docs: update memory docs and images in readme (#2898)

README.md

@@ -1,7 +1,6 @@
 <div align="center">
 
-![Logo of CrewAI](./docs/crewai_logo.png)
-
+![Logo of CrewAI](./docs/images/crewai_logo.png)
 
 </div>
 
@@ -27,6 +26,7 @@ that require secure, scalable, and easy-to-manage agent-driven automation.
 You can try one part of the suite the [Crew Control Plane for free](https://app.crewai.com)
 
 ## Crew Control Plane Key Features:
+
 - **Tracing & Observability**: Monitor and track your AI agents and workflows in real-time, including metrics, logs, and traces.
 - **Unified Control Plane**: A centralized platform for managing, monitoring, and scaling your AI agents and workflows.
 - **Seamless Integrations**: Easily connect with existing enterprise systems, data sources, and cloud infrastructure.
@@ -73,7 +73,7 @@ intelligent automations.
 ## Why CrewAI?
 
 <div align="center" style="margin-bottom: 30px;">
-  <img src="docs/asset.png" alt="CrewAI Logo" width="100%">
+  <img src="docs/images/asset.png" alt="CrewAI Logo" width="100%">
 </div>
 
 CrewAI unlocks the true potential of multi-agent automation, delivering the best-in-class combination of speed, flexibility, and control with either Crews of AI Agents or Flows of Events:
@@ -91,6 +91,7 @@ CrewAI empowers developers and enterprises to confidently build intelligent auto
 ### Learning Resources
 
 Learn CrewAI through our comprehensive courses:
+
 - [Multi AI Agent Systems with CrewAI](https://www.deeplearning.ai/short-courses/multi-ai-agent-systems-with-crewai/) - Master the fundamentals of multi-agent systems
 - [Practical Multi AI Agents and Advanced Use Cases](https://www.deeplearning.ai/short-courses/practical-multi-ai-agents-and-advanced-use-cases-with-crewai/) - Deep dive into advanced implementations
 
@@ -99,18 +100,20 @@ Learn CrewAI through our comprehensive courses:
 CrewAI offers two powerful, complementary approaches that work seamlessly together to build sophisticated AI applications:
 
 1. **Crews**: Teams of AI agents with true autonomy and agency, working together to accomplish complex tasks through role-based collaboration. Crews enable:
+
    - Natural, autonomous decision-making between agents
    - Dynamic task delegation and collaboration
    - Specialized roles with defined goals and expertise
    - Flexible problem-solving approaches
-
 2. **Flows**: Production-ready, event-driven workflows that deliver precise control over complex automations. Flows provide:
+
    - Fine-grained control over execution paths for real-world scenarios
    - Secure, consistent state management between tasks
    - Clean integration of AI agents with production Python code
    - Conditional branching for complex business logic
 
 The true power of CrewAI emerges when combining Crews and Flows. This synergy allows you to:
+
 - Build complex, production-grade applications
 - Balance autonomy with precise control
 - Handle sophisticated real-world scenarios
@@ -129,11 +132,13 @@ First, install CrewAI:
 ```shell
 pip install crewai
 ```
+
 If you want to install the 'crewai' package along with its optional features that include additional tools for agents, you can do so by using the following command:
 
 ```shell
 pip install 'crewai[tools]'
 ```
+
 The command above installs the basic package and also adds extra components which require more dependencies to function.
 
 ### Troubleshooting Dependencies
@@ -143,10 +148,11 @@ If you encounter issues during installation or usage, here are some common solut
 #### Common Issues
 
 1. **ModuleNotFoundError: No module named 'tiktoken'**
+
    - Install tiktoken explicitly: `pip install 'crewai[embeddings]'`
    - If using embedchain or other tools: `pip install 'crewai[tools]'`
-
 2. **Failed building wheel for tiktoken**
+
    - Ensure Rust compiler is installed (see installation steps above)
    - For Windows: Verify Visual C++ Build Tools are installed
    - Try upgrading pip: `pip install --upgrade pip`
@@ -407,7 +413,8 @@ You can test different real life examples of AI crews in the [CrewAI-examples re
 
 CrewAI's power truly shines when combining Crews with Flows to create sophisticated automation pipelines.
 CrewAI flows support logical operators like `or_` and `and_` to combine multiple conditions. This can be used with `@start`, `@listen`, or `@router` decorators to create complex triggering conditions.
-- `or_`: Triggers when any of the specified conditions are met. 
+
+- `or_`: Triggers when any of the specified conditions are met.
 - `and_`Triggers when all of the specified conditions are met.
 
