GoodMem
How-To Guides

Endpoint registration guide

Register embedders, rerankers, and LLMs with provider-specific base URLs and api_path behavior.

Endpoint registration guide

This page shows how to register embedders, rerankers, and LLMs with GoodMem and documents how endpoint_url and api_path are used.

Endpoint fields

GoodMem stores endpoints as two fields:

  • endpoint_url: absolute base URL (scheme + host + optional base path). Example: https://api.openai.com/v1.
  • api_path: provider route appended to the base. Example: /embeddings or /chat/completions.

GoodMem combines them for HTTP calls and the proxy. Example:

  • endpoint_url = https://api.openai.com/v1 + api_path = /embeddings -> https://api.openai.com/v1/embeddings
  • endpoint_url = https://api.jina.ai + api_path = /v1/embeddings -> https://api.jina.ai/v1/embeddings

GoodMem does not move /v1 between fields. Put the base path where the provider expects it.

api_path values and base URLs

If api_path is omitted or blank, GoodMem uses the default shown below. For embedders and LLMs, use the standard api_path values shown here. For rerankers, you can override api_path unless the table says "fixed". endpoint_url is required; use the suggested base URLs below.

Embedders

Tip: TEI defaults to port 3000 when run as a binary. The official Docker examples often map host port 8080 to container port 80. Use the port you actually run TEI on.

Provider typeSuggested endpoint_url (base)api_path
COHEREhttps://api.cohere.comfixed /v2/embed
JINAhttps://api.jina.aifixed /v1/embeddings
TEIhttp://<host>:<port>fixed /embed
OPENAIhttps://api.openai.com/v1fixed /embeddings
VLLMhttp://<host>:<port>/v1fixed /embeddings
LLAMA_CPPhttp://<host>:<port>/v1fixed /embeddings
VOYAGEhttps://api.voyageai.com/v1fixed /embeddings

Rerankers

Provider typeSuggested endpoint_url (base)api_path
COHEREhttps://api.cohere.comdefault /v2/rerank (override via api_path)
JINAhttps://api.jina.aidefault /v1/rerank (override via api_path)
TEIhttp://<host>:<port>fixed /rerank
VLLMhttp://<host>:<port>/v1default /rerank (override via api_path)
LLAMA_CPPhttp://<host>:<port>/v1default /rerank (override via api_path)
VOYAGEhttps://api.voyageai.com/v1default /rerank (override via api_path)

LLMs

Provider typeSuggested endpoint_url (base)api_path
OPENAIhttps://api.openai.com/v1fixed /chat/completions
LITELLM_PROXYhttps://<host>/v1fixed /chat/completions
OPEN_ROUTERhttps://openrouter.ai/api/v1fixed /chat/completions
VLLMhttp://<host>:<port>/v1fixed /chat/completions
OLLAMAhttp://<host>:11434/v1fixed /chat/completions
LLAMA_CPPhttp://<host>:<port>/v1fixed /chat/completions
CUSTOM_OPENAI_COMPATIBLEhttps://<host>/v1fixed /chat/completions

Registration recipes

The CLI examples use the gRPC API. The cURL examples call the REST API.

export GOODMEM_SERVER="https://localhost:9090"
export GOODMEM_REST_URL="http://localhost:8080"
export GOODMEM_API_KEY="gm_your_key"

REST scripting notes

  • REST JSON uses camelCase fields: endpointUrl, apiPath, embedderId, rerankerId, llmId.
  • apiPath is optional; if you omit it, GoodMem applies the provider defaults shown in the tables above.
  • For OpenAI-compatible providers, endpointUrl must end with /v1 (not /v1/embeddings or /v1/chat/completions).
  • If you do set apiPath, do not duplicate base paths already present in endpointUrl (for example, https://api.voyageai.com/v1 + /v1/rerank is invalid).
  • Create responses include the resource ID in the JSON body and a Location header (see create embedder, create reranker, and create LLM).
  • For idempotent scripts, pass a client ID (embedderId, rerankerId, llmId). A 409 means the resource already exists; list or look up the existing resource and reuse its ID.
  • If your REST endpoint uses HTTPS with a self-signed certificate, curl needs -k or a trusted CA, and HTTPie needs --verify=no or --verify=/path/to/ca.pem.

