diff --git a/examples/openai/custom_graph_openai.py b/examples/openai/custom_graph_openai.py
index 5744669b..14dd99bd 100644
--- a/examples/openai/custom_graph_openai.py
+++ b/examples/openai/custom_graph_openai.py
@@ -4,6 +4,8 @@
 
 import os
 from dotenv import load_dotenv
+
+from langchain_openai import OpenAIEmbeddings
 from scrapegraphai.models import OpenAI
 from scrapegraphai.graphs import BaseGraph
 from scrapegraphai.nodes import FetchNode, ParseNode, RAGNode, GenerateAnswerNode, RobotsNode
@@ -20,7 +22,7 @@
         "api_key": openai_key,
         "model": "gpt-3.5-turbo",
         "temperature": 0,
-        "streaming": True
+        "streaming": False
     },
 }
 
@@ -29,33 +31,50 @@
 # ************************************************
 
 llm_model = OpenAI(graph_config["llm"])
+embedder = OpenAIEmbeddings(api_key=llm_model.openai_api_key)
 
 # define the nodes for the graph
 robot_node = RobotsNode(
     input="url",
     output=["is_scrapable"],
-    node_config={"llm_model": llm_model}
+    node_config={
+        "llm_model": llm_model,
+        "verbose": True,
+        }
 )
 
 fetch_node = FetchNode(
     input="url | local_dir",
     output=["doc"],
-    node_config={"headless": True, "verbose": True}
+    node_config={
+        "verbose": True,
+        "headless": True,
+    }
 )
 parse_node = ParseNode(
     input="doc",
     output=["parsed_doc"],
-    node_config={"chunk_size": 4096}
+    node_config={
+        "chunk_size": 4096,
+        "verbose": True,
+    }
 )
 rag_node = RAGNode(
     input="user_prompt & (parsed_doc | doc)",
     output=["relevant_chunks"],
-    node_config={"llm_model": llm_model},
+    node_config={
+        "llm_model": llm_model,
+        "embedder_model": embedder,
+        "verbose": True,
+    }
 )
 generate_answer_node = GenerateAnswerNode(
     input="user_prompt & (relevant_chunks | parsed_doc | doc)",
     output=["answer"],
-    node_config={"llm_model": llm_model},
+    node_config={
+        "llm_model": llm_model,
+        "verbose": True,
+    }
 )
 
 # ************************************************
diff --git a/examples/openai/search_graph_multi.py b/examples/openai/search_graph_multi.py
new file mode 100644
index 00000000..962397c7
--- /dev/null
+++ b/examples/openai/search_graph_multi.py
@@ -0,0 +1,98 @@
+"""
+Example of custom graph using existing nodes
+"""
+
+import os
+from dotenv import load_dotenv
+from langchain_openai import OpenAIEmbeddings
+from scrapegraphai.models import OpenAI
+from scrapegraphai.graphs import BaseGraph, SmartScraperGraph
+from scrapegraphai.nodes import SearchInternetNode, GraphIteratorNode, MergeAnswersNode
+load_dotenv()
+
+# ************************************************
+# Define the configuration for the graph
+# ************************************************
+
+openai_key = os.getenv("OPENAI_APIKEY")
+
+graph_config = {
+    "llm": {
+        "api_key": openai_key,
+        "model": "gpt-3.5-turbo",
+    },
+}
+
+# ************************************************
+# Create a SmartScraperGraph instance
+# ************************************************
+
+smart_scraper_graph = SmartScraperGraph(
+    prompt="",
+    source="",
+    config=graph_config
+)
+
+# ************************************************
+# Define the graph nodes
+# ************************************************
+
+llm_model = OpenAI(graph_config["llm"])
+embedder = OpenAIEmbeddings(api_key=llm_model.openai_api_key)
+
+search_internet_node = SearchInternetNode(
+    input="user_prompt",
+    output=["urls"],
+    node_config={
+        "llm_model": llm_model,
+        "max_results": 5,  # num of search results to fetch
+        "verbose": True,
+    }
+)
+
+graph_iterator_node = GraphIteratorNode(
+    input="user_prompt & urls",
+    output=["results"],
+    node_config={
+        "graph_instance": smart_scraper_graph,
+        "verbose": True,
+    }
+)
+
+merge_answers_node = MergeAnswersNode(
+    input="user_prompt & results",
+    output=["answer"],
+    node_config={
+        "llm_model": llm_model,
+        "verbose": True,
+    }
+)
+
+# ************************************************
+# Create the graph by defining the connections
+# ************************************************
+
+graph = BaseGraph(
+    nodes=[
+        search_internet_node,
+        graph_iterator_node,
+        merge_answers_node
+    ],
+    edges=[
+        (search_internet_node, graph_iterator_node),
+        (graph_iterator_node, merge_answers_node)
+    ],
+    entry_point=search_internet_node
+)
+
+# ************************************************
+# Execute the graph
+# ************************************************
+
+result, execution_info = graph.execute({
+    "user_prompt": "List me all the typical Chioggia dishes."
+})
+
+# get the answer from the result
+result = result.get("answer", "No answer found.")
+print(result)
diff --git a/examples/openai/search_graph_openai.py b/examples/openai/search_graph_openai.py
index 0e0ca28d..486d9a62 100644
--- a/examples/openai/search_graph_openai.py
+++ b/examples/openai/search_graph_openai.py
@@ -19,6 +19,8 @@
         "api_key": openai_key,
         "model": "gpt-3.5-turbo",
     },
+    "max_results": 5,
+    "verbose": True,
 }
 
