5,140,594 AI resources indexedWorking toward the world’s largest AI resource index.

LangChain Install & Auth

Install and configure LangChain SDK/CLI authentication. Use when setting up a new LangChain integration, configuring API keys, or initializing LangChain in your project. Trigger with phrases like "install langchain", "setup langchain", "langchain auth", "configure langchain API key", "langchain c...

Installable skillMITBy DicklesworthstoneUpdated Oct 30, 2026
INTENDED FOROpenClawInstall in a listed agent.

instructions.md

---
name: langchain-install-auth-83114bbae50f
description: |
  Install and configure LangChain SDK/CLI authentication.
  Use when setting up a new LangChain integration, configuring API keys,
  or initializing LangChain in your project.
  Trigger with phrases like "install langchain", "setup langchain",
  "langchain auth", "configure langchain API key", "langchain credentials".
allowed-tools: Read, Write, Edit, Bash(npm:*), Bash(pip:*), Grep
version: 1.0.0
license: MIT
author: Jeremy Longshore <jeremy@intentsolutions.io>
---

# LangChain Install & Auth

## Overview
Set up LangChain SDK and configure LLM provider authentication credentials.

## Prerequisites
- Python 3.9+ or Node.js 18+
- Package manager (pip, poetry, or npm)
- LLM provider account (OpenAI, Anthropic, Google, etc.)
- API key from your LLM provider dashboard

## Instructions

### Step 1: Install LangChain Core
```bash
# Python (recommended)
pip install langchain langchain-core langchain-community

# Or with specific providers
pip install langchain-openai langchain-anthropic langchain-google-genai

# Node.js
npm install langchain @langchain/core @langchain/community
```

### Step 2: Configure Authentication
```bash
# OpenAI
export OPENAI_API_KEY="your-openai-key"

# Anthropic
export ANTHROPIC_API_KEY="your-anthropic-key"

# Google
export GOOGLE_API_KEY="your-google-key"

# Or create .env file
echo 'OPENAI_API_KEY=your-openai-key' >> .env
```

### Step 3: Verify Connection
```python
from langchain_openai import ChatOpenAI

llm = ChatOpenAI(model="gpt-4o-mini")
response = llm.invoke("Say hello!")
print(response.content)
```

## Output
- Installed LangChain packages in virtual environment
- Environment variables or .env file with API keys
- Successful connection verification output

## Error Handling
| Error | Cause | Solution |
|-------|-------|----------|
| Invalid API Key | Incorrect or expired key | Verify key in provider dashboard |
| Rate Limited | Exceeded quota | Check quota limits, implement backoff |
| Network Error | Firewall blocking | Ensure outbound HTTPS allowed |
| Module Not Found | Installation failed | Run `pip install` again, check Python version |
| Provider Error | Service unavailable | Check provider status page |

## Examples

### Python Setup (OpenAI)
```python
import os
from langchain_openai import ChatOpenAI

# Ensure API key is set
assert os.environ.get("OPENAI_API_KEY"), "Set OPENAI_API_KEY"

llm = ChatOpenAI(
    model="gpt-4o-mini",
    temperature=0.7,
    max_tokens=1000
)
```

### Python Setup (Anthropic)
```python
from langchain_anthropic import ChatAnthropic

llm = ChatAnthropic(
    model="claude-3-5-sonnet-20241022",
    temperature=0.7
)
```

### TypeScript Setup
```typescript
import { ChatOpenAI } from "@langchain/openai";

const llm = new ChatOpenAI({
  modelName: "gpt-4o-mini",
  temperature: 0.7
});
```

## Resources
- [LangChain Documentation](https://python.langchain.com/docs/)
- [LangChain JS/TS](https://js.langchain.com/docs/)
- [OpenAI API Keys](https://platform.openai.com/api-keys)
- [Anthropic Console](https://console.anthropic.com/)

## Next Steps
After successful auth, proceed to `langchain-hello-world` for your first chain.

Platform guidance

Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.