tools/affaan-m-ecc.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/affaan-m-ecc","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=affaan-m-ecc"}},{"type":"integrates_with","direction":"out","explanation":"Haystack integrates with LangChain through their shared focus on modular component design in AI application frameworks. Haystack's capability for building modular pipelines that include retrieval and generation tasks directly complements LangChain’s aim of chaining interoperable components to build agents and LLM-powered applications.","successor_context":null,"tool":{"slug":"langchain-ai-langchain","name":"langchain","tagline":"The agent engineering platform.","github_url":"https://github.com/langchain-ai/langchain","owner":"langchain-ai","repo":"langchain","owner_avatar_url":"https://avatars.githubusercontent.com/u/126733545?v=4","primary_language":"Python","stars":143615,"forks":23930,"topics":["agents","ai","ai-agents","anthropic","chatgpt","deepagents","enterprise","framework","gemini","generative-ai","langchain","langgraph","llm","multiagent","open-source","openai","pydantic","python","rag","typescript"],"archived":false,"github_pushed_at":"2026-08-07T08:27:07+00:00","maintenance_label":"Very active","stars_delta_30d":2337,"url":"https://www.graphcanon.com/tools/langchain-ai-langchain","markdown_url":"https://www.graphcanon.com/tools/langchain-ai-langchain.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/langchain-ai-langchain","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=langchain-ai-langchain"}},{"type":"successor","direction":"out","explanation":"LangChain is an agent engineering platform, evolving from the types of modular frameworks developed by tools like Haystack.","successor_context":{"status":"coexists","reason":"Both tools coexist in their respective niches within AI orchestration and may complement each other."},"tool":{"slug":"langchain-ai-langchain","name":"langchain","tagline":"The agent engineering platform.","github_url":"https://github.com/langchain-ai/langchain","owner":"langchain-ai","repo":"langchain","owner_avatar_url":"https://avatars.githubusercontent.com/u/126733545?v=4","primary_language":"Python","stars":143615,"forks":23930,"topics":["agents","ai","ai-agents","anthropic","chatgpt","deepagents","enterprise","framework","gemini","generative-ai","langchain","langgraph","llm","multiagent","open-source","openai","pydantic","python","rag","typescript"],"archived":false,"github_pushed_at":"2026-08-07T08:27:07+00:00","maintenance_label":"Very active","stars_delta_30d":2337,"url":"https://www.graphcanon.com/tools/langchain-ai-langchain","markdown_url":"https://www.graphcanon.com/tools/langchain-ai-langchain.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/langchain-ai-langchain","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=langchain-ai-langchain"}},{"type":"depends_on","direction":"out","explanation":null,"successor_context":null,"tool":{"slug":"huggingface-transformers","name":"transformers","tagline":"Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models","github_url":"https://github.com/huggingface/transformers","owner":"huggingface","repo":"transformers","owner_avatar_url":"https://avatars.githubusercontent.com/u/25720743?v=4","primary_language":"Python","stars":164121,"forks":34249,"topics":["audio","deep-learning","deepseek","gemma","glm","hacktoberfest","llm","machine-learning","model-hub","natural-language-processing","nlp","pretrained-models","python","pytorch","pytorch-transformers","qwen","speech-recognition","transformer","vlm"],"archived":false,"github_pushed_at":"2026-08-15T22:28:12+00:00","maintenance_label":"Very active","stars_delta_30d":1457,"url":"https://www.graphcanon.com/tools/huggingface-transformers","markdown_url":"https://www.graphcanon.com/tools/huggingface-transformers.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/huggingface-transformers","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=huggingface-transformers"}},{"type":"alternative","direction":"out","explanation":"Haystack and LangFlow both offer frameworks for building AI-powered agents and workflows, but with different designs and approaches.","successor_context":null,"tool":{"slug":"langflow-ai-langflow","name":"langflow","tagline":"Tool for building and deploying AI-powered agents and workflows","github_url":"https://github.com/langflow-ai/langflow","owner":"langflow-ai","repo":"langflow","owner_avatar_url":"https://avatars.githubusercontent.com/u/85702467?v=4","primary_language":"Python","stars":152744,"forks":9747,"topics":["agents","chatgpt","generative-ai","large-language-models","multiagent","react-flow"],"archived":false,"github_pushed_at":"2026-08-02T00:44:47+00:00","maintenance_label":"Very active","url":"https://www.graphcanon.com/tools/langflow-ai-langflow","markdown_url":"https://www.graphcanon.com/tools/langflow-ai-langflow.