 # ************************************************
@@ -26,7 +28,7 @@
 # ************************************************
 
 search_graph = SearchGraph(
-    prompt="List me top 5 eyeliner products for a gift.",
+    prompt="List me the best escursions near Trento",
     config=graph_config
 )
 
diff --git a/examples/openai/smart_scraper_openai.py b/examples/openai/smart_scraper_openai.py
index 32a1942b..610e6697 100644
--- a/examples/openai/smart_scraper_openai.py
+++ b/examples/openai/smart_scraper_openai.py
@@ -21,7 +21,7 @@
         "api_key": openai_key,
         "model": "gpt-3.5-turbo",
     },
-    "verbose": True,
+    "verbose": False,
 }
 
 # ************************************************
diff --git a/scrapegraphai/graphs/__init__.py b/scrapegraphai/graphs/__init__.py
index 9c736b66..64b8241c 100644
--- a/scrapegraphai/graphs/__init__.py
+++ b/scrapegraphai/graphs/__init__.py
@@ -2,6 +2,7 @@
 __init__.py file for graphs folder
 """
 
+from .abstract_graph import AbstractGraph
 from .base_graph import BaseGraph
 from .smart_scraper_graph import SmartScraperGraph
 from .speech_graph import SpeechGraph
diff --git a/scrapegraphai/graphs/abstract_graph.py b/scrapegraphai/graphs/abstract_graph.py
index 650ed988..089b0f95 100644
--- a/scrapegraphai/graphs/abstract_graph.py
+++ b/scrapegraphai/graphs/abstract_graph.py
@@ -56,7 +56,7 @@ def __init__(self, prompt: str, config: dict, source: Optional[str] = None):
         self.execution_info = None
 
         # Set common configuration parameters
-        self.verbose = True if config is None else config.get("verbose", False)
+        self.verbose = False if config is None else config.get("verbose", False)
         self.headless = True if config is None else config.get(
             "headless", True)
         common_params = {"headless": self.headless,
diff --git a/scrapegraphai/graphs/search_graph.py b/scrapegraphai/graphs/search_graph.py
index 9c463e1a..75d0d304 100644
--- a/scrapegraphai/graphs/search_graph.py
+++ b/scrapegraphai/graphs/search_graph.py
@@ -5,12 +5,11 @@
 from .base_graph import BaseGraph
 from ..nodes import (
     SearchInternetNode,
-    FetchNode,
-    ParseNode,
-    RAGNode,
-    GenerateAnswerNode
+    GraphIteratorNode,
+    MergeAnswersNode
 )
 from .abstract_graph import AbstractGraph
+from .smart_scraper_graph import SmartScraperGraph
 
 
 class SearchGraph(AbstractGraph):
@@ -38,6 +37,11 @@ class SearchGraph(AbstractGraph):
         >>> result = search_graph.run()
     """
 
