diff --git a/.gitignore b/.gitignore
index 2aaa1342a..d6333ae4a 100644
--- a/.gitignore
+++ b/.gitignore
@@ -13,4 +13,5 @@ db/
 test.py
 rc-tests/*
 *.pkl
-temp/*
\ No newline at end of file
+temp/*
+.vscode/*
\ No newline at end of file
diff --git a/README.md b/README.md
index a59fe544b..01e08821e 100644
--- a/README.md
+++ b/README.md
@@ -197,46 +197,6 @@ Please refer to the [Connect crewAI to LLMs](https://docs.crewai.com/how-to/LLM-
 **CrewAI's Advantage**: CrewAI is built with production in mind. It offers the flexibility of Autogen's conversational agents and the structured process approach of ChatDev, but without the rigidity. CrewAI's processes are designed to be dynamic and adaptable, fitting seamlessly into both development and production workflows.
 
 
-## Training
-
-The training feature in CrewAI allows you to train your AI agents using the command-line interface (CLI). By running the command `crewai train -n <n_iterations>`, you can specify the number of iterations for the training process.
-
-During training, CrewAI utilizes techniques to optimize the performance of your agents along with human feedback. This helps the agents improve their understanding, decision-making, and problem-solving abilities.
-
-To use the training feature, follow these steps:
-
-1. Open your terminal or command prompt.
-2. Navigate to the directory where your CrewAI project is located.
-3. Run the following command:
-
-```shell
-crewai train -n <n_iterations>
-```
-
-Replace `<n_iterations>` with the desired number of training iterations. This determines how many times the agents will go through the training process.
-
-Remember to also replace the placeholder inputs with the actual values you want to use on the main.py file in the `train` function.
-
-```python
-def train():
-    """
-    Train the crew for a given number of iterations.
-    """
-    inputs = {"topic": "AI LLMs"}
-    try:
-        ProjectCreationCrew().crew().train(n_iterations=int(sys.argv[1]), inputs=inputs)
-    ...
-```
-
-It is important to note that the training process may take some time, depending on the complexity of your agents and will also require your feedback on each iteration.
-
-Once the training is complete, your agents will be equipped with enhanced capabilities and knowledge, ready to tackle complex tasks and provide more consistent and valuable insights.
-
-Remember to regularly update and retrain your agents to ensure they stay up-to-date with the latest information and advancements in the field.
-
-Happy training with CrewAI!
-
-
 ## Contribution
 
 CrewAI is open-source and we welcome contributions. If you're looking to contribute, please:
diff --git a/docs/core-concepts/Agents.md b/docs/core-concepts/Agents.md
index 862c8e061..bb054f8b9 100644
--- a/docs/core-concepts/Agents.md
+++ b/docs/core-concepts/Agents.md
@@ -16,24 +16,24 @@ description: What are crewAI Agents and how to use them.
 
 ## Agent Attributes
 
-| Attribute                  | Description                                                                                                                                                                                                                                    |
-| :------------------------- | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| **Role**                   | Defines the agent's function within the crew. It determines the kind of tasks the agent is best suited for.                                                                                                                                    |
-| **Goal**                   | The individual objective that the agent aims to achieve. It guides the agent's decision-making process.                                                                                                                                        |
-| **Backstory**              | Provides context to the agent's role and goal, enriching the interaction and collaboration dynamics.                                                                                                                                           |
-| **LLM** *(optional)*       | Represents the language model that will run the agent. It dynamically fetches the model name from the `OPENAI_MODEL_NAME` environment variable, defaulting to "gpt-4" if not specified.                                                         |
-| **Tools** *(optional)*     | Set of capabilities or functions that the agent can use to perform tasks. Expected to be instances of custom classes compatible with the agent's execution environment. Tools are initialized with a default value of an empty list.             |
-| **Function Calling LLM** *(optional)* | Specifies the language model that will handle the tool calling for this agent, overriding the crew function calling LLM if passed. Default is `None`.                                                                                          |
-| **Max Iter** *(optional)*  | `max_iter` is the maximum number of iterations the agent can perform before being forced to give its best answer. Default is `25`.                                                                                                                           |
-| **Max RPM** *(optional)*   | `max_rpm` is Tte maximum number of requests per minute the agent can perform to avoid rate limits. It's optional and can be left unspecified, with a default value of `None`.                                                                               |
-| **Max Execution Time** *(optional)*   | `max_execution_time` is the Maximum execution time for an agent to execute a task. It's optional and can be left unspecified, with a default value of `None`, meaning no max execution time.                                                                     |
-| **Verbose** *(optional)*   | Setting this to `True` configures the internal logger to provide detailed execution logs, aiding in debugging and monitoring. Default is `False`.                                                                                              |
-| **Allow Delegation** *(optional)* | Agents can delegate tasks or questions to one another, ensuring that each task is handled by the most suitable agent. Default is `True`.                                                                                                       |
-| **Step Callback** *(optional)* | A function that is called after each step of the agent. This can be used to log the agent's actions or to perform other operations. It will overwrite the crew `step_callback`.                                                               |
-| **Cache** *(optional)*     | Indicates if the agent should use a cache for tool usage. Default is `True`.                                                                                                                                                                  |
-| **System Template** *(optional)*     | Specifies the system format for the agent. Default is `None`.                                                                                                                                                                  |
-| **Prompt Template** *(optional)*     | Specifies the prompt format for the agent. Default is `None`.                                                                                                                                                                  |
-| **Response Template** *(optional)*     | Specifies the response format for the agent. Default is `None`.                                                                                                                                                                  |
+| Attribute                  | Parameter  | Description                                                                                                                                                                                                                                    |
+| :------------------------- | :---- | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| **Role**                   | `role`  | Defines the agent's function within the crew. It determines the kind of tasks the agent is best suited for.                                                                                                                                    |
+| **Goal**                   | `goal`  | The individual objective that the agent aims to achieve. It guides the agent's decision-making process.                                                                                                                                        |
+| **Backstory**              | `backstory`  | Provides context to the agent's role and goal, enriching the interaction and collaboration dynamics.                                                                                                                                           |
+| **LLM** *(optional)*       | `llm`  | Represents the language model that will run the agent. It dynamically fetches the model name from the `OPENAI_MODEL_NAME` environment variable, defaulting to "gpt-4" if not specified.                                                         |
+| **Tools** *(optional)*     | `tools`  | Set of capabilities or functions that the agent can use to perform tasks. Expected to be instances of custom classes compatible with the agent's execution environment. Tools are initialized with a default value of an empty list.             |
+| **Function Calling LLM** *(optional)* | `function_calling_llm`  | Specifies the language model that will handle the tool calling for this agent, overriding the crew function calling LLM if passed. Default is `None`.                                                                                          |
+| **Max Iter** *(optional)*  | `max_iter` | Max Iter is the maximum number of iterations the agent can perform before being forced to give its best answer. Default is `25`.                                                                                                                           |
+| **Max RPM** *(optional)*   | `max_rpm`  | Max RPM is the maximum number of requests per minute the agent can perform to avoid rate limits. It's optional and can be left unspecified, with a default value of `None`.                                                                               |
+| **Max Execution Time** *(optional)*   | `max_execution_time`  | Max Execution Time is the Maximum execution time for an agent to execute a task. It's optional and can be left unspecified, with a default value of `None`, meaning no max execution time.                                                                     |
+| **Verbose** *(optional)*   | `verbose`  | Setting this to `True` configures the internal logger to provide detailed execution logs, aiding in debugging and monitoring. Default is `False`.                                                                                              |
+| **Allow Delegation** *(optional)* | `allow_delegation`  | Agents can delegate tasks or questions to one another, ensuring that each task is handled by the most suitable agent. Default is `True`.                                                                                                       |
+| **Step Callback** *(optional)* | `step_callback`  | A function that is called after each step of the agent. This can be used to log the agent's actions or to perform other operations. It will overwrite the crew `step_callback`.                                                               |
+| **Cache** *(optional)*     | `cache`  | Indicates if the agent should use a cache for tool usage. Default is `True`.                                                                                                                                                                  |
+| **System Template** *(optional)*     | `system_template`  | Specifies the system format for the agent. Default is `None`.                                                                                                                                                                  |
+| **Prompt Template** *(optional)*     | `prompt_template`  | Specifies the prompt format for the agent. Default is `None`.                                                                                                                                                                  |
+| **Response Template** *(optional)*     | `response_template`  | Specifies the response format for the agent. Default is `None`.                                                                                                                                                                  |
 