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/langflow-ai-langflow","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=langflow-ai-langflow"}},{"type":"integrates_with","direction":"out","explanation":"Haystack integrates with Langflow because Haystack's modular pipelines for creating production-ready LLM applications can be designed and visually authored using Langflow’s interface. This integration allows users to utilize Haystack’s capabilities within Langflow’s comprehensive AI workflow management environment.","successor_context":null,"tool":{"slug":"langflow-ai-langflow","name":"langflow","tagline":"Tool for building and deploying AI-powered agents and workflows","github_url":"https://github.com/langflow-ai/langflow","owner":"langflow-ai","repo":"langflow","owner_avatar_url":"https://avatars.githubusercontent.com/u/85702467?v=4","primary_language":"Python","stars":152744,"forks":9747,"topics":["agents","chatgpt","generative-ai","large-language-models","multiagent","react-flow"],"archived":false,"github_pushed_at":"2026-08-02T00:44:47+00:00","maintenance_label":"Very active","url":"https://www.graphcanon.com/tools/langflow-ai-langflow","markdown_url":"https://www.graphcanon.com/tools/langflow-ai-langflow.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/langflow-ai-langflow","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=langflow-ai-langflow"}},{"type":"alternative","direction":"out","explanation":"Haystack and ragflow both offer frameworks for building Retrieval-Augmented Generation (RAG) systems but differ in their approach. Haystack provides a broader set of tools for creating modular pipelines and managing various components like retrieval, routing, memory, and generation for diverse applications including RAG, while ragflow specifically focuses on integrating retrieval and generation to","successor_context":null,"tool":{"slug":"infiniflow-ragflow","name":"ragflow","tagline":"Retrieval-Augmented Generation engine with agent capabilities","github_url":"https://github.com/infiniflow/ragflow","owner":"infiniflow","repo":"ragflow","owner_avatar_url":"https://avatars.githubusercontent.com/u/69962740?v=4","primary_language":"Go","stars":86541,"forks":10167,"topics":["agent-harness","agentic-ai","agentic-retrieval","agentic-search","ai","ai-agents","context-engine","context-engineering","context-management","harness-engineering","knowledge-compilation","llm-apps","rag","retrieval-augmented-generation"],"archived":false,"github_pushed_at":"2026-07-31T14:59:12+00:00","maintenance_label":"Very active","url":"https://www.graphcanon.com/tools/infiniflow-ragflow","markdown_url":"https://www.graphcanon.com/tools/infiniflow-ragflow.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/infiniflow-ragflow","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=infiniflow-ragflow"}},{"type":"related","direction":"out","explanation":null,"successor_context":null,"tool":{"slug":"shubhamsaboo-awesome-llm-apps","name":"awesome-llm-apps","tagline":"Over 100 runnable AI Agent and RAG apps to clone, tweak, and deploy.","github_url":"https://github.com/Shubhamsaboo/awesome-llm-apps","owner":"Shubhamsaboo","repo":"awesome-llm-apps","owner_avatar_url":"https://avatars.githubusercontent.com/u/31396011?v=4","primary_language":"Python","stars":131230,"forks":19346,"topics":["agents","llms","python","rag"],"archived":false,"github_pushed_at":"2026-08-03T03:30:58+00:00","maintenance_label":"Very active","stars_delta_30d":14464,"url":"https://www.graphcanon.com/tools/shubhamsaboo-awesome-llm-apps","markdown_url":"https://www.graphcanon.com/tools/shubhamsaboo-awesome-llm-apps.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/shubhamsaboo-awesome-llm-apps","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=shubhamsaboo-awesome-llm-apps"}},{"type":"related","direction":"in","explanation":null,"successor_context":null,"tool":{"slug":"accumulatemore-cv","name":"CV","tagline":"超级全面的 深度学习 笔记","github_url":"https://github.com/AccumulateMore/CV","owner":"AccumulateMore","repo":"CV","owner_avatar_url":"https://avatars.githubusercontent.com/u/60348867?v=4","primary_language":"Jupyter Notebook","stars":23321,"forks":2617,"topics":["agent","agents","book","chinese","computer-vision","cv","deep-learning","jupyter-notebook","llm","llms","machine-learning","natural-language-processing","nlp","notebook","python","rag"],"archived":false,"github_pushed_at":"2026-06-30T14:36:23+00:00","maintenance_label":"Steady","stars_delta_30d":603,"url":"https://www.graphcanon.com/tools/accumulatemore-cv","markdown_url":"https://www.graphcanon.com/tools/accumulatemore-cv.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/accumulatemore-cv","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=accumulatemore-cv"}},{"type":"related","direction":"in","explanation":"Both are frameworks aimed at building context-aware, production-ready applications leveraging LLMs but with distinct focuses and not necessarily dependent on each other.","successor_context":null,"tool":{"slug":"run-llama-llama-index","name":"llama_index","tagline":"Leading document agent and OCR platform","github_url":"https://github.com/run-llama/llama_index","owner":"run-llama","repo":"llama_index","owner_avatar_url":"https://avatars.githubusercontent.com/u/130722866?v=4","primary_language":"Python","stars":51442,"forks":7885,"topics":["agents","application","data","fine-tuning","framework","llamaindex","llm","multi-agents","rag","vector-database"],"archived":false,"github_pushed_at":"2026-08-06T21:24:16+00:00","maintenance_label":"Very active","stars_delta_30d":719,"url":"https://www.graphcanon.com/tools/run-llama-llama-index","markdown_url":"https://www.graphcanon.com/tools/run-llama-llama-index.