docs: improved readme + fix csv scraper imports

examples/csv_scraper_graph/ollama/csv_scraper_graph_multi_ollama.py

@@ -3,9 +3,9 @@ Basic example of scraping pipeline using CSVScraperMultiGraph from CSV documents
 """
 
 import os
-import pandas as pd
+
 from scrapegraphai.graphs import CSVScraperMultiGraph
-from scrapegraphai.utils import convert_to_csv, convert_to_json, prettify_exec_info
+from scrapegraphai.utils import prettify_exec_info
 
 # ************************************************
 # Read the CSV file
@@ -15,7 +15,8 @@ FILE_NAME = "inputs/username.csv"
 curr_dir = os.path.dirname(os.path.realpath(__file__))
 file_path = os.path.join(curr_dir, FILE_NAME)
 
-text = pd.read_csv(file_path)
+with open(file_path, "r") as file:
+    text = file.read()
 
 # ************************************************
 # Define the configuration for the graph
@@ -44,7 +45,7 @@ graph_config = {
 csv_scraper_graph = CSVScraperMultiGraph(
     prompt="List me all the last names",
     source=[str(text), str(text)],
-    config=graph_config
+    config=graph_config,
 )
 
 result = csv_scraper_graph.run()
@@ -56,7 +57,3 @@ print(result)
 
 graph_exec_info = csv_scraper_graph.get_execution_info()
 print(prettify_exec_info(graph_exec_info))
-
-# Save to json or csv
-convert_to_csv(result, "result")
-convert_to_json(result, "result")

examples/csv_scraper_graph/ollama/csv_scraper_ollama.py

@@ -3,9 +3,9 @@ Basic example of scraping pipeline using CSVScraperGraph from CSV documents
 """
 
 import os
-import pandas as pd
+
 from scrapegraphai.graphs import CSVScraperGraph
-from scrapegraphai.utils import convert_to_csv, convert_to_json, prettify_exec_info
+from scrapegraphai.utils import prettify_exec_info
 
 # ************************************************
 # Read the CSV file
@@ -15,7 +15,8 @@ FILE_NAME = "inputs/username.csv"
 curr_dir = os.path.dirname(os.path.realpath(__file__))
 file_path = os.path.join(curr_dir, FILE_NAME)
 
-text = pd.read_csv(file_path)
+with open(file_path, "r") as file:
+    text = file.read()
 
 # ************************************************
 # Define the configuration for the graph
@@ -44,7 +45,7 @@ graph_config = {
 csv_scraper_graph = CSVScraperGraph(
     prompt="List me all the last names",
     source=str(text),  # Pass the content of the file, not the file object
-    config=graph_config
+    config=graph_config,
 )
 
 result = csv_scraper_graph.run()
@@ -56,7 +57,3 @@ print(result)
 
 graph_exec_info = csv_scraper_graph.get_execution_info()
 print(prettify_exec_info(graph_exec_info))
-
-# Save to json or csv
-convert_to_csv(result, "result")
-convert_to_json(result, "result")

examples/csv_scraper_graph/openai/csv_scraper_graph_multi_openai.py

@@ -1,11 +1,13 @@
 """
 Basic example of scraping pipeline using CSVScraperMultiGraph from CSV documents
 """
+
 import os
+
 from dotenv import load_dotenv
-import pandas as pd
+
 from scrapegraphai.graphs import CSVScraperMultiGraph
-from scrapegraphai.utils import convert_to_csv, convert_to_json, prettify_exec_info
+from scrapegraphai.utils import prettify_exec_info
 
 load_dotenv()
 # ************************************************
@@ -16,7 +18,8 @@ FILE_NAME = "inputs/username.csv"
 curr_dir = os.path.dirname(os.path.realpath(__file__))
 file_path = os.path.join(curr_dir, FILE_NAME)
 
-text = pd.read_csv(file_path)
+with open(file_path, "r") as file:
+    text = file.read()
 
