Whether the model should be enabled.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_CHAT_MODEL_ENABLED

Whether the embedding model should be enabled.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_EMBEDDING_MODEL_ENABLED

Whether the scoring model should be enabled.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_SCORING_MODEL_ENABLED

Specifies the mode of interaction with the LLM model.

This property allows you to choose between two modes of operation:

Allowable values: [chat, generation]

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_MODE

Base URL of the watsonx.ai API.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_BASE_URL

IBM Cloud API key.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_API_KEY

Timeout for watsonx.ai calls.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_TIMEOUT

The version date for the API of the form YYYY-MM-DD.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_VERSION

The space that contains the resource.

Either space_id or project_id has to be given.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_SPACE_ID

The project that contains the resource.

Either space_id or project_id has to be given.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_PROJECT_ID

Whether the watsonx.ai client should log requests.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_LOG_REQUESTS

Whether the watsonx.ai client should log responses.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_LOG_RESPONSES

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

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_ENABLE_INTEGRATION

Base URL of the IAM Authentication API.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_IAM_BASE_URL

Timeout for IAM authentication calls.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_IAM_TIMEOUT

Grant type for the IAM Authentication API.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_IAM_GRANT_TYPE

The model to use for the chat completion.

All available models are listed in the IBM Watsonx.ai documentation at the link: following link.

To use a model, locate the API model_id column in the table and copy the corresponding model ID.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_CHAT_MODEL_MODEL_ID

Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model’s likelihood to repeat the same line verbatim.

Possible values: -2 < value < 2

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_CHAT_MODEL_FREQUENCY_PENALTY

Whether to return log probabilities of the output tokens or not. If true, returns the log probabilities of each output token returned in the content of message.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_CHAT_MODEL_LOGPROBS

An integer specifying the number of most likely tokens to return at each token position, each with an associated log probability. The option logprobs must be set to true if this parameter is used.

Possible values: 0 ≤ value ≤ 20

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_CHAT_MODEL_TOP_LOGPROBS

The maximum number of tokens that can be generated in the chat completion. The total length of input tokens and generated tokens is limited by the model’s context length.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_CHAT_MODEL_MAX_TOKENS

How many chat completion choices to generate for each input message. Note that you will be charged based on the number of generated tokens across all of the choices. Keep n as 1 to minimize costs

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_CHAT_MODEL_N

Positive values penalize new tokens based on whether they appear in the text so far, increasing the model’s likelihood to talk about new topics.

Possible values: -2 < value < 2

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_CHAT_MODEL_PRESENCE_PENALTY

Random number generator seed to use in sampling mode for experimental repeatability.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_CHAT_MODEL_SEED

Stop sequences are one or more strings which will cause the text generation to stop if/when they are produced as part of the output. Stop sequences encountered prior to the minimum number of tokens being generated will be ignored.

Possible values: 0 ≤ number of items ≤ 4

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_CHAT_MODEL_STOP

What sampling temperature to use. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.

Possible values: 0 < value < 2

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_CHAT_MODEL_TEMPERATURE

An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.

Possible values: 0 < value < 1

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_CHAT_MODEL_TOP_P

Specifies the desired format for the model’s output.

Allowable values: [json_object]

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_CHAT_MODEL_RESPONSE_FORMAT

Whether chat model requests should be logged.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_CHAT_MODEL_LOG_REQUESTS

Whether chat model responses should be logged.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_CHAT_MODEL_LOG_RESPONSES

The id of the model to be used.

All available models are listed in the IBM Watsonx.ai documentation at the link: following link.

To use a model, locate the API model_id column in the table and copy the corresponding model ID.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_GENERATION_MODEL_MODEL_ID

Represents the strategy used for picking the tokens during generation of the output text. During text generation when parameter value is set to greedy, each successive token corresponds to the highest probability token given the text that has already been generated. This strategy can lead to repetitive results especially for longer output sequences. The alternative sample strategy generates text by picking subsequent tokens based on the probability distribution of possible next tokens defined by (i.e., conditioned on) the already-generated text and the top_k and top_p parameters.

Allowable values: [sample,greedy]

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_GENERATION_MODEL_DECODING_METHOD

Represents the factor of exponential decay. Larger values correspond to more aggressive decay.

Possible values: > 1

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_GENERATION_MODEL_LENGTH_PENALTY_DECAY_FACTOR

A number of generated tokens after which this should take effect.

Possible values: ≥ 0

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_GENERATION_MODEL_LENGTH_PENALTY_START_INDEX

The maximum number of new tokens to be generated. The maximum supported value for this field depends on the model being used. How the "token" is defined depends on the tokenizer and vocabulary size, which in turn depends on the model. Often the tokens are a mix of full words and sub-words. Depending on the users plan, and on the model being used, there may be an enforced maximum number of new tokens.

