Path to the directory containing the documents to be ingested. This is either an absolute or relative path in the filesystem. A relative path is resolved against the current working directory at runtime.

Environment variable: QUARKUS_LANGCHAIN4J_EASY_RAG_PATH

Does path() represent a filesystem reference or a classpath reference?

Environment variable: QUARKUS_LANGCHAIN4J_EASY_RAG_PATH_TYPE

Matcher used for filtering which files from the directory should be ingested. This uses the java.nio.file.FileSystem path matcher syntax. Example: glob:**.txt to recursively match all files with the .txt extension. The default is glob:**, recursively matching all files.

Environment variable: QUARKUS_LANGCHAIN4J_EASY_RAG_PATH_MATCHER

Whether to recursively ingest documents from subdirectories.

Environment variable: QUARKUS_LANGCHAIN4J_EASY_RAG_RECURSIVE

Maximum segment size when splitting documents, in tokens.

Environment variable: QUARKUS_LANGCHAIN4J_EASY_RAG_MAX_SEGMENT_SIZE

Maximum overlap (in tokens) when splitting documents.

Environment variable: QUARKUS_LANGCHAIN4J_EASY_RAG_MAX_OVERLAP_SIZE

Maximum number of results to return when querying the retrieval augmentor.

Environment variable: QUARKUS_LANGCHAIN4J_EASY_RAG_MAX_RESULTS

The minimum score for results to return when querying the retrieval augmentor.

Environment variable: QUARKUS_LANGCHAIN4J_EASY_RAG_MIN_SCORE

The strategy to decide whether document ingestion into the store should happen at startup or not. The default is ON. Changing to OFF generally only makes sense if running against a persistent embedding store that was already populated. When set to MANUAL, it is expected that the application will inject and call the io.quarkiverse.langchain4j.easyrag.EasyRagManualIngestion bean to trigger the ingestion when desired.

Environment variable: QUARKUS_LANGCHAIN4J_EASY_RAG_INGESTION_STRATEGY

Whether or not to reuse embeddings. Defaults to false.

Environment variable: QUARKUS_LANGCHAIN4J_EASY_RAG_REUSE_EMBEDDINGS_ENABLED

The file path to load/save embeddings, assuming quarkus.langchain4j.easy-rag.reuse-embeddings.enabled == true.

Defaults to easy-rag-embeddings.json in the current directory.

Environment variable: QUARKUS_LANGCHAIN4J_EASY_RAG_REUSE_EMBEDDINGS_FILE

Whether the MCP extension should automatically generate a ToolProvider that is wired up to all the configured MCP clients. The default is true if at least one MCP client is configured, false otherwise.

Environment variable: QUARKUS_LANGCHAIN4J_MCP_GENERATE_TOOL_PROVIDER

File containing the MCP servers configuration in the Claude Desktop format. This configuration can only be used to configure stdio transport type MCP servers.

This file is read at build time which means that which MCP servers the client will use, is determined at build time. However, specific configuration of each MCP server can be overridden at runtime.

Environment variable: QUARKUS_LANGCHAIN4J_MCP_CONFIG_FILE

Whether the MCP extension should automatically register a health check for configured MCP clients. The default is true if at least one MCP client is configured, false otherwise.

Environment variable: QUARKUS_LANGCHAIN4J_MCP_HEALTH_ENABLED

Whether resources should be exposed as MCP tools.

Environment variable: QUARKUS_LANGCHAIN4J_MCP_EXPOSE_RESOURCES_AS_TOOLS

Transport type

Environment variable: QUARKUS_LANGCHAIN4J_MCP__CLIENT_NAME__TRANSPORT_TYPE

The URL of the SSE endpoint. This only applies to MCP clients using the HTTP transport.

Environment variable: QUARKUS_LANGCHAIN4J_MCP__CLIENT_NAME__URL

The command to execute to spawn the MCP server process. This only applies to MCP clients using the STDIO transport.

Environment variable: QUARKUS_LANGCHAIN4J_MCP__CLIENT_NAME__COMMAND

Environment variables for the spawned MCP server process. This only applies to MCP clients using the STDIO transport.

