Contact Data
Cognism
Cognism
Provides GDPR-compliant B2B contact data and prospecting solutions.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet()
tools = composio_toolset.get_tools(apps=[App.COGNISM])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["COGNISM"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Apollo.io
Apollo.io
A sales intelligence platform for finding leads and automating outbound workflows.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['APOLLO'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["APOLLO"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Zoominfo
Zoominfo
Offers comprehensive contact and company information for sales and marketing teams.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['ZOOMINFO'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["ZOOMINFO"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
RocketReach
RocketReach
Delivers verified email addresses and contact details for professionals worldwide.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['ROCKET_REACH'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["ROCKET_REACH"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Uplead
Uplead
A B2B lead generation platform with real-time data enrichment.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['UPLEAD'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["UPLEAD"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
G2
G2
A platform for discovering and comparing software solutions based on user reviews.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['G2'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["G2"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Sales Engagement
Salesloft
Salesloft
A sales engagement platform to streamline prospecting and customer outreach.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['SALESLOFT'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["CODE_ANALYSIS_TOOL_CREATE_CODE_MAP"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Outreach
Outreach
Enables sales teams to manage and optimize multi-channel engagement.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['OUTREACH'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-api-key>" });
const tools = await toolset.getTools({ apps: ["OUTREACH"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Gong
Gong
Analyzes sales calls and provides actionable insights to improve team performance.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['GONG'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["GONG"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Close
Close
A CRM designed for inside sales with built-in calling, email, and pipeline management.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['CLOSE'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["CLOSE"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Intent Data
Clearbit
Clearbit
Offers company data, intent signals, and enrichment for targeting prospects.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['CLEARBIT'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["CLEARBIT"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
6 Sense
6 Sense
Uses AI-powered intent data to identify and prioritize potential buyers.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['SIX_SENSE'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["SIX_SENSE"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
RB2B
RB2B
Helps identify buyer intent with data-driven insights for B2B marketing and sales.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['RB_TWOB'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["RB_TWOB"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Email Warmup
Instantly
Instantly
Improves email deliverability through warmup and automated outreach.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['INSTANTLY'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["INSTANTLY"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Lemwarm
Lemwarm
Optimizes inbox placement by simulating email interactions.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['LEMWARM'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["LEMWARM"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Mailreach
Mailreach
Helps improve email deliverability through personalized email warmup.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['MAILREACH'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["MAILREACH"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Lemlist
Lemlist
An email outreach platform with personalization and deliverability optimization features.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['LEMLIST'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["LEMLIST"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Warmly
Warmly
A tool to enhance deliverability and inbox performance for email campaigns.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['WARMLY'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["WARMLY"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Research and Personalization
Regie AI
Regie AI
Creates AI-powered personalized content for outreach and sales.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['REGIE_AI'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["REGIE_AI"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Jasper
Jasper
Generates AI-driven content for emails, blogs, and personalized messaging.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['JASPER'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["JASPER"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Clay
Clay
Automates lead research and creates hyper-personalized outreach.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['CLAY'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["CLAY"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Aomni
Aomni
Enables personalized outreach through AI-driven data aggregation.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['AOMNI'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["AOMNI"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
CrunchBase
CrunchBase
Provides business information for market research and sales prospecting.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['CRUNCHBASE'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["CRUNCHBASE"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
CBInsights
CBInsights
Delivers market intelligence and insights for business decision-making.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['CB_INSIGHTS'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["CB_INSIGHTS"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Enrichment
Seamless AI
Seamless AI
Offers real-time data enrichment for contacts and companies.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['SEAMLESS'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["SEAMLESS"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Clay
Clay
Combines enrichment and automation to create highly personalized outreach campaigns.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['CLAY'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["CLAY"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Lusha
Lusha
Simplifies B2B prospecting with enriched contact and company data.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['LUSHA'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["LUSHA"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Meetings
Calendly
Calendly
Simplifies scheduling by automating meeting bookings.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['CALENDLY'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["CALENDLY"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Chili Piper
Chili Piper
Streamlines inbound meeting scheduling and routing for sales teams.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['CHILI_PIPER'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["CHILI_PIPER"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Cal.com
Cal.com
Simplifies scheduling by automating meeting bookings.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['CAL'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["CAL"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Caller
Just Call
Just Call
A cloud-based phone system for managing sales and support calls.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['JUST_CALL'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["JUST_CALL"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Nooks
Nooks
Performs code formatting and linting using ruff, addressing style issues and checking for errors
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['NOOKS'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["NOOKS"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Dialpad
Dialpad
A unified communications platform with AI-powered calling and messaging.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['DIALPAD'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["DIALPAD"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Twilio
Twilio
Enables developers to integrate messaging, voice, and video in applications.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['TWILIO'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["TWILIO"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Orum
Orum
A tool for automated, AI-powered sales calling.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['ORUM'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["ORUM"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Linkedin Automation
Octopus
Octopus
Automates LinkedIn outreach, connection requests, and messaging.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['OCTOPUS'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["OCTOPUS"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Expand io
Expand io
Boosts LinkedIn prospecting with automated workflows.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['EXPAND'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["EXPAND"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
PhantomBuster
PhantomBuster
Extracts data and automates actions on LinkedIn and other platforms.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['PHANTOM_BUSTER'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["PHANTOM_BUSTER"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Dripify
Dripify
Simplifies LinkedIn prospecting with drip campaigns and automation.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['DRIPIFY'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["DRIPIFY"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
CRM Tools
HubSpot
HubSpot
A robust CRM for marketing, sales, and customer service management.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['HUBSPOT'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["HUBSPOT"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Pipedrive
Pipedrive
A CRM tool designed to optimize and track the sales pipeline.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['PIPEDRIVE'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["PIPEDRIVE"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Salesforce
Salesforce
A leading CRM platform for managing customer relationships and automating processes.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['SALESFORCE'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["SALESFORCE"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Highlevel
Highlevel
An all-in-one CRM platform for managing leads, marketing, and sales.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['HIGHLEVEL'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["HIGHLEVEL"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Attio
Attio
A collaborative CRM built for fast-moving teams.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['ATTIO'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["ATTIO"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Email Deliverability
Gmail
Gmail
A widely used email platform with powerful organizational tools.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['GMAIL'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["GMAIL"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
MailChimp
MailChimp
A marketing platform for email campaigns and audience management.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['MAILCHIMP'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["MAILCHIMP"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Brevo
Brevo
(formerly Sendinblue) Offers tools for email marketing, SMS campaigns, and automation.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['BREVO'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["BREVO"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Selzy
Selzy
Simplifies email marketing with a beginner-friendly interface and tools.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['SELZY'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["SELZY"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Klaviyo
Klaviyo
An email marketing platform focused on personalization and eCommerce.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['KLAVIYO'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["KLAVIYO"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
CleverTap
CleverTap
Provides customer engagement and retention through personalized messaging campaigns.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(apps=['CLEVERTAP'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ apps: ["CLEVERTAP"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);