chore: import upstream snapshot with attribution

examples/code_generator_graph/openai/code_generator_graph_openai.py

@@ -0,0 +1,65 @@
+"""
+Basic example of scraping pipeline using Code Generator with schema
+"""
+
+import os
+from typing import List
+
+from dotenv import load_dotenv
+from pydantic import BaseModel, Field
+
+from scrapegraphai.graphs import CodeGeneratorGraph
+
+load_dotenv()
+
+# ************************************************
+# Define the output schema for the graph
+# ************************************************
+
+
+class Project(BaseModel):
+    title: str = Field(description="The title of the project")
+    description: str = Field(description="The description of the project")
+
+
+class Projects(BaseModel):
+    projects: List[Project]
+
+
+# ************************************************
+# Define the configuration for the graph
+# ************************************************
+
+openai_key = os.getenv("OPENAI_APIKEY")
+
+graph_config = {
+    "llm": {
+        "api_key": openai_key,
+        "model": "openai/gpt-4o-mini",
+    },
+    "verbose": True,
+    "headless": False,
+    "reduction": 2,
+    "max_iterations": {
+        "overall": 10,
+        "syntax": 3,
+        "execution": 3,
+        "validation": 3,
+        "semantic": 3,
+    },
+    "output_file_name": "extracted_data.py",
+}
+
+# ************************************************
+# Create the SmartScraperGraph instance and run it
+# ************************************************
+
+code_generator_graph = CodeGeneratorGraph(
+    prompt="List me all the projects with their description",
+    source="https://perinim.github.io/projects/",
+    schema=Projects,
+    config=graph_config,
+)
+
+result = code_generator_graph.run()
+print(result)