 ## Creating an Agent
 
diff --git a/docs/core-concepts/Crews.md b/docs/core-concepts/Crews.md
index 3342024b8..dec6adfc8 100644
--- a/docs/core-concepts/Crews.md
+++ b/docs/core-concepts/Crews.md
@@ -8,29 +8,29 @@ A crew in crewAI represents a collaborative group of agents working together to
 
 ## Crew Attributes
 
-| Attribute                   | Description                                                  |
-| :-------------------------- | :----------------------------------------------------------- |
-| **Tasks**                   | A list of tasks assigned to the crew.                        |
-| **Agents**                  | A list of agents that are part of the crew.                  |
-| **Process** *(optional)*    | The process flow (e.g., sequential, hierarchical) the crew follows. |
-| **Verbose** *(optional)*    | The verbosity level for logging during execution.            |
-| **Manager LLM** *(optional)*| The language model used by the manager agent in a hierarchical process. **Required when using a hierarchical process.** |
-| **Function Calling LLM** *(optional)* | If passed, the crew will use this LLM to do function calling for tools for all agents in the crew. Each agent can have its own LLM, which overrides the crew's LLM for function calling. |
-| **Config** *(optional)*     | Optional configuration settings for the crew, in `Json` or `Dict[str, Any]` format. |
-| **Max RPM** *(optional)*    | Maximum requests per minute the crew adheres to during execution. |
-| **Language**  *(optional)*  | Language used for the crew, defaults to English.             |
-| **Language File** *(optional)* | Path to the language file to be used for the crew.          |
-| **Memory** *(optional)*     | Utilized for storing execution memories (short-term, long-term, entity memory). |
-| **Cache** *(optional)*      | Specifies whether to use a cache for storing the results of tools' execution. |
-| **Embedder** *(optional)*   | Configuration for the embedder to be used by the crew. Mostly used by memory for now.       |
-| **Full Output** *(optional)*| Whether the crew should return the full output with all tasks outputs or just the final output. |
-| **Step Callback** *(optional)* | A function that is called after each step of every agent. This can be used to log the agent's actions or to perform other operations; it won't override the agent-specific `step_callback`. |
-| **Task Callback** *(optional)* | A function that is called after the completion of each task. Useful for monitoring or additional operations post-task execution. |
-| **Share Crew** *(optional)* | Whether you want to share the complete crew information and execution with the crewAI team to make the library better, and allow us to train models. |
-| **Output Log File** *(optional)* | Whether you want to have a file with the complete crew output and execution. You can set it using True and it will default to the folder you are currently in and it will be called logs.txt or passing a string with the full path and name of the file. |
-| **Manager Agent** *(optional)* | `manager` sets a custom agent that will be used as a manager. |
-| **Manager Callbacks** *(optional)* | `manager_callbacks` takes a list of callback handlers to be executed by the manager agent when a hierarchical process is used. |
-| **Prompt File** *(optional)* | Path to the prompt JSON file to be used for the crew. |
+| Attribute                   | Parameters          | Description                                                                                              |
+| :-------------------------- | :------------------ | :------------------------------------------------------------------------------------------------------- |
+| **Tasks**                   | `tasks`               | A list of tasks assigned to the crew.                                                                    |
+| **Agents**                  | `agents`              | A list of agents that are part of the crew.                                                              |
+| **Process** *(optional)*    | `process`             | The process flow (e.g., sequential, hierarchical) the crew follows.                                      |
+| **Verbose** *(optional)*    | `verbose`             | The verbosity level for logging during execution.                                                        |
+| **Manager LLM** *(optional)*| `manager_llm`         | The language model used by the manager agent in a hierarchical process. **Required when using a hierarchical process.** |
+| **Function Calling LLM** *(optional)* | `function_calling_llm` | If passed, the crew will use this LLM to do function calling for tools for all agents in the crew. Each agent can have its own LLM, which overrides the crew's LLM for function calling. |
+| **Config** *(optional)*     | `config`              | Optional configuration settings for the crew, in `Json` or `Dict[str, Any]` format.                       |
+| **Max RPM** *(optional)*    | `max_rpm`             | Maximum requests per minute the crew adheres to during execution.                                         |
+| **Language**  *(optional)*  | `language`            | Language used for the crew, defaults to English.                                                          |
+| **Language File** *(optional)* | `language_file`       | Path to the language file to be used for the crew.                                                        |
+| **Memory** *(optional)*     | `memory`              | Utilized for storing execution memories (short-term, long-term, entity memory).                           |
+| **Cache** *(optional)*      | `cache`               | Specifies whether to use a cache for storing the results of tools' execution.                             |
+| **Embedder** *(optional)*   | `embedder`            | Configuration for the embedder to be used by the crew. Mostly used by memory for now.                     |
+| **Full Output** *(optional)*| `full_output`         | Whether the crew should return the full output with all tasks outputs or just the final output.           |
+| **Step Callback** *(optional)* | `step_callback`       | A function that is called after each step of every agent. This can be used to log the agent's actions or to perform other operations; it won't override the agent-specific `step_callback`. |
+| **Task Callback** *(optional)* | `task_callback`       | A function that is called after the completion of each task. Useful for monitoring or additional operations post-task execution. |
+| **Share Crew** *(optional)* | `share_crew`          | Whether you want to share the complete crew information and execution with the crewAI team to make the library better, and allow us to train models. |
+| **Output Log File** *(optional)* | `output_log_file`    | Whether you want to have a file with the complete crew output and execution. You can set it using True and it will default to the folder you are currently in and it will be called logs.txt or passing a string with the full path and name of the file. |
+| **Manager Agent** *(optional)* | `manager_agent`      | `manager` sets a custom agent that will be used as a manager.                                             |
+| **Manager Callbacks** *(optional)* | `manager_callbacks` | `manager_callbacks` takes a list of callback handlers to be executed by the manager agent when a hierarchical process is used. |
+| **Prompt File** *(optional)* | `prompt_file`         | Path to the prompt JSON file to be used for the crew.                                                     |
 
 !!! note "Crew Max RPM"
     The `max_rpm` attribute sets the maximum number of requests per minute the crew can perform to avoid rate limits and will override individual agents' `max_rpm` settings if you set it.
diff --git a/docs/core-concepts/Tasks.md b/docs/core-concepts/Tasks.md
index bd6460f94..b3ea030c4 100644
--- a/docs/core-concepts/Tasks.md
+++ b/docs/core-concepts/Tasks.md
@@ -11,20 +11,20 @@ Tasks within crewAI can be collaborative, requiring multiple agents to work toge
 
 ## Task Attributes
 
-| Attribute              | Description                                                                                   |
-| :----------------------| :-------------------------------------------------------------------------------------------- |
-| **Description**        | A clear, concise statement of what the task entails.                                          |
-| **Agent**              | The agent responsible for the task, assigned either directly or by the crew's process.        |
-| **Expected Output**    | A detailed description of what the task's completion looks like.                              |
-| **Tools** *(optional)* | The functions or capabilities the agent can utilize to perform the task.                      |
-| **Async Execution** *(optional)* | If set, the task executes asynchronously, allowing progression without waiting for completion.|
-| **Context**  *(optional)* | Specifies tasks whose outputs are used as context for this task.                              |
-| **Config** *(optional)* | Additional configuration details for the agent executing the task, allowing further customization. |
-| **Output JSON**  *(optional)* | Outputs a JSON object, requiring an OpenAI client. Only one output format can be set.         |
-| **Output Pydantic**  *(optional)* | Outputs a Pydantic model object, requiring an OpenAI client. Only one output format can be set. |
-| **Output File**  *(optional)* | Saves the task output to a file. If used with `Output JSON` or `Output Pydantic`, specifies how the output is saved. |
-| **Callback**  *(optional)* | A Python callable that is executed with the task's output upon completion.                    |
-| **Human Input** *(optional)* | Indicates if the task requires human feedback at the end, useful for tasks needing human oversight. |
+| Attribute              | Parameters           | Description                                                                                   |
+| :----------------------| :------------------- | :-------------------------------------------------------------------------------------------- |
+| **Description**        | `description`          | A clear, concise statement of what the task entails.                                          |
+| **Agent**              | `agent`                | The agent responsible for the task, assigned either directly or by the crew's process.        |
+| **Expected Output**    | `expected_output`      | A detailed description of what the task's completion looks like.                              |
+| **Tools** *(optional)* | `tools`                | The functions or capabilities the agent can utilize to perform the task.                      |
+| **Async Execution** *(optional)* | `async_execution`      | If set, the task executes asynchronously, allowing progression without waiting for completion.|
+| **Context**  *(optional)* | `context`              | Specifies tasks whose outputs are used as context for this task.                              |
+| **Config** *(optional)* | `config`               | Additional configuration details for the agent executing the task, allowing further customization. |
+| **Output JSON**  *(optional)* | `output_json`          | Outputs a JSON object, requiring an OpenAI client. Only one output format can be set.         |
+| **Output Pydantic**  *(optional)* | `output_pydantic`      | Outputs a Pydantic model object, requiring an OpenAI client. Only one output format can be set. |
+| **Output File**  *(optional)* | `output_file`          | Saves the task output to a file. If used with `Output JSON` or `Output Pydantic`, specifies how the output is saved. |
+| **Callback**  *(optional)* | `callback`             | A Python callable that is executed with the task's output upon completion.                    |
+| **Human Input** *(optional)* | `human_input`         | Indicates if the task requires human feedback at the end, useful for tasks needing human oversight. |
 
 ## Creating a Task
 
diff --git a/docs/how-to/Sequential.md b/docs/how-to/Sequential.md
index ff9efcc94..ae351197b 100644
--- a/docs/how-to/Sequential.md
+++ b/docs/how-to/Sequential.md
@@ -37,10 +37,9 @@ writer = Agent(
   backstory='A skilled writer with a talent for crafting compelling narratives'
 )
 
-# Define the tasks in sequence
-research_task = Task(description='Gather relevant data...', agent=researcher)
-analysis_task = Task(description='Analyze the data...', agent=analyst)
-writing_task = Task(description='Compose the report...', agent=writer)
+research_task = Task(description='Gather relevant data...', agent=researcher, expected_output='Raw Data')
+analysis_task = Task(description='Analyze the data...', agent=analyst, expected_output='Data Insights')
+writing_task = Task(description='Compose the report...', agent=writer, expected_output='Final Report')
 
 # Form the crew with a sequential process
 report_crew = Crew(
@@ -83,4 +82,4 @@ CrewAI tracks token usage across all tasks and agents. You can access these metr
 1. **Order Matters**: Arrange tasks in a logical sequence where each task builds upon the previous one.
 2. **Clear Task Descriptions**: Provide detailed descriptions for each task to guide the agents effectively.
 3. **Appropriate Agent Selection**: Match agents' skills and roles to the requirements of each task.
-4. **Use Context**: Leverage the context from previous tasks to inform subsequent ones
\ No newline at end of file
+4. **Use Context**: Leverage the context from previous tasks to inform subsequent ones
diff --git a/docs/tools/CodeInterpreterTool.md b/docs/tools/CodeInterpreterTool.md
index e66a82e39..cb1bf3ad8 100644
--- a/docs/tools/CodeInterpreterTool.md
+++ b/docs/tools/CodeInterpreterTool.md
@@ -20,6 +20,7 @@ pip install 'crewai[tools]'
 Remember that when using this tool, the code must be generated by the Agent itself. The code must be a Python3 code. And it will take some time for the first time to run because it needs to build the Docker image.
 
 ```python
+from crewai import Agent
 from crewai_tools import CodeInterpreterTool
 
 Agent(
@@ -27,3 +28,14 @@ Agent(
     tools=[CodeInterpreterTool()],
 )
 ```
+
+We also provide a simple way to use it directly from the Agent.
+
+```python
+from crewai import Agent
+
+agent = Agent(
+    ...
+    allow_code_execution=True,
+)
+```
diff --git a/docs/tools/ComposioTool.md b/docs/tools/ComposioTool.md
new file mode 100644
index 000000000..eeb233be5
--- /dev/null
+++ b/docs/tools/ComposioTool.md
@@ -0,0 +1,72 @@
+# ComposioTool Documentation
+
+## Description
+
+This tools is a wrapper around the composio toolset and gives your agent access to a wide variety of tools from the composio SDK.
+
+## Installation
+
+To incorporate this tool into your project, follow the installation instructions below:
+
+```shell
+pip install composio-core
+pip install 'crewai[tools]'
+```
+
+after the installation is complete, either run `composio login` or export your composio API key as `COMPOSIO_API_KEY`.
+
+## Example
+
+The following example demonstrates how to initialize the tool and execute a github action:
+
+1. Initialize toolset
+
+```python
+from composio import App
+from crewai_tools import ComposioTool
+from crewai import Agent, Task
+
+
+tools = [ComposioTool.from_action(action=Action.GITHUB_ACTIVITY_STAR_REPO_FOR_AUTHENTICATED_USER)]
+```
+
+If you don't know what action you want to use, use `from_app` and `tags` filter to get relevant actions
+
+```python
+tools = ComposioTool.from_app(App.GITHUB, tags=["important"])
+```
+
+or use `use_case` to search relevant actions
+
+```python
+tools = ComposioTool.from_app(App.GITHUB, use_case="Star a github repository")
+```
+
+2. Define agent
+
+```python
+crewai_agent = Agent(
+    role="Github Agent",
+    goal="You take action on Github using Github APIs",
+    backstory=(
+        "You are AI agent that is responsible for taking actions on Github "
+        "on users behalf. You need to take action on Github using Github APIs"
+    ),
+    verbose=True,
+    tools=tools,
+)
+```
+
+3. Execute task
+
+```python
+task = Task(
+    description="Star a repo ComposioHQ/composio on GitHub",
+    agent=crewai_agent,
+    expected_output="if the star happened",
+)
+
+task.execute()
+```
+
+* More detailed list of tools can be found [here](https://app.composio.dev)
diff --git a/mkdocs.yml b/mkdocs.yml
index cb481858b..76024127a 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -148,6 +148,8 @@ nav:
   - Tools Docs:
     - Google Serper Search: 'tools/SerperDevTool.md'
     - Browserbase Web Loader: 'tools/BrowserbaseLoadTool.md'
+    - Composio Tools: 'tools/ComposioTool.md'
+    - Code Interpreter: 'tools/CodeInterpreterTool.md'
     - Scrape Website: 'tools/ScrapeWebsiteTool.md'
     - Directory Read: 'tools/DirectoryReadTool.md'
     - Exa Serch Web Loader: 'tools/EXASearchTool.md'
diff --git a/poetry.lock b/poetry.lock
index dacbf5918..f75da2851 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -323,17 +323,17 @@ lxml = ["lxml"]
 
 [[package]]
 name = "boto3"
-version = "1.34.136"
+version = "1.34.137"
 description = "The AWS SDK for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "boto3-1.34.136-py3-none-any.whl", hash = "sha256:d41037e2c680ab8d6c61a0a4ee6bf1fdd9e857f43996672830a95d62d6f6fa79"},
-    {file = "boto3-1.34.136.tar.gz", hash = "sha256:0314e6598f59ee0f34eb4e6d1a0f69fa65c146d2b88a6e837a527a9956ec2731"},
+    {file = "boto3-1.34.137-py3-none-any.whl", hash = "sha256:7cb697d67fd138ceebc6f789919ae370c092a50c6b0ccc4ef483027935502eab"},
+    {file = "boto3-1.34.137.tar.gz", hash = "sha256:0b21b84db4619b3711a6f643d465a5a25e81231ee43615c55a20ff6b89c6cc3c"},
 ]
 
 [package.dependencies]
-botocore = ">=1.34.136,<1.35.0"
+botocore = ">=1.34.137,<1.35.0"
 jmespath = ">=0.7.1,<2.0.0"
 s3transfer = ">=0.10.0,<0.11.0"
 