+    def __init__(self, prompt: str, config: dict):
+
+        self.max_results = config.get("max_results", 3)
+        super().__init__(prompt, config)
+
     def _create_graph(self) -> BaseGraph:
         """
         Creates the graph of nodes representing the workflow for web scraping and searching.
@@ -46,53 +50,53 @@ def _create_graph(self) -> BaseGraph:
             BaseGraph: A graph instance representing the web scraping and searching workflow.
         """
 
+        # ************************************************
+        # Create a SmartScraperGraph instance
+        # ************************************************
+
+        smart_scraper_instance = SmartScraperGraph(
+            prompt="",
+            source="",
+            config=self.config
+        )
+
+        # ************************************************
+        # Define the graph nodes
+        # ************************************************
+
         search_internet_node = SearchInternetNode(
             input="user_prompt",
-            output=["url"],
-            node_config={
-                "llm_model": self.llm_model
-            }
-        )
-        fetch_node = FetchNode(
-            input="url | local_dir",
-            output=["doc"]
-        )
-        parse_node = ParseNode(
-            input="doc",
-            output=["parsed_doc"],
+            output=["urls"],
             node_config={
-                "chunk_size": self.model_token
+                "llm_model": self.llm_model,
+                "max_results": self.max_results
             }
         )
-        rag_node = RAGNode(
-            input="user_prompt & (parsed_doc | doc)",
-            output=["relevant_chunks"],
+        graph_iterator_node = GraphIteratorNode(
+            input="user_prompt & urls",
+            output=["results"],
             node_config={
-                "llm_model": self.llm_model,
-                "embedder_model": self.embedder_model
+                "graph_instance": smart_scraper_instance,
             }
         )
-        generate_answer_node = GenerateAnswerNode(
-            input="user_prompt & (relevant_chunks | parsed_doc | doc)",
+
+        merge_answers_node = MergeAnswersNode(
+            input="user_prompt & results",
             output=["answer"],
             node_config={
-                "llm_model": self.llm_model
+                "llm_model": self.llm_model,
             }
         )
 
         return BaseGraph(
             nodes=[
                 search_internet_node,
-                fetch_node,
-                parse_node,
-                rag_node,
-                generate_answer_node,
+                graph_iterator_node,
+                merge_answers_node
             ],
             edges=[
-                (search_internet_node, fetch_node),
-                (fetch_node, parse_node),
-                (parse_node, rag_node),
-                (rag_node, generate_answer_node)
+                (search_internet_node, graph_iterator_node),
+                (graph_iterator_node, merge_answers_node)
             ],
             entry_point=search_internet_node
         )
diff --git a/scrapegraphai/nodes/__init__.py b/scrapegraphai/nodes/__init__.py
index 4804017e..87bc086b 100644
--- a/scrapegraphai/nodes/__init__.py
+++ b/scrapegraphai/nodes/__init__.py
@@ -17,3 +17,5 @@
 from .robots_node import RobotsNode
 from .generate_answer_csv_node import GenerateAnswerCSVNode
 from .generate_answer_pdf_node import GenerateAnswerPDFNode
+from .graph_iterator_node import GraphIteratorNode
+from .merge_answers_node import MergeAnswersNode
\ No newline at end of file
diff --git a/scrapegraphai/nodes/generate_answer_csv_node.py b/scrapegraphai/nodes/generate_answer_csv_node.py
index 6d2b84fc..b068f405 100644
--- a/scrapegraphai/nodes/generate_answer_csv_node.py
+++ b/scrapegraphai/nodes/generate_answer_csv_node.py
@@ -2,7 +2,7 @@
 Module for generating the answer node
 """
 # Imports from standard library
-from typing import List
+from typing import List, Optional
 from tqdm import tqdm
 
 # Imports from Langchain
@@ -39,7 +39,7 @@ class GenerateAnswerCSVNode(BaseNode):
                         updating the state with the generated answer under the 'answer' key.
     """
 
