With %pip install -q -U google-generativeai
%pip install python-dotenv ipywidgets
%pip install llama-index datasets llama-index-callbacks-arize-phoenix llama-index-vector-stores-chroma llama-index-llms-huggingface llama-index-llms-huggingface-api -U -q
%pip install llama-index-embeddings-huggingface
%pip install llama-index-embeddings-huggingface-api -U -q" i got the same: ModuleNotFoundError Traceback (most recent call last)
Cell In[6], line 1
----> 1 from llama_index.embeddings.huggingface_api import HuggingFaceInferenceAPIEmbedding
2 from llama_index.core.node_parser import SentenceSplitter
3 from llama_index.core.ingestion import IngestionPipeline

ModuleNotFoundError: No module named 'llama_index.embeddings.huggingface_api'

I found the solution on https://docs.llamaindex.ai/en/stable/examples/embeddings/huggingface/ in the chapter "
Base HuggingFace Embeddings" with this example working:
from llama_index.embeddings.huggingface import HuggingFaceEmbedding

loads BAAI/bge-small-en-v1.5

embed_model = HuggingFaceEmbedding(model_name="BAAI/bge-small-en-v1.5")
test_emeds = embed_model.get_text_embedding("Hello World!"). So finally my cell was running: from llama_index.embeddings.huggingface import HuggingFaceEmbedding
from llama_index.core.node_parser import SentenceSplitter
from llama_index.core.ingestion import IngestionPipeline

embed_model = HuggingFaceEmbedding(model_name="BAAI/bge-small-en-v1.5")

create the pipeline with transformations

pipeline = IngestionPipeline(
transformations=[
SentenceSplitter(),
embed_model ,
]
)

run the pipeline sync or async

nodes = await pipeline.arun(documents=documents[:10])
nodes

Result: [TextNode(id_='453ec6ba-6380-4ad6-87fb-23225f79318d', embedding=[-0.041332945227622986, 0.009067350067198277, 0.045314010232686996, -0.0031704942230135202, 0.004984738305211067, -0.03442731127142906, -0.01120108924806118, 0.01703874208033085, -0.05228905752301216, -0.06552951782941818, 0.0006800332339480519, -0.032225772738456726, -0.0361214205622673, 0.018456168472766876, -0.017449432983994484, -0.004060361068695784, 0.004597707651555538, 0.0856025218963623, 0.004833478946238756, 0.009958012029528618, 0.015292982570827007, -0.08044665306806564, 0.07174284011125565, -0.026560306549072266, -0.03583443537354469, 0.03176948055624962, 0.023099087178707123, -0.004005969036370516, 0.006027331110090017, -0.13000787794589996, -0.047905828803777695, 0.025874163955450058, -0.012980309315025806, -0.004410617519170046, 0.050506990402936935, 0.01496216282248497, 0.0032134917564690113, 0.05617731809616089, -0.0005276186857372522, 0.03524484485387802, 0.02124783769249916, 0.01660194993019104, 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'last_accessed_date'], excluded_llm_metadata_keys=['file_name', 'file_type', 'file_size', 'creation_date', 'last_modified_date', 'last_accessed_date'], relationships={<NodeRelationship.SOURCE: '1'>: RelatedNodeInfo(node_id='60db66b2-0d47-45a9-a2ef-7286c59d9e7c', node_type=<ObjectType.DOCUMENT: '4'>, metadata={'file_path': '/home/martin/ExternePlatten/LinuxData/LanguageModels/Trainings/HuggingFace/LLamaIndex/data/persona_0.txt', 'file_name': 'persona_0.txt', 'file_type': 'text/plain', 'file_size': 132, 'creation_date': '2025-03-12', 'last_modified_date': '2025-03-12'}, hash='58941961f90b934d82fa9d9b70fda325c381f42a776edd7a7dd312150a5e6268')}, metadata_template='{key}: {value}', metadata_separator='\n', text='A local art historian and museum professional interested in 19th-century American art and the local cultural heritage of Cincinnati.', mimetype='text/plain', start_char_idx=0, end_char_idx=132, metadata_seperator='\n', text_template='{metadata_str}\n\n{content}'),
TextNode(id_='71a0b2eb-1ecc-4157-b160-7a80d220914e', embedding=[0.018294867128133774, 0.08462988585233688, 0.037305593490600586, -0.04070982336997986, -0.017835011705756187, -0.06227517127990723, 0.07314393669366837, 0.02052365429699421, -0.015876999124884605, -0.035049330443143845, -0.01971106231212616, -0.09965484589338303, 0.02657662145793438, 0.013252542354166508, 0.013017113320529461, 0.03176000341773033, -0.0008040915708988905, 0.015870921313762665, 0.01783314347267151, 0.007858190685510635, 0.037690646946430206, -0.06152050942182541, -0.008311556652188301, -0.014004741795361042, -0.029202381148934364, 0.01456891093403101, 0.03514190763235092, -0.028521763160824776, -0.015729324892163277, -0.09152117371559143, -0.035128913819789886, 0.007489635143429041, -0.0031195003539323807, 0.014446535147726536, -0.01906348578631878, 0.00729037681594491, 0.028389587998390198, 0.02948128618299961, -0.0007086701807565987, 0.10824833065271378, 0.01851908303797245, -0.05295424163341522, 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