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/run-llama-llama-index","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=run-llama-llama-index"}},{"type":"alternative","direction":"in","explanation":"Haystack and LangChain4j both offer AI orchestration capabilities for integrating LLMs into real-world applications, making them alternatives tailored to different needs.","successor_context":null,"tool":{"slug":"langchain4j-langchain4j","name":"langchain4j","tagline":"Java library for building LLM-powered applications on the JVM","github_url":"https://github.com/langchain4j/langchain4j","owner":"langchain4j","repo":"langchain4j","owner_avatar_url":"https://avatars.githubusercontent.com/u/132277850?v=4","primary_language":"Java","stars":12813,"forks":2435,"topics":["anthropic","chatgpt","chroma","embeddings","gemini","gpt","huggingface","java","langchain","llama","llm","llms","milvus","ollama","onnx","openai","openai-api","pgvector","pinecone","vector-database"],"archived":false,"github_pushed_at":"2026-08-06T10:50:58+00:00","maintenance_label":"Very active","stars_delta_30d":265,"url":"https://www.graphcanon.com/tools/langchain4j-langchain4j","markdown_url":"https://www.graphcanon.com/tools/langchain4j-langchain4j.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/langchain4j-langchain4j","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=langchain4j-langchain4j"}},{"type":"integrates_with","direction":"in","explanation":"Haystack is an AI orchestration framework which can integrate various LLMs to build more complex applications and services, including deploying models on platforms like OpenLLM.","successor_context":null,"tool":{"slug":"bentoml-openllm","name":"OpenLLM","tagline":"Run any open-source LLMs as OpenAI compatible API endpoint in the cloud.","github_url":"https://github.com/bentoml/OpenLLM","owner":"bentoml","repo":"OpenLLM","owner_avatar_url":"https://avatars.githubusercontent.com/u/49176046?v=4","primary_language":"Python","stars":12454,"forks":828,"topics":["bentoml","fine-tuning","llama","llama2","llama3-1","llama3-2","llama3-2-vision","llm","llm-inference","llm-ops","llm-serving","llmops","mistral","mlops","model-inference","open-source-llm","openllm","vicuna"],"archived":false,"github_pushed_at":"2026-08-03T16:59:03+00:00","maintenance_label":"Very active","stars_delta_30d":66,"url":"https://www.graphcanon.com/tools/bentoml-openllm","markdown_url":"https://www.graphcanon.com/tools/bentoml-openllm.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/bentoml-openllm","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=bentoml-openllm"}},{"type":"related","direction":"in","explanation":"Both HRM and Haystack are related to AI development with a focus on large language models and deep learning technologies. They can be used in similar domains for tasks involving reasoning and inference.","successor_context":null,"tool":{"slug":"sapientinc-hrm","name":"HRM","tagline":"Hierarchical Reasoning Model Official Release","github_url":"https://github.com/sapientinc/HRM","owner":"sapientinc","repo":"HRM","owner_avatar_url":"https://avatars.githubusercontent.com/u/188930505?v=4","primary_language":"Python","stars":12613,"forks":1825,"topics":["brain-inspired-ai","deep-learning","large-language-models","reasoning"],"archived":false,"github_pushed_at":"2026-03-31T23:08:31+00:00","maintenance_label":"Slowing","stars_delta_30d":17,"url":"https://www.graphcanon.com/tools/sapientinc-hrm","markdown_url":"https://www.graphcanon.com/tools/sapientinc-hrm.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/sapientinc-hrm","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=sapientinc-hrm"}},{"type":"related","direction":"in","explanation":"'rig' focuses on building modular and scalable LLM applications in Rust, while 'haystack' provides an AI orchestration framework for production-ready LLM apps. Both tools share a focus area in LLM applications but do not integrate directly or provide clear alternative/succession connections.","successor_context":null,"tool":{"slug":"0xplaygrounds-rig","name":"rig","tagline":"Build modular and scalable LLM Applications in Rust","github_url":"https://github.com/0xPlaygrounds/rig","owner":"0xPlaygrounds","repo":"rig","owner_avatar_url":"https://avatars.githubusercontent.com/u/93353392?v=4","primary_language":"Rust","stars":8328,"forks":937,"topics":["agent","ai","artificial-intelligence","automation","generative-ai","large-language-model","llm","llmops","rust","scalable-ai"],"archived":false,"github_pushed_at":"2026-08-20T05:41:04+00:00","maintenance_label":"Very active","stars_delta_30d":333,"url":"https://www.graphcanon.com/tools/0xplaygrounds-rig","markdown_url":"https://www.graphcanon.com/tools/0xplaygrounds-rig.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/0xplaygrounds-rig","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=0xplaygrounds-rig"}},{"type":"integrates_with","direction":"in","explanation":"Haystack provides an orchestration framework, which could integrate with OpenChat's models to build production-ready LLM applications.","successor_context":null,"tool":{"slug":"imoneoi-openchat","name":"openchat","tagline":"Advancing Open-source Language Models with Imperfect Data","github_url":"https://github.com/imoneoi/openchat","owner":"imoneoi","repo":"openchat","owner_avatar_url":"https://avatars.githubusercontent.com/u/26354659?v=4","primary_language":"Python","stars":5487,"forks":432,"topics":["large-language-models","open-source","transformers"],"archived":false,"github_pushed_at":"2024-09-13T07:46:22+00:00","maintenance_label":"Dormant","stars_delta_30d":2,"url":"https://www.graphcanon.com/tools/imoneoi-openchat","markdown_url":"https://www.graphcanon.com/tools/imoneoi-openchat.