-    def __init__(self, input: str, output: List[str], node_config: dict,
+    def __init__(self, input: str, output: List[str], node_config: Optional[dict] = None,
                  node_name: str = "GenerateAnswer"):
         """
         Initializes the GenerateAnswerNodeCsv with a language model client and a node name.
diff --git a/scrapegraphai/nodes/generate_answer_node.py b/scrapegraphai/nodes/generate_answer_node.py
index df3078ef..49a2d87b 100644
--- a/scrapegraphai/nodes/generate_answer_node.py
+++ b/scrapegraphai/nodes/generate_answer_node.py
@@ -3,7 +3,7 @@
 """
 
 # Imports from standard library
-from typing import List
+from typing import List, Optional
 from tqdm import tqdm
 
 # Imports from Langchain
@@ -33,7 +33,7 @@ class GenerateAnswerNode(BaseNode):
         node_name (str): The unique identifier name for the node, defaulting to "GenerateAnswer".
     """
 
-    def __init__(self, input: str, output: List[str], node_config: dict,
+    def __init__(self, input: str, output: List[str], node_config: Optional[dict]=None,
                  node_name: str = "GenerateAnswer"):
         super().__init__(node_name, "node", input, output, 2, node_config)
         
diff --git a/scrapegraphai/nodes/generate_answer_node_csv.py b/scrapegraphai/nodes/generate_answer_node_csv.py
index 6d2b84fc..b068f405 100644
--- a/scrapegraphai/nodes/generate_answer_node_csv.py
+++ b/scrapegraphai/nodes/generate_answer_node_csv.py
@@ -2,7 +2,7 @@
 Module for generating the answer node
 """
 # Imports from standard library
-from typing import List
+from typing import List, Optional
 from tqdm import tqdm
 
 # Imports from Langchain
@@ -39,7 +39,7 @@ class GenerateAnswerCSVNode(BaseNode):
                         updating the state with the generated answer under the 'answer' key.
     """
 
-    def __init__(self, input: str, output: List[str], node_config: dict,
+    def __init__(self, input: str, output: List[str], node_config: Optional[dict] = None,
                  node_name: str = "GenerateAnswer"):
         """
         Initializes the GenerateAnswerNodeCsv with a language model client and a node name.
diff --git a/scrapegraphai/nodes/generate_answer_pdf_node.py b/scrapegraphai/nodes/generate_answer_pdf_node.py
index b5bfae79..688ff47f 100644
--- a/scrapegraphai/nodes/generate_answer_pdf_node.py
+++ b/scrapegraphai/nodes/generate_answer_pdf_node.py
@@ -2,7 +2,7 @@
 Module for generating the answer node
 """
 # Imports from standard library
-from typing import List
+from typing import List, Optional
 from tqdm import tqdm
 
 # Imports from Langchain
@@ -39,7 +39,7 @@ class GenerateAnswerPDFNode(BaseNode):
                         updating the state with the generated answer under the 'answer' key.
     """
 
-    def __init__(self, input: str, output: List[str], node_config: dict,
+    def __init__(self, input: str, output: List[str], node_config: Optional[dict] = None,
                  node_name: str = "GenerateAnswer"):
         """
         Initializes the GenerateAnswerNodePDF with a language model client and a node name.
diff --git a/scrapegraphai/nodes/generate_scraper_node.py b/scrapegraphai/nodes/generate_scraper_node.py
index 2e1f959e..f0f6469d 100644
--- a/scrapegraphai/nodes/generate_scraper_node.py
+++ b/scrapegraphai/nodes/generate_scraper_node.py
@@ -3,7 +3,7 @@
 """
 
 # Imports from standard library
-from typing import List
+from typing import List, Optional
 from tqdm import tqdm
 
 # Imports from Langchain
@@ -36,8 +36,8 @@ class GenerateScraperNode(BaseNode):
 
     """
 
