{"id":6,"date":"2026-08-09T20:53:14","date_gmt":"2026-08-09T20:53:14","guid":{"rendered":"http:\/\/corpolearn.wp\/gcloud\/\/vertex-ai-first-llm-pipeline\/"},"modified":"2026-08-09T20:53:14","modified_gmt":"2026-08-09T20:53:14","slug":"vertex-ai-first-llm-pipeline","status":"publish","type":"post","link":"https:\/\/corpolearn.com\/gcloud\/vertex-ai-first-llm-pipeline\/","title":{"rendered":"Getting Started with Vertex AI: Building &amp; Deploying Your First LLM Pipeline"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">Google Cloud&#8217;s <strong>Vertex AI<\/strong> provides an end-to-end platform for training, fine-tuning, and deploying machine learning and Generative AI models. With the integration of Gemini 1.5 Pro and Flash APIs, engineers can build production RAG (Retrieval-Augmented Generation) applications in record time.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Building a RAG Pipeline with Vertex AI Vector Search<\/h2>\n\n\n<p class=\"wp-block-paragraph\">1. Store source PDF\/HTML documents in Cloud Storage.<br>2. Generate 768-dimensional text embeddings using the <code>text-embedding-004<\/code> model.<br>3. Deploy the embeddings to a <strong>Vertex AI Vector Search<\/strong> index endpoint.<br>4. Query Gemini 1.5 Pro using the retrieved context for accurate, grounded responses.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Google Cloud&#8217;s Vertex AI provides an end-to-end platform for training, fine-tuning, and deploying machine learning and Generative AI models. With the integration of Gemini 1.5 Pro and Flash APIs, engineers can build production RAG (Retrieval-Augmented Generation) applications in record time. Building a RAG Pipeline with Vertex AI Vector Search 1. Store source PDF\/HTML documents in [&hellip;]<\/p>\n","protected":false},"author":0,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_cl_workflow_state":"","_cl_content_brief":"","_cl_target_topic":"","footnotes":""},"categories":[22],"tags":[],"class_list":["post-6","post","type-post","status-publish","format-standard","hentry","category-gcp-ai-ml"],"_links":{"self":[{"href":"https:\/\/corpolearn.com\/gcloud\/wp-json\/wp\/v2\/posts\/6","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/corpolearn.com\/gcloud\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/corpolearn.com\/gcloud\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/corpolearn.com\/gcloud\/wp-json\/wp\/v2\/comments?post=6"}],"version-history":[{"count":0,"href":"https:\/\/corpolearn.com\/gcloud\/wp-json\/wp\/v2\/posts\/6\/revisions"}],"wp:attachment":[{"href":"https:\/\/corpolearn.com\/gcloud\/wp-json\/wp\/v2\/media?parent=6"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/corpolearn.com\/gcloud\/wp-json\/wp\/v2\/categories?post=6"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/corpolearn.com\/gcloud\/wp-json\/wp\/v2\/tags?post=6"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}