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/imoneoi-openchat","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=imoneoi-openchat"}},{"type":"integrates_with","direction":"in","explanation":"Flash Linear Attention can be employed in Haystack to optimize performance of sequence models used within the orchestration framework for LLM applications.","successor_context":null,"tool":{"slug":"fla-org-flash-linear-attention","name":"flash-linear-attention","tagline":"🚀 Efficient implementations for emerging model architectures","github_url":"https://github.com/fla-org/flash-linear-attention","owner":"fla-org","repo":"flash-linear-attention","owner_avatar_url":"https://avatars.githubusercontent.com/u/40835596?v=4","primary_language":"Python","stars":5568,"forks":661,"topics":["large-language-models","machine-learning-systems","natural-language-processing","sequence-modeling"],"archived":false,"github_pushed_at":"2026-08-17T10:13:08+00:00","maintenance_label":"Very active","stars_delta_30d":208,"url":"https://www.graphcanon.com/tools/fla-org-flash-linear-attention","markdown_url":"https://www.graphcanon.com/tools/fla-org-flash-linear-attention.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/fla-org-flash-linear-attention","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=fla-org-flash-linear-attention"}},{"type":"integrates_with","direction":"in","explanation":"FlashRAG can integrate with Haystack to build more comprehensive and robust RAG applications, leveraging Haystack's orchestration capabilities.","successor_context":null,"tool":{"slug":"ruc-nlpir-flashrag","name":"FlashRAG","tagline":"A Python toolkit for efficient RAG research","github_url":"https://github.com/RUC-NLPIR/FlashRAG","owner":"RUC-NLPIR","repo":"FlashRAG","owner_avatar_url":"https://avatars.githubusercontent.com/u/139615285?v=4","primary_language":"Python","stars":3542,"forks":311,"topics":["benchmark","datasets","large-language-models","retrieval-augmented-generation"],"archived":false,"github_pushed_at":"2026-08-09T05:52:43+00:00","maintenance_label":"Active","stars_delta_30d":20,"url":"https://www.graphcanon.com/tools/ruc-nlpir-flashrag","markdown_url":"https://www.graphcanon.com/tools/ruc-nlpir-flashrag.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/ruc-nlpir-flashrag","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=ruc-nlpir-flashrag"}},{"type":"integrates_with","direction":"in","explanation":"MiniMax-M1 could work in tandem with Haystack, which offers an orchestration framework that can leverage large language models for production-ready applications.","successor_context":null,"tool":{"slug":"minimax-ai-minimax-m1","name":"MiniMax-M1","tagline":"Open-weight large-scale hybrid-attention reasoning model","github_url":"https://github.com/MiniMax-AI/MiniMax-M1","owner":"MiniMax-AI","repo":"MiniMax-M1","owner_avatar_url":"https://avatars.githubusercontent.com/u/194880281?v=4","primary_language":"Python","stars":3172,"forks":283,"topics":["large-language-models","llm","minimax-m1","reasoning-models"],"archived":false,"github_pushed_at":"2025-07-07T11:57:22+00:00","maintenance_label":"Dormant","stars_delta_30d":12,"url":"https://www.graphcanon.com/tools/minimax-ai-minimax-m1","markdown_url":"https://www.graphcanon.com/tools/minimax-ai-minimax-m1.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/minimax-ai-minimax-m1","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=minimax-ai-minimax-m1"}},{"type":"integrates_with","direction":"in","explanation":"Haystack and Infinispan can integrate well where Haystack is used to build context-engineered LLM applications, and Infinispan serves as a robust storage solution for data managed by these applications.","successor_context":null,"tool":{"slug":"infinispan-infinispan","name":"infinispan","tagline":"Highly scalable NoSQL cloud data store and in-memory cache platform","github_url":"https://github.com/infinispan/infinispan","owner":"infinispan","repo":"infinispan","owner_avatar_url":"https://avatars.githubusercontent.com/u/458093?v=4","primary_language":"Java","stars":1345,"forks":652,"topics":["datagrid","infinispan","infinispan-server","inmemory-cache","key-value-store","nosql","persistent-storage","search-engine","semantic-search","vector-database"],"archived":false,"github_pushed_at":"2026-08-21T04:10:51+00:00","maintenance_label":"Very active","stars_delta_30d":6,"url":"https://www.graphcanon.com/tools/infinispan-infinispan","markdown_url":"https://www.graphcanon.com/tools/infinispan-infinispan.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/infinispan-infinispan","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=infinispan-infinispan"}},{"type":"related","direction":"in","explanation":"neurocult/agency and haystack both deal with integrating AI into applications, but while agency is focused on the Go programming environment, Haystack addresses Python-based AI orchestration.","successor_context":null,"tool":{"slug":"neurocult-agency","name":"agency","tagline":"Library for exploring Large Language Models and generative AI in Go","github_url":"https://github.com/neurocult/agency","owner":"neurocult","repo":"agency","owner_avatar_url":"https://avatars.githubusercontent.com/u/112250396?v=4","primary_language":"Go","stars":514,"forks":36,"topics":["agents","ai","artificial-general-intelligence","artificial-intelligence","artificial-neural-networks","autonomous-agents","chatgpt","generative-ai","go","golang","gpt","language-models","llm","llmops","machine-learning","neural-network","nlp","openai","rag","vector-database"],"archived":false,"github_pushed_at":"2025-01-08T06:11:11+00:00","maintenance_label":"Dormant","stars_delta_30d":2,"url":"https://www.graphcanon.com/tools/neurocult-agency","markdown_url":"https://www.graphcanon.com/tools/neurocult-agency.