Possible values: ≥ 0

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_GENERATION_MODEL_MAX_NEW_TOKENS

If stop sequences are given, they are ignored until minimum tokens are generated.

Possible values: ≥ 0

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_GENERATION_MODEL_MIN_NEW_TOKENS

Random number generator seed to use in sampling mode for experimental repeatability.

Possible values: ≥ 1

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_GENERATION_MODEL_RANDOM_SEED

Stop sequences are one or more strings which will cause the text generation to stop if/when they are produced as part of the output. Stop sequences encountered prior to the minimum number of tokens being generated will be ignored.

Possible values: 0 ≤ number of items ≤ 6

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_GENERATION_MODEL_STOP_SEQUENCES

A value used to modify the next-token probabilities in sampling mode. Values less than 1.0 sharpen the probability distribution, resulting in "less random" output. Values greater than 1.0 flatten the probability distribution, resulting in "more random" output. A value of 1.0 has no effect.

Possible values: 0 ≤ value ≤ 2

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_GENERATION_MODEL_TEMPERATURE

The number of highest probability vocabulary tokens to keep for top-k-filtering. Only applies for sampling mode. When decoding_strategy is set to sample, only the top_k most likely tokens are considered as candidates for the next generated token.

Possible values: 1 ≤ value ≤ 100

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_GENERATION_MODEL_TOP_K

Similar to top_k except the candidates to generate the next token are the most likely tokens with probabilities that add up to at least top_p. Also known as nucleus sampling. A value of 1.0 is equivalent to disabled.

Possible values: 0 < value ≤ 1

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_GENERATION_MODEL_TOP_P

Represents the penalty for penalizing tokens that have already been generated or belong to the context. The value 1.0 means that there is no penalty.

Possible values: 1 ≤ value ≤ 2

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_GENERATION_MODEL_REPETITION_PENALTY

Represents the maximum number of input tokens accepted. This can be used to avoid requests failing due to input being longer than configured limits. If the text is truncated, then it truncates the start of the input (on the left), so the end of the input will remain the same. If this value exceeds the maximum sequence length (refer to the documentation to find this value for the model) then the call will fail if the total number of tokens exceeds the maximum sequence length. Zero means don’t truncate.

Possible values: ≥ 0

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_GENERATION_MODEL_TRUNCATE_INPUT_TOKENS

Pass false to omit matched stop sequences from the end of the output text. The default is true, meaning that the output will end with the stop sequence text when matched.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_GENERATION_MODEL_INCLUDE_STOP_SEQUENCE

Whether chat model requests should be logged.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_GENERATION_MODEL_LOG_REQUESTS

Whether chat model responses should be logged.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_GENERATION_MODEL_LOG_RESPONSES

Delimiter used to concatenate the ChatMessage elements into a single string. By setting this property, you can define your preferred way of concatenating messages to ensure that the prompt is structured in the correct way.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_GENERATION_MODEL_PROMPT_JOINER

The id of the model to be used.

All available models are listed in the IBM Watsonx.ai documentation at the link: following link.

To use a model, locate the API model_id column in the table and copy the corresponding model ID.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_EMBEDDING_MODEL_MODEL_ID

Represents the maximum number of input tokens accepted. This can be used to avoid requests failing due to input being longer than configured limits. If the text is truncated, then it truncates the end of the input (on the right), so the start of the input will remain the same. If this value exceeds the maximum sequence length (refer to the documentation to find this value for the model) then the call will fail if the total number of tokens exceeds the maximum sequence length.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_EMBEDDING_MODEL_TRUNCATE_INPUT_TOKENS

Whether embedding model requests should be logged.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_EMBEDDING_MODEL_LOG_REQUESTS

Whether embedding model responses should be logged.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_EMBEDDING_MODEL_LOG_RESPONSES

The id of the model to be used.

All available models are listed in the IBM Watsonx.ai documentation at the link: following link.

To use a model, locate the API model_id column in the table and copy the corresponding model ID.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_SCORING_MODEL_MODEL_ID

Represents the maximum number of input tokens accepted. This can be used to avoid requests failing due to input being longer than configured limits. If the text is truncated, then it truncates the end of the input (on the right), so the start of the input will remain the same. If this value exceeds the maximum sequence length (refer to the documentation to find this value for the model) then the call will fail if the total number of tokens exceeds the maximum sequence length.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_SCORING_MODEL_TRUNCATE_INPUT_TOKENS

Whether embedding model requests should be logged.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_SCORING_MODEL_LOG_REQUESTS

Whether embedding model responses should be logged.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX_SCORING_MODEL_LOG_RESPONSES

Base URL of the watsonx.ai API.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__BASE_URL

IBM Cloud API key.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__API_KEY

Timeout for watsonx.ai calls.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__TIMEOUT

The version date for the API of the form YYYY-MM-DD.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__VERSION

The space that contains the resource.