Replace model identifiers and dimensionality with your actual values.

Embedders

OpenAI (official endpoint):

goodmem embedder create \
  --display-name "OpenAI Embedder" \
  --provider-type OPENAI \
  --endpoint-url "https://api.openai.com/v1" \
  --model-identifier "text-embedding-3-small" \
  --dimensionality 1536 \
  --distribution-type DENSE \
  --cred-api-key "OPENAI_API_KEY"
curl -sS --json @- "$GOODMEM_REST_URL/v1/embedders" \
  --header "x-api-key: $GOODMEM_API_KEY" <<'JSON'
{
  "displayName": "OpenAI Embedder",
  "providerType": "OPENAI",
  "endpointUrl": "https://api.openai.com/v1",
  "modelIdentifier": "text-embedding-3-small",
  "dimensionality": 1536,
  "distributionType": "DENSE",
  "credentials": {
    "kind": "CREDENTIAL_KIND_API_KEY",
    "apiKey": {
      "inlineSecret": "OPENAI_API_KEY"
    }
  }
}
JSON
http POST "$GOODMEM_REST_URL/v1/embedders" \
  x-api-key:"$GOODMEM_API_KEY" \
  displayName="OpenAI Embedder" \
  providerType="OPENAI" \
  endpointUrl="https://api.openai.com/v1" \
  modelIdentifier="text-embedding-3-small" \
  dimensionality:=1536 \
  distributionType="DENSE" \
  credentials:='{
    "kind": "CREDENTIAL_KIND_API_KEY",
    "apiKey": {
      "inlineSecret": "OPENAI_API_KEY"
    }
  }'

vLLM (OpenAI-compatible embeddings):

goodmem embedder create \
  --display-name "vLLM Embedder" \
  --provider-type VLLM \
  --endpoint-url "http://vllm-host:8000/v1" \
  --model-identifier "all-MiniLM-L6-v2" \
  --dimensionality 384 \
  --distribution-type DENSE
curl -sS --json @- "$GOODMEM_REST_URL/v1/embedders" \
  --header "x-api-key: $GOODMEM_API_KEY" <<'JSON'
{
  "displayName": "vLLM Embedder",
  "providerType": "VLLM",
  "endpointUrl": "http://vllm-host:8000/v1",
  "modelIdentifier": "all-MiniLM-L6-v2",
  "dimensionality": 384,
  "distributionType": "DENSE"
}
JSON
http POST "$GOODMEM_REST_URL/v1/embedders" \
  x-api-key:"$GOODMEM_API_KEY" \
  displayName="vLLM Embedder" \
  providerType="VLLM" \
  endpointUrl="http://vllm-host:8000/v1" \
  modelIdentifier="all-MiniLM-L6-v2" \
  dimensionality:=384 \
  distributionType="DENSE"

TEI (Text Embeddings Inference):

goodmem embedder create \
  --display-name "TEI Embedder" \
  --provider-type TEI \
  --endpoint-url "http://tei-host:8080" \
  --model-identifier "Qwen3-Embedding-0.6B" \
  --dimensionality 1024 \
  --distribution-type DENSE
curl -sS --json @- "$GOODMEM_REST_URL/v1/embedders" \
  --header "x-api-key: $GOODMEM_API_KEY" <<'JSON'
{
  "displayName": "TEI Embedder",
  "providerType": "TEI",
  "endpointUrl": "http://tei-host:8080",
  "modelIdentifier": "Qwen3-Embedding-0.6B",
  "dimensionality": 1024,
  "distributionType": "DENSE"
}
JSON
http POST "$GOODMEM_REST_URL/v1/embedders" \
  x-api-key:"$GOODMEM_API_KEY" \
  displayName="TEI Embedder" \
  providerType="TEI" \
  endpointUrl="http://tei-host:8080" \
  modelIdentifier="Qwen3-Embedding-0.6B" \
  dimensionality:=1024 \
  distributionType="DENSE"

