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fixed llamaindex and langgraph docs by adding entity_id as optional
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@sohamganatra
sohamganatra committed Aug 18, 2024
1 parent 29bd844 commit bb60869
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175 changes: 102 additions & 73 deletions docs/framework/langgraph.mdx
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Original file line number Diff line number Diff line change
Expand Up @@ -20,56 +20,83 @@ Ensure you have the necessary packages installed and connect your GitHub account
pip install composio-langgraph
# login to composio
composio login
# Connect your GitHub using command below, so agents can use it.
composio add github
# Check all different apps which you can connect with
composio apps
```
</CodeGroup>

### Goal: Use LangGraph Agent to Interact with Github using Composio

<Steps>
<Step title="Connect GitHub account">

- Connect user `Jessica` GitHub account to allow your agents to utilize GitHub functionalities.
<Tabs>
<Tab title="CLI">
<CodeGroup>
```bash Authenticate GitHub Account
composio add github -e "Jessica"
```
</CodeGroup>
</Tab>
<Tab title="Python">
<CodeGroup>
```python Authenticate GitHub Account
from composio_langgraph import ComposioToolSet, App

toolset = ComposioToolSet(entity_id="Jessica")

entity = toolset.get_entity()

request = entity.initiate_connection(App.GITHUB)

print(
f"Open this URL in your browser: {request.redirectUrl}"
)
```
</CodeGroup>
</Tab>
</Tabs>
</Step>

<Step title="Import Base Packages">

Prepare your environment by initializing necessary imports from LangGraph & LangChain for setting up your agent.
- Prepare your environment by initializing necessary imports from LangGraph & LangChain for setting up your agent.

<CodeGroup>
```python Default Imports
from typing import Literal
```python Default Imports
from typing import Literal

from langchain_openai import ChatOpenAI
from langgraph.graph import MessagesState, StateGraph
from langgraph.prebuilt import ToolNode
```
from langchain_openai import ChatOpenAI
from langgraph.graph import MessagesState, StateGraph
from langgraph.prebuilt import ToolNode
```
</CodeGroup>

</Step>

<Step title="Fetch GitHub LangGraph Tools via Composio">

Access GitHub tools provided by Composio for LangGraph, initialize a `ToolNode` with necessary tools obtaned from `ComposioToolSet`.
- Access GitHub tools provided by Composio for LangGraph, initialize a `ToolNode` with necessary tools obtaned from `ComposioToolSet`.

<CodeGroup>
```python Get tools
from composio_langgraph import Action, ComposioToolSet

# Initialize the toolset for GitHub
composio_toolset = ComposioToolSet()
tools = composio_toolset.get_actions(
actions=[
Action.GITHUB_ACTIVITY_STAR_REPO_FOR_AUTHENTICATED_USER,
Action.GITHUB_USERS_GET_AUTHENTICATED,
])
tool_node = ToolNode(tools)
```
```python Get tools
from composio_langgraph import Action, ComposioToolSet

# Initialize the toolset for GitHub
composio_toolset = ComposioToolSet(entity_id="Jessica")
tools = composio_toolset.get_actions(
actions=[
Action.GITHUB_ACTIVITY_STAR_REPO_FOR_AUTHENTICATED_USER,
Action.GITHUB_USERS_GET_AUTHENTICATED,
])
tool_node = ToolNode(tools)
```
</CodeGroup>

</Step>

<Step title="Prepare the model">

Initialize the LLM class and bind obtained functions to the model.
- Initialize the LLM class and bind obtained functions to the model.

<CodeGroup>
```python Define model
Expand All @@ -83,49 +110,51 @@ Initialize the LLM class and bind obtained functions to the model.

<Step title="Define the Graph Nodes">

LangGraph expects you to define different nodes of the agentic workflow as separate functions. Here we define a node for calling the LLM model.
- LangGraph expects you to define different nodes of the agentic workflow as separate functions.

<CodeGroup>
```python Define nodes
def call_model(state: MessagesState):
messages = state["messages"]
response = model_with_tools.invoke(messages)
return {"messages": [response]}
```
```python Define nodes
def call_model(state: MessagesState):
messages = state["messages"]
response = model_with_tools.invoke(messages)
return {"messages": [response]}
```
</CodeGroup>

</Step>


<Step title="Define the Graph Nodes and Edges">

To establish the agent's workflow, we begin by initializing the workflow with `agent` and `tools` nodes, followed by specifying the connecting edges between nodes, finally compiling the workflow. These edges can be straightforward or conditional, depending on the workflow requirements.

