glean-agent-toolkit 0.2.0

AI Agent toolkit for adapting Glean's enterprise tools across multiple frameworks

Glean Agent Toolkit

The Glean Agent Toolkit makes it easy to integrate Glean's powerful search and knowledge discovery capabilities into your AI agents. Use our pre-built tools with popular agent frameworks like OpenAI Assistants, LangChain, CrewAI, and Google's Agent Development Kit (ADK), or adapt your own custom tools for cross-framework use.

Key Features

• Production-Ready Glean Tools: Instantly add capabilities like enterprise search, employee lookup, calendar search, Gmail search, and more to your agents.
• Framework Adapters: Seamlessly convert Glean tools into formats compatible with major agent SDKs.
• Custom Tool Creation: Define your own tools once using the @tool_spec decorator and use them across any supported framework.

Installation

Install the base toolkit:

pip install glean-agent-toolkit

To include support for specific agent frameworks, install the relevant extras:

pip install glean-agent-toolkit[openai]
pip install glean-agent-toolkit[adk]
pip install glean-agent-toolkit[langchain]
pip install glean-agent-toolkit[crewai]

You can also install all extras:

pip install glean-agent-toolkit[all]

Note: The [openai] extra installs the standard openai Python library, used for direct API interactions like Chat Completions or the Assistants API. The example below for the "OpenAI Agents SDK" uses a separate library, openai-agents, which you'll need to install independently: pip install openai-agents.

Prerequisites

Before using any Glean tools, you'll need:

1. Glean API credentials: Obtain these from your Glean administrator
2. Environment variables:

   export GLEAN_API_TOKEN="your-api-token"
   export GLEAN_INSTANCE="your-instance-name"
   

Available Tools

The toolkit comes with a suite of production-ready tools that connect to various Glean functionalities:

• glean_search: Search your company's knowledge base for relevant documents and information
• web_search: Search the public web for up-to-date external information
• ai_web_search: Query Google Gemini for AI-powered web information
• calendar_search: Find meetings and calendar events
• employee_search: Search for employees by name, team, department, or expertise
• code_search: Search your company's source code repositories
• gmail_search: Search Gmail messages and conversations
• outlook_search: Search Outlook mail and calendar items

Quick Start Examples

Using glean_search with Different Frameworks

OpenAI Agents SDK

import os
from glean.agent_toolkit.tools import glean_search
from agents import Agent, Runner

# Ensure environment variables are set
assert os.getenv("GLEAN_API_TOKEN"), "GLEAN_API_TOKEN must be set"
assert os.getenv("GLEAN_INSTANCE"), "GLEAN_INSTANCE must be set"
assert os.getenv("OPENAI_API_KEY"), "OPENAI_API_KEY must be set"

# Create an agent with the Glean search tool
agent = Agent(
    name="KnowledgeAssistant",
    instructions="You help users find information from the company knowledge base using Glean search.",
    tools=[glean_search.func]  # Use the underlying function
)

# Run a search query
result = Runner.run_sync(agent, "Find our Q4 planning documents")
print(f"Search results: {result.final_output}")

LangChain

import os
from glean.agent_toolkit.tools import glean_search
from langchain_openai import ChatOpenAI
from langchain.agents import AgentExecutor, create_react_agent
from langchain_core.prompts import ChatPromptTemplate

# Ensure environment variables are set
assert os.getenv("GLEAN_API_TOKEN"), "GLEAN_API_TOKEN must be set"
assert os.getenv("GLEAN_INSTANCE"), "GLEAN_INSTANCE must be set"

# Convert to LangChain tool format
langchain_tool = glean_search.as_langchain_tool()

llm = ChatOpenAI(model="gpt-4", temperature=0)
tools = [langchain_tool]

prompt_template = """You are a helpful assistant with access to company knowledge.
Use the glean_search tool to find relevant information when users ask questions.

