import goodmem_client
from goodmem_client.models.embedder_creation_request import EmbedderCreationRequest
from goodmem_client.models.embedder_response import EmbedderResponse
from goodmem_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost:8080/v1/default
# See configuration.py for a list of all supported configuration parameters.
configuration = goodmem_client.Configuration(
    host = "http://localhost:8080/v1/default"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure API key authorization: ApiKeyAuth
configuration.api_key['ApiKeyAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['ApiKeyAuth'] = 'Bearer'

# Enter a context with an instance of the API client
with goodmem_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = goodmem_client.EmbeddersApi(api_client)
    embedder_creation_request = {"displayName":"OpenAI Embedding Model","description":"OpenAI text embedding model with 1536 dimensions","providerType":"OPENAI","endpointUrl":"https://api.openai.com/v1","apiPath":"/embeddings","modelIdentifier":"text-embedding-3-small","dimensionality":"1536","distributionType":"DENSE","maxSequenceLength":"8192","supportedModalities":["TEXT"],"credentials":{"kind":"CREDENTIAL_KIND_API_KEY","apiKey":{"inlineSecret":"sk-your-api-key-here"}},"labels":{"environment":"production","team":"nlp"}} # EmbedderCreationRequest | Embedder configuration details

    try:
        # Create a new embedder
        api_response = api_instance.create_embedder(embedder_creation_request)
        print("The response of EmbeddersApi->create_embedder:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling EmbeddersApi->create_embedder: %s\n" % e)

import goodmem_client
from goodmem_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost:8080/v1/default
# See configuration.py for a list of all supported configuration parameters.
configuration = goodmem_client.Configuration(
    host = "http://localhost:8080/v1/default"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure API key authorization: ApiKeyAuth
configuration.api_key['ApiKeyAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['ApiKeyAuth'] = 'Bearer'

# Enter a context with an instance of the API client
with goodmem_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = goodmem_client.EmbeddersApi(api_client)
    id = '550e8400-e29b-41d4-a716-446655440000' # str | The unique identifier of the embedder to delete

    try:
        # Delete an embedder
        api_instance.delete_embedder(id)
    except Exception as e:
        print("Exception when calling EmbeddersApi->delete_embedder: %s\n" % e)

import goodmem_client
from goodmem_client.models.embedder_response import EmbedderResponse
from goodmem_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost:8080/v1/default
# See configuration.py for a list of all supported configuration parameters.
configuration = goodmem_client.Configuration(
    host = "http://localhost:8080/v1/default"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure API key authorization: ApiKeyAuth
configuration.api_key['ApiKeyAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['ApiKeyAuth'] = 'Bearer'

# Enter a context with an instance of the API client
with goodmem_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = goodmem_client.EmbeddersApi(api_client)
    id = '550e8400-e29b-41d4-a716-446655440000' # str | The unique identifier of the embedder to retrieve

    try:
        # Get an embedder by ID
        api_response = api_instance.get_embedder(id)
        print("The response of EmbeddersApi->get_embedder:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling EmbeddersApi->get_embedder: %s\n" % e)

import goodmem_client
from goodmem_client.models.list_embedders_response import ListEmbeddersResponse
from goodmem_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost:8080/v1/default
# See configuration.py for a list of all supported configuration parameters.
configuration = goodmem_client.Configuration(
    host = "http://localhost:8080/v1/default"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure API key authorization: ApiKeyAuth
configuration.api_key['ApiKeyAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['ApiKeyAuth'] = 'Bearer'

# Enter a context with an instance of the API client
with goodmem_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = goodmem_client.EmbeddersApi(api_client)
    owner_id = '550e8400-e29b-41d4-a716-446655440000' # str | Filter embedders by owner ID. With LIST_EMBEDDER_ANY permission, omitting this shows all accessible embedders; providing it filters by that owner. With LIST_EMBEDDER_OWN permission, only your own embedders are shown regardless of this parameter. (optional)
    provider_type = 'OPENAI' # str | Filter embedders by provider type (e.g., OPENAI, OPENAI_COMPATIBLE, COHERE, etc.) (optional)
    label_ = '?label.environment=production&label.team=nlp' # str | Filter by label value. Multiple label filters can be specified (e.g., ?label.environment=production&label.team=nlp) (optional)

    try:
        # List embedders
        api_response = api_instance.list_embedders(owner_id=owner_id, provider_type=provider_type, label_=label_)
        print("The response of EmbeddersApi->list_embedders:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling EmbeddersApi->list_embedders: %s\n" % e)

import goodmem_client
from goodmem_client.models.embedder_response import EmbedderResponse
from goodmem_client.models.update_embedder_request import UpdateEmbedderRequest
from goodmem_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost:8080/v1/default
# See configuration.py for a list of all supported configuration parameters.
configuration = goodmem_client.Configuration(
    host = "http://localhost:8080/v1/default"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure API key authorization: ApiKeyAuth
configuration.api_key['ApiKeyAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['ApiKeyAuth'] = 'Bearer'

# Enter a context with an instance of the API client
with goodmem_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = goodmem_client.EmbeddersApi(api_client)
    id = '550e8400-e29b-41d4-a716-446655440000' # str | The unique identifier of the embedder to update
    update_embedder_request = {"displayName":"Updated Production Embedder","description":"Updated OpenAI embedding model with enhanced configuration for production use","endpointUrl":"https://api.openai.com/v1","apiPath":"/embeddings","modelIdentifier":"text-embedding-3-large","dimensionality":"3072","maxSequenceLength":"8192","supportedModalities":["TEXT"],"credentials":"{\\\"kind\\\":\\\"CREDENTIAL_KIND_API_KEY\\\",\\\"apiKey\\\":{\\\"inlineSecret\\\":\\\"sk-updated-api-key-here\\\"}}","version":"2.0.1","monitoringEndpoint":"https://monitoring.company.com/embedders/status","replaceLabels":{"environment":"production","team":"ml-platform","cost-center":"ai-infrastructure"}} # UpdateEmbedderRequest | Embedder update details

    try:
        # Update an embedder
        api_response = api_instance.update_embedder(id, update_embedder_request)
        print("The response of EmbeddersApi->update_embedder:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling EmbeddersApi->update_embedder: %s\n" % e)