langgraph multi agent workflows

langgraph is a framework designed for the development and management of multi-agent workflows that utilize language models. it allows developers to create sophisticated applications where multiple agents collaborate to accomplish tasks, leveraging the capabilities of language models like gpt-3 or similar.

in this tutorial, we will cover the basics of creating a multi-agent workflow using langgraph, including setting up agents, defining their roles, and orchestrating the interactions between them.

prerequisites

1. **python**: ensure you have python installed.
2. **langgraph**: install langgraph via pip:
```bash
pip install langgraph
```
3. **openai api key**: if you are using openai's models, ensure you have an api key.

step 1: setting up your environment

first, let’s import the necessary components from langgraph. you’ll also need to set up your openai api key.

```python
import os
from langgraph import agent, workflow

set your openai api key
```

step 2: defining agents

you can create multiple agents, each with a specific role. for example, let’s create two agents: a researcher and a summarizer.

```python
class researcher(agent):
def act(self, input_question):
generate a response based on the input question
response = f"researching about: {input_question}."
return response

class summarizer(agent):
def act(self, research_output):
summarize the research output
summary = f"summary of the research: {research_output}."
return summary
```

step 3: creating a workflow

a workflow orchestrates the interaction between agents. we will create a workflow where the researcher gathers information and the summarizer condenses that information.

```python
class researchworkflow(workflow):
def __init__(self):
super().__init__()

def run(self, input_ques ...

#Langgraph #MultiAgentWorkflows #numpy
Langgraph
multi-agent workflows
automation
collaborative agents
task management
workflow optimization
AI integration
real-time communication
process automation
agent coordination
dataflow management
intelligent agents
distributed systems
workflow design
application interoperability