Llama.cpp (OpenAI-compatible embeddings):

goodmem embedder create \
  --display-name "Llama.cpp Embedder" \
  --provider-type LLAMA_CPP \
  --endpoint-url "http://llama-cpp-host:8080/v1" \
  --model-identifier "all-MiniLM-L6-v2" \
  --dimensionality 384 \
  --distribution-type DENSE
curl -sS --json @- "$GOODMEM_REST_URL/v1/embedders" \
  --header "x-api-key: $GOODMEM_API_KEY" <<'JSON'
{
  "displayName": "Llama.cpp Embedder",
  "providerType": "LLAMA_CPP",
  "endpointUrl": "http://llama-cpp-host:8080/v1",
  "modelIdentifier": "all-MiniLM-L6-v2",
  "dimensionality": 384,
  "distributionType": "DENSE"
}
JSON
http POST "$GOODMEM_REST_URL/v1/embedders" \
  x-api-key:"$GOODMEM_API_KEY" \
  displayName="Llama.cpp Embedder" \
  providerType="LLAMA_CPP" \
  endpointUrl="http://llama-cpp-host:8080/v1" \
  modelIdentifier="all-MiniLM-L6-v2" \
  dimensionality:=384 \
  distributionType="DENSE"

Voyage AI:

goodmem embedder create \
  --display-name "Voyage Embedder" \
  --provider-type VOYAGE \
  --endpoint-url "https://api.voyageai.com/v1" \
  --model-identifier "voyage-3-large" \
  --dimensionality 1024 \
  --distribution-type DENSE \
  --cred-api-key "VOYAGE_API_KEY"
curl -sS --json @- "$GOODMEM_REST_URL/v1/embedders" \
  --header "x-api-key: $GOODMEM_API_KEY" <<'JSON'
{
  "displayName": "Voyage Embedder",
  "providerType": "VOYAGE",
  "endpointUrl": "https://api.voyageai.com/v1",
  "modelIdentifier": "voyage-3-large",
  "dimensionality": 1024,
  "distributionType": "DENSE",
  "credentials": {
    "kind": "CREDENTIAL_KIND_API_KEY",
    "apiKey": {
      "inlineSecret": "VOYAGE_API_KEY"
    }
  }
}
JSON
http POST "$GOODMEM_REST_URL/v1/embedders" \
  x-api-key:"$GOODMEM_API_KEY" \
  displayName="Voyage Embedder" \
  providerType="VOYAGE" \
  endpointUrl="https://api.voyageai.com/v1" \
  modelIdentifier="voyage-3-large" \
  dimensionality:=1024 \
  distributionType="DENSE" \
  credentials:='{
    "kind": "CREDENTIAL_KIND_API_KEY",
    "apiKey": {
      "inlineSecret": "VOYAGE_API_KEY"
    }
  }'

Cohere:

goodmem embedder create \
  --display-name "Cohere Embedder" \
  --provider-type COHERE \
  --endpoint-url "https://api.cohere.com" \
  --model-identifier "embed-english-v3.0" \
  --dimensionality 1024 \
  --distribution-type DENSE \
  --cred-api-key "COHERE_API_KEY"
curl -sS --json @- "$GOODMEM_REST_URL/v1/embedders" \
  --header "x-api-key: $GOODMEM_API_KEY" <<'JSON'
{
  "displayName": "Cohere Embedder",
  "providerType": "COHERE",
  "endpointUrl": "https://api.cohere.com",
  "modelIdentifier": "embed-english-v3.0",
  "dimensionality": 1024,
  "distributionType": "DENSE",
  "credentials": {
    "kind": "CREDENTIAL_KIND_API_KEY",
    "apiKey": {
      "inlineSecret": "COHERE_API_KEY"
    }
  }
}
JSON
http POST "$GOODMEM_REST_URL/v1/embedders" \
  x-api-key:"$GOODMEM_API_KEY" \
  displayName="Cohere Embedder" \
  providerType="COHERE" \
  endpointUrl="https://api.cohere.com" \
  modelIdentifier="embed-english-v3.0" \
  dimensionality:=1024 \
  distributionType="DENSE" \
  credentials:='{
    "kind": "CREDENTIAL_KIND_API_KEY",
    "apiKey": {
      "inlineSecret": "COHERE_API_KEY"
    }
  }'