 Here's how you can orchestrate multiple Crews within a Flow:
@@ -495,6 +502,7 @@ class AdvancedAnalysisFlow(Flow[MarketState]):
 ```
 
 This example demonstrates how to:
+
 1. Use Python code for basic data operations
 2. Create and execute Crews as steps in your workflow
 3. Use Flow decorators to manage the sequence of operations
@@ -515,7 +523,6 @@ Please refer to the [Connect CrewAI to LLMs](https://docs.crewai.com/how-to/LLM-
 *P.S. CrewAI demonstrates significant performance advantages over LangGraph, executing 5.76x faster in certain cases like this QA task example ([see comparison](https://github.com/crewAIInc/crewAI-examples/tree/main/Notebooks/CrewAI%20Flows%20%26%20Langgraph/QA%20Agent)) while achieving higher evaluation scores with faster completion times in certain coding tasks, like in this example ([detailed analysis](https://github.com/crewAIInc/crewAI-examples/blob/main/Notebooks/CrewAI%20Flows%20%26%20Langgraph/Coding%20Assistant/coding_assistant_eval.ipynb)).*
 
 - **Autogen**: While Autogen excels at creating conversational agents capable of working together, it lacks an inherent concept of process. In Autogen, orchestrating agents' interactions requires additional programming, which can become complex and cumbersome as the scale of tasks grows.
-
 - **ChatDev**: ChatDev introduced the idea of processes into the realm of AI agents, but its implementation is quite rigid. Customizations in ChatDev are limited and not geared towards production environments, which can hinder scalability and flexibility in real-world applications.
 
 ## Contribution
@@ -606,10 +613,10 @@ Users can opt-in to Further Telemetry, sharing the complete telemetry data by se
 
 CrewAI is released under the [MIT License](https://github.com/crewAIInc/crewAI/blob/main/LICENSE).
 
-
 ## Frequently Asked Questions (FAQ)
 
 ### General
+
 - [What exactly is CrewAI?](#q-what-exactly-is-crewai)
 - [How do I install CrewAI?](#q-how-do-i-install-crewai)
 - [Does CrewAI depend on LangChain?](#q-does-crewai-depend-on-langchain)
@@ -617,6 +624,7 @@ CrewAI is released under the [MIT License](https://github.com/crewAIInc/crewAI/b
 - [Does CrewAI collect data from users?](#q-does-crewai-collect-data-from-users)
 
 ### Features and Capabilities
+
 - [Can CrewAI handle complex use cases?](#q-can-crewai-handle-complex-use-cases)
 - [Can I use CrewAI with local AI models?](#q-can-i-use-crewai-with-local-ai-models)
 - [What makes Crews different from Flows?](#q-what-makes-crews-different-from-flows)
@@ -624,84 +632,110 @@ CrewAI is released under the [MIT License](https://github.com/crewAIInc/crewAI/b
 - [Does CrewAI support fine-tuning or training custom models?](#q-does-crewai-support-fine-tuning-or-training-custom-models)
 
 ### Resources and Community
+
 - [Where can I find real-world CrewAI examples?](#q-where-can-i-find-real-world-crewai-examples)
 - [How can I contribute to CrewAI?](#q-how-can-i-contribute-to-crewai)
 
 ### Enterprise Features
+
 - [What additional features does CrewAI Enterprise offer?](#q-what-additional-features-does-crewai-enterprise-offer)
 - [Is CrewAI Enterprise available for cloud and on-premise deployments?](#q-is-crewai-enterprise-available-for-cloud-and-on-premise-deployments)
 - [Can I try CrewAI Enterprise for free?](#q-can-i-try-crewai-enterprise-for-free)
 
-
-
 ### Q: What exactly is CrewAI?
+
 A: CrewAI is a standalone, lean, and fast Python framework built specifically for orchestrating autonomous AI agents. Unlike frameworks like LangChain, CrewAI does not rely on external dependencies, making it leaner, faster, and simpler.
 
 ### Q: How do I install CrewAI?
+
 A: Install CrewAI using pip:
+
 ```shell
 pip install crewai
 ```
+
 For additional tools, use:
+
 ```shell
 pip install 'crewai[tools]'
 ```
+
 ### Q: Does CrewAI depend on LangChain?
+
 A: No. CrewAI is built entirely from the ground up, with no dependencies on LangChain or other agent frameworks. This ensures a lean, fast, and flexible experience.
 
 ### Q: Can CrewAI handle complex use cases?
+
 A: Yes. CrewAI excels at both simple and highly complex real-world scenarios, offering deep customization options at both high and low levels, from internal prompts to sophisticated workflow orchestration.
 