 # ************************************************
 # Define the configuration for the graph
@@ -24,7 +27,7 @@ text = pd.read_csv(file_path)
 openai_key = os.getenv("OPENAI_APIKEY")
 
 graph_config = {
-     "llm": {
+    "llm": {
         "api_key": openai_key,
         "model": "openai/gpt-4o",
     },
@@ -37,7 +40,7 @@ graph_config = {
 csv_scraper_graph = CSVScraperMultiGraph(
     prompt="List me all the last names",
     source=[str(text), str(text)],
-    config=graph_config
+    config=graph_config,
 )
 
 result = csv_scraper_graph.run()
@@ -49,7 +52,3 @@ print(result)
 
 graph_exec_info = csv_scraper_graph.get_execution_info()
 print(prettify_exec_info(graph_exec_info))
-
-# Save to json or csv
-convert_to_csv(result, "result")
-convert_to_json(result, "result")

examples/csv_scraper_graph/openai/csv_scraper_openai.py

@@ -1,11 +1,13 @@
 """
 Basic example of scraping pipeline using CSVScraperGraph from CSV documents
 """
+
 import os
+
 from dotenv import load_dotenv
-import pandas as pd
+
 from scrapegraphai.graphs import CSVScraperGraph
-from scrapegraphai.utils import convert_to_csv, convert_to_json, prettify_exec_info
+from scrapegraphai.utils import prettify_exec_info
 
 load_dotenv()
 
@@ -17,7 +19,8 @@ FILE_NAME = "inputs/username.csv"
 curr_dir = os.path.dirname(os.path.realpath(__file__))
 file_path = os.path.join(curr_dir, FILE_NAME)
 
-text = pd.read_csv(file_path)
+with open(file_path, "r") as file:
+    text = file.read()
 
 # ************************************************
 # Define the configuration for the graph
@@ -39,7 +42,7 @@ graph_config = {
 csv_scraper_graph = CSVScraperGraph(
     prompt="List me all the last names",
     source=str(text),  # Pass the content of the file, not the file object
-    config=graph_config
+    config=graph_config,
 )
 
 result = csv_scraper_graph.run()
@@ -51,7 +54,3 @@ print(result)
 
 graph_exec_info = csv_scraper_graph.get_execution_info()
 print(prettify_exec_info(graph_exec_info))
-
-# Save to json or csv
-convert_to_csv(result, "result")
-convert_to_json(result, "result")

examples/readme.md

@@ -1,32 +1,62 @@
-# Scrapegraph-ai Examples
+# 🕷️ Scrapegraph-ai Examples
 
-This directory contains various example implementations of Scrapegraph-ai for different use cases.
+This directory contains various example implementations of Scrapegraph-ai for different use cases. Each example demonstrates how to leverage the power of Scrapegraph-ai for specific scenarios.
 
-If you want more specific examples, visit [this](https://github.com/ScrapeGraphAI/ScrapegraphLib-Examples).
+> **Note:** While these examples showcase implementations using OpenAI and Ollama, Scrapegraph-ai supports many other LLM providers! Check out our [documentation](https://docs-oss.scrapegraphai.com/examples) for the full list of supported providers.
 
-## Available Examples
+## 📚 Available Examples
 
-- `smart_scraper/` - Advanced web scraping with intelligent content extraction
+- 🧠 `smart_scraper/` - Advanced web scraping with intelligent content extraction
-- `depth_search_graph/` - Deep web crawling and content exploration
+- 🔎 `search_graph/` - Web search and data retrieval
-- `csv_scraper_graph/` - Scraping and processing data into CSV format
+- ⚙️ `script_generator_graph/` - Automated script generation
-- `xml_scraper_graph/` - XML data extraction and processing
+- 🌐 `depth_search_graph/` - Deep web crawling and content exploration
-- `speech_graph/` - Speech processing and analysis
+- 📊 `csv_scraper_graph/` - Scraping and processing data into CSV format
-- `omni_scraper_graph/` - Universal web scraping for multiple data types
+- 📑 `xml_scraper_graph/` - XML data extraction and processing
-- `omni_search_graph/` - Comprehensive search across multiple sources
+- 🎤 `speech_graph/` - Speech processing and analysis
-- `document_scraper_graph/` - Document parsing and data extraction
+- 🔄 `omni_scraper_graph/` - Universal web scraping for multiple data types
-- `script_generator_graph/` - Automated script generation
+- 🔍 `omni_search_graph/` - Comprehensive search across multiple sources
-- `custom_graph/` - Custom graph implementation examples
+- 📄 `document_scraper_graph/` - Document parsing and data extraction
-- `code_generator_graph/` - Code generation utilities
+- 🛠️ `custom_graph/` - Custom graph implementation examples
-- `json_scraper_graph/` - JSON data extraction and processing
+- 💻 `code_generator_graph/` - Code generation utilities
-- `search_graph/` - Web search and data retrieval
+- 📋 `json_scraper_graph/` - JSON data extraction and processing
 
-## Getting Started
+## 🚀 Getting Started
 
 1. Choose the example that best fits your use case
 2. Navigate to the corresponding directory
 3. Follow the README instructions in each directory
 4. Configure any required environment variables using the provided `.env.example` files
 
-## Requirements
+## ⚡ Quick Setup
+
+```bash
+pip install scrapegraphai
+
+playwright install
+
+# choose an example
+cd examples/smart_scraper_graph/openai
+
+# run the example
+python smart_scraper_openai.py
+```
+
+## 📋 Requirements
 
 Each example may have its own specific requirements. Please refer to the individual README files in each directory for detailed setup instructions.
+
+## 📚 Additional Resources
+
+- 📖 [Full Documentation](https://docs-oss.scrapegraphai.com/examples)
+- 💡 [Examples Repository](https://github.com/ScrapeGraphAI/ScrapegraphLib-Examples)
+- 🤝 [Community Support](https://github.com/ScrapeGraphAI/scrapegraph-ai/discussions)
+
+## 🤔 Need Help?
+
+- Check out our [documentation](https://docs-oss.scrapegraphai.com)
+- Join our [Discord community](https://discord.gg/scrapegraphai)
+- Open an [issue](https://github.com/ScrapeGraphAI/scrapegraph-ai/issues)
+
+---
+
+⭐ Don't forget to star our repository if you find these examples helpful!

examples/smart_scraper_graph/ollama/smart_scraper_lite_ollama.py

@@ -2,7 +2,9 @@
 Basic example of scraping pipeline using SmartScraper
 
 """
+
 import json
+
 from scrapegraphai.graphs import SmartScraperLiteGraph
 from scrapegraphai.utils import prettify_exec_info
 
@@ -14,13 +16,13 @@ graph_config = {
         "base_url": "http://localhost:11434",
     },
     "verbose": True,
-    "headless": False
+    "headless": False,
 }
 
 smart_scraper_lite_graph = SmartScraperLiteGraph(
     prompt="Who is Marco Perini?",
     source="https://perinim.github.io/",
-    config=graph_config
+    config=graph_config,
 )
 
 result = smart_scraper_lite_graph.run()

examples/smart_scraper_graph/ollama/smart_scraper_multi_concat_ollama.py

@@ -2,9 +2,10 @@
 Basic example of scraping pipeline using SmartScraper
 """
 
-import os
 import json
+
 from dotenv import load_dotenv
+
 from scrapegraphai.graphs import SmartScraperMultiConcatGraph
 
 load_dotenv()
@@ -18,10 +19,10 @@ graph_config = {
         "model": "ollama/llama3.1",
         "temperature": 0,
         "format": "json",  # Ollama needs the format to be specified explicitly
-        "base_url": "http://localhost:11434", # set ollama URL arbitrarily
+        "base_url": "http://localhost:11434",  # set ollama URL arbitrarily
     },
     "verbose": True,
-    "headless": False
+    "headless": False,
 }
 