Jina:

goodmem embedder create \
  --display-name "Jina Embedder" \
  --provider-type JINA \
  --endpoint-url "https://api.jina.ai" \
  --model-identifier "jina-embeddings-v3" \
  --dimensionality 1024 \
  --distribution-type DENSE \
  --cred-api-key "JINA_API_KEY"
curl -sS --json @- "$GOODMEM_REST_URL/v1/embedders" \
  --header "x-api-key: $GOODMEM_API_KEY" <<'JSON'
{
  "displayName": "Jina Embedder",
  "providerType": "JINA",
  "endpointUrl": "https://api.jina.ai",
  "modelIdentifier": "jina-embeddings-v3",
  "dimensionality": 1024,
  "distributionType": "DENSE",
  "credentials": {
    "kind": "CREDENTIAL_KIND_API_KEY",
    "apiKey": {
      "inlineSecret": "JINA_API_KEY"
    }
  }
}
JSON
http POST "$GOODMEM_REST_URL/v1/embedders" \
  x-api-key:"$GOODMEM_API_KEY" \
  displayName="Jina Embedder" \
  providerType="JINA" \
  endpointUrl="https://api.jina.ai" \
  modelIdentifier="jina-embeddings-v3" \
  dimensionality:=1024 \
  distributionType="DENSE" \
  credentials:='{
    "kind": "CREDENTIAL_KIND_API_KEY",
    "apiKey": {
      "inlineSecret": "JINA_API_KEY"
    }
  }'

Rerankers

TEI (cross-encoder reranking):

goodmem reranker create \
  --display-name "TEI Reranker" \
  --provider-type TEI \
  --endpoint-url "http://tei-host:8080" \
  --model-identifier "cross-encoder/ms-marco-MiniLM-L-6-v2"
curl -sS --json @- "$GOODMEM_REST_URL/v1/rerankers" \
  --header "x-api-key: $GOODMEM_API_KEY" <<'JSON'
{
  "displayName": "TEI Reranker",
  "providerType": "TEI",
  "endpointUrl": "http://tei-host:8080",
  "modelIdentifier": "cross-encoder/ms-marco-MiniLM-L-6-v2"
}
JSON
http POST "$GOODMEM_REST_URL/v1/rerankers" \
  x-api-key:"$GOODMEM_API_KEY" \
  displayName="TEI Reranker" \
  providerType="TEI" \
  endpointUrl="http://tei-host:8080" \
  modelIdentifier="cross-encoder/ms-marco-MiniLM-L-6-v2"

vLLM (Jina-compatible rerank API):

goodmem reranker create \
  --display-name "vLLM Reranker" \
  --provider-type VLLM \
  --endpoint-url "http://vllm-host:8000/v1" \
  --model-identifier "BAAI/bge-reranker-v2-m3"
curl -sS --json @- "$GOODMEM_REST_URL/v1/rerankers" \
  --header "x-api-key: $GOODMEM_API_KEY" <<'JSON'
{
  "displayName": "vLLM Reranker",
  "providerType": "VLLM",
  "endpointUrl": "http://vllm-host:8000/v1",
  "modelIdentifier": "BAAI/bge-reranker-v2-m3"
}
JSON
http POST "$GOODMEM_REST_URL/v1/rerankers" \
  x-api-key:"$GOODMEM_API_KEY" \
  displayName="vLLM Reranker" \
  providerType="VLLM" \
  endpointUrl="http://vllm-host:8000/v1" \
  modelIdentifier="BAAI/bge-reranker-v2-m3"