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/neurocult-agency","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=neurocult-agency"}},{"type":"integrates_with","direction":"in","explanation":"Neum AI can integrate with Haystack to leverage its context-engineered orchestration capabilities in integrating large language model applications.","successor_context":null,"tool":{"slug":"neumtry-neumai","name":"NeumAI","tagline":"Framework to manage creation and synchronization of vector embeddings at large scale","github_url":"https://github.com/NeumTry/NeumAI","owner":"NeumTry","repo":"NeumAI","owner_avatar_url":"https://avatars.githubusercontent.com/u/129831068?v=4","primary_language":"Python","stars":867,"forks":50,"topics":["ai","chatgpt","data","data-engineering","database","embeddings","etl","llm","llmops","mlops","ops","pipeline","python","rag","retrieval","vector-database","vectors"],"archived":false,"github_pushed_at":"2024-01-15T23:00:58+00:00","maintenance_label":"Dormant","stars_delta_30d":3,"url":"https://www.graphcanon.com/tools/neumtry-neumai","markdown_url":"https://www.graphcanon.com/tools/neumtry-neumai.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/neumtry-neumai","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=neumtry-neumai"}},{"type":"related","direction":"in","explanation":"Haystack focuses on context-engineered production-ready LLM applications which includes RAG, whereas PageIndex is specifically designed for a vectorless reasoning-based approach to RAG.","successor_context":null,"tool":{"slug":"vectifyai-pageindex","name":"PageIndex","tagline":"Document Index for Vectorless, Reasoning-based RAG","github_url":"https://github.com/VectifyAI/PageIndex","owner":"VectifyAI","repo":"PageIndex","owner_avatar_url":"https://avatars.githubusercontent.com/u/133959746?v=4","primary_language":"Python","stars":35204,"forks":3097,"topics":["agentic-ai","agents","ai","ai-agents","context-engineering","information-retrieval","llm","rag","reasoning","retrieval","retrieval-augmented-generation","vector-database"],"archived":false,"github_pushed_at":"2026-08-14T23:11:17+00:00","maintenance_label":"Very active","stars_delta_30d":1134,"url":"https://www.graphcanon.com/tools/vectifyai-pageindex","markdown_url":"https://www.graphcanon.com/tools/vectifyai-pageindex.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/vectifyai-pageindex","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=vectifyai-pageindex"}},{"type":"integrates_with","direction":"in","explanation":"Haystack is an orchestration framework for building LLM applications that aims to be flexible and production-ready. Nacos can be integrated with Haystack as a dynamic service discovery and configuration management platform enabling efficient management across microservices.","successor_context":null,"tool":{"slug":"alibaba-nacos","name":"nacos","tagline":"Dynamic service discovery, configuration and management platform","github_url":"https://github.com/alibaba/nacos","owner":"alibaba","repo":"nacos","owner_avatar_url":"https://avatars.githubusercontent.com/u/1961952?v=4","primary_language":"Java","stars":33281,"forks":13280,"topics":["a2a-registry","agent","ai-registry","configuration-management","distributed-configuration","dubbo","istio","kubernetes","mcp","mcp-management","mcp-registry","microservices","nacos","prompt","skills","spring-cloud"],"archived":false,"github_pushed_at":"2026-08-18T15:41:18+00:00","maintenance_label":"Very active","stars_delta_30d":105,"url":"https://www.graphcanon.com/tools/alibaba-nacos","markdown_url":"https://www.graphcanon.com/tools/alibaba-nacos.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/alibaba-nacos","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=alibaba-nacos"}},{"type":"integrates_with","direction":"in","explanation":"BentoML, which serves as a unified framework for model serving in AI applications, integrates with Haystack to enable the deployment of Haystack's modular pipelines and agent workflows, thus facilitating the scalable execution of tasks such as retrieval, routing, memory management, and generation within production-ready LLM applications.","successor_context":null,"tool":{"slug":"bentoml-bentoml","name":"BentoML","tagline":"The easiest way to serve AI apps and models","github_url":"https://github.com/bentoml/BentoML","owner":"bentoml","repo":"BentoML","owner_avatar_url":"https://avatars.githubusercontent.com/u/49176046?v=4","primary_language":"Python","stars":8793,"forks":1010,"topics":["ai-inference","deep-learning","generative-ai","inference-platform","llm","llm-inference","llm-serving","llmops","machine-learning","ml-engineering","mlops","model-inference-service","model-serving","multimodal","python"],"archived":false,"github_pushed_at":"2026-08-03T17:00:21+00:00","maintenance_label":"Active","stars_delta_30d":65,"url":"https://www.graphcanon.com/tools/bentoml-bentoml","markdown_url":"https://www.graphcanon.com/tools/bentoml-bentoml.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/bentoml-bentoml","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=bentoml-bentoml"}},{"type":"integrates_with","direction":"in","explanation":"Haystack is an open-source framework for building context-engineered applications, while Vector focuses on data pipelines. Haystack could leverage the high performance of Vector's pipeline capabilities when handling streams of data for further processing and contextualization.","successor_context":null,"tool":{"slug":"vectordotdev-vector","name":"vector","tagline":"A high-performance observability data pipeline","github_url":"https://github.com/vectordotdev/vector","owner":"vectordotdev","repo":"vector","owner_avatar_url":"https://avatars.githubusercontent.com/u/16866914?v=4","primary_language":"Rust","stars":22396,"forks":2258,"topics":["agent","cloud-native","data-transformation","datadog","etl","events","forwarder","hacktoberfest","high-performance","logs","metrics","monitoring","observability","pipelines","rust-lang","stream-processing","telemetry","traces"],"archived":false,"github_pushed_at":"2026-08-18T21:55:24+00:00","maintenance_label":"Very active","stars_delta_30d":198,"url":"https://www.graphcanon.com/tools/vectordotdev-vector","markdown_url":"https://www.graphcanon.com/tools/vectordotdev-vector.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/vectordotdev-vector","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=vectordotdev-vector"}},{"type":"related","direction":"in","explanation":"Haystack is an orchestration framework for building context-engineered applications, while SeaGOAT is a specific application targeting code search. Both use AI techniques but are not direct alternatives or dependencies.","successor_context":null,"tool":{"slug":"kantord-seagoat","name":"SeaGOAT","tagline":"local-first semantic code search engine","github_url":"https://github.com/kantord/SeaGOAT","owner":"kantord","repo":"SeaGOAT","owner_avatar_url":"https://avatars.githubusercontent.com/u/3704904?v=4","primary_language":"Python","stars":1302,"forks":91,"topics":["ai","ai-project","code-search","code-search-engine","embeddings","grep","grep-like","hacktoberfest","hacktoberfest2023","llm","regular-expression","ripgrep","vector-database","vector-embeddings"],"archived":false,"github_pushed_at":"2026-07-21T03:16:49+00:00","maintenance_label":"Steady","stars_delta_30d":0,"url":"https://www.graphcanon.com/tools/kantord-seagoat","markdown_url":"https://www.graphcanon.com/tools/kantord-seagoat.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/kantord-seagoat","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=kantord-seagoat"}},{"type":"related","direction":"in","explanation":"Both Neum AI and Haystack are involved in the orchestration of data and context-engineering processes for LLM applications but cater to different aspects of the workflow.","successor_context":null,"tool":{"slug":"neumtry-neumai","name":"NeumAI","tagline":"Framework to manage creation and synchronization of vector embeddings at large scale","github_url":"https://github.com/NeumTry/NeumAI","owner":"NeumTry","repo":"NeumAI","owner_avatar_url":"https://avatars.githubusercontent.com/u/129831068?v=4","primary_language":"Python","stars":867,"forks":50,"topics":["ai","chatgpt","data","data-engineering","database","embeddings","etl","llm","llmops","mlops","ops","pipeline","python","rag","retrieval","vector-database","vectors"],"archived":false,"github_pushed_at":"2024-01-15T23:00:58+00:00","maintenance_label":"Dormant","stars_delta_30d":3,"url":"https://www.graphcanon.com/tools/neumtry-neumai","markdown_url":"https://www.graphcanon.com/tools/neumtry-neumai.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/neumtry-neumai","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=neumtry-neumai"}},{"type":"integrates_with","direction":"in","explanation":"Haystack is an open-source AI orchestration framework that can integrate with RAGFlow to create a robust context layer for LLM applications.","successor_context":null,"tool":{"slug":"infiniflow-ragflow","name":"ragflow","tagline":"Retrieval-Augmented Generation engine with agent capabilities","github_url":"https://github.com/infiniflow/ragflow","owner":"infiniflow","repo":"ragflow","owner_avatar_url":"https://avatars.githubusercontent.com/u/69962740?v=4","primary_language":"Go","stars":86541,"forks":10167,"topics":["agent-harness","agentic-ai","agentic-retrieval","agentic-search","ai","ai-agents","context-engine","context-engineering","context-management","harness-engineering","knowledge-compilation","llm-apps","rag","retrieval-augmented-generation"],"archived":false,"github_pushed_at":"2026-07-31T14:59:12+00:00","maintenance_label":"Very active","url":"https://www.graphcanon.com/tools/infiniflow-ragflow","markdown_url":"https://www.graphcanon.com/tools/infiniflow-ragflow.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/infiniflow-ragflow","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=infiniflow-ragflow"}}],"neighbours":[{"slug":"pathwaycom-llm-app","name":"llm-app","tagline":"Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data.","github_url":"https://github.com/pathwaycom/llm-app","owner":"pathwaycom","repo":"llm-app","owner_avatar_url":"https://avatars.githubusercontent.com/u/25750857?v=4","primary_language":"Jupyter Notebook","stars":59037,"forks":1466,"topics":["chatbot","hugging-face","llm","llm-local","llm-prompting","llm-security","llmops","machine-learning","open-ai","pathway","rag","real-time","retrieval-augmented-generation","vector-database","vector-index"],"archived":false,"github_pushed_at":"2026-07-05T17:59:07+00:00","maintenance_label":"Steady","url":"https://www.graphcanon.com/tools/pathwaycom-llm-app","markdown_url":"https://www.graphcanon.com/tools/pathwaycom-llm-app.