 # *******************************************************
@@ -30,12 +31,9 @@ graph_config = {
 
 multiple_search_graph = SmartScraperMultiConcatGraph(
     prompt="Who is Marco Perini?",
-    source= [
+    source=["https://perinim.github.io/", "https://perinim.github.io/cv/"],
-        "https://perinim.github.io/",
-        "https://perinim.github.io/cv/"
-        ],
     schema=None,
-    config=graph_config
+    config=graph_config,
 )
 
 result = multiple_search_graph.run()

examples/smart_scraper_graph/ollama/smart_scraper_multi_lite_ollama.py

@@ -1,7 +1,9 @@
 """
 Basic example of scraping pipeline using SmartScraper
 """
+
 import json
+
 from scrapegraphai.graphs import SmartScraperMultiLiteGraph
 from scrapegraphai.utils import prettify_exec_info
 
@@ -17,7 +19,7 @@ graph_config = {
         "base_url": "http://localhost:11434",  # set ollama URL arbitrarily
     },
     "verbose": True,
-    "headless": False
+    "headless": False,
 }
 
 # ************************************************
@@ -26,11 +28,8 @@ graph_config = {
 
 smart_scraper_multi_lite_graph = SmartScraperMultiLiteGraph(
     prompt="Who is Marco Perini?",
-    source= [
+    source=["https://perinim.github.io/", "https://perinim.github.io/cv/"],
-        "https://perinim.github.io/",
+    config=graph_config,
-        "https://perinim.github.io/cv/"
-    ],
-    config=graph_config
 )
 
 result = smart_scraper_multi_lite_graph.run()
@@ -42,4 +41,3 @@ print(json.dumps(result, indent=4))
 
 graph_exec_info = smart_scraper_multi_lite_graph.get_execution_info()
 print(prettify_exec_info(graph_exec_info))
-

examples/smart_scraper_graph/ollama/smart_scraper_multi_ollama.py

@@ -3,6 +3,7 @@ Basic example of scraping pipeline using SmartScraper
 """
 
 import json
+
 from scrapegraphai.graphs import SmartScraperMultiGraph
 
 # ************************************************
@@ -15,9 +16,8 @@ graph_config = {
         "format": "json",  # Ollama needs the format to be specified explicitly
         # "base_url": "http://localhost:11434", # set ollama URL arbitrarily
     },
-   
     "verbose": True,
-    "headless": False
+    "headless": False,
 }
 
 
@@ -27,12 +27,9 @@ graph_config = {
 
 multiple_search_graph = SmartScraperMultiGraph(
     prompt="Who is Marco Perini?",
-    source= [
+    source=["https://perinim.github.io/", "https://perinim.github.io/cv/"],
-        "https://perinim.github.io/",
-        "https://perinim.github.io/cv/"
-        ],
     schema=None,
-    config=graph_config
+    config=graph_config,
 )
 
 result = multiple_search_graph.run()

examples/smart_scraper_graph/ollama/smart_scraper_schema_ollama.py

@@ -1,12 +1,16 @@
 """
 Basic example of scraping pipeline using SmartScraper with schema
 """
+
 import json
 from typing import List
+
 from pydantic import BaseModel, Field
+
 from scrapegraphai.graphs import SmartScraperGraph
 from scrapegraphai.utils import prettify_exec_info
 
+
 # ************************************************
 # Define the configuration for the graph
 # ************************************************
@@ -14,9 +18,11 @@ 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]
 
+
 graph_config = {
     "llm": {
         "model": "ollama/llama3.1",
@@ -25,7 +31,7 @@ graph_config = {
         # "base_url": "http://localhost:11434", # set ollama URL arbitrarily
     },
     "verbose": True,
-    "headless": False
+    "headless": False,
 }
 
 # ************************************************
@@ -36,8 +42,15 @@ smart_scraper_graph = SmartScraperGraph(
     prompt="List me all the projects with their description",
     source="https://perinim.github.io/projects/",
     schema=Projects,
-    config=graph_config
+    config=graph_config,
 )
 
 result = smart_scraper_graph.run()
 print(json.dumps(result, indent=4))
+
+# ************************************************
+# Get graph execution info
+# ************************************************
+
+graph_exec_info = smart_scraper_graph.get_execution_info()
+print(prettify_exec_info(graph_exec_info))

examples/smart_scraper_graph/openai/smart_scraper_lite_openai.py

@@ -1,9 +1,12 @@
 """
 Basic example of scraping pipeline using SmartScraper
 """
-import os
+
 import json
+import os
+
 from dotenv import load_dotenv
+
 from scrapegraphai.graphs import SmartScraperLiteGraph
 from scrapegraphai.utils import prettify_exec_info
 