Llama.cpp (Jina-compatible rerank API):

goodmem reranker create \
  --display-name "Llama.cpp Reranker" \
  --provider-type LLAMA_CPP \
  --endpoint-url "http://llama-cpp-host:8080/v1" \
  --model-identifier "BAAI/bge-reranker-v2-m3"
curl -sS --json @- "$GOODMEM_REST_URL/v1/rerankers" \
  --header "x-api-key: $GOODMEM_API_KEY" <<'JSON'
{
  "displayName": "Llama.cpp Reranker",
  "providerType": "LLAMA_CPP",
  "endpointUrl": "http://llama-cpp-host:8080/v1",
  "modelIdentifier": "BAAI/bge-reranker-v2-m3"
}
JSON
http POST "$GOODMEM_REST_URL/v1/rerankers" \
  x-api-key:"$GOODMEM_API_KEY" \
  displayName="Llama.cpp Reranker" \
  providerType="LLAMA_CPP" \
  endpointUrl="http://llama-cpp-host:8080/v1" \
  modelIdentifier="BAAI/bge-reranker-v2-m3"

Jina:

goodmem reranker create \
  --display-name "Jina Reranker" \
  --provider-type JINA \
  --endpoint-url "https://api.jina.ai" \
  --model-identifier "jina-reranker-v2-base-multilingual" \
  --cred-api-key "JINA_API_KEY"
curl -sS --json @- "$GOODMEM_REST_URL/v1/rerankers" \
  --header "x-api-key: $GOODMEM_API_KEY" <<'JSON'
{
  "displayName": "Jina Reranker",
  "providerType": "JINA",
  "endpointUrl": "https://api.jina.ai",
  "modelIdentifier": "jina-reranker-v2-base-multilingual",
  "credentials": {
    "kind": "CREDENTIAL_KIND_API_KEY",
    "apiKey": {
      "inlineSecret": "JINA_API_KEY"
    }
  }
}
JSON
http POST "$GOODMEM_REST_URL/v1/rerankers" \
  x-api-key:"$GOODMEM_API_KEY" \
  displayName="Jina Reranker" \
  providerType="JINA" \
  endpointUrl="https://api.jina.ai" \
  modelIdentifier="jina-reranker-v2-base-multilingual" \
  credentials:='{
    "kind": "CREDENTIAL_KIND_API_KEY",
    "apiKey": {
      "inlineSecret": "JINA_API_KEY"
    }
  }'

Voyage AI:

goodmem reranker create \
  --display-name "Voyage Reranker" \
  --provider-type VOYAGE \
  --endpoint-url "https://api.voyageai.com/v1" \
  --model-identifier "rerank-2.5" \
  --cred-api-key "VOYAGE_API_KEY"
curl -sS --json @- "$GOODMEM_REST_URL/v1/rerankers" \
  --header "x-api-key: $GOODMEM_API_KEY" <<'JSON'
{
  "displayName": "Voyage Reranker",
  "providerType": "VOYAGE",
  "endpointUrl": "https://api.voyageai.com/v1",
  "modelIdentifier": "rerank-2.5",
  "credentials": {
    "kind": "CREDENTIAL_KIND_API_KEY",
    "apiKey": {
      "inlineSecret": "VOYAGE_API_KEY"
    }
  }
}
JSON
http POST "$GOODMEM_REST_URL/v1/rerankers" \
  x-api-key:"$GOODMEM_API_KEY" \
  displayName="Voyage Reranker" \
  providerType="VOYAGE" \
  endpointUrl="https://api.voyageai.com/v1" \
  modelIdentifier="rerank-2.5" \
  credentials:='{
    "kind": "CREDENTIAL_KIND_API_KEY",
    "apiKey": {
      "inlineSecret": "VOYAGE_API_KEY"
    }
  }'

