diff --git a/src/crewai_tools/tools/code_docs_search_tool/README.md b/src/crewai_tools/tools/code_docs_search_tool/README.md
index 6c58a49bc..879461427 100644
--- a/src/crewai_tools/tools/code_docs_search_tool/README.md
+++ b/src/crewai_tools/tools/code_docs_search_tool/README.md
@@ -25,4 +25,32 @@ tool = CodeDocsSearchTool(docs_url='https://docs.example.com/reference')
 Note: Substitute 'https://docs.example.com/reference' with your target documentation URL and 'How to use search tool' with the search query relevant to your needs.
 
 ## Arguments
-- `docs_url`: Optional. Specifies the URL of the code documentation to be searched. Providing this during the tool's initialization focuses the search on the specified documentation content.
\ No newline at end of file
+- `docs_url`: Optional. Specifies the URL of the code documentation to be searched. Providing this during the tool's initialization focuses the search on the specified documentation content.
+
+## Custom model and embeddings
+
+By default, the tool uses OpenAI for both embeddings and summarization. To customize the model, you can use a config dictionary as follows:
+
+```python
+tool = YoutubeVideoSearchTool(
+    config=dict(
+        llm=dict(
+            provider="ollama", # or google, openai, anthropic, llama2, ...
+            config=dict(
+                model="llama2",
+                # temperature=0.5,
+                # top_p=1,
+                # stream=true,
+            ),
+        ),
+        embedder=dict(
+            provider="google",
+            config=dict(
+                model="models/embedding-001",
+                task_type="retrieval_document",
+                # title="Embeddings",
+            ),
+        ),
+    )
+)
+```
diff --git a/src/crewai_tools/tools/csv_search_tool/README.md b/src/crewai_tools/tools/csv_search_tool/README.md
index 66dd46cc0..c0bcbae3d 100644
--- a/src/crewai_tools/tools/csv_search_tool/README.md
+++ b/src/crewai_tools/tools/csv_search_tool/README.md
@@ -28,4 +28,32 @@ tool = CSVSearchTool()
 
 ## Arguments
 
-- `csv` : The path to the CSV file you want to search. This is a mandatory argument if the tool was initialized without a specific CSV file; otherwise, it is optional.
\ No newline at end of file
+- `csv` : The path to the CSV file you want to search. This is a mandatory argument if the tool was initialized without a specific CSV file; otherwise, it is optional.
+
+## Custom model and embeddings
+
+By default, the tool uses OpenAI for both embeddings and summarization. To customize the model, you can use a config dictionary as follows:
+
+```python
+tool = CSVSearchTool(
+    config=dict(
+        llm=dict(
+            provider="ollama", # or google, openai, anthropic, llama2, ...
+            config=dict(
+                model="llama2",
+                # temperature=0.5,
+                # top_p=1,
+                # stream=true,
+            ),
+        ),
+        embedder=dict(
+            provider="google",
+            config=dict(
+                model="models/embedding-001",
+                task_type="retrieval_document",
+                # title="Embeddings",
+            ),
+        ),
+    )
+)
+```
diff --git a/src/crewai_tools/tools/directory_read_tool/README.md b/src/crewai_tools/tools/directory_read_tool/README.md
index b1bed2e6b..9305fd1a3 100644
--- a/src/crewai_tools/tools/directory_read_tool/README.md
+++ b/src/crewai_tools/tools/directory_read_tool/README.md
@@ -37,4 +37,4 @@ The DirectoryReadTool requires minimal configuration for use. The essential argu
 The DirectoryReadTool provides a user-friendly and efficient way to list directory contents, making it an invaluable tool for managing and inspecting directory structures.
 ```
 
-This revised documentation for the DirectoryReadTool maintains the structure and content requirements as outlined, with adjustments made for clarity, consistency, and adherence to the high-quality standards exemplified in the provided documentation example.
\ No newline at end of file
+This revised documentation for the DirectoryReadTool maintains the structure and content requirements as outlined, with adjustments made for clarity, consistency, and adherence to the high-quality standards exemplified in the provided documentation example.
diff --git a/src/crewai_tools/tools/directory_search_tool/README.md b/src/crewai_tools/tools/directory_search_tool/README.md
index acc971807..b39e9fe96 100644
--- a/src/crewai_tools/tools/directory_search_tool/README.md
+++ b/src/crewai_tools/tools/directory_search_tool/README.md
@@ -24,4 +24,32 @@ tool = DirectorySearchTool(directory='/path/to/directory')
 ```
 