Environment variable: QUARKUS_LANGCHAIN4J_MCP__CLIENT_NAME__ENVIRONMENT__ENV_VAR_

Whether to log requests

Environment variable: QUARKUS_LANGCHAIN4J_MCP__CLIENT_NAME__LOG_REQUESTS

Whether to log responses

Environment variable: QUARKUS_LANGCHAIN4J_MCP__CLIENT_NAME__LOG_RESPONSES

Whether to prefer MicroProfile health checks. Applies to MCP HTTP clients only.

If this property is enabled, an HTTP GET call is made to an MCP Server MicroProfile Health endpoint. MicroProfile Health endpoint URL is calculated by extracting a base URL that has no path component from the url() property and adding the microprofile-health-check-path() path to it.

Default MCP Client health check that opens a Streamable HTTP or SSE transport channel is attempted when a MicroProfile health check returns an HTTP 404 or other error status.

Environment variable: QUARKUS_LANGCHAIN4J_MCP__CLIENT_NAME__MICROPROFILE_HEALTH_CHECK

Relative path of an MCP Server MicroProfile Health endpoint. This property is effective only when the microprofile-health-check() property is enabled.

MicroProfile Health endpoint URL is calculated by extracting the base URL that has no path component from the url() property and adding a value of this property to it.

Environment variable: QUARKUS_LANGCHAIN4J_MCP__CLIENT_NAME__MICROPROFILE_HEALTH_CHECK_PATH

Timeout for tool executions performed by the MCP client

Environment variable: QUARKUS_LANGCHAIN4J_MCP__CLIENT_NAME__TOOL_EXECUTION_TIMEOUT

Timeout for resource-related operations (retrieving a list of resources as well as the actual contents of resources).

Environment variable: QUARKUS_LANGCHAIN4J_MCP__CLIENT_NAME__RESOURCES_TIMEOUT

Timeout for pinging the MCP server process to check if it’s still alive. If a ping times out, the client’s health check will start failing.

Environment variable: QUARKUS_LANGCHAIN4J_MCP__CLIENT_NAME__PING_TIMEOUT

The initial list of MCP roots that the client can present to the server. The list can be later updated programmatically during runtime. The list is formatted as key-value pairs separated by commas. For example: workspace1=/path/to/workspace1,workspace2=/path/to/workspace2

Environment variable: QUARKUS_LANGCHAIN4J_MCP__CLIENT_NAME__ROOTS

The name of the TLS configuration (bucket) used for client authentication in the TLS registry. This does not have any effect when the stdio transport is used.

Environment variable: QUARKUS_LANGCHAIN4J_MCP__CLIENT_NAME__TLS_CONFIGURATION_NAME

Whether to cache the tool list obtained from the MCP server. When set to true (the default), the tool list is cached until the server notifies of changes or the cache is manually evicted. When false, the client always fetches a fresh tool list from the server. This is useful when using MCP servers that don’t support tool list change notifications.

Environment variable: QUARKUS_LANGCHAIN4J_MCP__CLIENT_NAME__CACHE_TOOL_LIST

The base URL of the MCP registry, without the API version segment. The default value points at the official registry (https://registry.modelcontextprotocol.io).

Environment variable: QUARKUS_LANGCHAIN4J_MCP_REGISTRY_CLIENT__REGISTRY_CLIENT_NAME__BASE_URL

Whether to log requests

Environment variable: QUARKUS_LANGCHAIN4J_MCP_REGISTRY_CLIENT__REGISTRY_CLIENT_NAME__LOG_REQUESTS

Whether to log responses

Environment variable: QUARKUS_LANGCHAIN4J_MCP_REGISTRY_CLIENT__REGISTRY_CLIENT_NAME__LOG_RESPONSES

The name of the TLS configuration (bucket) that this MCP client registry will use.

Environment variable: QUARKUS_LANGCHAIN4J_MCP_REGISTRY_CLIENT__REGISTRY_CLIENT_NAME__TLS_CONFIGURATION_NAME

The read timeout for the MCP registry’s underlying http client

Environment variable: QUARKUS_LANGCHAIN4J_MCP_REGISTRY_CLIENT__REGISTRY_CLIENT_NAME__READ_TIMEOUT

The connect timeout for the MCP registry’s underlying http client

Environment variable: QUARKUS_LANGCHAIN4J_MCP_REGISTRY_CLIENT__REGISTRY_CLIENT_NAME__CONNECT_TIMEOUT

Dimension of the embeddings that will be stored in the Neo4j store.