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/pathwaycom-llm-app","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=pathwaycom-llm-app","shared_categories":["data-retrieval","llm-frameworks"]},{"slug":"nirdiamant-rag-techniques","name":"RAG_Techniques","tagline":"Showcases advanced techniques for Retrieval-Augmented Generation (RAG) systems with detailed notebook tutorials.","github_url":"https://github.com/NirDiamant/RAG_Techniques","owner":"NirDiamant","repo":"RAG_Techniques","owner_avatar_url":"https://avatars.githubusercontent.com/u/28316913?v=4","primary_language":"Jupyter Notebook","stars":29076,"forks":3540,"topics":["agentic-rag","ai","embeddings","generative-ai","gpt","langchain","llama-index","llm","llms","machine-learning","nlp","openai","python","rag","retrieval-augmented-generation","semantic-search","tutorials","vector-database"],"archived":false,"github_pushed_at":"2026-08-15T00:52:05+00:00","maintenance_label":"Active","url":"https://www.graphcanon.com/tools/nirdiamant-rag-techniques","markdown_url":"https://www.graphcanon.com/tools/nirdiamant-rag-techniques.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/nirdiamant-rag-techniques","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=nirdiamant-rag-techniques","shared_categories":["data-retrieval"]},{"slug":"langchain-ai-langchainjs","name":"langchainjs","tagline":"The agent engineering platform","github_url":"https://github.com/langchain-ai/langchainjs","owner":"langchain-ai","repo":"langchainjs","owner_avatar_url":"https://avatars.githubusercontent.com/u/126733545?v=4","primary_language":"TypeScript","stars":18020,"forks":3298,"topics":[],"archived":false,"github_pushed_at":"2026-08-07T15:58:42+00:00","maintenance_label":"Active","url":"https://www.graphcanon.com/tools/langchain-ai-langchainjs","markdown_url":"https://www.graphcanon.com/tools/langchain-ai-langchainjs.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/langchain-ai-langchainjs","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=langchain-ai-langchainjs","shared_categories":["ai-agents"]},{"slug":"raga-ai-hub-ragaai-catalyst","name":"RagaAI-Catalyst","tagline":"Python SDK for AI agent observability and evaluation","github_url":"https://github.com/raga-ai-hub/RagaAI-Catalyst","owner":"raga-ai-hub","repo":"RagaAI-Catalyst","owner_avatar_url":"https://avatars.githubusercontent.com/u/161833182?v=4","primary_language":"Python","stars":16148,"forks":3565,"topics":["agentic-ai","agentic-ai-development","agentneo","agents","ai-agent-monitoring","ai-application-debugging","ai-evaluation-tools","ai-performance-optimization","ai-tool-interaction-monitoring","llm-testing","llm-tracing","llmops"],"archived":false,"github_pushed_at":"2026-02-11T14:43:33+00:00","maintenance_label":"Slowing","url":"https://www.graphcanon.com/tools/raga-ai-hub-ragaai-catalyst","markdown_url":"https://www.graphcanon.com/tools/raga-ai-hub-ragaai-catalyst.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/raga-ai-hub-ragaai-catalyst","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=raga-ai-hub-ragaai-catalyst","shared_categories":["ai-agents"]},{"slug":"neuml-txtai","name":"txtai","tagline":"All-in-one AI framework for semantic search, LLM orchestration and language model workflows","github_url":"https://github.com/neuml/txtai","owner":"neuml","repo":"txtai","owner_avatar_url":"https://avatars.githubusercontent.com/u/59890304?v=4","primary_language":"Python","stars":12890,"forks":873,"topics":["agents","ai","ai-agents","embeddings","information-retrieval","language-model","large-language-models","llm","nlp","python","rag","retrieval-augmented-generation","search","search-engine","semantic-search","sentence-embeddings","transformers","txtai","vector-database","vector-search"],"archived":false,"github_pushed_at":"2026-08-12T13:42:39+00:00","maintenance_label":"Active","url":"https://www.graphcanon.com/tools/neuml-txtai","markdown_url":"https://www.graphcanon.com/tools/neuml-txtai.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/neuml-txtai","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=neuml-txtai","shared_categories":["ai-agents","data-retrieval","llm-frameworks"]},{"slug":"run-llama-rags","name":"rags","tagline":"Build ChatGPT over your data with natural language","github_url":"https://github.com/run-llama/rags","owner":"run-llama","repo":"rags","owner_avatar_url":"https://avatars.githubusercontent.com/u/130722866?v=4","primary_language":"Python","stars":6549,"forks":656,"topics":["agent","chatbot","chatgpt","gpts","llamaindex","llm","openai","rag","streamlit"],"archived":false,"github_pushed_at":"2024-04-05T05:36:59+00:00","maintenance_label":"Dormant","url":"https://www.graphcanon.com/tools/run-llama-rags","markdown_url":"https://www.graphcanon.com/tools/run-llama-rags.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/run-llama-rags","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=run-llama-rags","shared_categories":["ai-agents","data-retrieval"]},{"slug":"tensorchord-awesome-llmops","name":"Awesome-LLMOps","tagline":"An awesome & curated list of best LLMOps tools for developers","github_url":"https://github.com/tensorchord/Awesome-LLMOps","owner":"tensorchord","repo":"Awesome-LLMOps","owner_avatar_url":"https://avatars.githubusercontent.com/u/100543303?v=4","primary_language":"Shell","stars":5915,"forks":993,"topics":["ai-development-tools","awesome-list","llmops","mlops"],"archived":false,"github_pushed_at":"2026-05-21T09:12:50+00:00","maintenance_label":"Slowing","url":"https://www.graphcanon.com/tools/tensorchord-awesome-llmops","markdown_url":"https://www.graphcanon.com/tools/tensorchord-awesome-llmops.