Discuter avec les spécifications OpenAPI de GitHub via RAG (Pinecone et OpenAI)

Name: Discuter avec les spécifications OpenAPI de GitHub via RAG (Pinecone et OpenAI)
Rating: 4.5 (10 reviews)
Author: Mihai Farcas

Avancé

Ceci est unEngineering, AIworkflow d'automatisation du domainecontenant 17 nœuds.Utilise principalement des nœuds comme HttpRequest, ManualTrigger, Agent, ChatTrigger, LmChatOpenAi, combinant la technologie d'intelligence artificielle pour une automatisation intelligente. Dialoguer avec la documentation de l'API GitHub : un bot de conversation basé sur RAG, utilisant Pinecone et OpenAI

Prérequis

•Peut nécessiter les informations d'identification d'authentification de l'API cible
•Clé API OpenAI
•Clé API Pinecone

Nœuds utilisés (17)

DocumentDefaultDataLoader

TextSplitterRecursiveCharacterTextSplitter

Catégorie

Ingénierie

Intelligence Artificielle

Aperçu du workflow

Visualisation des connexions entre les nœuds, avec support du zoom et du déplacement

Lors du clic sur 'Tester le workflow'

HTTP Request

Pinecone Vector Store

Default Data Loader

Recursive Character Text Splitter

À la réception d'un message de chat

AI Agent

OpenAI Chat Model

Window Buffer Memory

Vector Store Tool

OpenAI Chat Model1

Generate User Query Embedding

Pinecone Vector Store (Querying)

Generate Embeddings

React Flow

Exporter le workflow

Copiez la configuration JSON suivante dans n8n pour importer et utiliser ce workflow