@@ -342,13 +342,13 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
 
 [[package]]
 name = "botocore"
-version = "1.34.136"
+version = "1.34.137"
 description = "Low-level, data-driven core of boto 3."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "botocore-1.34.136-py3-none-any.whl", hash = "sha256:c63fe9032091fb9e9477706a3ebfa4d0c109b807907051d892ed574f9b573e61"},
-    {file = "botocore-1.34.136.tar.gz", hash = "sha256:7f7135178692b39143c8f152a618d2a3b71065a317569a7102d2306d4946f42f"},
+    {file = "botocore-1.34.137-py3-none-any.whl", hash = "sha256:a980fa4adec4bfa23fff70a3512622e9412c69c791898a52cafc2458b0be6040"},
+    {file = "botocore-1.34.137.tar.gz", hash = "sha256:e29c8e9bfda0b20a1997792968e85868bfce42fefad9730f633a81adcff3f2ef"},
 ]
 
 [package.dependencies]
@@ -359,137 +359,6 @@ urllib3 = {version = ">=1.25.4,<2.2.0 || >2.2.0,<3", markers = "python_version >
 [package.extras]
 crt = ["awscrt (==0.20.11)"]
 
-[[package]]
-name = "brotli"
-version = "1.1.0"
-description = "Python bindings for the Brotli compression library"
-optional = false
-python-versions = "*"
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-
 [[package]]
 name = "build"
 version = "1.2.1"
@@ -951,13 +820,13 @@ files = [
 
 [[package]]
 name = "crewai-tools"
-version = "0.4.1"
+version = "0.4.5"
 description = "Set of tools for the crewAI framework"
 optional = false
 python-versions = "<=3.13,>=3.10"
 files = [
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 chromadb = ">=0.4.22,<0.5.0"
 docker = ">=7.1.0,<8.0.0"
 docx2txt = ">=0.8,<0.9"
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+embedchain = ">=0.1.113,<0.2.0"
 lancedb = ">=0.5.4,<0.6.0"
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 openai = ">=1.12.0,<2.0.0"
 pydantic = ">=2.6.1,<3.0.0"
 pyright = ">=1.1.350,<2.0.0"
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 requests = ">=2.31.0,<3.0.0"
 selenium = ">=4.18.1,<5.0.0"
 
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-
-[package.dependencies]
-cffi = {version = ">=1.12", markers = "platform_python_implementation != \"PyPy\""}
-
-[package.extras]
-docs = ["sphinx (>=5.3.0)", "sphinx-rtd-theme (>=1.1.1)"]
-docstest = ["pyenchant (>=1.6.11)", "readme-renderer", "sphinxcontrib-spelling (>=4.0.1)"]
-nox = ["nox"]
-pep8test = ["check-sdist", "click", "mypy", "ruff"]
-sdist = ["build"]
-ssh = ["bcrypt (>=3.1.5)"]
-test = ["certifi", "pretend", "pytest (>=6.2.0)", "pytest-benchmark", "pytest-cov", "pytest-xdist"]
-test-randomorder = ["pytest-randomly"]
-
 [[package]]
 name = "cssselect2"
 version = "0.7.0"
@@ -1049,6 +864,21 @@ webencodings = "*"
 doc = ["sphinx", "sphinx_rtd_theme"]
 test = ["flake8", "isort", "pytest"]
 
+[[package]]
+name = "dataclasses-json"
+version = "0.6.7"
+description = "Easily serialize dataclasses to and from JSON."
+optional = false
+python-versions = "<4.0,>=3.7"
+files = [
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+]
+
+[package.dependencies]
+marshmallow = ">=3.18.0,<4.0.0"
+typing-inspect = ">=0.4.0,<1"
+
 [[package]]
 name = "decorator"
 version = "5.1.1"
@@ -1203,14 +1033,14 @@ dnspython = ">=2.0.0"
 idna = ">=2.0.0"
 
 [[package]]
-name = "embedchain-crewai"
-version = "0.1.114"
+name = "embedchain"
+version = "0.1.113"
 description = "Simplest open source retrieval (RAG) framework"
 optional = false
 python-versions = "<=3.13,>=3.9"
 files = [
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 ]
 
 [package.dependencies]
@@ -1218,15 +1048,13 @@ alembic = ">=1.13.1,<2.0.0"
 beautifulsoup4 = ">=4.12.2,<5.0.0"
 chromadb = ">=0.4.24,<0.5.0"
 clarifai = ">=10.0.1,<11.0.0"
-gitpython = {version = ">=3.1.38,<4.0.0", optional = true, markers = "extra == \"github\""}
 google-cloud-aiplatform = ">=1.26.1,<2.0.0"
 gptcache = ">=0.1.43,<0.2.0"
-langchain = ">0.2,<=0.3"
+langchain = ">=0.1.4,<0.2.0"
 langchain-cohere = ">=0.1.4,<0.2.0"
 langchain-openai = ">=0.1.7,<0.2.0"
 openai = ">=1.1.1"
 posthog = ">=3.0.2,<4.0.0"
-PyGithub = {version = ">=1.59.1,<2.0.0", optional = true, markers = "extra == \"github\""}
 pypdf = ">=4.0.1,<5.0.0"
 pysbd = ">=0.3.4,<0.4.0"
 python-dotenv = ">=1.0.0,<2.0.0"
@@ -1234,8 +1062,6 @@ rich = ">=13.7.0,<14.0.0"
 schema = ">=0.7.5,<0.8.0"
 sqlalchemy = ">=2.0.27,<3.0.0"
 tiktoken = ">=0.7.0,<0.8.0"
-youtube-transcript-api = {version = ">=0.6.1,<0.7.0", optional = true, markers = "extra == \"dataloaders\" or extra == \"youtube\""}
-yt_dlp = {version = ">=2023.11.14,<2024.0.0", optional = true, markers = "extra == \"youtube\""}
 
 [package.extras]
 aws-bedrock = ["boto3 (>=1.34.20,<2.0.0)"]
@@ -1252,7 +1078,7 @@ huggingface-hub = ["huggingface_hub (>=0.17.3,<0.18.0)"]
 lancedb = ["lancedb (>=0.6.2,<0.7.0)"]
 llama2 = ["replicate (>=0.15.4,<0.16.0)"]
 milvus = ["pymilvus (==2.4.3)"]
-mistralai = ["langchain-mistralai (>=0.1.9,<0.2.0)"]
+mistralai = ["langchain-mistralai (>=0.0.3,<0.0.4)"]
 modal = ["modal (>=0.56.4329,<0.57.0)"]
 mysql = ["mysql-connector-python (>=8.1.0,<9.0.0)"]
 opensearch = ["opensearch-py (==2.3.1)"]
@@ -1263,7 +1089,7 @@ qdrant = ["qdrant-client (>=1.6.3,<2.0.0)"]
 rss-feed = ["feedparser (>=6.0.10,<7.0.0)", "listparser (>=0.19,<0.20)", "newspaper3k (>=0.2.8,<0.3.0)"]
 slack = ["flask (>=2.3.3,<3.0.0)", "slack-sdk (==3.21.3)"]
 together = ["together (>=0.2.8,<0.3.0)"]
-vertexai = ["langchain-google-vertexai (>=1.0.6,<2.0.0)"]
+vertexai = ["langchain-google-vertexai (>=0.0.5,<0.0.6)"]
 weaviate = ["weaviate-client (>=3.24.1,<4.0.0)"]
 whatsapp = ["flask (>=2.3.3,<3.0.0)", "twilio (>=8.5.0,<9.0.0)"]
 youtube = ["youtube-transcript-api (>=0.6.1,<0.7.0)", "yt_dlp (>=2023.11.14,<2024.0.0)"]
@@ -1541,38 +1367,6 @@ python-dateutil = ">=2.8.1"
 [package.extras]
 dev = ["flake8", "markdown", "twine", "wheel"]
 