-    def __init__(self, input: str, output: List[str], node_config: dict,
-                 library: str, website: str, node_name: str = "GenerateAnswer"):
+    def __init__(self, input: str, output: List[str], library: str, website: str,
+                 node_config: Optional[dict]=None, node_name: str = "GenerateAnswer"):
         super().__init__(node_name, "node", input, output, 2, node_config)
 
         self.llm_model = node_config["llm_model"]
diff --git a/scrapegraphai/nodes/get_probable_tags_node.py b/scrapegraphai/nodes/get_probable_tags_node.py
index 11977c62..e970c285 100644
--- a/scrapegraphai/nodes/get_probable_tags_node.py
+++ b/scrapegraphai/nodes/get_probable_tags_node.py
@@ -2,7 +2,7 @@
 GetProbableTagsNode Module
 """
 
-from typing import List
+from typing import List, Optional
 from langchain.output_parsers import CommaSeparatedListOutputParser
 from langchain.prompts import PromptTemplate
 from .base_node import BaseNode
diff --git a/scrapegraphai/nodes/graph_iterator_node.py b/scrapegraphai/nodes/graph_iterator_node.py
new file mode 100644
index 00000000..663adc62
--- /dev/null
+++ b/scrapegraphai/nodes/graph_iterator_node.py
@@ -0,0 +1,79 @@
+"""
+GraphIterator Module
+"""
+
+from typing import List, Optional
+import copy
+from tqdm import tqdm
+from .base_node import BaseNode
+
+
+class GraphIteratorNode(BaseNode):
+    """
+    A node responsible for instantiating and running multiple graph instances in parallel.
+    It creates as many graph instances as the number of elements in the input list.
+
+    Attributes:
+        verbose (bool): A flag indicating whether to show print statements during execution.
+
+    Args:
+        input (str): Boolean expression defining the input keys needed from the state.
+        output (List[str]): List of output keys to be updated in the state.
+        node_config (dict): Additional configuration for the node.
+        node_name (str): The unique identifier name for the node, defaulting to "Parse".
+    """
+
+    def __init__(self, input: str, output: List[str], node_config: Optional[dict]=None, node_name: str = "GraphIterator"):
+        super().__init__(node_name, "node", input, output, 2, node_config)
+
+        self.verbose = False if node_config is None else node_config.get("verbose", False)
+
+    def execute(self,  state: dict) -> dict:
+        """
+        Executes the node's logic to instantiate and run multiple graph instances in parallel.
+
+        Args:
+            state (dict): The current state of the graph. The input keys will be used to fetch
+                            the correct data from the state.
+
+        Returns:
+            dict: The updated state with the output key containing the results of the graph instances.
+
+        Raises:
+            KeyError: If the input keys are not found in the state, indicating that the
+                        necessary information for running the graph instances is missing.
+        """
+
+        if self.verbose:
+            print(f"--- Executing {self.node_name} Node ---")
+
+        # Interpret input keys based on the provided input expression
+        input_keys = self.get_input_keys(state)
+
+        # Fetching data from the state based on the input keys
+        input_data = [state[key] for key in input_keys]
+
+        user_prompt = input_data[0]
+        urls = input_data[1]
+
+        graph_instance = self.node_config.get("graph_instance", None)
+        if graph_instance is None:
+            raise ValueError("Graph instance is required for graph iteration.")
+        
+        # set the prompt and source for each url
+        graph_instance.prompt = user_prompt
+        graphs_instances = []
+        for url in urls:
+            # make a copy of the graph instance
+            copy_graph_instance = copy.copy(graph_instance)
+            copy_graph_instance.source = url
+            graphs_instances.append(copy_graph_instance)
+
+        # run the graph for each url and use tqdm for progress bar
+        graphs_answers = []
+        for graph in tqdm(graphs_instances, desc="Processing Graph Instances", disable=not self.verbose):
+            result = graph.run()
+            graphs_answers.append(result)
+
+        state.update({self.output[0]: graphs_answers})
+        return state
diff --git a/scrapegraphai/nodes/image_to_text_node.py b/scrapegraphai/nodes/image_to_text_node.py
index d9d4f1cc..0e4221c7 100644
--- a/scrapegraphai/nodes/image_to_text_node.py
+++ b/scrapegraphai/nodes/image_to_text_node.py
@@ -2,7 +2,7 @@
 ImageToTextNode Module
 """
 
