Update examples for standalond CLI usage

Author: lemorage

examples/amazon_s3_embedding/main.py

@@ -1,5 +1,3 @@
-from dotenv import load_dotenv
-
 import cocoindex
 import os
 
@@ -52,7 +50,6 @@ def amazon_s3_text_embedding_flow(flow_builder: cocoindex.FlowBuilder, data_scop
             model="sentence-transformers/all-MiniLM-L6-v2")),
     default_similarity_metric=cocoindex.VectorSimilarityMetric.COSINE_SIMILARITY)
 
-@cocoindex.main_fn()
 def _run():
     # Use a `FlowLiveUpdater` to keep the flow data updated.
     with cocoindex.FlowLiveUpdater(amazon_s3_text_embedding_flow):
@@ -73,5 +70,4 @@ def _run():
                 break
 
 if __name__ == "__main__":
-    load_dotenv(override=True)
     _run()

examples/code_embedding/main.py

@@ -1,5 +1,3 @@
-from dotenv import load_dotenv
-
 import cocoindex
 import os
 
@@ -54,7 +52,6 @@ def code_embedding_flow(flow_builder: cocoindex.FlowBuilder, data_scope: cocoind
     query_transform_flow=code_to_embedding,
     default_similarity_metric=cocoindex.VectorSimilarityMetric.COSINE_SIMILARITY)
 
-@cocoindex.main_fn()
 def _run():
     # Run queries in a loop to demonstrate the query capabilities.
     while True:
@@ -73,5 +70,4 @@ def _run():
             break
 
 if __name__ == "__main__":
-    load_dotenv(override=True)
     _run()

examples/docs_to_knowledge_graph/main.py

@@ -2,7 +2,6 @@
 This example shows how to extract relationships from documents and build a knowledge graph.
 """
 import dataclasses
-from dotenv import load_dotenv
 import cocoindex
 
 @dataclasses.dataclass
@@ -148,10 +147,8 @@ def docs_to_kg_flow(flow_builder: cocoindex.FlowBuilder, data_scope: cocoindex.D
         primary_key_fields=["id"],
     )
 
-@cocoindex.main_fn()
 def _run():
     pass
 
 if __name__ == "__main__":
-    load_dotenv(override=True)
     _run()

examples/fastapi_server_docker/main.py

@@ -2,7 +2,6 @@
 import uvicorn
 
 from fastapi import FastAPI
-from dotenv import load_dotenv
 
 from src.cocoindex_funs import code_embedding_flow, code_to_embedding
 
@@ -21,10 +20,8 @@ def query_endpoint(string: str):
     results, _ = query_handler.search(string, 10)
     return results
 
-@cocoindex.main_fn()
 def _run():
     uvicorn.run(fastapi_app, host="0.0.0.0", port=8080)
 
 if __name__ == "__main__":
-    load_dotenv(override=True)
     _run()

examples/gdrive_text_embedding/main.py

@@ -1,5 +1,3 @@
-from dotenv import load_dotenv
-
 import cocoindex
 import datetime
 import os
@@ -51,7 +49,6 @@ def gdrive_text_embedding_flow(flow_builder: cocoindex.FlowBuilder, data_scope:
             model="sentence-transformers/all-MiniLM-L6-v2")),
     default_similarity_metric=cocoindex.VectorSimilarityMetric.COSINE_SIMILARITY)
 
-@cocoindex.main_fn()
 def _run():
     # Use a `FlowLiveUpdater` to keep the flow data updated.
     with cocoindex.FlowLiveUpdater(gdrive_text_embedding_flow):
@@ -72,5 +69,4 @@ def _run():
                 break
 
 if __name__ == "__main__":
-    load_dotenv(override=True)
     _run()

examples/image_search_example/main.py

@@ -1,4 +1,3 @@
-from dotenv import load_dotenv
 import cocoindex
 import datetime
 import os
@@ -7,9 +6,6 @@
 from fastapi import FastAPI, Query
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.staticfiles import StaticFiles
-from cocoindex.lib import main_fn
-
-load_dotenv(override=True)
 
 OLLAMA_URL = "http://localhost:11434/api/generate"
 OLLAMA_MODEL = "gemma3"
@@ -120,8 +116,6 @@ def search(q: str = Query(..., description="Search query"), limit: int = Query(5
         })
     return {"results": out}
 
-# --- CLI entrypoint ---
-@main_fn()
 def _run():
     pass
 

examples/manuals_llm_extraction/main.py

@@ -1,7 +1,6 @@
 import tempfile
 import dataclasses
 
-from dotenv import load_dotenv
 from marker.converters.pdf import PdfConverter
 from marker.models import create_model_dict
 from marker.output import text_from_rendered
@@ -117,10 +116,8 @@ def manual_extraction_flow(flow_builder: cocoindex.FlowBuilder, data_scope: coco
         primary_key_fields=["filename"],
     )
 
-@cocoindex.main_fn()
 def _run():
     pass
 
 if __name__ == "__main__":
-    load_dotenv(override=True)
     _run()

examples/pdf_embedding/main.py

@@ -1,6 +1,5 @@
 import tempfile
 
-from dotenv import load_dotenv
 from marker.converters.pdf import PdfConverter
 from marker.models import create_model_dict
 from marker.output import text_from_rendered
@@ -75,7 +74,6 @@ def pdf_embedding_flow(flow_builder: cocoindex.FlowBuilder, data_scope: cocoinde
     query_transform_flow=text_to_embedding,
     default_similarity_metric=cocoindex.VectorSimilarityMetric.COSINE_SIMILARITY)
 
-@cocoindex.main_fn()
 def _run():
     # Run queries in a loop to demonstrate the query capabilities.
     while True:
@@ -94,5 +92,4 @@ def _run():
             break
 
 if __name__ == "__main__":
-    load_dotenv(override=True)
     _run()

examples/product_recommendation/main.py

@@ -3,7 +3,6 @@
 """
 import dataclasses
 import datetime
-from dotenv import load_dotenv
 import cocoindex
 from jinja2 import Template
 
@@ -176,10 +175,8 @@ def store_product_flow(flow_builder: cocoindex.FlowBuilder, data_scope: cocoinde
         primary_key_fields=["id"],
     )
 
-@cocoindex.main_fn()
 def _run():
     pass
 
 if __name__ == "__main__":
-    load_dotenv(override=True)
     _run()

examples/text_embedding/main.py

@@ -1,4 +1,3 @@
-from dotenv import load_dotenv
 from psycopg_pool import ConnectionPool
 import cocoindex
 import os
@@ -60,7 +59,6 @@ def search(pool: ConnectionPool, query: str, top_k: int = 5):
                 for row in cur.fetchall()
             ]
 
-@cocoindex.main_fn()
 def _run():
     # Initialize the database connection pool.
     pool = ConnectionPool(os.getenv("COCOINDEX_DATABASE_URL"))
@@ -82,5 +80,4 @@ def _run():
             break
 
 if __name__ == "__main__":
-    load_dotenv(override=True)
     _run()