Add Elasticsearch integration for RAG storage

Co-Authored-By: Joe Moura <joao@crewai.com>

docs/how-to/elasticsearch-integration.md

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+# Elasticsearch Integration
+
+CrewAI supports using Elasticsearch as an alternative to ChromaDB for RAG (Retrieval Augmented Generation) storage. This allows you to leverage Elasticsearch's powerful search capabilities and scalability for your AI agents.
+
+## Installation
+
+To use Elasticsearch with CrewAI, you need to install the Elasticsearch Python client:
+
+```bash
+pip install elasticsearch
+```
+
+## Using Elasticsearch for Memory
+
+You can configure your crew to use Elasticsearch for memory storage:
+
+```python
+from crewai import Agent, Crew, Task
+
+# Create agents and tasks
+agent = Agent(
+    role="Researcher",
+    goal="Research a topic",
+    backstory="You are a researcher who loves to find information.",
+)
+
+task = Task(
+    description="Research about AI",
+    expected_output="Information about AI",
+    agent=agent,
+)
+
+# Create a crew with Elasticsearch memory
+crew = Crew(
+    agents=[agent],
+    tasks=[task],
+    memory_config={
+        "provider": "elasticsearch",
+        "host": "localhost",  # Optional, defaults to localhost
+        "port": 9200,         # Optional, defaults to 9200
+        "username": "user",   # Optional
+        "password": "pass",   # Optional
+    },
+)
+
+# Execute the crew
+result = crew.kickoff()
+```
+
+## Using Elasticsearch for Knowledge
+
+You can also use Elasticsearch for knowledge storage:
+
+```python
+from crewai import Agent, Crew, Task
+from crewai.knowledge import Knowledge
+from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSource
+
+# Create knowledge with Elasticsearch storage
+content = "AI is a field of computer science that focuses on creating machines that can perform tasks that typically require human intelligence."
+string_source = StringKnowledgeSource(
+    content=content, metadata={"topic": "AI"}
+)
+
+knowledge = Knowledge(
+    collection_name="test",
+    sources=[string_source],
+    storage_provider="elasticsearch",  # Use Elasticsearch
+    # Optional Elasticsearch configuration
+    host="localhost",
+    port=9200,
+    username="user",
+    password="pass",
+)
+
+# Create an agent with the knowledge
+agent = Agent(
+    role="AI Expert",
+    goal="Explain AI",
+    backstory="You are an AI expert who loves to explain AI concepts.",
+    knowledge=[knowledge],
+)
+
+# Create a task
+task = Task(
+    description="Explain what AI is",
+    expected_output="Explanation of AI",
+    agent=agent,
+)
+
+# Create a crew
+crew = Crew(
+    agents=[agent],
+    tasks=[task],
+)
+
+# Execute the crew
+result = crew.kickoff()
+```
+
+## Configuration Options
+
+The Elasticsearch integration supports the following configuration options:
+
+- `host`: Elasticsearch host (default: "localhost")
+- `port`: Elasticsearch port (default: 9200)
+- `username`: Elasticsearch username (optional)
+- `password`: Elasticsearch password (optional)
+- Additional keyword arguments are passed directly to the Elasticsearch client
+
+## Running Tests
+
+To run the Elasticsearch tests, you need to set the `RUN_ELASTICSEARCH_TESTS` environment variable to `true`:
+
+```bash
+RUN_ELASTICSEARCH_TESTS=true pytest tests/memory/elasticsearch_storage_test.py tests/knowledge/elasticsearch_knowledge_storage_test.py tests/integration/elasticsearch_integration_test.py
+```