-from typing import List
+from typing import List, Optional
 from .base_node import BaseNode
 
 
@@ -21,7 +21,7 @@ class ImageToTextNode(BaseNode):
         node_name (str): The unique identifier name for the node, defaulting to "ImageToText".
     """
 
-    def __init__(self, input: str, output: List[str], node_config: dict,
+    def __init__(self, input: str, output: List[str], node_config: Optional[dict]=None,
                  node_name: str = "ImageToText"):
         super().__init__(node_name, "node", input, output, 1, node_config)
 
diff --git a/scrapegraphai/nodes/merge_answers_node.py b/scrapegraphai/nodes/merge_answers_node.py
new file mode 100644
index 00000000..2d6bf560
--- /dev/null
+++ b/scrapegraphai/nodes/merge_answers_node.py
@@ -0,0 +1,100 @@
+"""
+MergeAnswersNode Module
+"""
+
+# Imports from standard library
+from typing import List, Optional
+from tqdm import tqdm
+
+# Imports from Langchain
+from langchain.prompts import PromptTemplate
+from langchain_core.output_parsers import JsonOutputParser
+
+# Imports from the library
+from .base_node import BaseNode
+
+
+class MergeAnswersNode(BaseNode):
+    """
+    A node responsible for merging the answers from multiple graph instances into a single answer.
+
+    Attributes:
+        llm_model: An instance of a language model client, configured for generating answers.
+        verbose (bool): A flag indicating whether to show print statements during execution.
+
+    Args:
+        input (str): Boolean expression defining the input keys needed from the state.
+        output (List[str]): List of output keys to be updated in the state.
+        node_config (dict): Additional configuration for the node.
+        node_name (str): The unique identifier name for the node, defaulting to "GenerateAnswer".
+    """
+
+    def __init__(self, input: str, output: List[str], node_config: Optional[dict] = None,
+                 node_name: str = "MergeAnswers"):
+        super().__init__(node_name, "node", input, output, 2, node_config)
+
+        self.llm_model = node_config["llm_model"]
+        self.verbose = True if node_config is None else node_config.get(
+            "verbose", False)
+
+    def execute(self, state: dict) -> dict:
+        """
+        Executes the node's logic to merge the answers from multiple graph instances into a single answer.
+
+        Args:
+            state (dict): The current state of the graph. The input keys will be used
+                            to fetch the correct data from the state.
+
+        Returns:
+            dict: The updated state with the output key containing the generated answer.
+
+        Raises:
+            KeyError: If the input keys are not found in the state, indicating
+                      that the necessary information for generating an answer is missing.
+        """
+
+        if self.verbose:
+            print(f"--- Executing {self.node_name} Node ---")
+
+        # Interpret input keys based on the provided input expression
+        input_keys = self.get_input_keys(state)
+
+        # Fetching data from the state based on the input keys
+        input_data = [state[key] for key in input_keys]
+
+        user_prompt = input_data[0]
+        answers = input_data[1]
+
+        # merge the answers in one string
+        answers_str = ""
+        for i, answer in enumerate(answers):
+            answers_str += f"CONTENT WEBSITE {i+1}: {answer}\n"
+
+        output_parser = JsonOutputParser()
+        format_instructions = output_parser.get_format_instructions()
+
+        template_merge = """
+        You are a website scraper and you have just scraped some content from multiple websites.\n
+        You are now asked to provide an answer to a USER PROMPT based on the content you have scraped.\n
+        You need to merge the content from the different websites into a single answer without repetitions (if there are any). \n
+        The scraped contents are in a JSON format and you need to merge them based on the context and providing a correct JSON structure.\n
+        OUTPUT INSTRUCTIONS: {format_instructions}\n
+        USER PROMPT: {user_prompt}\n
+        WEBSITE CONTENT: {website_content}
+        """
+
+        prompt_template = PromptTemplate(
+            template=template_merge,
+            input_variables=["user_prompt"],
+            partial_variables={
+                "format_instructions": format_instructions,
+                "website_content": answers_str,
+            },
+        )
+
+        merge_chain = prompt_template | self.llm_model | output_parser
+        answer = merge_chain.invoke({"user_prompt": user_prompt})
+
+        # Update the state with the generated answer
+        state.update({self.output[0]: answer})
+        return state
diff --git a/scrapegraphai/nodes/parse_node.py b/scrapegraphai/nodes/parse_node.py
index b552ece4..34602340 100644
--- a/scrapegraphai/nodes/parse_node.py
+++ b/scrapegraphai/nodes/parse_node.py
@@ -2,7 +2,7 @@
 ParseNode Module
 """
 