Either space_id or project_id has to be given.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__SPACE_ID

The project that contains the resource.

Either space_id or project_id has to be given.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__PROJECT_ID

Whether the watsonx.ai client should log requests.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__LOG_REQUESTS

Whether the watsonx.ai client should log responses.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__LOG_RESPONSES

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

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__ENABLE_INTEGRATION

Base URL of the IAM Authentication API.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__IAM_BASE_URL

Timeout for IAM authentication calls.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__IAM_TIMEOUT

Grant type for the IAM Authentication API.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__IAM_GRANT_TYPE

The model to use for the chat completion.

All available models are listed in the IBM Watsonx.ai documentation at the link: following link.

To use a model, locate the API model_id column in the table and copy the corresponding model ID.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__CHAT_MODEL_MODEL_ID

Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model’s likelihood to repeat the same line verbatim.

Possible values: -2 < value < 2

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__CHAT_MODEL_FREQUENCY_PENALTY

Whether to return log probabilities of the output tokens or not. If true, returns the log probabilities of each output token returned in the content of message.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__CHAT_MODEL_LOGPROBS

An integer specifying the number of most likely tokens to return at each token position, each with an associated log probability. The option logprobs must be set to true if this parameter is used.

Possible values: 0 ≤ value ≤ 20

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__CHAT_MODEL_TOP_LOGPROBS

The maximum number of tokens that can be generated in the chat completion. The total length of input tokens and generated tokens is limited by the model’s context length.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__CHAT_MODEL_MAX_TOKENS

How many chat completion choices to generate for each input message. Note that you will be charged based on the number of generated tokens across all of the choices. Keep n as 1 to minimize costs

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__CHAT_MODEL_N

Positive values penalize new tokens based on whether they appear in the text so far, increasing the model’s likelihood to talk about new topics.

Possible values: -2 < value < 2

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__CHAT_MODEL_PRESENCE_PENALTY

Random number generator seed to use in sampling mode for experimental repeatability.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__CHAT_MODEL_SEED

Stop sequences are one or more strings which will cause the text generation to stop if/when they are produced as part of the output. Stop sequences encountered prior to the minimum number of tokens being generated will be ignored.

Possible values: 0 ≤ number of items ≤ 4

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__CHAT_MODEL_STOP

What sampling temperature to use. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.

Possible values: 0 < value < 2

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__CHAT_MODEL_TEMPERATURE

An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.

Possible values: 0 < value < 1

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__CHAT_MODEL_TOP_P

Specifies the desired format for the model’s output.

Allowable values: [json_object]

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__CHAT_MODEL_RESPONSE_FORMAT

Whether chat model requests should be logged.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__CHAT_MODEL_LOG_REQUESTS

Whether chat model responses should be logged.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__CHAT_MODEL_LOG_RESPONSES

The id of the model to be used.

All available models are listed in the IBM Watsonx.ai documentation at the link: following link.

To use a model, locate the API model_id column in the table and copy the corresponding model ID.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__GENERATION_MODEL_MODEL_ID

Represents the strategy used for picking the tokens during generation of the output text. During text generation when parameter value is set to greedy, each successive token corresponds to the highest probability token given the text that has already been generated. This strategy can lead to repetitive results especially for longer output sequences. The alternative sample strategy generates text by picking subsequent tokens based on the probability distribution of possible next tokens defined by (i.e., conditioned on) the already-generated text and the top_k and top_p parameters.

Allowable values: [sample,greedy]

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__GENERATION_MODEL_DECODING_METHOD

Represents the factor of exponential decay. Larger values correspond to more aggressive decay.

Possible values: > 1

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__GENERATION_MODEL_LENGTH_PENALTY_DECAY_FACTOR

A number of generated tokens after which this should take effect.

Possible values: ≥ 0

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__GENERATION_MODEL_LENGTH_PENALTY_START_INDEX

The maximum number of new tokens to be generated. The maximum supported value for this field depends on the model being used. How the "token" is defined depends on the tokenizer and vocabulary size, which in turn depends on the model. Often the tokens are a mix of full words and sub-words. Depending on the users plan, and on the model being used, there may be an enforced maximum number of new tokens.

Possible values: ≥ 0

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__GENERATION_MODEL_MAX_NEW_TOKENS

If stop sequences are given, they are ignored until minimum tokens are generated.