Environment variable: QUARKUS_LANGCHAIN4J_NEO4J_DIMENSION

Label for the created nodes.

Environment variable: QUARKUS_LANGCHAIN4J_NEO4J_LABEL

Name of the property to store the embedding vectors.

Environment variable: QUARKUS_LANGCHAIN4J_NEO4J_EMBEDDING_PROPERTY

Name of the property to store embedding IDs.

Environment variable: QUARKUS_LANGCHAIN4J_NEO4J_ID_PROPERTY

Prefix to be added to the metadata keys. By default, no prefix is used.

Environment variable: QUARKUS_LANGCHAIN4J_NEO4J_METADATA_PREFIX

Name of the property to store the embedding text.

Environment variable: QUARKUS_LANGCHAIN4J_NEO4J_TEXT_PROPERTY

Name of the index to be created for vector search.

Environment variable: QUARKUS_LANGCHAIN4J_NEO4J_INDEX_NAME

Name of the database to connect to.

Environment variable: QUARKUS_LANGCHAIN4J_NEO4J_DATABASE_NAME

The query to use when retrieving embeddings. This query has to return the following columns:

Environment variable: QUARKUS_LANGCHAIN4J_NEO4J_RETRIEVAL_QUERY

The API key to Pinecone.

Environment variable: QUARKUS_LANGCHAIN4J_PINECONE_API_KEY

Environment name, e.g. gcp-starter or northamerica-northeast1-gcp.

Environment variable: QUARKUS_LANGCHAIN4J_PINECONE_ENVIRONMENT

ID of the project.

Environment variable: QUARKUS_LANGCHAIN4J_PINECONE_PROJECT_ID

Name of the index within the project. If the index doesn’t exist, it will be created.

Environment variable: QUARKUS_LANGCHAIN4J_PINECONE_INDEX_NAME

Dimension of the embeddings in the index. This is required only in case that the index doesn’t exist yet and needs to be created.

Environment variable: QUARKUS_LANGCHAIN4J_PINECONE_DIMENSION

The type of the pod to use. This is only used if the index doesn’t exist yet and needs to be created. The format: One of s1, p1, or p2 appended with . and one of x1, x2, x4, or x8.

Environment variable: QUARKUS_LANGCHAIN4J_PINECONE_POD_TYPE

The timeout duration for the index to become ready. Only relevant if the index doesn’t exist yet and needs to be created. If not specified, 1 minute will be used.

Environment variable: QUARKUS_LANGCHAIN4J_PINECONE_INDEX_READINESS_TIMEOUT

The namespace.

Environment variable: QUARKUS_LANGCHAIN4J_PINECONE_NAMESPACE

The name of the field that contains the text segment.

Environment variable: QUARKUS_LANGCHAIN4J_PINECONE_TEXT_FIELD_NAME

The timeout duration for the Pinecone client. If not specified, 5 seconds will be used.

Environment variable: QUARKUS_LANGCHAIN4J_PINECONE_TIMEOUT

Base URL of the Tavily API

Environment variable: QUARKUS_LANGCHAIN4J_TAVILY_BASE_URL

API key for the Tavily API

Environment variable: QUARKUS_LANGCHAIN4J_TAVILY_API_KEY

Maximum number of results to return

Environment variable: QUARKUS_LANGCHAIN4J_TAVILY_MAX_RESULTS

The timeout duration for Tavily requests.

Environment variable: QUARKUS_LANGCHAIN4J_TAVILY_TIMEOUT

Whether requests to Tavily should be logged

Environment variable: QUARKUS_LANGCHAIN4J_TAVILY_LOG_REQUESTS

Whether responses from Tavily should be logged

Environment variable: QUARKUS_LANGCHAIN4J_TAVILY_LOG_RESPONSES

The search depth to use. This can be "basic" or "advanced". Basic is the default.

Environment variable: QUARKUS_LANGCHAIN4J_TAVILY_SEARCH_DEPTH

Include a short answer to original query. Default is false.

Environment variable: QUARKUS_LANGCHAIN4J_TAVILY_INCLUDE_ANSWER

Include the cleaned and parsed HTML content of each search result. Default is false.

