chore: import upstream snapshot with attribution

examples/code_generator_graph/.env.example

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+# OpenAI API Configuration
+OPENAI_API_KEY=your-openai-api-key-here
+
+# Optional Configurations
+MAX_TOKENS=4000
+MODEL_NAME=gpt-4-1106-preview
+TEMPERATURE=0.7
+
+# Code Generator Settings
+DEFAULT_LANGUAGE=python
+GENERATE_TESTS=true
+ADD_DOCUMENTATION=true
+CODE_STYLE=pep8
+TYPE_CHECKING=true

examples/code_generator_graph/README.md

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+# Code Generator Graph Example
+
+This example demonstrates how to use Scrapegraph-ai to generate code based on specifications and requirements.
+
+## Features
+
+- Code generation from specifications
+- Multiple programming languages support
+- Code documentation
+- Best practices implementation
+
+## Setup
+
+1. Install required dependencies
+2. Copy `.env.example` to `.env`
+3. Configure your API keys in the `.env` file
+
+## Usage
+
+```python
+from scrapegraphai.graphs import CodeGeneratorGraph
+
+graph = CodeGeneratorGraph()
+code = graph.generate("code specification")
+```
+
+## Environment Variables
+
+Required environment variables:
+- `OPENAI_API_KEY`: Your OpenAI API key

examples/code_generator_graph/ollama/code_generator_graph_ollama.py

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+"""
+Basic example of scraping pipeline using Code Generator with schema
+"""
+
+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
+# ************************************************
+
+
+graph_config = {
+    "llm": {
+        "model": "ollama/llama3",
+        "temperature": 0,
+        "format": "json",
+        "base_url": "http://localhost:11434",
+    },
+    "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)

examples/code_generator_graph/openai/code_generator_graph_openai.py

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+"""
+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)