Possible values: ≥ 0

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__GENERATION_MODEL_MIN_NEW_TOKENS

Random number generator seed to use in sampling mode for experimental repeatability.

Possible values: ≥ 1

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__GENERATION_MODEL_RANDOM_SEED

Stop sequences are one or more strings which will cause the text generation to stop if/when they are produced as part of the output. Stop sequences encountered prior to the minimum number of tokens being generated will be ignored.

Possible values: 0 ≤ number of items ≤ 6

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__GENERATION_MODEL_STOP_SEQUENCES

A value used to modify the next-token probabilities in sampling mode. Values less than 1.0 sharpen the probability distribution, resulting in "less random" output. Values greater than 1.0 flatten the probability distribution, resulting in "more random" output. A value of 1.0 has no effect.

Possible values: 0 ≤ value ≤ 2

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__GENERATION_MODEL_TEMPERATURE

The number of highest probability vocabulary tokens to keep for top-k-filtering. Only applies for sampling mode. When decoding_strategy is set to sample, only the top_k most likely tokens are considered as candidates for the next generated token.

Possible values: 1 ≤ value ≤ 100

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__GENERATION_MODEL_TOP_K

Similar to top_k except the candidates to generate the next token are the most likely tokens with probabilities that add up to at least top_p. Also known as nucleus sampling. A value of 1.0 is equivalent to disabled.

Possible values: 0 < value ≤ 1

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__GENERATION_MODEL_TOP_P

Represents the penalty for penalizing tokens that have already been generated or belong to the context. The value 1.0 means that there is no penalty.

Possible values: 1 ≤ value ≤ 2

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__GENERATION_MODEL_REPETITION_PENALTY

Represents the maximum number of input tokens accepted. This can be used to avoid requests failing due to input being longer than configured limits. If the text is truncated, then it truncates the start of the input (on the left), so the end of the input will remain the same. If this value exceeds the maximum sequence length (refer to the documentation to find this value for the model) then the call will fail if the total number of tokens exceeds the maximum sequence length. Zero means don’t truncate.

Possible values: ≥ 0

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__GENERATION_MODEL_TRUNCATE_INPUT_TOKENS

Pass false to omit matched stop sequences from the end of the output text. The default is true, meaning that the output will end with the stop sequence text when matched.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__GENERATION_MODEL_INCLUDE_STOP_SEQUENCE

Whether chat model requests should be logged.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__GENERATION_MODEL_LOG_REQUESTS

Whether chat model responses should be logged.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__GENERATION_MODEL_LOG_RESPONSES

Delimiter used to concatenate the ChatMessage elements into a single string. By setting this property, you can define your preferred way of concatenating messages to ensure that the prompt is structured in the correct way.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__GENERATION_MODEL_PROMPT_JOINER

The id of the model to be used.

All available models are listed in the IBM Watsonx.ai documentation at the link: following link.

To use a model, locate the API model_id column in the table and copy the corresponding model ID.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__EMBEDDING_MODEL_MODEL_ID

Represents the maximum number of input tokens accepted. This can be used to avoid requests failing due to input being longer than configured limits. If the text is truncated, then it truncates the end of the input (on the right), so the start of the input will remain the same. If this value exceeds the maximum sequence length (refer to the documentation to find this value for the model) then the call will fail if the total number of tokens exceeds the maximum sequence length.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__EMBEDDING_MODEL_TRUNCATE_INPUT_TOKENS

Whether embedding model requests should be logged.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__EMBEDDING_MODEL_LOG_REQUESTS

Whether embedding model responses should be logged.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__EMBEDDING_MODEL_LOG_RESPONSES

The id of the model to be used.

All available models are listed in the IBM Watsonx.ai documentation at the link: following link.

To use a model, locate the API model_id column in the table and copy the corresponding model ID.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__SCORING_MODEL_MODEL_ID

Represents the maximum number of input tokens accepted. This can be used to avoid requests failing due to input being longer than configured limits. If the text is truncated, then it truncates the end of the input (on the right), so the start of the input will remain the same. If this value exceeds the maximum sequence length (refer to the documentation to find this value for the model) then the call will fail if the total number of tokens exceeds the maximum sequence length.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__SCORING_MODEL_TRUNCATE_INPUT_TOKENS

Whether embedding model requests should be logged.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__SCORING_MODEL_LOG_REQUESTS

Whether embedding model responses should be logged.

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__SCORING_MODEL_LOG_RESPONSES

Specifies the mode of interaction with the LLM model.

This property allows you to choose between two modes of operation:

Allowable values: [chat, generation]

Environment variable: QUARKUS_LANGCHAIN4J_WATSONX__MODEL_NAME__MODE