Tools available:
{tools}

Use this format:
Question: {input}
Thought: I should search for information about this topic
Action: {tool_names}
Action Input: your search query
Observation: the search results
Thought: I can now provide a helpful response
Final Answer: your response based on the search results

Question: {input}
{agent_scratchpad}"""

prompt = ChatPromptTemplate.from_template(prompt_template)
agent = create_react_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)

# Search for company information
result = agent_executor.invoke({"input": "What is our vacation policy?"})
print(result["output"])

CrewAI

import os
from glean.agent_toolkit.tools import glean_search
from crewai import Agent, Task, Crew

# Ensure environment variables are set
assert os.getenv("GLEAN_API_TOKEN"), "GLEAN_API_TOKEN must be set"
assert os.getenv("GLEAN_INSTANCE"), "GLEAN_INSTANCE must be set"

# Convert to CrewAI tool format
crewai_tool = glean_search.as_crewai_tool()

# Create a research agent
researcher = Agent(
    role="Corporate Knowledge Researcher",
    goal="Find and summarize relevant company information",
    backstory="You are an expert at navigating company knowledge bases to find accurate, up-to-date information.",
    tools=[crewai_tool],
    verbose=True
)

# Create a research task
research_task = Task(
    description="Find information about our company's remote work policy and summarize the key points.",
    expected_output="A clear summary of the remote work policy including eligibility, expectations, and guidelines.",
    agent=researcher
)

# Execute the research
crew = Crew(agents=[researcher], tasks=[research_task])
result = crew.kickoff()
print(result)

Real-World Use Cases

Employee Directory Search

from glean.agent_toolkit.tools import employee_search

# Find engineering team members
engineering_team = employee_search.as_langchain_tool()

# Example usage in an agent:
# "Who are the senior engineers in the backend team?"
# "Find Sarah Johnson's contact information"
# "List all product managers in the San Francisco office"

Code Discovery

from glean.agent_toolkit.tools import code_search

# Search company codebases
code_tool = code_search.as_langchain_tool()

# Example queries:
# "Find authentication middleware implementations"
# "Show me recent changes to the payment processing module"
# "Locate configuration files for the staging environment"

Email and Calendar Integration

from glean.agent_toolkit.tools import gmail_search, calendar_search

# Search emails and meetings
gmail_tool = gmail_search.as_langchain_tool()
calendar_tool = calendar_search.as_langchain_tool()

# Example queries:
# "Find emails about the product launch from last month"
# "Show me my meetings with the design team this week"
# "Search for messages containing budget discussions"

Web Research with Context

from glean.agent_toolkit.tools import web_search, ai_web_search

# External information gathering
web_tool = web_search.as_langchain_tool()
ai_web_tool = ai_web_search.as_langchain_tool()

# Example queries:
# "Latest industry trends in machine learning"
# "Current market analysis for SaaS companies"
# "Recent news about our competitors"

Creating Custom Tools with @tool_spec

Define your own tools that work across all supported frameworks:

from glean.agent_toolkit import tool_spec
from pydantic import BaseModel
import requests

class WeatherResponse(BaseModel):
    temperature: float
    condition: str
    humidity: int
    city: str

@tool_spec(
    name="get_current_weather",
    description="Get current weather information for a specified city",
    output_model=WeatherResponse
)
def get_weather(city: str, units: str = "celsius") -> WeatherResponse:
    """Fetch current weather for a city."""
    # Replace with actual weather API call
    api_key = os.getenv("WEATHER_API_KEY")
    response = requests.get(
        f"https://api.weather.com/v1/current?key={api_key}&q={city}&units={units}"
    )
    data = response.json()
    
    return WeatherResponse(
        temperature=data["temp"],
        condition=data["condition"],
        humidity=data["humidity"],
        city=city
    )

# Use across frameworks
openai_weather = get_weather.as_openai_tool()
langchain_weather = get_weather.as_langchain_tool()
crewai_weather = get_weather.as_crewai_tool()

Contributing

Interested in contributing? Check out our Contributing Guide for instructions on setting up the development environment and submitting changes.

License

This project is licensed under the MIT License.