<CodeGroup>
```python Define edges
def should_continue(state: MessagesState) -> Literal["tools", "__end__"]:
messages = state["messages"]
last_message = messages[-1]
if last_message.tool_calls:
return "tools"
return "__end__"

- We begin by initializing the workflow with `agent` and `tools` nodes, followed by specifying the connecting edges between nodes, finally compiling the workflow.

workflow = StateGraph(MessagesState)
- These edges can be straightforward or conditional, depending on the workflow requirements.

# Define the two nodes we will cycle between
workflow.add_node("agent", call_model)
workflow.add_node("tools", tool_node)

workflow.add_edge("__start__", "agent")
workflow.add_conditional_edges(
"agent",
should_continue,
)
workflow.add_edge("tools", "agent")

app = workflow.compile()
```
<CodeGroup>
```python Define edges
def should_continue(state: MessagesState) -> Literal["tools", "__end__"]:
messages = state["messages"]
last_message = messages[-1]
if last_message.tool_calls:
return "tools"
return "__end__"


workflow = StateGraph(MessagesState)

# Define the two nodes we will cycle between
workflow.add_node("agent", call_model)
workflow.add_node("tools", tool_node)

workflow.add_edge("__start__", "agent")
workflow.add_conditional_edges(
"agent",
should_continue,
)
workflow.add_edge("tools", "agent")

app = workflow.compile()
```
</CodeGroup>

</Step>
Expand All @@ -134,24 +163,24 @@ To establish the agent's workflow, we begin by initializing the workflow with `a

<Step title="Invoke & Check Response">

After the compilation of workflow, we invoke the LLM with a task, and stream the response.
- After the compilation of workflow, we invoke the LLM with a task, and stream the response.

<CodeGroup>
```python Execute workflow
for chunk in app.stream(
{
"messages": [
(
"human",
# "Star the Github Repository composiohq/composio",
"Get my information.",
)
]
},
stream_mode="values",
):
chunk["messages"][-1].pretty_print()
```
```python Execute workflow
for chunk in app.stream(
{
"messages": [
(
"human",
# "Star the Github Repository composiohq/composio",
"Get my information.",
)
]
},
stream_mode="values",
):
chunk["messages"][-1].pretty_print()
```
</CodeGroup>

</Step>
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38 changes: 31 additions & 7 deletions docs/framework/llamaindex.mdx
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Original file line number Diff line number Diff line change
Expand Up @@ -18,17 +18,41 @@ These commands prepare your environment for seamless interaction between LlamaIn
<CodeGroup>
```bash Run Command
pip install composio-llamaindex
```
</CodeGroup>

<Steps>
<Step title="Connect GitHub account">

- Connect a user Jessica's Github account to allow your agents to utilize GitHub functionalities.
<Tabs>
<Tab title="CLI">
<CodeGroup>
```bash Authenticate GitHub Account
composio add github -e "Jessica"
```
</CodeGroup>
</Tab>
<Tab title="Python">
<CodeGroup>
```python Authenticate Jessica's GitHub Account
from composio_langgraph import ComposioToolSet, App

#Connect your Github so agents can use it
composio add github
toolset = ComposioToolSet(entity_id="Jessica")

#Check all different apps which you can connect with
composio apps
entity = toolset.get_entity()

```
request = entity.initiate_connection(App.GITHUB)

print(
f"Open this URL in your browser: {request.redirectUrl}"
)
```
</CodeGroup>
</Tab>
</Tabs>
</Step>

<Steps>
<Step title="Import Base Packages">
<CodeGroup>
```python Default Imports
Expand All @@ -54,7 +78,7 @@ These commands prepare your environment for seamless interaction between LlamaIn

# Get All the tools

composio_toolset = ComposioToolSet()
composio_toolset = ComposioToolSet(entity_id="Jessica")
tools = composio_toolset.get_tools(apps=[App.GITHUB])
```
</CodeGroup>
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