h2ogpte 1.3.8

Client library for Enterprise h2oGPTe

H2O H2OGPTE Python Client

Install

pip install h2ogpte

Usage

from h2ogpte import H2OGPTE

client = H2OGPTE(
    address='https://h2ogpte.genai.h2o.ai',
    api_key='sk-XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX',
)

# Create a new collection
collection_id = client.create_collection(
    name='Contracts',
    description='Paper clip supply contracts',
)

# Create documents
# Note: Done for demonstration purposes only (not usually needed)
with open('dunder_mifflin.txt', 'w') as f:
    f.write('There were 55 paper clips shipped, 22 to Scranton and 33 to Filmer.')

with open('initech.txt', 'w') as f:
    f.write('David Brent did not sign any contract with Initech.')

# Upload documents
# Many file types are supported: text/image/audio documents and archives
with open('dunder_mifflin.txt', 'rb') as f:
    dunder_mifflin = client.upload('Dunder Mifflin.txt', f)

with open('initech.txt', 'rb') as f:
    initech = client.upload('IniTech.txt', f)

# Ingest documents (Creates previews, chunks and embeddings)
client.ingest_uploads(collection_id, [dunder_mifflin, initech])

# Create a chat session
chat_session_id = client.create_chat_session(collection_id)

# Query the collection
with client.connect(chat_session_id) as session:
    reply = session.query(
        'How many paper clips were shipped to Scranton?',
        timeout=60,
    )
    print(reply.content)

    reply = session.query(
        'Did David Brent co-sign the contract with Initech?',
        timeout=60,
    )
    print(reply.content)

# Summarize each document
documents = client.list_documents_in_collection(collection_id, offset=0, limit=99)
for doc in documents:
    summary = client.summarize_document(
        document_id=doc.id,
        timeout=60,
    )
    print(summary.content)