AnythingLLM

Connect AnythingLLM to TensorX and chat with your documents using any of our models.

---

What is AnythingLLM?

AnythingLLM is an all-in-one AI application that lets you chat with your documents, use AI agents, and manage multiple workspaces. It supports many LLM providers including OpenAI-compatible APIs like TensorX.

---

Prerequisites

• AnythingLLM installed (Desktop or Docker)

• A TensorX API key (sign up here)

---

Configuration

AnythingLLM supports TensorX through the OpenAI (Generic) provider.

Step 1: Open LLM Settings

1. Launch AnythingLLM

2. Click the Settings gear icon

3. Navigate to LLM settings

Step 2: Select OpenAI (Generic)

1. In the LLM provider dropdown, select OpenAI (Generic)

2. Configure the following settings:

Field	Value
Base URL	https://api.tensorx.ai/v1
API Key	Your TensorX API key
Model Name	An ID returned by GET /v1/models
Max Tokens	Leave unset unless the workspace needs an explicit response limit

1. Click Save Changes

Important: The Base URL must include /v1 at the end.

---

Docker Deployment

Deploy AnythingLLM with TensorX pre-configured:

docker run -d \
  --name anythingllm \
  -p 3001:3001 \
  -v anythingllm-data:/app/server/storage \
  -e LLM_PROVIDER=generic-openai \
  -e GENERIC_OPEN_AI_BASE_PATH=https://api.tensorx.ai/v1 \
  -e GENERIC_OPEN_AI_API_KEY=your-tensorx-api-key \
  -e GENERIC_OPEN_AI_MODEL_PREF=z-ai/glm-5.2 \
  mintplexlabs/anythingllm

Then open http://localhost:3001 in your browser.

Docker Compose

version: '3.8'

services:
  anythingllm:
    image: mintplexlabs/anythingllm
    container_name: anythingllm
    ports:
      - "3001:3001"
    environment:
      - LLM_PROVIDER=generic-openai
      - GENERIC_OPEN_AI_BASE_PATH=https://api.tensorx.ai/v1
      - GENERIC_OPEN_AI_API_KEY=your-tensorx-api-key
      - GENERIC_OPEN_AI_MODEL_PREF=z-ai/glm-5.2
    volumes:
      - anythingllm-data:/app/server/storage

volumes:
  anythingllm-data:

Deploy with:

docker compose up -d

---

Model selection

Call GET /v1/models with your TensorX API key and use one of the returned IDs. If the integration depends on a capability or token limit, query GET /v1/model/info before selecting the model. See Models for examples.

---

Workspace Configuration

You can set different models per workspace:

1. Open a workspace

2. Click the Settings icon for that workspace

3. Under Chat Settings, select Workspace LLM

4. Choose OpenAI (Generic) and configure with a different TensorX model

This allows you to use different models for different use cases within the same AnythingLLM instance.

---

Features with TensorX

Document Upload

Upload and chat with various document types:

• PDFs

• Word documents (.docx)

• Text files

• Web pages (via URL)

• And more

AI Agents

Create custom agents that can:

• Browse the web

• Execute code

• Use custom tools

• Access your documents

Workspaces

Organize your documents into separate workspaces, each with its own:

• Document collection

• Chat history

• Model settings

Embed Widget

Create embeddable chat widgets for your website (Docker version only).

---

Environment Variables

For Docker deployments, these environment variables configure TensorX:

Variable	Value	Description
LLM_PROVIDER	generic-openai	Use OpenAI-compatible provider
GENERIC_OPEN_AI_BASE_PATH	https://api.tensorx.ai/v1	TensorX API endpoint
GENERIC_OPEN_AI_API_KEY	Your API key	TensorX API key
GENERIC_OPEN_AI_MODEL_PREF	Model name	Default model to use
GENERIC_OPEN_AI_MAX_TOKENS	Optional application limit	Max tokens per response

---

Troubleshooting

"Invalid API Key" Error

1. Verify your API key is correct

2. Check that the key has available credits

3. Test your key:

curl https://api.tensorx.ai/v1/models \
  -H "Authorization: Bearer YOUR_API_KEY"

"Model Not Found" Error

1. Verify the model name is correct (e.g., z-ai/glm-5.2)

2. Check available models at tensorx.ai/models

Connection Errors

1. Ensure Base URL is https://api.tensorx.ai/v1 (with /v1)

2. Check your internet connection

3. Verify no firewall is blocking the connection

Slow Responses

1. Reduce the document size in your workspace.

2. Check the selected model and request latency in the TensorX usage dashboard.

Check Logs (Docker)

docker logs anythingllm

---

Resources

• AnythingLLM Documentation

• AnythingLLM GitHub

• TensorX Models & Pricing

---

See Also

• Open WebUI - Another self-hosted chat interface

• LibreChat - Multi-provider chat interface

• API Examples - Code examples for TensorX API