Cohere:

goodmem reranker create \
  --display-name "Cohere Reranker" \
  --provider-type COHERE \
  --endpoint-url "https://api.cohere.com" \
  --model-identifier "rerank-english-v3.0" \
  --cred-api-key "COHERE_API_KEY"
curl -sS --json @- "$GOODMEM_REST_URL/v1/rerankers" \
  --header "x-api-key: $GOODMEM_API_KEY" <<'JSON'
{
  "displayName": "Cohere Reranker",
  "providerType": "COHERE",
  "endpointUrl": "https://api.cohere.com",
  "modelIdentifier": "rerank-english-v3.0",
  "credentials": {
    "kind": "CREDENTIAL_KIND_API_KEY",
    "apiKey": {
      "inlineSecret": "COHERE_API_KEY"
    }
  }
}
JSON
http POST "$GOODMEM_REST_URL/v1/rerankers" \
  x-api-key:"$GOODMEM_API_KEY" \
  displayName="Cohere Reranker" \
  providerType="COHERE" \
  endpointUrl="https://api.cohere.com" \
  modelIdentifier="rerank-english-v3.0" \
  credentials:='{
    "kind": "CREDENTIAL_KIND_API_KEY",
    "apiKey": {
      "inlineSecret": "COHERE_API_KEY"
    }
  }'

LLMs

All LLM providers use OpenAI-compatible APIs. The endpoint_url must end in /v1, and api_path defaults to /chat/completions.

OpenAI:

goodmem llm create \
  --display-name "OpenAI LLM" \
  --provider-type OPENAI \
  --endpoint-url "https://api.openai.com/v1" \
  --model-identifier "gpt-4o" \
  --supports-chat \
  --cred-api-key "OPENAI_API_KEY"
curl -sS --json @- "$GOODMEM_REST_URL/v1/llms" \
  --header "x-api-key: $GOODMEM_API_KEY" <<'JSON'
{
  "displayName": "OpenAI LLM",
  "providerType": "OPENAI",
  "endpointUrl": "https://api.openai.com/v1",
  "modelIdentifier": "gpt-4o",
  "capabilities": {
    "supportsChat": true
  },
  "credentials": {
    "kind": "CREDENTIAL_KIND_API_KEY",
    "apiKey": {
      "inlineSecret": "OPENAI_API_KEY"
    }
  }
}
JSON
http POST "$GOODMEM_REST_URL/v1/llms" \
  x-api-key:"$GOODMEM_API_KEY" \
  displayName="OpenAI LLM" \
  providerType="OPENAI" \
  endpointUrl="https://api.openai.com/v1" \
  modelIdentifier="gpt-4o" \
  capabilities:='{"supportsChat": true}' \
  credentials:='{
    "kind": "CREDENTIAL_KIND_API_KEY",
    "apiKey": {
      "inlineSecret": "OPENAI_API_KEY"
    }
  }'

LiteLLM Proxy:

goodmem llm create \
  --display-name "LiteLLM Proxy" \
  --provider-type LITELLM_PROXY \
  --endpoint-url "https://litellm-host/v1" \
  --model-identifier "gpt-4o" \
  --supports-chat \
  --cred-api-key "LITELLM_API_KEY"
curl -sS --json @- "$GOODMEM_REST_URL/v1/llms" \
  --header "x-api-key: $GOODMEM_API_KEY" <<'JSON'
{
  "displayName": "LiteLLM Proxy",
  "providerType": "LITELLM_PROXY",
  "endpointUrl": "https://litellm-host/v1",
  "modelIdentifier": "gpt-4o",
  "capabilities": {
    "supportsChat": true
  },
  "credentials": {
    "kind": "CREDENTIAL_KIND_API_KEY",
    "apiKey": {
      "inlineSecret": "LITELLM_API_KEY"
    }
  }
}
JSON
http POST "$GOODMEM_REST_URL/v1/llms" \
  x-api-key:"$GOODMEM_API_KEY" \
  displayName="LiteLLM Proxy" \
  providerType="LITELLM_PROXY" \
  endpointUrl="https://litellm-host/v1" \
  modelIdentifier="gpt-4o" \
  capabilities:='{"supportsChat": true}' \
  credentials:='{
    "kind": "CREDENTIAL_KIND_API_KEY",
    "apiKey": {
      "inlineSecret": "LITELLM_API_KEY"
    }
  }'

