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Harrison Chase
2024-06-26 21:56:31 -07:00
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docs/docs/cloud/quick_start.md
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@@ -23,15 +23,15 @@ This tutorial will use:
2. The `agent.py` file should contain Python code for defining your graph. The following code is a simple example, the important thing is that at some point in your file you compile your graph and assign the compiled graph to a variable (in this case the `graph` variable). This example code uses `create_react_agent`, a prebuilt agent, read more about it [here](..//concepts/agentic_concepts.md#react-agent).
```python
from langchain_anthropic import ChatAnthropic
from langchain_community.tools.tavily_search import TavilySearchResults
from langgraph.prebuilt import create_react_agent
from langchain_anthropic import ChatAnthropic
from langchain_community.tools.tavily_search import TavilySearchResults
from langgraph.prebuilt import create_react_agent
model = ChatAnthropic(model="claude-3-5-sonnet-20240620")
model = ChatAnthropic(model="claude-3-5-sonnet-20240620")
tools = [TavilySearchResults(max_results=2)]
tools = [TavilySearchResults(max_results=2)]
graph = create_react_agent(model, tools)
graph = create_react_agent(model, tools)
```
3. The `requirements.txt` file should contain any dependencies for your graph(s). In this case we only require four packages for our graph to run:
@@ -231,8 +231,6 @@ async for chunk in client.runs.stream(
{'agent': {'messages': [{'content': "Hi Bagatur! It's nice to meet you. How can I assist you today?", 'additional_kwargs': {}, 'response_metadata': {'finish_reason': 'stop', 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_9cb5d38cf7'}, 'type': 'ai', 'name': None, 'id': 'run-c89118b7-1b1e-42b9-a85d-c43fe99881cd', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [], 'usage_metadata': None}]}}
You can learn more about the Python SDK in [this how-to guide](./sdk/python_sdk.ipynb), and read up on the Javascript SDK in [this how-to guide](./sdk/js_sdk.ipynb)
## What's Next
Congratulations! If you've worked your way through this tutorial you are well on your way to becoming a LangGraph Cloud expert. Here are some other resources to check out to help you out on the path to expertise: