Pipedream

Pipedream is a developer-focused automation platform that combines no-code workflows with the ability to write custom code in Node.js or Python.

Prerequisites

• A Pipedream account (pipedream.com)
• Your TensorX API key from app.tensorx.ai

Configuration

Pipedream offers two methods to connect to TensorX:

1. Code Step - Write Node.js or Python code (recommended for flexibility)
2. HTTP Request Action - No-code approach

Method 1: Node.js Code Step (Recommended)

Step 1: Add a Code Step

1. Create a new workflow or open an existing one
2. Click + to add a step
3. Select Node → Run Node.js code

Step 2: Write the API Call

import { axios } from "@pipedream/platform";

export default defineComponent({
  props: {
    tensorxApiKey: {
      type: "string",
      label: "TensorX API Key",
      secret: true,
    },
  },
  async run({ steps, $ }) {
    const response = await axios($, {
      method: "POST",
      url: "https://api.tensorx.ai/v1/chat/completions",
      headers: {
        "Authorization": `Bearer ${this.tensorxApiKey}`,
        "Content-Type": "application/json",
      },
      data: {
        model: "deepseek/deepseek-chat-v3.1",
        messages: [
          {
            role: "system",
            content: "You are a helpful assistant."
          },
          {
            role: "user",
            content: steps.trigger.event.message // Adjust based on your trigger
          }
        ],
        temperature: 0.7,
        max_tokens: 1000,
      },
    });
    
    return {
      content: response.choices[0].message.content,
      model: response.model,
      usage: response.usage,
    };
  },
});

Step 3: Configure the API Key

1. When you run the workflow, Pipedream will prompt for the API key
2. Enter your TensorX API key
3. The key is stored securely and can be reused

Method 2: Python Code Step

import requests

def handler(pd: "pipedream"):
    api_key = pd.inputs["tensorx_api_key"]
    user_message = pd.steps["trigger"]["event"]["message"]
    
    response = requests.post(
        "https://api.tensorx.ai/v1/chat/completions",
        headers={
            "Authorization": f"Bearer {api_key}",
            "Content-Type": "application/json",
        },
        json={
            "model": "deepseek/deepseek-chat-v3.1",
            "messages": [
                {"role": "system", "content": "You are a helpful assistant."},
                {"role": "user", "content": user_message}
            ],
            "temperature": 0.7,
            "max_tokens": 1000,
        }
    )
    
    data = response.json()
    return {
        "content": data["choices"][0]["message"]["content"],
        "model": data["model"],
        "usage": data["usage"],
    }

Method 3: HTTP Request Action

For a no-code approach:

1. Click + → HTTP / Webhook → Send any HTTP Request
2. Configure:

Field	Value
Method	POST
URL	https://api.tensorx.ai/v1/chat/completions

1. Add Headers:

   • Authorization: Bearer YOUR_API_KEY
   • Content-Type: application/json
2. Set Body to:

{
  "model": "deepseek/deepseek-chat-v3.1",
  "messages": [
    {"role": "user", "content": "{{steps.trigger.event.message}}"}
  ]
}

Example Workflows

Slack AI Assistant

Trigger: New Slack message in channel Action: Reply with AI-generated response

import { axios } from "@pipedream/platform";

export default defineComponent({
  props: {
    tensorxApiKey: {
      type: "string",
      label: "TensorX API Key",
      secret: true,
    },
  },
  async run({ steps, $ }) {
    // Get the Slack message
    const userMessage = steps.trigger.event.text;
    
    // Skip if it's a bot message
    if (steps.trigger.event.bot_id) {
      return { skipped: true };
    }
    
    // Call TensorX API
    const response = await axios($, {
      method: "POST",
      url: "https://api.tensorx.ai/v1/chat/completions",
      headers: {
        "Authorization": `Bearer ${this.tensorxApiKey}`,
        "Content-Type": "application/json",
      },
      data: {
        model: "deepseek/deepseek-chat-v3.1",
        messages: [
          {
            role: "system",
            content: "You are a helpful Slack assistant. Keep responses concise."
          },
          { role: "user", content: userMessage }
        ],
        temperature: 0.7,
        max_tokens: 500,
      },
    });
    
    return { reply: response.choices[0].message.content };
  },
});

