For Vietnamese document embeddings, the most direct options are Hugging Face, which hosts embedding models and offers an inference API and sentence-transformers training 2, and Sbert/SentenceTransformers, the Python library for computing text embeddings and fine-tuning them 3. Replicate can run open-source embedding models through a cloud API, including one that generates document embeddings for semantic search 1. OpenAI's embeddings endpoint turns text into vectors, though its multilingua
- 1
Hugging Face Inference Providershuggingface.coverified and signed
Hosts a large catalog of models, including embedding models, and provides an inference API plus sentence-transformers fine-tuning to run Vietnamese document embeddings 2.
official:MCP server · @huggingface/mcp-clientSDK · huggingface-hubCLI · text-embeddings-inferencerepository · pwc-cliskill · hf-cli+23 community tools built for it
for agents: document_question_answering · train-sentence-transformers · huggingface-inference-api
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Sentence Transformerssbert.netverified and signed
A Python library for computing embeddings from text and training or fine-tuning embedding models, which can be used for Vietnamese document embeddings 3.
official:SDK · sentence-transformers+24 community tools built for it
for agents: embedding · XLNet · Transformer
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Replicatereplicate.comverified and signed
Runs open-source embedding models through a cloud API, including an all-mpnet-base-v2 model that produces document embeddings for semantic search 1.
+14 community tools built for it
for agents: replicate/all-mpnet-base-v2 · daanelson/imagebind · center-for-curriculum-redesign/bge_1-5_query_embeddings
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OpenAI Embeddings APIopenai.comverified and signed
Creates an embedding vector from input text through the createEmbedding endpoint, usable for semantic search over Vietnamese documents 6.
official:MCP server · mcp-extensionsAPI · OpenAI APISDK · openailibrary · OpenAICLI · openai-whisper+177 community tools built for it
for agents: createEmbedding · create_embedding · search_embeddings
Sources
- 1Replicate - Run AI with an APIreplicate.com · read 2026-10-29
- 2Hugging Face – The AI community building the future.huggingface.co · read 2026-10-29
- 3SentenceTransformers Documentation — Sentence Transformers documentationsbert.net · read 2026-10-29
- 6Openaiopenai.com ·
For agents: the 10 actions behind this answer
replicate/all-mpnet-base-v2 · replicate/all-mpnet-base-v2 verified and signed
This is a language model that can be used to obtain document embeddings suitable for downstream tasks like semantic search and clustering.
document_question_answering · Hugging Face (Activepieces) verified and signed
Document Question Answering — Answer questions from document images using Hugging Face models
embedding · sentence-transformers verified and signed
graph_sage_predict · neo4j-gds found in code, not yet checked
Generates node embeddings using a previously trained GraphSAGE model from the model catalog (see graph_sage_train).
integrate-context-matic · integrate-context-matic verified and signed
Discovers and integrates third-party APIs using the context-matic MCP server. Uses `fetch_api` to find available API SDKs, `ask` for integration guidance, `model_search` and `endpoint_search` for SDK details. Use when the user asks to integrate a third-party API, add an API client, implement feature
createEmbedding · OpenAI API verified and signed
Creates an embedding vector representing the input text.
sentence-transformers · fastembed verified and signed
generate_image · MCP-Brave-Search found in code, not yet checked
Generate images using EverArt Models and returns a clickable link to view the generated image.
databricks-model-serving · databricks-model-serving verified and signed
Databricks Model Serving endpoint lifecycle and ops. Use when asked to: CRUD serving endpoints (CLI or MLflow Deployments client); configure traffic routing for A/B / canary deploys and zero-downtime version swaps; retrieve OpenAPI schemas; inspect logs, metrics, or permissions; manage legacy AI Gat
create_embedding · LocalAI (Activepieces) verified and signed
Create Embedding — Turn text into a vector for semantic search or clustering.
Labels are the instruments' verdict and are never changed by ranking. Agents and robots get this same answer as JSON at /api/v1/find?q=…&answer=1 and through the MCP server.