 ## Arguments
-- `directory` : This string argument specifies the directory within which to search. It is mandatory if the tool has not been initialized with a directory; otherwise, the tool will only search within the initialized directory.
\ No newline at end of file
+- `directory` : This string argument specifies the directory within which to search. It is mandatory if the tool has not been initialized with a directory; otherwise, the tool will only search within the initialized directory.
+
+## Custom model and embeddings
+
+By default, the tool uses OpenAI for both embeddings and summarization. To customize the model, you can use a config dictionary as follows:
+
+```python
+tool = DirectorySearchTool(
+    config=dict(
+        llm=dict(
+            provider="ollama", # or google, openai, anthropic, llama2, ...
+            config=dict(
+                model="llama2",
+                # temperature=0.5,
+                # top_p=1,
+                # stream=true,
+            ),
+        ),
+        embedder=dict(
+            provider="google",
+            config=dict(
+                model="models/embedding-001",
+                task_type="retrieval_document",
+                # title="Embeddings",
+            ),
+        ),
+    )
+)
+```
diff --git a/src/crewai_tools/tools/docx_search_tool/README.md b/src/crewai_tools/tools/docx_search_tool/README.md
index 033c72226..c99a4984e 100644
--- a/src/crewai_tools/tools/docx_search_tool/README.md
+++ b/src/crewai_tools/tools/docx_search_tool/README.md
@@ -27,3 +27,31 @@ tool = DOCXSearchTool(docx='path/to/your/document.docx')
 
 ## Arguments
 - `docx`: An optional file path to a specific DOCX document you wish to search. If not provided during initialization, the tool allows for later specification of any DOCX file's content path for searching.
+
+## Custom model and embeddings
+
+By default, the tool uses OpenAI for both embeddings and summarization. To customize the model, you can use a config dictionary as follows:
+
+```python
+tool = DOCXSearchTool(
+    config=dict(
+        llm=dict(
+            provider="ollama", # or google, openai, anthropic, llama2, ...
+            config=dict(
+                model="llama2",
+                # temperature=0.5,
+                # top_p=1,
+                # stream=true,
+            ),
+        ),
+        embedder=dict(
+            provider="google",
+            config=dict(
+                model="models/embedding-001",
+                task_type="retrieval_document",
+                # title="Embeddings",
+            ),
+        ),
+    )
+)
+```
diff --git a/src/crewai_tools/tools/github_search_tool/README.md b/src/crewai_tools/tools/github_search_tool/README.md
index 0ed6faeef..220e0aeb8 100644
--- a/src/crewai_tools/tools/github_search_tool/README.md
+++ b/src/crewai_tools/tools/github_search_tool/README.md
@@ -34,3 +34,31 @@ tool = GitHubSearchTool(
 ## Arguments
 - `github_repo` : The URL of the GitHub repository where the search will be conducted. This is a mandatory field and specifies the target repository for your search.
 - `content_types` : Specifies the types of content to include in your search. You must provide a list of content types from the following options: `code` for searching within the code, `repo` for searching within the repository's general information, `pr` for searching within pull requests, and `issue` for searching within issues. This field is mandatory and allows tailoring the search to specific content types within the GitHub repository.
+
+## Custom model and embeddings
+
+By default, the tool uses OpenAI for both embeddings and summarization. To customize the model, you can use a config dictionary as follows:
+
+```python
+tool = GitHubSearchTool(
+    config=dict(
+        llm=dict(
+            provider="ollama", # or google, openai, anthropic, llama2, ...
+            config=dict(
+                model="llama2",
+                # temperature=0.5,
+                # top_p=1,
+                # stream=true,
+            ),
+        ),
+        embedder=dict(
+            provider="google",
+            config=dict(
+                model="models/embedding-001",
+                task_type="retrieval_document",
+                # title="Embeddings",
+            ),
+        ),
+    )
+)
+```
diff --git a/src/crewai_tools/tools/json_search_tool/README.md b/src/crewai_tools/tools/json_search_tool/README.md
index df43cc4a6..51510932e 100644
--- a/src/crewai_tools/tools/json_search_tool/README.md
+++ b/src/crewai_tools/tools/json_search_tool/README.md
@@ -24,4 +24,32 @@ tool = JSONSearchTool(json_path='./path/to/your/file.json')
 ```
 
 ## Arguments
-- `json_path` (str): An optional argument that defines the path to the JSON file to be searched. This parameter is only necessary if the tool is initialized without a specific JSON path. Providing this argument restricts the search to the specified JSON file.
\ No newline at end of file
+- `json_path` (str): An optional argument that defines the path to the JSON file to be searched. This parameter is only necessary if the tool is initialized without a specific JSON path. Providing this argument restricts the search to the specified JSON file.
+
+## Custom model and embeddings
+
+By default, the tool uses OpenAI for both embeddings and summarization. To customize the model, you can use a config dictionary as follows:
+
+```python
+tool = JSONSearchTool(
+    config=dict(
+        llm=dict(
+            provider="ollama", # or google, openai, anthropic, llama2, ...
+            config=dict(
+                model="llama2",
+                # temperature=0.5,
+                # top_p=1,
+                # stream=true,
+            ),
+        ),
+        embedder=dict(
+            provider="google",
+            config=dict(
+                model="models/embedding-001",
+                task_type="retrieval_document",
+                # title="Embeddings",
+            ),
+        ),
+    )
+)
+```
diff --git a/src/crewai_tools/tools/mdx_seach_tool/README.md b/src/crewai_tools/tools/mdx_seach_tool/README.md
index 751988c9b..71b58131a 100644
--- a/src/crewai_tools/tools/mdx_seach_tool/README.md
+++ b/src/crewai_tools/tools/mdx_seach_tool/README.md
@@ -26,4 +26,32 @@ tool = MDXSearchTool(mdx='path/to/your/document.mdx')
 ```
 
 ## Arguments
-- mdx: **Optional** The MDX path for the search. Can be provided at initialization
\ No newline at end of file
+- mdx: **Optional** The MDX path for the search. Can be provided at initialization
+
+## Custom model and embeddings
+
+By default, the tool uses OpenAI for both embeddings and summarization. To customize the model, you can use a config dictionary as follows:
+
+```python
+tool = MDXSearchTool(
+    config=dict(
+        llm=dict(
+            provider="ollama", # or google, openai, anthropic, llama2, ...
+            config=dict(
+                model="llama2",
+                # temperature=0.5,
+                # top_p=1,
+                # stream=true,
+            ),
+        ),
+        embedder=dict(
+            provider="google",
+            config=dict(
+                model="models/embedding-001",
+                task_type="retrieval_document",
+                # title="Embeddings",
+            ),
+        ),
+    )
+)
+```
diff --git a/src/crewai_tools/tools/pdf_search_tool/README.md b/src/crewai_tools/tools/pdf_search_tool/README.md
index c927d1bcb..a4bf5d8ed 100644
--- a/src/crewai_tools/tools/pdf_search_tool/README.md
+++ b/src/crewai_tools/tools/pdf_search_tool/README.md
@@ -27,3 +27,31 @@ tool = PDFSearchTool(pdf='path/to/your/document.pdf')
 
 ## Arguments
 - `pdf`: **Optinal** The PDF path for the search. Can be provided at initialization or within the `run` method's arguments. If provided at initialization, the tool confines its search to the specified document.
+
+## Custom model and embeddings
+
+By default, the tool uses OpenAI for both embeddings and summarization. To customize the model, you can use a config dictionary as follows:
+
+```python
+tool = PDFSearchTool(
+    config=dict(
+        llm=dict(
+            provider="ollama", # or google, openai, anthropic, llama2, ...
+            config=dict(
+                model="llama2",
+                # temperature=0.5,
+                # top_p=1,
+                # stream=true,
+            ),
+        ),
+        embedder=dict(
+            provider="google",
+            config=dict(
+                model="models/embedding-001",
+                task_type="retrieval_document",
+                # title="Embeddings",
+            ),
+        ),
+    )
+)
+```
diff --git a/src/crewai_tools/tools/pg_seach_tool/README.md b/src/crewai_tools/tools/pg_seach_tool/README.md
index a8bae491f..e462be803 100644
--- a/src/crewai_tools/tools/pg_seach_tool/README.md
+++ b/src/crewai_tools/tools/pg_seach_tool/README.md
@@ -25,4 +25,32 @@ tool = PGSearchTool(db_uri='postgresql://user:password@localhost:5432/mydatabase
 The PGSearchTool requires the following arguments for its operation:
 
