Feature: Documentation Site (#188)

docs/getting-started.md

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+# Getting Started
+
+To get started with CrewAI, follow these simple steps:
+
+1. **Installation**:
+
+```shell
+pip install crewai
+```
+
+The example below also uses duckduckgo, so also install that
+```shell
+pip install duckduckgo-search
+```
+
+2. **Setting Up Your Crew**:
+
+```python
+import os
+from crewai import Agent, Task, Crew, Process
+
+os.environ["OPENAI_API_KEY"] = "YOUR KEY"
+
+# You can choose to use a local model through Ollama for example. See ./docs/llm-connections.md for more information.
+# from langchain.llms import Ollama
+# ollama_llm = Ollama(model="openhermes")
+
+# Install duckduckgo-search for this example:
+# !pip install -U duckduckgo-search
+
+from langchain.tools import DuckDuckGoSearchRun
+search_tool = DuckDuckGoSearchRun()
+
+# Define your agents with roles and goals
+researcher = Agent(
+  role='Senior Research Analyst',
+  goal='Uncover cutting-edge developments in AI and data science',
+  backstory="""You work at a leading tech think tank.
+  Your expertise lies in identifying emerging trends.
+  You have a knack for dissecting complex data and presenting
+  actionable insights.""",
+  verbose=True,
+  allow_delegation=False,
+  tools=[search_tool]
+  # You can pass an optional llm attribute specifying what mode you wanna use.
+  # It can be a local model through Ollama / LM Studio or a remote
+  # model like OpenAI, Mistral, Antrophic of others (https://python.langchain.com/docs/integrations/llms/)
+  #
+  # Examples:
+  # llm=ollama_llm # was defined above in the file
+  # llm=ChatOpenAI(model_name="gpt-3.5", temperature=0.7)
+)
+writer = Agent(
+  role='Tech Content Strategist',
+  goal='Craft compelling content on tech advancements',
+  backstory="""You are a renowned Content Strategist, known for
+  your insightful and engaging articles.
+  You transform complex concepts into compelling narratives.""",
+  verbose=True,
+  allow_delegation=True,
+  # (optional) llm=ollama_llm
+)
+
+# Create tasks for your agents
+task1 = Task(
+  description="""Conduct a comprehensive analysis of the latest advancements in AI in 2024.
+  Identify key trends, breakthrough technologies, and potential industry impacts.
+  Your final answer MUST be a full analysis report""",
+  agent=researcher
+)
+
+task2 = Task(
+  description="""Using the insights provided, develop an engaging blog
+  post that highlights the most significant AI advancements.
+  Your post should be informative yet accessible, catering to a tech-savvy audience.
+  Make it sound cool, avoid complex words so it doesn't sound like AI.
+  Your final answer MUST be the full blog post of at least 4 paragraphs.""",
+  agent=writer
+)
+
+# Instantiate your crew with a sequential process
+crew = Crew(
+  agents=[researcher, writer],
+  tasks=[task1, task2],
+  verbose=2, # You can set it to 1 or 2 to different logging levels
+)
+
+# Get your crew to work!
+result = crew.kickoff()
+
+print("######################")
+print(result)
+```
+
+Currently the only supported process is `Process.sequential`, where one task is executed after the other and the outcome of one is passed as extra content into this next.