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/tensorchord-awesome-llmops","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=tensorchord-awesome-llmops","shared_categories":["data-retrieval","llm-frameworks"]},{"slug":"giovannipasq-agentic-rag-for-dummies","name":"agentic-rag-for-dummies","tagline":"A modular Agentic RAG built with LangGraph for learning Retrieval-Augmented Generation Agents","github_url":"https://github.com/GiovanniPasq/agentic-rag-for-dummies","owner":"GiovanniPasq","repo":"agentic-rag-for-dummies","owner_avatar_url":"https://avatars.githubusercontent.com/u/33225259?v=4","primary_language":"Jupyter Notebook","stars":3893,"forks":499,"topics":["agent","agentic-ai","agentic-rag","agents","ai-agents","bm25","generative-ai","gradio","langchain","langgraph","llm","ollama","qdrant","rag","rag-agents","rag-chatbot","rag-pipeline","retrieval-augmented-generation","retrieval-augmented-generation-rag"],"archived":false,"github_pushed_at":"2026-07-25T11:33:02+00:00","maintenance_label":"Active","url":"https://www.graphcanon.com/tools/giovannipasq-agentic-rag-for-dummies","markdown_url":"https://www.graphcanon.com/tools/giovannipasq-agentic-rag-for-dummies.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/giovannipasq-agentic-rag-for-dummies","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=giovannipasq-agentic-rag-for-dummies","shared_categories":["ai-agents","data-retrieval"]},{"slug":"lazyagi-lazyllm","name":"LazyLLM","tagline":"Easiest and laziest way for building multi-agent LLMs applications.","github_url":"https://github.com/LazyAGI/LazyLLM","owner":"LazyAGI","repo":"LazyLLM","owner_avatar_url":"https://avatars.githubusercontent.com/u/171651681?v=4","primary_language":"Python","stars":3866,"forks":404,"topics":["agents","ai-agent","data","deep-learning","documentation-tool","finetuning","framework","knowlege-graph","langchain","lazyllm","llamaindex","llm","llms","rag"],"archived":false,"github_pushed_at":"2026-08-07T03:03:46+00:00","maintenance_label":"Active","url":"https://www.graphcanon.com/tools/lazyagi-lazyllm","markdown_url":"https://www.graphcanon.com/tools/lazyagi-lazyllm.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/lazyagi-lazyllm","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=lazyagi-lazyllm","shared_categories":["ai-agents"]},{"slug":"av-harbor","name":"harbor","tagline":"Complete pre-wired LLM stack via one command","github_url":"https://github.com/av/harbor","owner":"av","repo":"harbor","owner_avatar_url":"https://avatars.githubusercontent.com/u/38184623?v=4","primary_language":"Python","stars":3162,"forks":220,"topics":["ai","automation","bash","cli","container","docker","docker-compose","homelab","llm","local","mcp","npm","package","pypi","safetensors","self-hosted","server","tool","tools"],"archived":false,"github_pushed_at":"2026-08-02T18:10:59+00:00","maintenance_label":"Active","url":"https://www.graphcanon.com/tools/av-harbor","markdown_url":"https://www.graphcanon.com/tools/av-harbor.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/av-harbor","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=av-harbor","shared_categories":["llm-frameworks"]},{"slug":"agent-field-agentfield","name":"agentfield","tagline":"Build, run and scale AI agents like API and microservices","github_url":"https://github.com/Agent-Field/agentfield","owner":"Agent-Field","repo":"agentfield","owner_avatar_url":"https://avatars.githubusercontent.com/u/204899035?v=4","primary_language":"Go","stars":2472,"forks":392,"topics":["agent","agent-auth","agent-authentication","agent-indentity","agent-scaling","agentic-ai","ai","ai-backend","aiagent","anthropic","cloud-native","genai","go","kubernetes","llm","multiagent","multiagent-systems","python","rag","typescript"],"archived":false,"github_pushed_at":"2026-08-01T22:54:29+00:00","maintenance_label":"Active","url":"https://www.graphcanon.com/tools/agent-field-agentfield","markdown_url":"https://www.graphcanon.com/tools/agent-field-agentfield.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/agent-field-agentfield","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=agent-field-agentfield","shared_categories":["ai-agents"]},{"slug":"antoinezambelli-forge","name":"forge","tagline":"A Python framework for self-hosted LLM tool-calling and multi-step agentic workflows","github_url":"https://github.com/antoinezambelli/forge","owner":"antoinezambelli","repo":"forge","owner_avatar_url":"https://avatars.githubusercontent.com/u/2261593?v=4","primary_language":"Python","stars":2217,"forks":173,"topics":["agentic-ai","agentic-workflow","agents","function-calling","llama-cpp","llamafile","llm","ollama","python","self-hosted","tool-calling"],"archived":false,"github_pushed_at":"2026-08-13T22:14:44+00:00","maintenance_label":"Active","url":"https://www.graphcanon.com/tools/antoinezambelli-forge","markdown_url":"https://www.graphcanon.com/tools/antoinezambelli-forge.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/antoinezambelli-forge","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=antoinezambelli-forge","shared_categories":["ai-agents","llm-frameworks"]}]}}