-[[package]]
-name = "gitdb"
-version = "4.0.11"
-description = "Git Object Database"
-optional = false
-python-versions = ">=3.7"
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-]
-
-[package.dependencies]
-smmap = ">=3.0.1,<6"
-
-[[package]]
-name = "gitpython"
-version = "3.1.43"
-description = "GitPython is a Python library used to interact with Git repositories"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "GitPython-3.1.43-py3-none-any.whl", hash = "sha256:eec7ec56b92aad751f9912a73404bc02ba212a23adb2c7098ee668417051a1ff"},
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-]
-
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-gitdb = ">=4.0.1,<5"
-
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-doc = ["sphinx (==4.3.2)", "sphinx-autodoc-typehints", "sphinx-rtd-theme", "sphinxcontrib-applehelp (>=1.0.2,<=1.0.4)", "sphinxcontrib-devhelp (==1.0.2)", "sphinxcontrib-htmlhelp (>=2.0.0,<=2.0.1)", "sphinxcontrib-qthelp (==1.0.3)", "sphinxcontrib-serializinghtml (==1.1.5)"]
-test = ["coverage[toml]", "ddt (>=1.1.1,!=1.4.3)", "mock", "mypy", "pre-commit", "pytest (>=7.3.1)", "pytest-cov", "pytest-instafail", "pytest-mock", "pytest-sugar", "typing-extensions"]
-
 [[package]]
 name = "google-api-core"
 version = "2.19.1"
@@ -1606,13 +1400,13 @@ grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
 
 [[package]]
 name = "google-auth"
-version = "2.30.0"
+version = "2.31.0"
 description = "Google Authentication Library"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-auth-2.30.0.tar.gz", hash = "sha256:ab630a1320f6720909ad76a7dbdb6841cdf5c66b328d690027e4867bdfb16688"},
-    {file = "google_auth-2.30.0-py2.py3-none-any.whl", hash = "sha256:8df7da660f62757388b8a7f249df13549b3373f24388cb5d2f1dd91cc18180b5"},
+    {file = "google-auth-2.31.0.tar.gz", hash = "sha256:87805c36970047247c8afe614d4e3af8eceafc1ebba0c679fe75ddd1d575e871"},
+    {file = "google_auth-2.31.0-py2.py3-none-any.whl", hash = "sha256:042c4702efa9f7d3c48d3a69341c209381b125faa6dbf3ebe56bc7e40ae05c23"},
 ]
 
 [package.dependencies]
@@ -2563,97 +2357,139 @@ tests = ["aiohttp", "duckdb", "pandas (>=1.4)", "polars (>=0.19)", "pytest", "py
 
 [[package]]
 name = "langchain"
-version = "0.2.6"
+version = "0.1.20"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langchain-0.2.6-py3-none-any.whl", hash = "sha256:f86e8a7afd3e56f8eb5ba47f01dd00144fb9fc2f1db9873bd197347be2857aa4"},
-    {file = "langchain-0.2.6.tar.gz", hash = "sha256:867f6add370c1e3911b0e87d3dd0e36aec1e8f513bf06131340fe8f151d89dc5"},
+    {file = "langchain-0.1.20-py3-none-any.whl", hash = "sha256:09991999fbd6c3421a12db3c7d1f52d55601fc41d9b2a3ef51aab2e0e9c38da9"},
+    {file = "langchain-0.1.20.tar.gz", hash = "sha256:f35c95eed8c8375e02dce95a34f2fd4856a4c98269d6dc34547a23dba5beab7e"},
 ]
 
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 async-timeout = {version = ">=4.0.0,<5.0.0", markers = "python_version < \"3.11\""}
-langchain-core = ">=0.2.10,<0.3.0"
-langchain-text-splitters = ">=0.2.0,<0.3.0"
+dataclasses-json = ">=0.5.7,<0.7"
+langchain-community = ">=0.0.38,<0.1"
+langchain-core = ">=0.1.52,<0.2.0"
+langchain-text-splitters = ">=0.0.1,<0.1"
 langsmith = ">=0.1.17,<0.2.0"
-numpy = [
-    {version = ">=1,<2", markers = "python_version < \"3.12\""},
-    {version = ">=1.26.0,<2.0.0", markers = "python_version >= \"3.12\""},
-]
+numpy = ">=1,<2"
 pydantic = ">=1,<3"
 PyYAML = ">=5.3"
 requests = ">=2,<3"
 SQLAlchemy = ">=1.4,<3"
-tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<9.0.0"
+tenacity = ">=8.1.0,<9.0.0"
+
+[package.extras]
+azure = ["azure-ai-formrecognizer (>=3.2.1,<4.0.0)", "azure-ai-textanalytics (>=5.3.0,<6.0.0)", "azure-cognitiveservices-speech (>=1.28.0,<2.0.0)", "azure-core (>=1.26.4,<2.0.0)", "azure-cosmos (>=4.4.0b1,<5.0.0)", "azure-identity (>=1.12.0,<2.0.0)", "azure-search-documents (==11.4.0b8)", "openai (<2)"]
+clarifai = ["clarifai (>=9.1.0)"]
+cli = ["typer (>=0.9.0,<0.10.0)"]
+cohere = ["cohere (>=4,<6)"]
+docarray = ["docarray[hnswlib] (>=0.32.0,<0.33.0)"]
+embeddings = ["sentence-transformers (>=2,<3)"]
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+text-helpers = ["chardet (>=5.1.0,<6.0.0)"]
 
 [[package]]
 name = "langchain-cohere"
-version = "0.1.8"
+version = "0.1.5"
 description = "An integration package connecting Cohere and LangChain"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
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+cohere = ">=5.5,<6.0"
+langchain-core = ">=0.1.42,<0.3"
+
+[[package]]
+name = "langchain-community"
+version = "0.0.38"
+description = "Community contributed LangChain integrations."
+optional = false
+python-versions = "<4.0,>=3.8.1"
+files = [
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 [[package]]
 name = "langchain-core"
-version = "0.2.10"
+version = "0.1.52"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langchain_core-0.2.10-py3-none-any.whl", hash = "sha256:6eb72086b6bc86db9812da98f79e507c2209a15c0112aefd214a04182ada8586"},
-    {file = "langchain_core-0.2.10.tar.gz", hash = "sha256:33d1fc234ab58c80476eb5bbde2107ef522a2ce8f46bdf47d9e1bd21e054208f"},
+    {file = "langchain_core-0.1.52-py3-none-any.whl", hash = "sha256:62566749c92e8a1181c255c788548dc16dbc319d896cd6b9c95dc17af9b2a6db"},
+    {file = "langchain_core-0.1.52.tar.gz", hash = "sha256:084c3fc452f5a6966c28ab3ec5dbc8b8d26fc3f63378073928f4e29d90b6393f"},
 ]
 
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 jsonpatch = ">=1.33,<2.0"
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-packaging = ">=23.2,<25"
-pydantic = [
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-    {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""},
-]
+langsmith = ">=0.1.0,<0.2.0"
+packaging = ">=23.2,<24.0"
+pydantic = ">=1,<3"
 PyYAML = ">=5.3"
-tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<9.0.0"
+tenacity = ">=8.1.0,<9.0.0"
+
+[package.extras]
+extended-testing = ["jinja2 (>=3,<4)"]
 
 [[package]]
 name = "langchain-openai"
-version = "0.1.13"
+version = "0.1.7"
 description = "An integration package connecting OpenAI and LangChain"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langchain_openai-0.1.13-py3-none-any.whl", hash = "sha256:4344b6c5c67088a28eed80ba763157fdd1d690cee679966a021b42f305dbf7b5"},
-    {file = "langchain_openai-0.1.13.tar.gz", hash = "sha256:03318669bcb3238f7d1bb043329f91d150ca09246f1faf569ef299f535405c71"},
+    {file = "langchain_openai-0.1.7-py3-none-any.whl", hash = "sha256:39c3cb22bb739900ae8294d4d9939a6138c0ca7ad11198e57038eb14c08d04ec"},
+    {file = "langchain_openai-0.1.7.tar.gz", hash = "sha256:fd7e1c33ba8e2cab4b2154f3a2fd4a0d9cc6518b41cf49bb87255f9f732a4896"},
 ]
 
 [package.dependencies]
-langchain-core = ">=0.2.2,<0.3"
-openai = ">=1.32.0,<2.0.0"
+langchain-core = ">=0.1.46,<0.3"
+openai = ">=1.24.0,<2.0.0"
 tiktoken = ">=0.7,<1"
 
