Langchain Example update (#328)
Small update to reflect some changes to the `langchain-arcade` package in the last release. --------- Co-authored-by: Eric Gustin <34000337+EricGustin@users.noreply.github.com>
This commit is contained in:
Sam Partee
GitHub
parent
89a009d1af
commit
13a01254df
2 changed files with 59 additions and 34 deletions
85
README.md
85
README.md
|
|
@ -196,7 +196,7 @@ To create a new toolkit, you can use the `arcade new` command. This will create
|
|||
The template is meant to be customized so feel free to change anything about the structure,
|
||||
package management, linting, etc.
|
||||
|
||||
4. **Show the tools in the template Toolkit:**
|
||||
3. **Show the tools in the template Toolkit:**
|
||||
|
||||
```bash
|
||||
# show the tools in Mytoolkit
|
||||
|
|
@ -359,47 +359,72 @@ Here's an example of how to use the Tools API with LangChain/Langgraph:
|
|||
|
||||
```python
|
||||
import os
|
||||
from langchain_arcade import ArcadeToolManager
|
||||
|
||||
from langchain_arcade import ToolManager
|
||||
from langchain_openai import ChatOpenAI
|
||||
from langgraph.checkpoint.memory import MemorySaver
|
||||
from langgraph.prebuilt import create_react_agent
|
||||
|
||||
arcade_api_key = os.environ["ARCADE_API_KEY"]
|
||||
openai_api_key = os.environ["OPENAI_API_KEY"]
|
||||
# 1) Set API keys (place your real keys in env variables or directly below)
|
||||
arcade_api_key = os.environ.get("ARCADE_API_KEY", "YOUR_ARCADE_API_KEY")
|
||||
openai_api_key = os.environ.get("OPENAI_API_KEY", "YOUR_OPENAI_API_KEY")
|
||||
|
||||
manager = ArcadeToolManager(api_key=arcade_api_key)
|
||||
tools = manager.get_tools(tools=["Mytoolkit.SayHello"])
|
||||
# 2) Create an ToolManager and fetch/add tools/toolkits
|
||||
manager = ToolManager(api_key=arcade_api_key)
|
||||
|
||||
model = ChatOpenAI(
|
||||
model="gpt-4o",
|
||||
api_key=openai_api_key,
|
||||
)
|
||||
# Tool names follow the format "ToolkitName.ToolName"
|
||||
tools = manager.init_tools(tools=["Web.ScrapeUrl"])
|
||||
print(manager.tools)
|
||||
|
||||
bound_model = model.bind_tools(tools)
|
||||
graph = create_react_agent(model=bound_model, tools=tools)
|
||||
# Get all tools from a toolkit
|
||||
tools = manager.init_tools(toolkits=["github"])
|
||||
print(manager.tools)
|
||||
|
||||
config = {
|
||||
"configurable": {
|
||||
"thread_id": "1",
|
||||
"user_id": "user@unique_id.com",
|
||||
}
|
||||
}
|
||||
user_input = {
|
||||
"messages": [
|
||||
{
|
||||
"role": "system",
|
||||
"content": "You are a helpful assistant",
|
||||
},
|
||||
{
|
||||
"role": "user",
|
||||
"content": "Say hello to Sam",
|
||||
},
|
||||
]
|
||||
}
|
||||
# add a tool
|
||||
manager.add_tool("Search.SearchGoogle")
|
||||
print(manager.tools)
|
||||
|
||||
# add a toolkit
|
||||
manager.add_toolkit("Search")
|
||||
print(manager.tools)
|
||||
|
||||
# 3) Get StructuredTool objects for langchain
|
||||
lc_tools = manager.to_langchain()
|
||||
|
||||
# 4) Create a ChatOpenAI model and bind the Arcade tools.
|
||||
model = ChatOpenAI(model="gpt-4o", api_key=openai_api_key)
|
||||
bound_model = model.bind_tools(lc_tools)
|
||||
|
||||
# 5) Use MemorySaver for checkpointing.
|
||||
memory = MemorySaver()
|
||||
|
||||
# 6) Create a ReAct-style agent from the prebuilt function.
|
||||
graph = create_react_agent(model=bound_model, tools=lc_tools, checkpointer=memory)
|
||||
|
||||
# 7) Provide basic config and a user query.
|
||||
# Note: user_id is required for the tool to be authorized
|
||||
config = {"configurable": {"thread_id": "1", "user_id": "user@example.com"}}
|
||||
user_input = {"messages": [("user", "star the arcadeai/arcade-ai repo on github")]}
|
||||
|
||||
# 8) Stream the agent's output. If the tool is unauthorized, it may trigger interrupts
|
||||
for chunk in graph.stream(user_input, config, stream_mode="values"):
|
||||
chunk["messages"][-1].pretty_print()
|
||||
|
||||
# if we were interrupted, we can check for interrupts in state
|
||||
current_state = graph.get_state(config)
|
||||
if current_state.tasks:
|
||||
for task in current_state.tasks:
|
||||
if hasattr(task, "interrupts"):
|
||||
for interrupt in task.interrupts:
|
||||
print(interrupt.value)
|
||||
```
|
||||
|
||||
The last message may result in an authorization prompt.
|
||||
|
||||
If so, the user will need to authorize the tool by visiting the url in the response. Once authorized, running the
|
||||
same script will return the completed action since the tool will be authorized for that
|
||||
user.
|
||||
|
||||
### Arcade Auth API
|
||||
|
||||
The Auth API provides the lowest-level integration with Arcade, for when you only need Arcade's authentication capabilities. This API is ideal for:
|
||||
|
|
|
|||
|
|
@ -17,7 +17,7 @@ tools = manager.init_tools(tools=["Web.ScrapeUrl"])
|
|||
print(manager.tools)
|
||||
|
||||
# Get all tools from a toolkit
|
||||
tools = manager.init_tools(toolkits=["Google"])
|
||||
tools = manager.init_tools(toolkits=["github"])
|
||||
print(manager.tools)
|
||||
|
||||
# add a tool
|
||||
|
|
@ -43,11 +43,11 @@ graph = create_react_agent(model=bound_model, tools=lc_tools, checkpointer=memor
|
|||
|
||||
# 6) Provide basic config and a user query.
|
||||
# Note: user_id is required for the tool to be authorized
|
||||
config = {"configurable": {"thread_id": "1", "user_id": "userrerr@example.coom"}}
|
||||
user_input = {"messages": [("user", "List any new and important emails in my inbox.")]}
|
||||
config = {"configurable": {"thread_id": "1", "user_id": "user@example.com"}}
|
||||
user_input = {"messages": [("user", "star the arcadeai/arcade-ai repo on github")]}
|
||||
|
||||
# 7) Stream the agent's output. If the tool is unauthorized, it may trigger interrupts
|
||||
for chunk in graph.stream(user_input, config, stream_mode="values", debug=True):
|
||||
for chunk in graph.stream(user_input, config, stream_mode="values"):
|
||||
chunk["messages"][-1].pretty_print()
|
||||
|
||||
# if we were interrupted, we can check for interrupts in state
|
||||
|
|
|
|||
Loading…
Reference in a new issue