OpenRouter:

goodmem llm create \
  --display-name "OpenRouter" \
  --provider-type OPEN_ROUTER \
  --endpoint-url "https://openrouter.ai/api/v1" \
  --model-identifier "openai/gpt-4o" \
  --supports-chat \
  --cred-api-key "OPENROUTER_API_KEY"
curl -sS --json @- "$GOODMEM_REST_URL/v1/llms" \
  --header "x-api-key: $GOODMEM_API_KEY" <<'JSON'
{
  "displayName": "OpenRouter",
  "providerType": "OPEN_ROUTER",
  "endpointUrl": "https://openrouter.ai/api/v1",
  "modelIdentifier": "openai/gpt-4o",
  "capabilities": {
    "supportsChat": true
  },
  "credentials": {
    "kind": "CREDENTIAL_KIND_API_KEY",
    "apiKey": {
      "inlineSecret": "OPENROUTER_API_KEY"
    }
  }
}
JSON
http POST "$GOODMEM_REST_URL/v1/llms" \
  x-api-key:"$GOODMEM_API_KEY" \
  displayName="OpenRouter" \
  providerType="OPEN_ROUTER" \
  endpointUrl="https://openrouter.ai/api/v1" \
  modelIdentifier="openai/gpt-4o" \
  capabilities:='{"supportsChat": true}' \
  credentials:='{
    "kind": "CREDENTIAL_KIND_API_KEY",
    "apiKey": {
      "inlineSecret": "OPENROUTER_API_KEY"
    }
  }'

vLLM:

goodmem llm create \
  --display-name "vLLM LLM" \
  --provider-type VLLM \
  --endpoint-url "http://vllm-host:8000/v1" \
  --model-identifier "your-llm-model" \
  --supports-chat
curl -sS --json @- "$GOODMEM_REST_URL/v1/llms" \
  --header "x-api-key: $GOODMEM_API_KEY" <<'JSON'
{
  "displayName": "vLLM LLM",
  "providerType": "VLLM",
  "endpointUrl": "http://vllm-host:8000/v1",
  "modelIdentifier": "your-llm-model",
  "capabilities": {
    "supportsChat": true
  }
}
JSON
http POST "$GOODMEM_REST_URL/v1/llms" \
  x-api-key:"$GOODMEM_API_KEY" \
  displayName="vLLM LLM" \
  providerType="VLLM" \
  endpointUrl="http://vllm-host:8000/v1" \
  modelIdentifier="your-llm-model" \
  capabilities:='{"supportsChat": true}'

Ollama:

goodmem llm create \
  --display-name "Ollama LLM" \
  --provider-type OLLAMA \
  --endpoint-url "http://ollama-host:11434/v1" \
  --model-identifier "llama3.1" \
  --supports-chat
curl -sS --json @- "$GOODMEM_REST_URL/v1/llms" \
  --header "x-api-key: $GOODMEM_API_KEY" <<'JSON'
{
  "displayName": "Ollama LLM",
  "providerType": "OLLAMA",
  "endpointUrl": "http://ollama-host:11434/v1",
  "modelIdentifier": "llama3.1",
  "capabilities": {
    "supportsChat": true
  }
}
JSON
http POST "$GOODMEM_REST_URL/v1/llms" \
  x-api-key:"$GOODMEM_API_KEY" \
  displayName="Ollama LLM" \
  providerType="OLLAMA" \
  endpointUrl="http://ollama-host:11434/v1" \
  modelIdentifier="llama3.1" \
  capabilities:='{"supportsChat": true}'