 [[package]]
 name = "langchain-text-splitters"
-version = "0.2.2"
+version = "0.0.2"
 description = "LangChain text splitting utilities"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langchain_text_splitters-0.2.2-py3-none-any.whl", hash = "sha256:1c80d4b11b55e2995f02d2a326c0323ee1eeff24507329bb22924e420c782dff"},
-    {file = "langchain_text_splitters-0.2.2.tar.gz", hash = "sha256:a1e45de10919fa6fb080ef0525deab56557e9552083600455cb9fa4238076140"},
+    {file = "langchain_text_splitters-0.0.2-py3-none-any.whl", hash = "sha256:13887f32705862c1e1454213cb7834a63aae57c26fcd80346703a1d09c46168d"},
+    {file = "langchain_text_splitters-0.0.2.tar.gz", hash = "sha256:ac8927dc0ba08eba702f6961c9ed7df7cead8de19a9f7101ab2b5ea34201b3c1"},
 ]
 
 [package.dependencies]
-langchain-core = ">=0.2.10,<0.3.0"
+langchain-core = ">=0.1.28,<0.3"
+
+[package.extras]
+extended-testing = ["beautifulsoup4 (>=4.12.3,<5.0.0)", "lxml (>=4.9.3,<6.0)"]
 
 [[package]]
 name = "langsmith"
@@ -2801,6 +2637,25 @@ files = [
     {file = "MarkupSafe-2.1.5.tar.gz", hash = "sha256:d283d37a890ba4c1ae73ffadf8046435c76e7bc2247bbb63c00bd1a709c6544b"},
 ]
 
+[[package]]
+name = "marshmallow"
+version = "3.21.3"
+description = "A lightweight library for converting complex datatypes to and from native Python datatypes."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "marshmallow-3.21.3-py3-none-any.whl", hash = "sha256:86ce7fb914aa865001a4b2092c4c2872d13bc347f3d42673272cabfdbad386f1"},
+    {file = "marshmallow-3.21.3.tar.gz", hash = "sha256:4f57c5e050a54d66361e826f94fba213eb10b67b2fdb02c3e0343ce207ba1662"},
+]
+
+[package.dependencies]
+packaging = ">=17.0"
+
+[package.extras]
+dev = ["marshmallow[tests]", "pre-commit (>=3.5,<4.0)", "tox"]
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@@ -4449,32 +4108,6 @@ pyyaml = "*"
 [package.extras]
 extra = ["pygments (>=2.12)"]
 
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@@ -5102,18 +4735,18 @@ files = [
 
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@@ -5194,17 +4827,6 @@ files = [
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+python-versions = "*"
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+
 [[package]]
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@@ -6375,41 +6012,6 @@ files = [
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-python-versions = "*"
-files = [
-    {file = "youtube_transcript_api-0.6.2-py3-none-any.whl", hash = "sha256:019dbf265c6a68a0591c513fff25ed5a116ce6525832aefdfb34d4df5567121c"},
-    {file = "youtube_transcript_api-0.6.2.tar.gz", hash = "sha256:cad223d7620633cec44f657646bffc8bbc5598bd8e70b1ad2fa8277dec305eb7"},
-]
-
-[package.dependencies]
-requests = "*"
-
-[[package]]
-name = "yt-dlp"
-version = "2023.12.30"
-description = "A youtube-dl fork with additional features and patches"
-optional = false
-python-versions = ">=3.8"
-files = [
-    {file = "yt-dlp-2023.12.30.tar.gz", hash = "sha256:a11862e57721b0a0f0883dfeb5a4d79ba213a2d4c45e1880e9fd70f8e6570c38"},
-    {file = "yt_dlp-2023.12.30-py2.py3-none-any.whl", hash = "sha256:c00d9a71d64472ad441bcaa1ec0c3797d6e60c9f934f270096a96fe51657e7b3"},
-]
-
-[package.dependencies]
-brotli = {version = "*", markers = "implementation_name == \"cpython\""}
-brotlicffi = {version = "*", markers = "implementation_name != \"cpython\""}
-certifi = "*"
-mutagen = "*"
-pycryptodomex = "*"
-requests = ">=2.31.0,<3"
-urllib3 = ">=1.26.17,<3"
-websockets = ">=12.0"
-
 [[package]]
 name = "zipp"
 version = "3.19.2"
@@ -6431,4 +6033,4 @@ tools = ["crewai-tools"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10,<=3.13"
-content-hash = "93cf2828a0b5157c46d35cd95db4b8c69461b0473e6d9f10643064b2bb2b6e15"
+content-hash = "d4ea0d71723ecc2bad629c387dd786b6a96c553b1e3e298516fdfcd2059d1019"
diff --git a/pyproject.toml b/pyproject.toml
index 19e317ad2..17c6f526e 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "crewai"
-version = "0.35.4"
+version = "0.35.8"
 description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
 authors = ["Joao Moura <joao@crewai.com>"]
 readme = "README.md"
@@ -14,22 +14,24 @@ Repository = "https://github.com/joaomdmoura/crewai"
 [tool.poetry.dependencies]
 python = ">=3.10,<=3.13"
 pydantic = "^2.4.2"
-langchain = ">=0.2,<=0.3"
+langchain = ">=0.1.4,<0.2.0"
 openai = "^1.13.3"
 opentelemetry-api = "^1.22.0"
 opentelemetry-sdk = "^1.22.0"
 opentelemetry-exporter-otlp-proto-http = "^1.22.0"
 instructor = "1.3.3"
 regex = "^2023.12.25"
-crewai-tools = { version = "^0.4.1", optional = true }
+crewai-tools = { version = "^0.4.6", optional = true }
 click = "^8.1.7"
 python-dotenv = "^1.0.0"
-embedchain-crewai = {extras = ["github", "youtube"], version = "^0.1.114"}
 appdirs = "^1.4.4"
 jsonref = "^1.1.0"
+agentops = { version = "^0.1.9", optional = true }
+embedchain = "^0.1.113"
 
 [tool.poetry.extras]
 tools = ["crewai-tools"]
+agentops = ["agentops"]
 
 [tool.poetry.group.dev.dependencies]
 isort = "^5.13.2"
@@ -43,7 +45,7 @@ mkdocs-material = { extras = ["imaging"], version = "^9.5.7" }
 mkdocs-material-extensions = "^1.3.1"
 pillow = "^10.2.0"
 cairosvg = "^2.7.1"
-crewai-tools = "^0.4.1"
+crewai-tools = "^0.4.6"
 
 [tool.poetry.group.test.dependencies]
 pytest = "^8.0.0"
@@ -60,4 +62,4 @@ exclude = ["cli/templates/main.py", "cli/templates/crew.py"]
 
 [build-system]
 requires = ["poetry-core"]
-build-backend = "poetry.core.masonry.api"
\ No newline at end of file
+build-backend = "poetry.core.masonry.api"
diff --git a/src/crewai/agent.py b/src/crewai/agent.py
index 661d3f1f7..45797cc7f 100644
--- a/src/crewai/agent.py
+++ b/src/crewai/agent.py
@@ -18,7 +18,20 @@ from crewai.utilities.constants import TRAINED_AGENTS_DATA_FILE, TRAINING_DATA_F
 from crewai.utilities.token_counter_callback import TokenCalcHandler
 from crewai.utilities.training_handler import CrewTrainingHandler
 
+agentops = None
+try:
+    import agentops
+    from agentops import track_agent
+except ImportError:
 
+    def track_agent():
+        def noop(f):
+            return f
+
+        return noop
+
+
+@track_agent()
 class Agent(BaseAgent):
     """Represents an agent in a system.
 
@@ -47,6 +60,8 @@ class Agent(BaseAgent):
         default=None,
         description="Maximum execution time for an agent to execute a task",
     )
+    agent_ops_agent_name: str = None
+    agent_ops_agent_id: str = None
     cache_handler: InstanceOf[CacheHandler] = Field(
         default=None, description="An instance of the CacheHandler class."
     )
@@ -82,6 +97,7 @@ class Agent(BaseAgent):
     def __init__(__pydantic_self__, **data):
         config = data.pop("config", {})
         super().__init__(**config, **data)
+        __pydantic_self__.agent_ops_agent_name = __pydantic_self__.role
 
     @model_validator(mode="after")
     def set_agent_executor(self) -> "Agent":
@@ -99,6 +115,12 @@ class Agent(BaseAgent):
             ):
                 self.llm.callbacks.append(token_handler)
 
+            if agentops and not any(
+                isinstance(handler, agentops.LangchainCallbackHandler) for handler in self.llm.callbacks
+            ):
+                agentops.stop_instrumenting()
+                self.llm.callbacks.append(agentops.LangchainCallbackHandler())
+
         if not self.agent_executor:
             if not self.cache_handler:
                 self.cache_handler = CacheHandler()
diff --git a/src/crewai/agents/agent_builder/base_agent.py b/src/crewai/agents/agent_builder/base_agent.py
index a9549e5a8..90e27dec6 100644
--- a/src/crewai/agents/agent_builder/base_agent.py
+++ b/src/crewai/agents/agent_builder/base_agent.py
@@ -15,8 +15,9 @@ from pydantic import (
 )
 from pydantic_core import PydanticCustomError
 
-from crewai.agents import CacheHandler, ToolsHandler
 from crewai.agents.agent_builder.utilities.base_token_process import TokenProcess
+from crewai.agents.cache.cache_handler import CacheHandler
+from crewai.agents.tools_handler import ToolsHandler
 from crewai.utilities import I18N, Logger, RPMController
 
 T = TypeVar("T", bound="BaseAgent")
diff --git a/src/crewai/agents/agent_builder/base_agent_executor_mixin.py b/src/crewai/agents/agent_builder/base_agent_executor_mixin.py
index 7d31defaf..e3c0aa211 100644
--- a/src/crewai/agents/agent_builder/base_agent_executor_mixin.py
+++ b/src/crewai/agents/agent_builder/base_agent_executor_mixin.py
@@ -1,65 +1,109 @@
 import time
+from typing import TYPE_CHECKING, Optional
 
 from crewai.memory.entity.entity_memory_item import EntityMemoryItem
 from crewai.memory.long_term.long_term_memory_item import LongTermMemoryItem
 from crewai.memory.short_term.short_term_memory_item import ShortTermMemoryItem
 from crewai.utilities.converter import ConverterError
 from crewai.utilities.evaluators.task_evaluator import TaskEvaluator
+from crewai.utilities import I18N
+
+
+if TYPE_CHECKING:
+    from crewai.crew import Crew
+    from crewai.task import Task
+    from crewai.agents.agent_builder.base_agent import BaseAgent
 
 
 class CrewAgentExecutorMixin:
+    crew: Optional["Crew"]
+    crew_agent: Optional["BaseAgent"]
+    task: Optional["Task"]
+    iterations: int
+    force_answer_max_iterations: int
+    have_forced_answer: bool
+    _i18n: I18N
+
     def _should_force_answer(self) -> bool:
+        """Determine if a forced answer is required based on iteration count."""
         return (
             self.iterations == self.force_answer_max_iterations
         ) and not self.have_forced_answer
 
     def _create_short_term_memory(self, output) -> None:
+        """Create and save a short-term memory item if conditions are met."""
+        if (
+            self.crew
+            and self.crew_agent
+            and self.task
+            and "Action: Delegate work to coworker" not in output.log
+        ):
+            try:
+                memory = ShortTermMemoryItem(
+                    data=output.log,
+                    agent=self.crew_agent.role,
+                    metadata={
+                        "observation": self.task.description,
+                    },
+                )
+                if (
+                    hasattr(self.crew, "_short_term_memory")
+                    and self.crew._short_term_memory
+                ):
+                    self.crew._short_term_memory.save(memory)
+            except Exception as e:
+                print(f"Failed to add to short term memory: {e}")
+                pass
+
+    def _create_long_term_memory(self, output) -> None:
+        """Create and save long-term and entity memory items based on evaluation."""
         if (
             self.crew
             and self.crew.memory
-            and "Action: Delegate work to coworker" not in output.log
+            and self.crew._long_term_memory
+            and self.crew._entity_memory
+            and self.task
+            and self.crew_agent
         ):
-            memory = ShortTermMemoryItem(
-                data=output.log,
-                agent=self.crew_agent.role,
-                metadata={
-                    "observation": self.task.description,
-                },
-            )
-            self.crew._short_term_memory.save(memory)
+            try:
+                ltm_agent = TaskEvaluator(self.crew_agent)
+                evaluation = ltm_agent.evaluate(self.task, output.log)
 
-    def _create_long_term_memory(self, output) -> None:
-        if self.crew and self.crew.memory:
-            ltm_agent = TaskEvaluator(self.crew_agent)
-            evaluation = ltm_agent.evaluate(self.task, output.log)
+                if isinstance(evaluation, ConverterError):
+                    return
 
-            if isinstance(evaluation, ConverterError):
-                return
-
-            long_term_memory = LongTermMemoryItem(
-                task=self.task.description,
-                agent=self.crew_agent.role,
-                quality=evaluation.quality,
-                datetime=str(time.time()),
-                expected_output=self.task.expected_output,
-                metadata={
-                    "suggestions": evaluation.suggestions,
-                    "quality": evaluation.quality,
-                },
-            )
-            self.crew._long_term_memory.save(long_term_memory)
-
-            for entity in evaluation.entities:
-                entity_memory = EntityMemoryItem(
-                    name=entity.name,
-                    type=entity.type,
-                    description=entity.description,
-                    relationships="\n".join([f"- {r}" for r in entity.relationships]),
+                long_term_memory = LongTermMemoryItem(
+                    task=self.task.description,
+                    agent=self.crew_agent.role,
+                    quality=evaluation.quality,
+                    datetime=str(time.time()),
+                    expected_output=self.task.expected_output,
+                    metadata={
+                        "suggestions": evaluation.suggestions,
+                        "quality": evaluation.quality,
+                    },
                 )
-                self.crew._entity_memory.save(entity_memory)
+                self.crew._long_term_memory.save(long_term_memory)
+
+                for entity in evaluation.entities:
+                    entity_memory = EntityMemoryItem(
+                        name=entity.name,
+                        type=entity.type,
+                        description=entity.description,
+                        relationships="\n".join(
+                            [f"- {r}" for r in entity.relationships]
+                        ),
+                    )
+                    self.crew._entity_memory.save(entity_memory)
+            except AttributeError as e:
+                print(f"Missing attributes for long term memory: {e}")
+                pass
+            except Exception as e:
+                print(f"Failed to add to long term memory: {e}")
+                pass
 
     def _ask_human_input(self, final_answer: dict) -> str:
-        """Get human input."""
+        """Prompt human input for final decision making."""
         return input(
             self._i18n.slice("getting_input").format(final_answer=final_answer)
         )
diff --git a/src/crewai/agents/executor.py b/src/crewai/agents/executor.py
index 365d04f78..192dc190e 100644
--- a/src/crewai/agents/executor.py
+++ b/src/crewai/agents/executor.py
@@ -1,6 +1,14 @@
 import threading
 import time
-from typing import Any, Dict, Iterator, List, Optional, Tuple, Union
+from typing import (
+    Any,
+    Dict,
+    Iterator,
+    List,
+    Optional,
+    Tuple,
+    Union,
+)
 
 from langchain.agents import AgentExecutor
 from langchain.agents.agent import ExceptionTool
@@ -11,13 +19,15 @@ from langchain_core.exceptions import OutputParserException
 from langchain_core.tools import BaseTool
 from langchain_core.utils.input import get_color_mapping
 from pydantic import InstanceOf
-from crewai.agents.agent_builder.base_agent_executor_mixin import CrewAgentExecutorMixin
+from crewai.agents.agent_builder.base_agent_executor_mixin import (
+    CrewAgentExecutorMixin,
+)
 
 from crewai.agents.tools_handler import ToolsHandler
 from crewai.tools.tool_usage import ToolUsage, ToolUsageErrorException
-from crewai.utilities import I18N
 from crewai.utilities.constants import TRAINING_DATA_FILE
 from crewai.utilities.training_handler import CrewTrainingHandler
+from crewai.utilities import I18N
 
 
 class CrewAgentExecutor(AgentExecutor, CrewAgentExecutorMixin):
diff --git a/src/crewai/cli/templates/pyproject.toml b/src/crewai/cli/templates/pyproject.toml
index b113cd889..7c097a727 100644
--- a/src/crewai/cli/templates/pyproject.toml
+++ b/src/crewai/cli/templates/pyproject.toml
@@ -6,7 +6,7 @@ authors = ["Your Name <you@example.com>"]
 