 - `db_uri`: A string representing the URI of the PostgreSQL database to be queried. This argument is mandatory and must include the necessary authentication details and the location of the database.
-- `table_name`: A string specifying the name of the table within the database on which the semantic search will be performed. This argument is mandatory.
\ No newline at end of file
+- `table_name`: A string specifying the name of the table within the database on which the semantic search will be performed. This argument is mandatory.
+
+## Custom model and embeddings
+
+By default, the tool uses OpenAI for both embeddings and summarization. To customize the model, you can use a config dictionary as follows:
+
+```python
+tool = PGSearchTool(
+    config=dict(
+        llm=dict(
+            provider="ollama", # or google, openai, anthropic, llama2, ...
+            config=dict(
+                model="llama2",
+                # temperature=0.5,
+                # top_p=1,
+                # stream=true,
+            ),
+        ),
+        embedder=dict(
+            provider="google",
+            config=dict(
+                model="models/embedding-001",
+                task_type="retrieval_document",
+                # title="Embeddings",
+            ),
+        ),
+    )
+)
+```
diff --git a/src/crewai_tools/tools/txt_search_tool/README.md b/src/crewai_tools/tools/txt_search_tool/README.md
index 720a47d35..aaf68c291 100644
--- a/src/crewai_tools/tools/txt_search_tool/README.md
+++ b/src/crewai_tools/tools/txt_search_tool/README.md
@@ -29,3 +29,31 @@ tool = TXTSearchTool(txt='path/to/text/file.txt')
 
 ## Arguments
 - `txt` (str): **Optinal**. The path to the text file you want to search. This argument is only required if the tool was not initialized with a specific text file; otherwise, the search will be conducted within the initially provided text file.
+
+## Custom model and embeddings
+
+By default, the tool uses OpenAI for both embeddings and summarization. To customize the model, you can use a config dictionary as follows:
+
+```python
+tool = TXTSearchTool(
+    config=dict(
+        llm=dict(
+            provider="ollama", # or google, openai, anthropic, llama2, ...
+            config=dict(
+                model="llama2",
+                # temperature=0.5,
+                # top_p=1,
+                # stream=true,
+            ),
+        ),
+        embedder=dict(
+            provider="google",
+            config=dict(
+                model="models/embedding-001",
+                task_type="retrieval_document",
+                # title="Embeddings",
+            ),
+        ),
+    )
+)
+```
diff --git a/src/crewai_tools/tools/website_search/README.md b/src/crewai_tools/tools/website_search/README.md
index 306caae85..a86c75b45 100644
--- a/src/crewai_tools/tools/website_search/README.md
+++ b/src/crewai_tools/tools/website_search/README.md
@@ -26,4 +26,32 @@ tool = WebsiteSearchTool(website='https://example.com')
 ```
 
 ## Arguments
-- `website` : An optional argument that specifies the valid website URL to perform the search on. This becomes necessary if the tool is initialized without a specific website. In the `WebsiteSearchToolSchema`, this argument is mandatory. However, in the `FixedWebsiteSearchToolSchema`, it becomes optional if a website is provided during the tool's initialization, as it will then only search within the predefined website's content.
\ No newline at end of file
+- `website` : An optional argument that specifies the valid website URL to perform the search on. This becomes necessary if the tool is initialized without a specific website. In the `WebsiteSearchToolSchema`, this argument is mandatory. However, in the `FixedWebsiteSearchToolSchema`, it becomes optional if a website is provided during the tool's initialization, as it will then only search within the predefined website's content.
+
+## Custom model and embeddings
+
+By default, the tool uses OpenAI for both embeddings and summarization. To customize the model, you can use a config dictionary as follows:
+
+```python
+tool = WebsiteSearchTool(
+    config=dict(
+        llm=dict(
+            provider="ollama", # or google, openai, anthropic, llama2, ...
+            config=dict(
+                model="llama2",
+                # temperature=0.5,
+                # top_p=1,
+                # stream=true,
+            ),
+        ),
+        embedder=dict(
+            provider="google",
+            config=dict(
+                model="models/embedding-001",
+                task_type="retrieval_document",
+                # title="Embeddings",
+            ),
+        ),
+    )
+)
+```
diff --git a/src/crewai_tools/tools/xml_search_tool/README.md b/src/crewai_tools/tools/xml_search_tool/README.md
index 416cb2c67..a019d9e15 100644
--- a/src/crewai_tools/tools/xml_search_tool/README.md
+++ b/src/crewai_tools/tools/xml_search_tool/README.md
@@ -27,3 +27,31 @@ tool = XMLSearchTool(xml='path/to/your/xmlfile.xml')
 
 ## Arguments
 - `xml`: This is the path to the XML file you wish to search. It is an optional parameter during the tool's initialization but must be provided either at initialization or as part of the `run` method's arguments to execute a search.
+
+## Custom model and embeddings
+
+By default, the tool uses OpenAI for both embeddings and summarization. To customize the model, you can use a config dictionary as follows:
+
+```python
+tool = XMLSearchTool(
+    config=dict(
+        llm=dict(
+            provider="ollama", # or google, openai, anthropic, llama2, ...
+            config=dict(
+                model="llama2",
+                # temperature=0.5,
+                # top_p=1,
+                # stream=true,
+            ),
+        ),
+        embedder=dict(
+            provider="google",
+            config=dict(
+                model="models/embedding-001",
+                task_type="retrieval_document",
+                # title="Embeddings",
+            ),
+        ),
+    )
+)
+```
diff --git a/src/crewai_tools/tools/youtube_channel_search_tool/README.md b/src/crewai_tools/tools/youtube_channel_search_tool/README.md
index 95f34721e..090684f48 100644
--- a/src/crewai_tools/tools/youtube_channel_search_tool/README.md
+++ b/src/crewai_tools/tools/youtube_channel_search_tool/README.md
@@ -27,3 +27,31 @@ tool = YoutubeChannelSearchTool(youtube_channel_handle='@exampleChannel')
 
 ## Arguments
 - `youtube_channel_handle` : A mandatory string representing the Youtube channel handle. This parameter is crucial for initializing the tool to specify the channel you want to search within. The tool is designed to only search within the content of the provided channel handle.
+
+## Custom model and embeddings
+
+By default, the tool uses OpenAI for both embeddings and summarization. To customize the model, you can use a config dictionary as follows:
+
+```python
+tool = YoutubeChannelSearchTool(
+    config=dict(
+        llm=dict(
+            provider="ollama", # or google, openai, anthropic, llama2, ...
+            config=dict(
+                model="llama2",
+                # temperature=0.5,
+                # top_p=1,
+                # stream=true,
+            ),
+        ),
+        embedder=dict(
+            provider="google",
+            config=dict(
+                model="models/embedding-001",
+                task_type="retrieval_document",
+                # title="Embeddings",
+            ),
+        ),
+    )
+)
+```
diff --git a/src/crewai_tools/tools/youtube_video_search_tool/README.md b/src/crewai_tools/tools/youtube_video_search_tool/README.md
index 55faa0002..8b84613b4 100644
--- a/src/crewai_tools/tools/youtube_video_search_tool/README.md
+++ b/src/crewai_tools/tools/youtube_video_search_tool/README.md
@@ -29,4 +29,32 @@ tool = YoutubeVideoSearchTool(youtube_video_url='https://youtube.com/watch?v=exa
 
 The YoutubeVideoSearchTool accepts the following initialization arguments:
 
-- `youtube_video_url`: An optional argument at initialization but required if targeting a specific Youtube video. It specifies the Youtube video URL path you want to search within.
\ No newline at end of file
+- `youtube_video_url`: An optional argument at initialization but required if targeting a specific Youtube video. It specifies the Youtube video URL path you want to search within.
+
+## Custom model and embeddings
+
+By default, the tool uses OpenAI for both embeddings and summarization. To customize the model, you can use a config dictionary as follows:
+
+```python
+tool = YoutubeVideoSearchTool(
+    config=dict(
+        llm=dict(
+            provider="ollama", # or google, openai, anthropic, llama2, ...
+            config=dict(
+                model="llama2",
+                # temperature=0.5,
+                # top_p=1,
+                # stream=true,
+            ),
+        ),
+        embedder=dict(
+            provider="google",
+            config=dict(
+                model="models/embedding-001",
+                task_type="retrieval_document",
+                # title="Embeddings",
+            ),
+        ),
+    )
+)
+```