Llama.cpp:

goodmem llm create \
  --display-name "Llama.cpp LLM" \
  --provider-type LLAMA_CPP \
  --endpoint-url "http://llama-cpp-host:8080/v1" \
  --model-identifier "your-llm-model" \
  --supports-chat
curl -sS --json @- "$GOODMEM_REST_URL/v1/llms" \
  --header "x-api-key: $GOODMEM_API_KEY" <<'JSON'
{
  "displayName": "Llama.cpp LLM",
  "providerType": "LLAMA_CPP",
  "endpointUrl": "http://llama-cpp-host:8080/v1",
  "modelIdentifier": "your-llm-model",
  "capabilities": {
    "supportsChat": true
  }
}
JSON
http POST "$GOODMEM_REST_URL/v1/llms" \
  x-api-key:"$GOODMEM_API_KEY" \
  displayName="Llama.cpp LLM" \
  providerType="LLAMA_CPP" \
  endpointUrl="http://llama-cpp-host:8080/v1" \
  modelIdentifier="your-llm-model" \
  capabilities:='{"supportsChat": true}'

Custom OpenAI-compatible endpoint:

If your endpoint does not require authentication, omit --cred-api-key in the CLI and the credentials object in the REST examples.

goodmem llm create \
  --display-name "Custom LLM" \
  --provider-type CUSTOM_OPENAI_COMPATIBLE \
  --endpoint-url "https://your-custom-host/v1" \
  --model-identifier "your-model" \
  --supports-chat \
  --cred-api-key "OPTIONAL_API_KEY"
curl -sS --json @- "$GOODMEM_REST_URL/v1/llms" \
  --header "x-api-key: $GOODMEM_API_KEY" <<'JSON'
{
  "displayName": "Custom LLM",
  "providerType": "CUSTOM_OPENAI_COMPATIBLE",
  "endpointUrl": "https://your-custom-host/v1",
  "modelIdentifier": "your-model",
  "capabilities": {
    "supportsChat": true
  },
  "credentials": {
    "kind": "CREDENTIAL_KIND_API_KEY",
    "apiKey": {
      "inlineSecret": "OPTIONAL_API_KEY"
    }
  }
}
JSON
http POST "$GOODMEM_REST_URL/v1/llms" \
  x-api-key:"$GOODMEM_API_KEY" \
  displayName="Custom LLM" \
  providerType="CUSTOM_OPENAI_COMPATIBLE" \
  endpointUrl="https://your-custom-host/v1" \
  modelIdentifier="your-model" \
  capabilities:='{"supportsChat": true}' \
  credentials:='{
    "kind": "CREDENTIAL_KIND_API_KEY",
    "apiKey": {
      "inlineSecret": "OPTIONAL_API_KEY"
    }
  }'

Does api_path affect inference?

Not always. Some provider integrations use SDKs or generated clients that hardcode the route, so api_path is fixed and ignored at inference time:

  • Embedders: OPENAI, VLLM, LLAMA_CPP, VOYAGE (OpenAI SDK), TEI (TEI client), JINA (Jina4j), COHERE (Cohere SDK)
  • Rerankers: TEI (TEI client)
  • LLMs: all providers (OpenAI SDK)

api_path is used for rerankers that call Jina-compatible HTTP endpoints (JINA, VLLM, LLAMA_CPP, VOYAGE, COHERE). In those cases, put only the base host (and any required base path) in endpoint_url, and put the operation route in api_path.

When to override api_path

Only override api_path when your provider's route differs from the defaults above and the integration uses api_path at inference time (the Jina-compatible reranker path cases).

Work Through Metadata Filters

Upload a sample memory and practice GoodMem filter expressions with real retrieval calls.

Building a Basic RAG Agent using GoodMem

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Endpoint registration guideEndpoint fieldsapi_path values and base URLsEmbeddersRerankersLLMsRegistration recipesREST scripting notesEmbeddersRerankersLLMsDoes api_path affect inference?When to override api_path