@@ -21,7 +24,7 @@ graph_config = {
 smart_scraper_lite_graph = SmartScraperLiteGraph(
     prompt="Who is Marco Perini?",
     source="https://perinim.github.io/",
-    config=graph_config
+    config=graph_config,
 )
 
 result = smart_scraper_lite_graph.run()
@@ -29,4 +32,3 @@ print(json.dumps(result, indent=4))
 
 graph_exec_info = smart_scraper_lite_graph.get_execution_info()
 print(prettify_exec_info(graph_exec_info))
-

examples/smart_scraper_graph/openai/smart_scraper_multi_concat_openai.py

@@ -1,9 +1,12 @@
 """
 Basic example of scraping pipeline using SmartScraper
 """
-import os
+
 import json
+import os
+
 from dotenv import load_dotenv
+
 from scrapegraphai.graphs import SmartScraperMultiConcatGraph
 
 load_dotenv()
@@ -28,12 +31,9 @@ graph_config = {
 
 multiple_search_graph = SmartScraperMultiConcatGraph(
     prompt="Who is Marco Perini?",
-    source= [
+    source=["https://perinim.github.io/", "https://perinim.github.io/cv/"],
-        "https://perinim.github.io/",
-        "https://perinim.github.io/cv/"
-        ],
     schema=None,
-    config=graph_config
+    config=graph_config,
 )
 
 result = multiple_search_graph.run()

examples/smart_scraper_graph/openai/smart_scraper_multi_lite_openai.py

@@ -1,9 +1,12 @@
 """
 Basic example of scraping pipeline using SmartScraper
 """
-import os
+
 import json
+import os
+
 from dotenv import load_dotenv
+
 from scrapegraphai.graphs import SmartScraperMultiLiteGraph
 from scrapegraphai.utils import prettify_exec_info
 
@@ -29,11 +32,8 @@ graph_config = {
 
 smart_scraper_multi_lite_graph = SmartScraperMultiLiteGraph(
     prompt="Who is Marco Perini?",
-    source= [
+    source=["https://perinim.github.io/", "https://perinim.github.io/cv/"],
-        "https://perinim.github.io/",
+    config=graph_config,
-        "https://perinim.github.io/cv/"
-    ],
-    config=graph_config
 )
 
 result = smart_scraper_multi_lite_graph.run()

examples/smart_scraper_graph/openai/smart_scraper_multi_openai.py

@@ -1,9 +1,12 @@
 """
 Basic example of scraping pipeline using SmartScraper
 """
-import os
+
 import json
+import os
+
 from dotenv import load_dotenv
+
 from scrapegraphai.graphs import SmartScraperMultiGraph
 
 load_dotenv()
@@ -29,12 +32,9 @@ graph_config = {
 
 multiple_search_graph = SmartScraperMultiGraph(
     prompt="Who is Marco Perini?",
-    source= [
+    source=["https://perinim.github.io/", "https://perinim.github.io/cv/"],
-        "https://perinim.github.io/",
-        "https://perinim.github.io/cv/"
-        ],
     schema=None,
-    config=graph_config
+    config=graph_config,
 )
 
 result = multiple_search_graph.run()

examples/smart_scraper_graph/openai/smart_scraper_schema_openai.py

@@ -1,10 +1,13 @@
 """
 Basic example of scraping pipeline using SmartScraper with schema
 """
+
 import os
 from typing import List
+
 from dotenv import load_dotenv
 from pydantic import BaseModel, Field
+
 from scrapegraphai.graphs import SmartScraperGraph
 
 load_dotenv()
@@ -13,13 +16,16 @@ 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
 # ************************************************
@@ -43,7 +49,7 @@ smart_scraper_graph = SmartScraperGraph(
     prompt="List me all the projects with their description",
     source="https://perinim.github.io/projects/",
     schema=Projects,
-    config=graph_config
+    config=graph_config,
 )
 
 result = smart_scraper_graph.run()