{
  "id": "FD0bHNaehP3LzCNN",
  "meta": {
    "instanceId": "69133932b9ba8e1ef14816d0b63297bb44feb97c19f759b5d153ff6b0c59e18d"
  },
  "name": "Chat with GitHub OpenAPI Specification using RAG (Pinecone and OpenAI)",
  "tags": [],
  "nodes": [
    {
      "id": "362cb773-7540-4753-a401-e585cdf4af8a",
      "name": "Lors du clic sur 'Tester le workflow'",
      "type": "n8n-nodes-base.manualTrigger",
      "position": [
        0,
        0
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "45470036-cae6-48d0-ac66-addc8999e776",
      "name": "HTTP Request",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        300,
        0
      ],
      "parameters": {
        "url": "https://raw.githubusercontent.com/github/rest-api-description/refs/heads/main/descriptions/api.github.com/api.github.com.json",
        "options": {}
      },
      "typeVersion": 4.2
    },
    {
      "id": "a9e65897-52c9-4941-bf49-e1a659e442ef",
      "name": "Pinecone Vector Store",
      "type": "@n8n/n8n-nodes-langchain.vectorStorePinecone",
      "position": [
        520,
        0
      ],
      "parameters": {
        "mode": "insert",
        "options": {},
        "pineconeIndex": {
          "__rl": true,
          "mode": "list",
          "value": "n8n-demo",
          "cachedResultName": "n8n-demo"
        }
      },
      "credentials": {
        "pineconeApi": {
          "id": "bQTNry52ypGLqt47",
          "name": "PineconeApi account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "c2a2354b-5457-4ceb-abfc-9a58e8593b81",
      "name": "Default Data Loader",
      "type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
      "position": [
        660,
        180
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 1
    },
    {
      "id": "7338d9ea-ae8f-46eb-807f-a15dc7639fc9",
      "name": "Recursive Character Text Splitter",
      "type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
      "position": [
        740,
        360
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 1
    },
    {
      "id": "44fd7a59-f208-4d5d-a22d-e9f8ca9badf1",
      "name": "À la réception d'un message de chat",
      "type": "@n8n/n8n-nodes-langchain.chatTrigger",
      "position": [
        -20,
        760
      ],
      "webhookId": "089e38ab-4eee-4c34-aa5d-54cf4a8f53b7",
      "parameters": {
        "options": {}
      },
      "typeVersion": 1.1
    },
    {
      "id": "51d819d6-70ff-428d-aa56-1d7e06490dee",
      "name": "AI Agent",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        320,
        760
      ],
      "parameters": {
        "options": {
          "systemMessage": "You are a helpful assistant providing information about the GitHub API and how to use it based on the OpenAPI V3 specifications."
        }
      },
      "typeVersion": 1.7
    },
    {
      "id": "aed548bf-7083-44ad-a3e0-163dee7423ef",
      "name": "OpenAI Chat Model",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        220,
        980
      ],
      "parameters": {
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "tQLWnWRzD8aebYvp",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1.1
    },
    {
      "id": "dfe9f356-2225-4f4b-86c7-e56a230b4193",
      "name": "Window Buffer Memory",
      "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
      "position": [
        420,
        1020
      ],
      "parameters": {},
      "typeVersion": 1.3
    },
    {
      "id": "4cf672ee-13b8-4355-b8e0-c2e7381671bc",
      "name": "Vector Store Tool",
      "type": "@n8n/n8n-nodes-langchain.toolVectorStore",
      "position": [
        580,
        980
      ],
      "parameters": {
        "name": "GitHub_OpenAPI_Specification",
        "description": "Use this tool to get information about the GitHub   API. This database contains OpenAPI v3 specifications."
      },
      "typeVersion": 1
    },
    {
      "id": "1df7fb85-9d4a-4db5-9bed-41d28e2e4643",
      "name": "OpenAI Chat Model1",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        840,
        1160
      ],
      "parameters": {
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "tQLWnWRzD8aebYvp",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1.1
    },
    {
      "id": "7b52ef7a-5935-451e-8747-efe16ce288af",
      "name": "Sticky Note",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -40,
        -260
      ],
      "parameters": {
        "width": 640,
        "height": 200,
        "content": "## Indexing content in the vector database\nThis part of the workflow is responsible for extracting content, generating embeddings and sending them to the Pinecone vector store.\n\nIt requests the OpenAPI specifications from GitHub using a HTTP request. Then, it splits the file in chunks, generating embeddings for each chunk using OpenAI, and saving them in Pinecone vector DB."
      },
      "typeVersion": 1
    },
    {
      "id": "3508d602-56d4-4818-84eb-ca75cdeec1d0",
      "name": "Sticky Note1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -20,
        560
      ],
      "parameters": {
        "width": 580,
        "content": "## Querying and response generation \n\nThis part of the workflow is responsible for the chat interface, querying the vector store and generating relevant responses.\n\nIt uses OpenAI GPT 4o-mini to generate responses."
      },
      "typeVersion": 1
    },
    {
      "id": "5a9808ef-4edd-4ec9-ba01-2fe50b2dbf4b",
      "name": "Generate User Query Embedding",
      "type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
      "position": [
        480,
        1400
      ],
      "parameters": {
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "tQLWnWRzD8aebYvp",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "f703dc8e-9d4b-45e3-8994-789b3dfe8631",
      "name": "Pinecone Vector Store (Querying)",
      "type": "@n8n/n8n-nodes-langchain.vectorStorePinecone",
      "position": [
        440,
        1220
      ],
      "parameters": {
        "options": {},
        "pineconeIndex": {
          "__rl": true,
          "mode": "list",
          "value": "n8n-demo",
          "cachedResultName": "n8n-demo"
        }
      },
      "credentials": {
        "pineconeApi": {
          "id": "bQTNry52ypGLqt47",
          "name": "PineconeApi account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "ea64a7a5-1fa5-4938-83a9-271929733a8e",
      "name": "Generate Embeddings",
      "type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
      "position": [
        480,
        220
      ],
      "parameters": {
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "tQLWnWRzD8aebYvp",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "65cbd4e3-91f6-441a-9ef1-528c3019e238",
      "name": "Sticky Note2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -820,
        -260
      ],
      "parameters": {
        "width": 620,
        "height": 320,
        "content": "## RAG workflow in n8n\n\nThis is an example of how to use RAG techniques to create a chatbot with n8n. It is an API documentation chatbot that can answer questions about the GitHub API. It uses OpenAI for generating embeddings, the gpt-4o-mini LLM for generating responses and Pinecone as a vector database.\n\n### Before using this template\n* create OpenAI and Pinecone accounts\n* obtain API keys OpenAI and Pinecone \n* configure credentials in n8n for both\n* ensure you have a Pinecone index named \"n8n-demo\" or adjust the workflow accordingly."
      },
      "typeVersion": 1
    }
  ],
  "active": false,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "2908105f-c20c-4183-bb9d-26e3559b9911",
  "connections": {
    "45470036-cae6-48d0-ac66-addc8999e776": {
      "main": [
        [
          {
            "node": "a9e65897-52c9-4941-bf49-e1a659e442ef",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "aed548bf-7083-44ad-a3e0-163dee7423ef": {
      "ai_languageModel": [
        [
          {
            "node": "51d819d6-70ff-428d-aa56-1d7e06490dee",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "4cf672ee-13b8-4355-b8e0-c2e7381671bc": {
      "ai_tool": [
        [
          {
            "node": "51d819d6-70ff-428d-aa56-1d7e06490dee",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    },
    "1df7fb85-9d4a-4db5-9bed-41d28e2e4643": {
      "ai_languageModel": [
        [
          {
            "node": "4cf672ee-13b8-4355-b8e0-c2e7381671bc",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "c2a2354b-5457-4ceb-abfc-9a58e8593b81": {
      "ai_document": [
        [
          {
            "node": "a9e65897-52c9-4941-bf49-e1a659e442ef",
            "type": "ai_document",
            "index": 0
          }
        ]
      ]
    },
    "ea64a7a5-1fa5-4938-83a9-271929733a8e": {
      "ai_embedding": [
        [
          {
            "node": "a9e65897-52c9-4941-bf49-e1a659e442ef",
            "type": "ai_embedding",
            "index": 0
          }
        ]
      ]
    },
    "dfe9f356-2225-4f4b-86c7-e56a230b4193": {
      "ai_memory": [
        [
          {
            "node": "51d819d6-70ff-428d-aa56-1d7e06490dee",
            "type": "ai_memory",
            "index": 0
          }
        ]
      ]
    },
    "44fd7a59-f208-4d5d-a22d-e9f8ca9badf1": {
      "main": [
        [
          {
            "node": "51d819d6-70ff-428d-aa56-1d7e06490dee",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "5a9808ef-4edd-4ec9-ba01-2fe50b2dbf4b": {
      "ai_embedding": [
        [
          {
            "node": "f703dc8e-9d4b-45e3-8994-789b3dfe8631",
            "type": "ai_embedding",
            "index": 0
          }
        ]
      ]
    },
    "f703dc8e-9d4b-45e3-8994-789b3dfe8631": {
      "ai_vectorStore": [
        [
          {
            "node": "4cf672ee-13b8-4355-b8e0-c2e7381671bc",
            "type": "ai_vectorStore",
            "index": 0
          }
        ]
      ]
    },
    "7338d9ea-ae8f-46eb-807f-a15dc7639fc9": {
      "ai_textSplitter": [
        [
          {
            "node": "c2a2354b-5457-4ceb-abfc-9a58e8593b81",
            "type": "ai_textSplitter",
            "index": 0
          }
        ]
      ]
    },
    "362cb773-7540-4753-a401-e585cdf4af8a": {
      "main": [
        [
          {
            "node": "45470036-cae6-48d0-ac66-addc8999e776",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}

Foire aux questions

Comment utiliser ce workflow ?

Copiez le code de configuration JSON ci-dessus, créez un nouveau workflow dans votre instance n8n et sélectionnez "Importer depuis le JSON", collez la configuration et modifiez les paramètres d'authentification selon vos besoins.

Dans quelles scénarios ce workflow est-il adapté ?

Avancé - Ingénierie, Intelligence Artificielle

Est-ce payant ?

Ce workflow est entièrement gratuit et peut être utilisé directement. Veuillez noter que les services tiers utilisés dans le workflow (comme l'API OpenAI) peuvent nécessiter un paiement de votre part.

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Informations sur le workflow

Niveau de difficulté

Avancé

Nombre de nœuds17

Catégorie2

Types de nœuds12

Description de la difficulté

Adapté aux utilisateurs avancés, avec des workflows complexes contenant 16+ nœuds

Auteur

Mihai Farcas

@mihailtd

Full-stack developer with 5+ years streamlining healthcare processes. Proficient in NodeJS, VueJS, MongoDB, PostgreSQL, Kubernetes, and n8n. Ready to optimize your workflows – book a consult via my link.

Liens externes

Voir sur n8n.io →

Partager ce workflow

Discuter avec les spécifications OpenAPI de GitHub via RAG (Pinecone et OpenAI)

Nœuds utilisés (17)

Catégorie

Comment utiliser ce workflow ?

Dans quelles scénarios ce workflow est-il adapté ?

Est-ce payant ?

Workflows recommandés

Catégories