Deployment Overview

# schema.py: declarative schema (idempotent, safe to re-run)
import pixeltable as pxt
from pixeltable.functions.huggingface import sentence_transformer
from pixeltable.functions.string import string_splitter
from pixeltable.functions.uuid import uuid7

pxt.create_dir('pipeline', if_exists='ignore')
embed_fn = sentence_transformer.using(model_id='all-MiniLM-L6-v2')

documents = pxt.create_table('pipeline.documents', {
    'title': pxt.String,
    'body': pxt.String,
    'source_id': pxt.String,
    'uuid': uuid7(),
    'timestamp': pxt.Timestamp,
}, primary_key=['uuid'], if_exists='ignore')

sentences = pxt.create_view(
    'pipeline.sentences', documents,
    iterator=string_splitter(text=documents.body, separators='sentence'),
    if_exists='ignore',
)
sentences.add_embedding_index(
    'text', idx_name='sentences_embed', string_embed=embed_fn, if_exists='ignore'
)

# pipeline.py: ingest, compute, export, exit
import json
from datetime import datetime
from pixeltable.io.sql import export_sql
import schema

SERVING_DB_URL = 'postgresql+psycopg://user:pass@host/db'

with open('batch.json') as f:
    batch = json.load(f)

now = datetime.now()
for row in batch['documents']:
    row.setdefault('timestamp', now)

# Insert triggers computed columns: chunking, embeddings, etc.
schema.documents.insert(batch['documents'])

# Export structured results to serving DB
export_sql(
    schema.documents.select(
        schema.documents.source_id,
        schema.documents.title,
        schema.documents.body,
    ),
    'processed_documents',
    db_connect_str=SERVING_DB_URL,
    if_exists='replace',
)

# Example: FastAPIRouter endpoints backed by Pixeltable
import fastapi
import pixeltable as pxt
from pixeltable.serving import FastAPIRouter

app = fastapi.FastAPI()
router = FastAPIRouter(prefix="/api", tags=["documents"])

docs = pxt.get_table('myapp/documents')

# File upload with background processing (returns job handle)
router.add_insert_route(docs, path="/upload",
    uploadfile_inputs=["document"], inputs=["uploaded_at"],
    outputs=["uuid"], background=True)

# Search via @pxt.query
@pxt.query
def search_documents(query_text: str, limit: int = 10):
    sim = docs.embedding.similarity(string=query_text)
    return docs.order_by(sim, asc=False).limit(limit).select(
        docs.document, docs.summary, similarity=sim)

router.add_query_route(path="/search", query=search_documents)

# Delete by primary key
router.add_delete_route(docs, path="/delete")

app.include_router(router)

# pyproject.toml
[project]
name = "my-api"
requires-python = ">=3.10"

[[tool.pixeltable.service]]
name = "my-service"
prefix = "/api"
modules = ["schema"]

[[tool.pixeltable.service.routes]]
type = "query"
path = "/search"
query = "schema:search_documents"

[[tool.pixeltable.service.routes]]
type = "insert"
table = "pipeline.documents"
path = "/ingest"
inputs = ["title", "body"]
outputs = ["title", "body"]

[[tool.pixeltable.service.routes]]
type = "export_sql"
path = "/export"
query = "schema:export_query"
db_url = "postgresql+psycopg://user:pass@host/db"
table_name = "exported_docs"
if_exists = "replace"

pxt serve my-service
# curl -X POST localhost:8000/api/search -d '{"query_text": "machine learning"}'

uvx pixeltable-new myapp              # declarative serving (default)
uvx pixeltable-new myapp --backend    # full FastAPI + React app
uvx pixeltable-new myapp --batch      # batch processing script

uvx pixeltable-new myapp --template knowledge-base         # cross-modal search + RAG Q&A
uvx pixeltable-new myapp --template chat-agent             # tool-calling agent with memory
uvx pixeltable-new myapp --template audio-transcription    # audio transcription + search
uvx pixeltable-new myapp --template full-stack-showcase    # FastAPI + React reference app
uvx pixeltable-new myapp --template video-search           # video frame analysis + search
uvx pixeltable-new myapp --template media-indexing         # enterprise media processing + export
uvx pixeltable-new myapp --template image-dataset          # ML dataset auto-labeling + export