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GitHub Document Loader Node#

Verwenden Sie den GitHub Document Loader Node, um Daten aus einem GitHub-Repository für Vektorspeicher oder Zusammenfassungen zu laden.

Auf dieser Seite finden Sie die Node-Parameter für den GitHub Document Loader Node sowie Links zu weiteren Ressourcen.

Anmeldeinformationen

Informationen zur Authentifizierung für diesen Node finden Sie hier. Dieser Node unterstützt keine OAuth-Authentifizierung.

Parameter resolution in sub-nodes

Sub-nodes behave differently to other nodes when processing multiple items using an expression.

Most nodes, including root nodes, take any number of items as input, process these items, and output the results. You can use expressions to refer to input items, and the node resolves the expression for each item in turn. For example, given an input of five name values, the expression {{ $json.name }} resolves to each name in turn.

In sub-nodes, the expression always resolves to the first item. For example, given an input of five name values, the expression {{ $json.name }} always resolves to the first name.

Node-Parameter#

  • Repository-Link: Geben Sie die URL Ihres GitHub-Repositorys ein.
  • Branch: Geben Sie den zu verwendenden Branch-Namen ein.

Node-Optionen#

  • Rekursiv: Wählen Sie aus, ob Unterordner und Dateien einbezogen werden sollen (eingeschaltet) oder nicht (ausgeschaltet).
  • Pfade ignorieren: Geben Sie zu ignorierende Verzeichnisse ein.

Zugehörige Ressourcen#

Refer to LangChain's documentation on document loaders for more information about the service.

View Localmind Automate's Advanced AI documentation.

AI glossary#

  • completion: Completions are the responses generated by a model like GPT.
  • hallucinations: Hallucination in AI is when an LLM (large language model) mistakenly perceives patterns or objects that don't exist.
  • vector database: A vector database stores mathematical representations of information. Use with embeddings and retrievers to create a database that your AI can access when answering questions.
  • vector store: A vector store, or vector database, stores mathematical representations of information. Use with embeddings and retrievers to create a database that your AI can access when answering questions.