HopBase | PrivateGPT

HopBase is a hosted AI API gateway with an OpenAI-compatible endpoint at https://api.hop-base.com/v1. It serves chat models from OpenAI, Anthropic, Google and xAI alongside DeepSeek, Zhipu GLM, Moonshot Kimi and Alibaba Qwen, so you can switch the model PrivateGPT answers with by changing a model ID. PrivateGPT uses it through the existing OpenAI-compatible integration.

HopBase serves chat models and does not serve embedding models. This setup sends chat requests to HopBase and keeps embeddings on your own embeddings server, for example a local Ollama instance.

Capabilities with PrivateGPT

Capability	Status
Model discovery (`/v1/models`)	✅ returns only the models your key can call
Tokenizer endpoint (`/tokenize`)	❌
Embeddings	❌ use a separate embeddings server
Tool / function calling	✅ model-dependent
Structured output (JSON schema)	✅ model-dependent
Streaming	✅
Vision / image input	✅ model-dependent

Tool calling and streaming were checked against the live API with gpt-6.1-sol and glm-5.3. JSON-schema output follows the schema on gpt-6.1-sol; glm-5.3 accepts the parameter but does not reliably follow the schema, so validate its output. Image input was checked with gpt-6.1-sol; glm-5.3 rejects images.

Setup

Create a key and pick a chat model

Sign in to the HopBase console and create an API key. A key can call the models of the groups it includes.
Set HOPBASE_API_KEY in your environment or .env file. Keep the secret out of committed files.

export HOPBASE_API_KEY="your-hopbase-api-key"

List the model IDs your key can call and use one of them unchanged:

curl https://api.hop-base.com/v1/models \
  -H "Authorization: Bearer $HOPBASE_API_KEY"

Model IDs, context windows and parameters are documented in the HopBase docs, and per-model prices are on the pricing page.

Start a local embeddings server

Skip this step if you already have an embeddings server. Otherwise, start Ollama and pull an embeddings model:

ollama pull mxbai-embed-large

The examples below use Ollama’s OpenAI-compatible API at http://localhost:11434/v1 with the placeholder key ollama.

Run PrivateGPT

Package install

Docker

uv (local)

OPENAI_API_BASE=https://api.hop-base.com/v1 \
  OPENAI_API_KEY="$HOPBASE_API_KEY" \
  OPENAI_EMBEDDING_API_BASE=http://localhost:11434/v1 \
  OPENAI_EMBEDDING_API_KEY=ollama \
  PGPT_LLM_DEFAULT=glm-5.3 \
  PGPT_EMBEDDING_DEFAULT=mxbai-embed-large \
  private-gpt serve

Follow the corresponding installation guide first, including PrivateGPT’s other required services.

Advanced profile example

/v1/models returns model IDs without a context length and there is no /tokenize endpoint, so set context_window explicitly. The values below are the documented context windows of each model.

# settings-model.yaml
llm:
  default_model: glm-5.3
models:
  - name: glm-5.3
    type: llm
    mode: openai
    context_window: 1000000
    support_tools: true
    support_reasoning: true
  - name: gpt-6.1-sol
    type: llm
    mode: openai
    context_window: 1050000
    support_tools: true
    support_reasoning: true
  - name: claude-sonnet-5-5
    type: llm
    mode: openai
    context_window: 1000000
    support_tools: true
    support_reasoning: true

Run with the profile:

OPENAI_API_BASE=https://api.hop-base.com/v1 \
  OPENAI_API_KEY="$HOPBASE_API_KEY" \
  OPENAI_EMBEDDING_API_BASE=http://localhost:11434/v1 \
  OPENAI_EMBEDDING_API_KEY=ollama \
  PGPT_EMBEDDING_DEFAULT=mxbai-embed-large \
  PGPT_PROFILES=model \
  uv run python -m private_gpt

Notes

Model IDs come from /v1/models for your key. If a model is missing from the list, the key’s groups do not include it.
Regional variants of some models (for example DeepSeek in Singapore or the US) have their own model IDs; pick the one you want explicitly.
Embeddings stay on your server, but retrieved document excerpts that PrivateGPT puts into a chat prompt are sent to the hosted API.
HopBase also exposes an Anthropic Messages-compatible endpoint. PrivateGPT uses the OpenAI-compatible one, and Claude models are available on it too.