 ### Q: Can I use CrewAI with local AI models?
+
 A: Absolutely! CrewAI supports various language models, including local ones. Tools like Ollama and LM Studio allow seamless integration. Check the [LLM Connections documentation](https://docs.crewai.com/how-to/LLM-Connections/) for more details.
 
 ### Q: What makes Crews different from Flows?
+
 A: Crews provide autonomous agent collaboration, ideal for tasks requiring flexible decision-making and dynamic interaction. Flows offer precise, event-driven control, ideal for managing detailed execution paths and secure state management. You can seamlessly combine both for maximum effectiveness.
 
 ### Q: How is CrewAI better than LangChain?
+
 A: CrewAI provides simpler, more intuitive APIs, faster execution speeds, more reliable and consistent results, robust documentation, and an active community—addressing common criticisms and limitations associated with LangChain.
 
 ### Q: Is CrewAI open-source?
+
 A: Yes, CrewAI is open-source and actively encourages community contributions and collaboration.
 
 ### Q: Does CrewAI collect data from users?
+
 A: CrewAI collects anonymous telemetry data strictly for improvement purposes. Sensitive data such as prompts, tasks, or API responses are never collected unless explicitly enabled by the user.
 
 ### Q: Where can I find real-world CrewAI examples?
+
 A: Check out practical examples in the [CrewAI-examples repository](https://github.com/crewAIInc/crewAI-examples), covering use cases like trip planners, stock analysis, and job postings.
 
 ### Q: How can I contribute to CrewAI?
+
 A: Contributions are warmly welcomed! Fork the repository, create your branch, implement your changes, and submit a pull request. See the Contribution section of the README for detailed guidelines.
 
 ### Q: What additional features does CrewAI Enterprise offer?
+
 A: CrewAI Enterprise provides advanced features such as a unified control plane, real-time observability, secure integrations, advanced security, actionable insights, and dedicated 24/7 enterprise support.
 
 ### Q: Is CrewAI Enterprise available for cloud and on-premise deployments?
+
 A: Yes, CrewAI Enterprise supports both cloud-based and on-premise deployment options, allowing enterprises to meet their specific security and compliance requirements.
 
 ### Q: Can I try CrewAI Enterprise for free?
+
 A: Yes, you can explore part of the CrewAI Enterprise Suite by accessing the [Crew Control Plane](https://app.crewai.com) for free.
 
 ### Q: Does CrewAI support fine-tuning or training custom models?
+
 A: Yes, CrewAI can integrate with custom-trained or fine-tuned models, allowing you to enhance your agents with domain-specific knowledge and accuracy.
 
 ### Q: Can CrewAI agents interact with external tools and APIs?
+
 A: Absolutely! CrewAI agents can easily integrate with external tools, APIs, and databases, empowering them to leverage real-world data and resources.
 
 ### Q: Is CrewAI suitable for production environments?
+
 A: Yes, CrewAI is explicitly designed with production-grade standards, ensuring reliability, stability, and scalability for enterprise deployments.
 
 ### Q: How scalable is CrewAI?
+
 A: CrewAI is highly scalable, supporting simple automations and large-scale enterprise workflows involving numerous agents and complex tasks simultaneously.
 
 ### Q: Does CrewAI offer debugging and monitoring tools?
+
 A: Yes, CrewAI Enterprise includes advanced debugging, tracing, and real-time observability features, simplifying the management and troubleshooting of your automations.
 
 ### Q: What programming languages does CrewAI support?
+
 A: CrewAI is primarily Python-based but easily integrates with services and APIs written in any programming language through its flexible API integration capabilities.
 
 ### Q: Does CrewAI offer educational resources for beginners?
+
 A: Yes, CrewAI provides extensive beginner-friendly tutorials, courses, and documentation through learn.crewai.com, supporting developers at all skill levels.
 
 ### Q: Can CrewAI automate human-in-the-loop workflows?
+
 A: Yes, CrewAI fully supports human-in-the-loop workflows, allowing seamless collaboration between human experts and AI agents for enhanced decision-making.