> ## Documentation Index
> Fetch the complete documentation index at: https://composio-27-feat-docs-revamp.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.
# Tools For AI SDR Kit
> List of tools you can use for your AI SDR Development, compatible with agentic frameworks like CrewAI, LangChain, and LlamaIndex etc. These utilities enable file system operations, command execution, and other core development tasks
## Contact Data
Provides GDPR-compliant B2B contact data and prospecting solutions.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
A sales intelligence platform for finding leads and automating outbound workflows.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
Offers comprehensive contact and company information for sales and marketing teams.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
Delivers verified email addresses and contact details for professionals worldwide.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
A B2B lead generation platform with real-time data enrichment.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
A platform for discovering and comparing software solutions based on user reviews.
```python Python
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)
```
```javascript JS
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: "" });
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
A sales engagement platform to streamline prospecting and customer outreach.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
Enables sales teams to manage and optimize multi-channel engagement.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
Analyzes sales calls and provides actionable insights to improve team performance.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
A CRM designed for inside sales with built-in calling, email, and pipeline management.
```python Python
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)
```
```javascript JS
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: "" });
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
Offers company data, intent signals, and enrichment for targeting prospects.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
Uses AI-powered intent data to identify and prioritize potential buyers.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
Helps identify buyer intent with data-driven insights for B2B marketing and sales.
```python Python
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)
```
```javascript JS
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: "" });
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
Improves email deliverability through warmup and automated outreach.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
Optimizes inbox placement by simulating email interactions.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
Helps improve email deliverability through personalized email warmup.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
An email outreach platform with personalization and deliverability optimization features.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
A tool to enhance deliverability and inbox performance for email campaigns.
```python Python
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)
```
```javascript JS
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: "" });
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
Creates AI-powered personalized content for outreach and sales.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
Generates AI-driven content for emails, blogs, and personalized messaging.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
Automates lead research and creates hyper-personalized outreach.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
Enables personalized outreach through AI-driven data aggregation.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
Provides business information for market research and sales prospecting.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
Delivers market intelligence and insights for business decision-making.
```python Python
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)
```
```javascript JS
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: "" });
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
Offers real-time data enrichment for contacts and companies.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
Combines enrichment and automation to create highly personalized outreach campaigns.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
Simplifies B2B prospecting with enriched contact and company data.
```python Python
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)
```
```javascript JS
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: "" });
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
Simplifies scheduling by automating meeting bookings.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
Streamlines inbound meeting scheduling and routing for sales teams.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
Simplifies scheduling by automating meeting bookings.
```python Python
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)
```
```javascript JS
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: "" });
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
A cloud-based phone system for managing sales and support calls.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
Performs code formatting and linting using ruff, addressing style issues and checking for errors
```python Python
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)
```
```javascript JS
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: "" });
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);
```
A unified communications platform with AI-powered calling and messaging.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
Enables developers to integrate messaging, voice, and video in applications.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
A tool for automated, AI-powered sales calling.
```python Python
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)
```
```javascript JS
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: "" });
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
Automates LinkedIn outreach, connection requests, and messaging.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
Boosts LinkedIn prospecting with automated workflows.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
Extracts data and automates actions on LinkedIn and other platforms.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
Simplifies LinkedIn prospecting with drip campaigns and automation.
```python Python
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)
```
```javascript JS
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: "" });
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
A robust CRM for marketing, sales, and customer service management.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
A CRM tool designed to optimize and track the sales pipeline.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
A leading CRM platform for managing customer relationships and automating processes.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
An all-in-one CRM platform for managing leads, marketing, and sales.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
A collaborative CRM built for fast-moving teams.
```python Python
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)
```
```javascript JS
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: "" });
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
A widely used email platform with powerful organizational tools.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
A marketing platform for email campaigns and audience management.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
(formerly Sendinblue) Offers tools for email marketing, SMS campaigns, and automation.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
Simplifies email marketing with a beginner-friendly interface and tools.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
An email marketing platform focused on personalization and eCommerce.
```python Python
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)
```
```javascript JS
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: "" });
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);
```
Provides customer engagement and retention through personalized messaging campaigns.
```python Python
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)
```
```javascript JS
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: "" });
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);
```