Générer des réponses à l'aide du fichier RAG
Restez organisé à l'aide des collections
Enregistrez et classez les contenus selon vos préférences.
Cet exemple montre comment générer le contenu à l'aide d'un fichier RAG.
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Pour obtenir une documentation détaillée incluant cet exemple de code, consultez les articles suivants :
Exemple de code
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[[["Facile à comprendre","easyToUnderstand","thumb-up"],["J'ai pu résoudre mon problème","solvedMyProblem","thumb-up"],["Autre","otherUp","thumb-up"]],[["Difficile à comprendre","hardToUnderstand","thumb-down"],["Informations ou exemple de code incorrects","incorrectInformationOrSampleCode","thumb-down"],["Il n'y a pas l'information/les exemples dont j'ai besoin","missingTheInformationSamplesINeed","thumb-down"],["Problème de traduction","translationIssue","thumb-down"],["Autre","otherDown","thumb-down"]],[],[],[],null,["# Generate responses using the RAG file\n\nThis sample demonstrates how to generate the content using a RAG file.\n\nExplore further\n---------------\n\n\nFor detailed documentation that includes this code sample, see the following:\n\n- [RAG Engine API](/vertex-ai/generative-ai/docs/model-reference/rag-api-v1)\n- [Use a Weaviate database with Vertex AI RAG Engine](/vertex-ai/generative-ai/docs/rag-engine/use-weaviate-db)\n- [Use Vertex AI Feature Store in Vertex AI RAG Engine](/vertex-ai/generative-ai/docs/rag-engine/use-feature-store-with-rag)\n- [Use Vertex AI Search as a retrieval backend using Vertex AI RAG Engine](/vertex-ai/generative-ai/docs/rag-engine/use-vertexai-search)\n- [Use Vertex AI Vector Search with Vertex AI RAG Engine](/vertex-ai/generative-ai/docs/rag-engine/use-vertexai-vector-search)\n\nCode sample\n-----------\n\n### Python\n\n\nBefore trying this sample, follow the Python setup instructions in the\n[Vertex AI quickstart using\nclient libraries](/vertex-ai/docs/start/client-libraries).\n\n\nFor more information, see the\n[Vertex AI Python API\nreference documentation](/python/docs/reference/aiplatform/latest).\n\n\nTo authenticate to Vertex AI, set up Application Default Credentials.\nFor more information, see\n\n[Set up authentication for a local development environment](/docs/authentication/set-up-adc-local-dev-environment).\n\n\n from vertexai import rag\n from vertexai.generative_models import https://cloud.google.com/python/docs/reference/vertexai/latest/vertexai.preview.generative_models.GenerativeModel.html, https://cloud.google.com/python/docs/reference/vertexai/latest/vertexai.preview.generative_models.Tool.html\n import https://cloud.google.com/python/docs/reference/vertexai/latest/\n\n # TODO(developer): Update and un-comment below lines\n # PROJECT_ID = \"your-project-id\"\n # corpus_name = \"projects/{PROJECT_ID}/locations/us-central1/ragCorpora/{rag_corpus_id}\"\n\n # Initialize Vertex AI API once per session\n https://cloud.google.com/python/docs/reference/vertexai/latest/.init(project=PROJECT_ID, location=\"us-central1\")\n\n rag_retrieval_tool = https://cloud.google.com/python/docs/reference/vertexai/latest/vertexai.preview.generative_models.Tool.html.from_retrieval(\n retrieval=rag.Retrieval(\n source=rag.VertexRagStore(\n rag_resources=[\n rag.RagResource(\n rag_corpus=corpus_name,\n # Optional: supply IDs from `rag.list_files()`.\n # rag_file_ids=[\"rag-file-1\", \"rag-file-2\", ...],\n )\n ],\n rag_retrieval_config=rag.RagRetrievalConfig(\n top_k=10,\n filter=rag.utils.resources.Filter(vector_distance_threshold=0.5),\n ),\n ),\n )\n )\n\n rag_model = GenerativeModel(\n model_name=\"gemini-2.0-flash-001\", tools=[rag_retrieval_tool]\n )\n response = rag_model.https://cloud.google.com/python/docs/reference/vertexai/latest/vertexai.preview.generative_models.GenerativeModel.html#vertexai_preview_generative_models_GenerativeModel_generate_content(\"Why is the sky blue?\")\n print(response.text)\n # Example response:\n # The sky appears blue due to a phenomenon called Rayleigh scattering.\n # Sunlight, which contains all colors of the rainbow, is scattered\n # by the tiny particles in the Earth's atmosphere....\n # ...\n\nWhat's next\n-----------\n\n\nTo search and filter code samples for other Google Cloud products, see the\n[Google Cloud sample browser](/docs/samples?product=generativeaionvertexai)."]]