Email Classifier

import { axios } from "@pipedream/platform";

export default defineComponent({
  props: {
    tensorxApiKey: {
      type: "string",
      label: "TensorX API Key",
      secret: true,
    },
  },
  async run({ steps, $ }) {
    const emailSubject = steps.trigger.event.subject;
    const emailBody = steps.trigger.event.body;
    
    const response = await axios($, {
      method: "POST",
      url: "https://api.tensorx.ai/v1/chat/completions",
      headers: {
        "Authorization": `Bearer ${this.tensorxApiKey}`,
        "Content-Type": "application/json",
      },
      data: {
        model: "z-ai/glm-5.1",
        messages: [
          {
            role: "system",
            content: `Classify this email into one category: sales, support, spam, newsletter, personal. 
                      Return JSON: {"category": "...", "priority": "high|medium|low", "summary": "..."}`
          },
          {
            role: "user",
            content: `Subject: ${emailSubject}\n\nBody: ${emailBody}`
          }
        ],
        temperature: 0.1,
        max_tokens: 200,
      },
    });
    
    return JSON.parse(response.choices[0].message.content);
  },
});

Content Generator with Streaming

import { axios } from "@pipedream/platform";

export default defineComponent({
  props: {
    tensorxApiKey: {
      type: "string",
      label: "TensorX API Key",
      secret: true,
    },
  },
  async run({ steps, $ }) {
    const topic = steps.trigger.event.topic;
    
    const response = await axios($, {
      method: "POST",
      url: "https://api.tensorx.ai/v1/chat/completions",
      headers: {
        "Authorization": `Bearer ${this.tensorxApiKey}`,
        "Content-Type": "application/json",
      },
      data: {
        model: "deepseek/deepseek-chat-v3.1",
        messages: [
          {
            role: "system",
            content: "You are a professional content writer."
          },
          {
            role: "user",
            content: `Write a blog post about: ${topic}`
          }
        ],
        temperature: 0.8,
        max_tokens: 2000,
      },
    });
    
    return {
      content: response.choices[0].message.content,
      wordCount: response.choices[0].message.content.split(' ').length,
      tokensUsed: response.usage.total_tokens,
    };
  },
});

Recommended Models

For Coding Tasks:

• z-ai/glm-5.1 - Best for tool calling and structured outputs
• minimax/minimax-m2.5 - Best for complex reasoning tasks

Model ID	Best For
deepseek/deepseek-chat-v3.1	General chat, content generation
z-ai/glm-5.1	Classification, structured JSON output
minimax/minimax-m2.5	Complex reasoning, analysis
moonshotai/kimi-k2.5	Vision, long context

Using Environment Variables

Store your API key securely:

1. Go to Settings → Environment Variables
2. Add TENSORX_API_KEY with your key
3. Access in code: process.env.TENSORX_API_KEY

const response = await axios($, {
  url: "https://api.tensorx.ai/v1/chat/completions",
  headers: {
    "Authorization": `Bearer ${process.env.TENSORX_API_KEY}`,
  },
  // ...
});

Error Handling

try {
  const response = await axios($, {
    method: "POST",
    url: "https://api.tensorx.ai/v1/chat/completions",
    headers: {
      "Authorization": `Bearer ${this.tensorxApiKey}`,
      "Content-Type": "application/json",
    },
    data: {
      model: "deepseek/deepseek-chat-v3.1",
      messages: [{ role: "user", content: "Hello" }],
    },
  });
  return response;
} catch (error) {
  if (error.response?.status === 401) {
    throw new Error("Invalid API key");
  } else if (error.response?.status === 429) {
    throw new Error("Rate limit exceeded");
  }
  throw error;
}

Troubleshooting

"Unauthorized" Error

• Check that your API key is correct
• Ensure the Authorization header format is Bearer YOUR_KEY

"Model Not Found" Error

• Use the full model ID: deepseek/deepseek-chat-v3.1
• Check available models at app.tensorx.ai/models

Timeout Errors

• Increase the timeout in axios config: timeout: 60000
• Use a faster model for time-sensitive workflows

Support

Need help? Contact us at [e-mail]