-from typing import List
+from typing import List, Optional
 from langchain.text_splitter import RecursiveCharacterTextSplitter
 from langchain_community.document_transformers import Html2TextTransformer
 from .base_node import BaseNode
@@ -26,7 +26,7 @@ class ParseNode(BaseNode):
         node_name (str): The unique identifier name for the node, defaulting to "Parse".
     """
 
-    def __init__(self, input: str, output: List[str], node_config: dict, node_name: str = "Parse"):
+    def __init__(self, input: str, output: List[str], node_config: Optional[dict]=None, node_name: str = "Parse"):
         super().__init__(node_name, "node", input, output, 1, node_config)
 
         self.verbose = True if node_config is None else node_config.get("verbose", False)
diff --git a/scrapegraphai/nodes/rag_node.py b/scrapegraphai/nodes/rag_node.py
index 8c692ec8..d9dbc83b 100644
--- a/scrapegraphai/nodes/rag_node.py
+++ b/scrapegraphai/nodes/rag_node.py
@@ -2,7 +2,7 @@
 RAGNode Module
 """
 
-from typing import List
+from typing import List, Optional
 from langchain.docstore.document import Document
 from langchain.retrievers import ContextualCompressionRetriever
 from langchain.retrievers.document_compressors import EmbeddingsFilter, DocumentCompressorPipeline
@@ -31,7 +31,7 @@ class RAGNode(BaseNode):
         node_name (str): The unique identifier name for the node, defaulting to "Parse".
     """
 
-    def __init__(self, input: str, output: List[str], node_config: dict, node_name: str = "RAG"):
+    def __init__(self, input: str, output: List[str], node_config: Optional[dict]=None, node_name: str = "RAG"):
         super().__init__(node_name, "node", input, output, 2, node_config)
 
         self.llm_model = node_config["llm_model"]
diff --git a/scrapegraphai/nodes/robots_node.py b/scrapegraphai/nodes/robots_node.py
index 8c341183..e56a95d1 100644
--- a/scrapegraphai/nodes/robots_node.py
+++ b/scrapegraphai/nodes/robots_node.py
@@ -2,9 +2,9 @@
 RobotsNode Module
 """
 
-from typing import List
+from typing import List, Optional
 from urllib.parse import urlparse
-from langchain_community.document_loaders import AsyncHtmlLoader
+from langchain_community.document_loaders import AsyncChromiumLoader
 from langchain.prompts import PromptTemplate
 from langchain.output_parsers import CommaSeparatedListOutputParser
 from .base_node import BaseNode
@@ -34,7 +34,7 @@ class RobotsNode(BaseNode):
         node_name (str): The unique identifier name for the node, defaulting to "Robots".
     """
 
-    def __init__(self, input: str, output: List[str],  node_config: dict, force_scraping=True,
+    def __init__(self, input: str, output: List[str],  node_config: Optional[dict]=None, force_scraping=True,
                  node_name: str = "Robots"):
         super().__init__(node_name, "node", input, output, 1)
 