 [tool.poetry.dependencies]
 python = ">=3.10,<=3.13"
-crewai = { extras = ["tools"], version = "^0.35.4" }
+crewai = { extras = ["tools"], version = "^0.35.8" }
 
 [tool.poetry.scripts]
 {{folder_name}} = "{{folder_name}}.main:run"
diff --git a/src/crewai/crew.py b/src/crewai/crew.py
index 729d48aa8..85c0094e5 100644
--- a/src/crewai/crew.py
+++ b/src/crewai/crew.py
@@ -31,6 +31,11 @@ from crewai.utilities import I18N, FileHandler, Logger, RPMController
 from crewai.utilities.evaluators.task_evaluator import TaskEvaluator
 from crewai.utilities.training_handler import CrewTrainingHandler
 
+try:
+    import agentops
+except ImportError:
+    agentops = None
+
 
 class Crew(BaseModel):
     """
@@ -547,6 +552,10 @@ class Crew(BaseModel):
     def _finish_execution(self, output) -> None:
         if self.max_rpm:
             self._rpm_controller.stop_rpm_counter()
+        if agentops:
+            agentops.end_session(
+                end_state="Success", end_state_reason="Finished Execution", is_auto_end=True
+            )
         self._telemetry.end_crew(self, output)
 
     def calculate_usage_metrics(self) -> Dict[str, int]:
diff --git a/src/crewai/tools/tool_usage.py b/src/crewai/tools/tool_usage.py
index cb7757d84..9bcd1ce91 100644
--- a/src/crewai/tools/tool_usage.py
+++ b/src/crewai/tools/tool_usage.py
@@ -11,6 +11,12 @@ from crewai.telemetry import Telemetry
 from crewai.tools.tool_calling import InstructorToolCalling, ToolCalling
 from crewai.utilities import I18N, Converter, ConverterError, Printer
 
+agentops = None
+try:
+    import agentops
+except ImportError:
+    pass
+
 OPENAI_BIGGER_MODELS = ["gpt-4"]
 
 
@@ -91,15 +97,16 @@ class ToolUsage:
             self.task.increment_tools_errors()
             self._printer.print(content=f"\n\n{error}\n", color="red")
             return error
-        return f"{self._use(tool_string=tool_string, tool=tool, calling=calling)}"  # type: ignore # BUG?: "_use" of "ToolUsage" does not return a value (it only ever returns None)
+        return f"{self._use(tool_string=tool_string, tool=tool, calling=calling)}" # type: ignore # BUG?: "_use" of "ToolUsage" does not return a value (it only ever returns None)
 
     def _use(
         self,
         tool_string: str,
         tool: BaseTool,
         calling: Union[ToolCalling, InstructorToolCalling],
-    ) -> str:  # TODO: Fix this return type --> finecwg : I updated return type to str
-        if self._check_tool_repeated_usage(calling=calling):  # type: ignore # _check_tool_repeated_usage of "ToolUsage" does not return a value (it only ever returns None)
+    ) -> str:  # TODO: Fix this return type
+        tool_event = agentops.ToolEvent(name=calling.tool_name) if agentops else None        
+        if self._check_tool_repeated_usage(calling=calling): # type: ignore # _check_tool_repeated_usage of "ToolUsage" does not return a value (it only ever returns None)
             try:
                 result = self._i18n.errors("task_repeated_usage").format(
                     tool_names=self.tools_names
@@ -110,13 +117,13 @@ class ToolUsage:
                     tool_name=tool.name,
                     attempts=self._run_attempts,
                 )
-                result = self._format_result(result=result)  # type: ignore #  "_format_result" of "ToolUsage" does not return a value (it only ever returns None)
+                result = self._format_result(result=result) # type: ignore #  "_format_result" of "ToolUsage" does not return a value (it only ever returns None)
                 return result  # type: ignore # Fix the reutrn type of this function
 
             except Exception:
                 self.task.increment_tools_errors()
 
-        result = None  # type: ignore # Incompatible types in assignment (expression has type "None", variable has type "str")
+        result = None # type: ignore # Incompatible types in assignment (expression has type "None", variable has type "str")
 
         if self.tools_handler.cache:
             result = self.tools_handler.cache.read(  # type: ignore # Incompatible types in assignment (expression has type "str | None", variable has type "str")
@@ -133,7 +140,7 @@ class ToolUsage:
 
                 if calling.arguments:
                     try:
-                        acceptable_args = tool.args_schema.schema()["properties"].keys()  # type: ignore # Item "None" of "type[BaseModel] | None" has no attribute "schema"
+                        acceptable_args = tool.args_schema.schema()["properties"].keys() # type: ignore # Item "None" of "type[BaseModel] | None" has no attribute "schema"
                         arguments = {
                             k: v
                             for k, v in calling.arguments.items()
@@ -145,7 +152,7 @@ class ToolUsage:
                             arguments = calling.arguments
                             result = tool._run(**arguments)
                         else:
-                            arguments = calling.arguments.values()  # type: ignore # Incompatible types in assignment (expression has type "dict_values[str, Any]", variable has type "dict[str, Any]")
+                            arguments = calling.arguments.values() # type: ignore # Incompatible types in assignment (expression has type "dict_values[str, Any]", variable has type "dict[str, Any]")
                             result = tool._run(*arguments)
                 else:
                     result = tool._run()
@@ -164,6 +171,10 @@ class ToolUsage:
                     return error  # type: ignore # No return value expected
 
                 self.task.increment_tools_errors()
+                if agentops:
+                    agentops.record(
+                        agentops.ErrorEvent(exception=e, trigger_event=tool_event)
+                    )
                 return self.use(calling=calling, tool_string=tool_string)  # type: ignore # No return value expected
 
             if self.tools_handler:
@@ -184,18 +195,20 @@ class ToolUsage:
                 )
 
         self._printer.print(content=f"\n\n{result}\n", color="purple")
+        if agentops:
+            agentops.record(tool_event)
         self._telemetry.tool_usage(
             llm=self.function_calling_llm,
             tool_name=tool.name,
             attempts=self._run_attempts,
-        )
-        result = self._format_result(result=result)  # type: ignore # "_format_result" of "ToolUsage" does not return a value (it only ever returns None)
+        )        
+        result = self._format_result(result=result) # type: ignore # "_format_result" of "ToolUsage" does not return a value (it only ever returns None)
         return result  # type: ignore # No return value expected
 
     def _format_result(self, result: Any) -> None:
         self.task.used_tools += 1
         if self._should_remember_format():  # type: ignore # "_should_remember_format" of "ToolUsage" does not return a value (it only ever returns None)
-            result = self._remember_format(result=result)  # type: ignore # "_remember_format" of "ToolUsage" does not return a value (it only ever returns None)
+            result = self._remember_format(result=result) # type: ignore # "_remember_format" of "ToolUsage" does not return a value (it only ever returns None)
         return result
 
     def _should_remember_format(self) -> None:
diff --git a/src/crewai/utilities/evaluators/task_evaluator.py b/src/crewai/utilities/evaluators/task_evaluator.py
index 299590ba5..252541b66 100644
--- a/src/crewai/utilities/evaluators/task_evaluator.py
+++ b/src/crewai/utilities/evaluators/task_evaluator.py
@@ -5,6 +5,17 @@ from pydantic import BaseModel, Field
 
 from crewai.utilities import Converter
 from crewai.utilities.pydantic_schema_parser import PydanticSchemaParser
+agentops = None
+try:
+    import agentops
+    from agentops import track_agent
+except ImportError:
+
+    def track_agent(name):
+        def noop(f):
+            return f
+
+        return noop
 
 
 class Entity(BaseModel):
@@ -38,6 +49,7 @@ class TrainingTaskEvaluation(BaseModel):
     )
 
 
+@track_agent(name="Task Evaluator")
 class TaskEvaluator:
     def __init__(self, original_agent):
         self.llm = original_agent.llm
diff --git a/src/crewai/utilities/logger.py b/src/crewai/utilities/logger.py
index e0c74d5ce..b54595c9c 100644
--- a/src/crewai/utilities/logger.py
+++ b/src/crewai/utilities/logger.py
@@ -1,7 +1,7 @@
 from datetime import datetime
 
 from crewai.utilities.printer import Printer
-
+from datetime import datetime
 
 class Logger:
     _printer = Printer()