Whether the model should be enabled

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA_CHAT_MODEL_ENABLED

Whether the model should be enabled

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA_EMBEDDING_MODEL_ENABLED

If Dev Services for Ollama has been explicitly enabled or disabled. Dev Services are generally enabled by default, unless there is an existing configuration present.

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA_DEVSERVICES_ENABLED

The Ollama container image to use.

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA_DEVSERVICES_IMAGE_NAME

Model to use

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA_CHAT_MODEL_MODEL_ID

Model to use. According to Ollama docs, the default value is nomic-embed-text

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA_EMBEDDING_MODEL_MODEL_ID

Base URL where the Ollama serving is running

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA_BASE_URL

If set, the named TLS configuration with the configured name will be applied to the REST Client

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA_TLS_CONFIGURATION_NAME

Timeout for Ollama calls

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA_TIMEOUT

Whether the Ollama client should log requests

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA_LOG_REQUESTS

Whether the Ollama client should log responses

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA_LOG_RESPONSES

Whether to enable the integration. Defaults to true, which means requests are made to the OpenAI provider. Set to false to disable all requests.

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA_ENABLE_INTEGRATION

The temperature of the model. Increasing the temperature will make the model answer with more variability. A lower temperature will make the model answer more conservatively.

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA_CHAT_MODEL_TEMPERATURE

Maximum number of tokens to predict when generating text

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA_CHAT_MODEL_NUM_PREDICT

Sets the stop sequences to use. When this pattern is encountered the LLM will stop generating text and return

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA_CHAT_MODEL_STOP

Works together with top-k. A higher value (e.g., 0.95) will lead to more diverse text, while a lower value (e.g., 0.5) will generate more focused and conservative text

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA_CHAT_MODEL_TOP_P

Reduces the probability of generating nonsense. A higher value (e.g. 100) will give more diverse answers, while a lower value (e.g. 10) will be more conservative

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA_CHAT_MODEL_TOP_K

With a static number the result is always the same. With a random number the result varies Example:

Random random = new Random(); int x = random.nextInt(Integer.MAX_VALUE);

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA_CHAT_MODEL_SEED

The format to return a response in. Format can be json or a JSON schema.

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA_CHAT_MODEL_FORMAT

Whether chat model requests should be logged

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA_CHAT_MODEL_LOG_REQUESTS

Whether chat model responses should be logged

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA_CHAT_MODEL_LOG_RESPONSES

The temperature of the model. Increasing the temperature will make the model answer with more variability. A lower temperature will make the model answer more conservatively.

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA_EMBEDDING_MODEL_TEMPERATURE

Maximum number of tokens to predict when generating text

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA_EMBEDDING_MODEL_NUM_PREDICT

Sets the stop sequences to use. When this pattern is encountered the LLM will stop generating text and return

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA_EMBEDDING_MODEL_STOP

Works together with top-k. A higher value (e.g., 0.95) will lead to more diverse text, while a lower value (e.g., 0.5) will generate more focused and conservative text

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA_EMBEDDING_MODEL_TOP_P

Reduces the probability of generating nonsense. A higher value (e.g. 100) will give more diverse answers, while a lower value (e.g. 10) will be more conservative

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA_EMBEDDING_MODEL_TOP_K

Whether embedding model requests should be logged

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA_EMBEDDING_MODEL_LOG_REQUESTS

Whether embedding model responses should be logged

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA_EMBEDDING_MODEL_LOG_RESPONSES

Model to use

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA__MODEL_NAME__CHAT_MODEL_MODEL_ID

Model to use. According to Ollama docs, the default value is nomic-embed-text

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA__MODEL_NAME__EMBEDDING_MODEL_MODEL_ID

Base URL where the Ollama serving is running

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA__MODEL_NAME__BASE_URL

If set, the named TLS configuration with the configured name will be applied to the REST Client

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA__MODEL_NAME__TLS_CONFIGURATION_NAME

Timeout for Ollama calls

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA__MODEL_NAME__TIMEOUT

Whether the Ollama client should log requests

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA__MODEL_NAME__LOG_REQUESTS

Whether the Ollama client should log responses

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA__MODEL_NAME__LOG_RESPONSES

Whether to enable the integration. Defaults to true, which means requests are made to the OpenAI provider. Set to false to disable all requests.

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA__MODEL_NAME__ENABLE_INTEGRATION

The temperature of the model. Increasing the temperature will make the model answer with more variability. A lower temperature will make the model answer more conservatively.

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA__MODEL_NAME__CHAT_MODEL_TEMPERATURE

Maximum number of tokens to predict when generating text

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA__MODEL_NAME__CHAT_MODEL_NUM_PREDICT

Sets the stop sequences to use. When this pattern is encountered the LLM will stop generating text and return

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA__MODEL_NAME__CHAT_MODEL_STOP

Works together with top-k. A higher value (e.g., 0.95) will lead to more diverse text, while a lower value (e.g., 0.5) will generate more focused and conservative text

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA__MODEL_NAME__CHAT_MODEL_TOP_P

Reduces the probability of generating nonsense. A higher value (e.g. 100) will give more diverse answers, while a lower value (e.g. 10) will be more conservative

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA__MODEL_NAME__CHAT_MODEL_TOP_K

With a static number the result is always the same. With a random number the result varies Example:

Random random = new Random(); int x = random.nextInt(Integer.MAX_VALUE);

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA__MODEL_NAME__CHAT_MODEL_SEED

The format to return a response in. Format can be json or a JSON schema.

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA__MODEL_NAME__CHAT_MODEL_FORMAT

Whether chat model requests should be logged

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA__MODEL_NAME__CHAT_MODEL_LOG_REQUESTS

Whether chat model responses should be logged

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA__MODEL_NAME__CHAT_MODEL_LOG_RESPONSES

The temperature of the model. Increasing the temperature will make the model answer with more variability. A lower temperature will make the model answer more conservatively.

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA__MODEL_NAME__EMBEDDING_MODEL_TEMPERATURE

Maximum number of tokens to predict when generating text

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA__MODEL_NAME__EMBEDDING_MODEL_NUM_PREDICT

Sets the stop sequences to use. When this pattern is encountered the LLM will stop generating text and return

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA__MODEL_NAME__EMBEDDING_MODEL_STOP

Works together with top-k. A higher value (e.g., 0.95) will lead to more diverse text, while a lower value (e.g., 0.5) will generate more focused and conservative text

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA__MODEL_NAME__EMBEDDING_MODEL_TOP_P

Reduces the probability of generating nonsense. A higher value (e.g. 100) will give more diverse answers, while a lower value (e.g. 10) will be more conservative

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA__MODEL_NAME__EMBEDDING_MODEL_TOP_K

Whether embedding model requests should be logged

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA__MODEL_NAME__EMBEDDING_MODEL_LOG_REQUESTS

Whether embedding model responses should be logged

Environment variable: QUARKUS_LANGCHAIN4J_OLLAMA__MODEL_NAME__EMBEDDING_MODEL_LOG_RESPONSES