@@ -93,11 +93,11 @@ def execute(self, state: dict) -> dict:
         else:
             parsed_url = urlparse(source)
             base_url = f"{parsed_url.scheme}://{parsed_url.netloc}"
-            loader = AsyncHtmlLoader(f"{base_url}/robots.txt")
+            loader = AsyncChromiumLoader(f"{base_url}/robots.txt")
             document = loader.load()
-            if "ollama" in self.llm_model.model:
-                self.llm_model.model = self.llm_model.model.split("/")[-1]
-                model = self.llm_model.model.split("/")[-1]
+            if "ollama" in self.llm_model.model_name:
+                self.llm_model.model_name = self.llm_model.model_name.split("/")[-1]
+                model = self.llm_model.model_name.split("/")[-1]
 
             else:
                 model = self.llm_model.model_name
diff --git a/scrapegraphai/nodes/search_internet_node.py b/scrapegraphai/nodes/search_internet_node.py
index 01095ef8..f38e16e4 100644
--- a/scrapegraphai/nodes/search_internet_node.py
+++ b/scrapegraphai/nodes/search_internet_node.py
@@ -2,7 +2,7 @@
 SearchInternetNode Module
 """
 
-from typing import List
+from typing import List, Optional
 from langchain.output_parsers import CommaSeparatedListOutputParser
 from langchain.prompts import PromptTemplate
 from ..utils.research_web import search_on_web
@@ -27,12 +27,13 @@ class SearchInternetNode(BaseNode):
         node_name (str): The unique identifier name for the node, defaulting to "SearchInternet".
     """
 
-    def __init__(self, input: str, output: List[str], node_config: dict,
+    def __init__(self, input: str, output: List[str], node_config: Optional[dict]=None,
                  node_name: str = "SearchInternet"):
         super().__init__(node_name, "node", input, output, 1, node_config)
 
         self.llm_model = node_config["llm_model"]
         self.verbose = True if node_config is None else node_config.get("verbose", False)
+        self.max_results = node_config.get("max_results", 3)
 
     def execute(self, state: dict) -> dict:
         """
@@ -85,8 +86,11 @@ def execute(self, state: dict) -> dict:
         if self.verbose:
             print(f"Search Query: {search_query}")
             
-        # TODO: handle multiple URLs
-        answer = search_on_web(query=search_query, max_results=1)[0]
+        answer = search_on_web(query=search_query, max_results=self.max_results)
+
+        if len(answer) == 0:
+            # raise an exception if no answer is found
+            raise ValueError("Zero results found for the search query.")
 
         # Update the state with the generated answer
         state.update({self.output[0]: answer})
diff --git a/scrapegraphai/nodes/search_link_node.py b/scrapegraphai/nodes/search_link_node.py
index 037b862e..5029d0d7 100644
--- a/scrapegraphai/nodes/search_link_node.py
+++ b/scrapegraphai/nodes/search_link_node.py
@@ -3,7 +3,7 @@
 """
 
 # Imports from standard library
-from typing import List
+from typing import List, Optional
 from tqdm import tqdm
 from bs4 import BeautifulSoup
 
@@ -33,7 +33,7 @@ class SearchLinkNode(BaseNode):
         node_name (str): The unique identifier name for the node, defaulting to "GenerateAnswer".
     """
 
-    def __init__(self, input: str, output: List[str], node_config: dict,
+    def __init__(self, input: str, output: List[str], node_config: Optional[dict]=None,
                  node_name: str = "GenerateLinks"):
         super().__init__(node_name, "node", input, output, 1, node_config)
 
diff --git a/scrapegraphai/nodes/text_to_speech_node.py b/scrapegraphai/nodes/text_to_speech_node.py
index 53da713a..80ab998f 100644
--- a/scrapegraphai/nodes/text_to_speech_node.py
+++ b/scrapegraphai/nodes/text_to_speech_node.py
@@ -2,7 +2,7 @@
 TextToSpeechNode Module
 """
 
-from typing import List
+from typing import List, Optional
 from .base_node import BaseNode
 
 
@@ -22,7 +22,7 @@ class TextToSpeechNode(BaseNode):
     """
 
     def __init__(self, input: str, output: List[str],
-                 node_config: dict, node_name: str = "TextToSpeech"):
+                 node_config: Optional[dict]=None, node_name: str = "TextToSpeech"):
         super().__init__(node_name, "node", input, output, 1, node_config)
 
         self.tts_model = node_config["tts_model"]