Environment variable: QUARKUS_LANGCHAIN4J_TAVILY_INCLUDE_RAW_CONTENT

A list of domains to specifically include in the search results. By default all domains are included.

Environment variable: QUARKUS_LANGCHAIN4J_TAVILY_INCLUDE_DOMAINS

A list of domains to specifically exclude from the search results. By default no domains are excluded.

Environment variable: QUARKUS_LANGCHAIN4J_TAVILY_EXCLUDE_DOMAINS

Whether the model should be enabled

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI_CHAT_MODEL_ENABLED

Whether the model should be enabled

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI_EMBEDDING_MODEL_ENABLED

The api key

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI_API_KEY

Publisher of model

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI_PUBLISHER

Meant to be used for testing only in order to override the base URL used by the client

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI_BASE_URL

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

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI_ENABLE_INTEGRATION

Whether the Vertex AI client should log requests

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI_LOG_REQUESTS

Whether the Vertex AI client should log responses

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI_LOG_RESPONSES

Timeout for requests to gemini APIs

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI_TIMEOUT

The id of the model to use.

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI_CHAT_MODEL_MODEL_ID

The temperature is used for sampling during response generation, which occurs when topP and topK are applied. Temperature controls the degree of randomness in token selection. Lower temperatures are good for prompts that require a less open-ended or creative response, while higher temperatures can lead to more diverse or creative results. A temperature of 0 means that the highest probability tokens are always selected. In this case, responses for a given prompt are mostly deterministic, but a small amount of variation is still possible.

If the model returns a response that’s too generic, too short, or the model gives a fallback response, try increasing the temperature.

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI_CHAT_MODEL_TEMPERATURE

Maximum number of tokens that can be generated in the response. A token is approximately four characters. 100 tokens correspond to roughly 60-80 words. Specify a lower value for shorter responses and a higher value for potentially longer responses.

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI_CHAT_MODEL_MAX_OUTPUT_TOKENS

Top-P changes how the model selects tokens for output. Tokens are selected from the most (see top-K) to least probable until the sum of their probabilities equals the top-P value. For example, if tokens A, B, and C have a probability of 0.3, 0.2, and 0.1 and the top-P value is 0.5, then the model will select either A or B as the next token by using temperature and excludes C as a candidate.

Specify a lower value for less random responses and a higher value for more random responses.

Range: 0.0 - 1.0

Default for gemini-2.5-flash: 0.95

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI_CHAT_MODEL_TOP_P

Top-K changes how the model selects tokens for output. A top-K of 1 means the next selected token is the most probable among all tokens in the model’s vocabulary (also called greedy decoding), while a top-K of 3 means that the next token is selected from among the three most probable tokens by using temperature.

For each token selection step, the top-K tokens with the highest probabilities are sampled. Then tokens are further filtered based on top-P with the final token selected using temperature sampling.

Specify a lower value for less random responses and a higher value for more random responses.

Range: 1-40

gemini-2.5-flash doesn’t support topK

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI_CHAT_MODEL_TOP_K

Whether chat model requests should be logged

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI_CHAT_MODEL_LOG_REQUESTS

Whether chat model responses should be logged

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI_CHAT_MODEL_LOG_RESPONSES

Global timeout for requests to gemini APIs

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI_CHAT_MODEL_TIMEOUT

Controls whether thought summaries are enabled. Thought summaries are synthesized versions of the model’s raw thoughts and offer insights into the model’s internal reasoning process.

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI_CHAT_MODEL_THINKING_INCLUDE_THOUGHTS

The thinkingBudget parameter guides the model on the number of thinking tokens to use when generating a response. A higher token count generally allows for more detailed reasoning, which can be beneficial for tackling more complex tasks. If latency is more important, use a lower budget or disable thinking by setting thinkingBudget to 0. Setting the thinkingBudget to -1 turns on dynamic thinking, meaning the model will adjust the budget based on the complexity of the request.

The thinkingBudget is only supported in Gemini 2.5 Flash, 2.5 Pro, and 2.5 Flash-Lite. Depending on the prompt, the model might overflow or underflow the token budget. See Gemini API docs for more details.

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI_CHAT_MODEL_THINKING_THINKING_BUDGET

The id of the model to use.

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI_EMBEDDING_MODEL_MODEL_ID

Reduced dimension for the output embedding

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI_EMBEDDING_MODEL_OUTPUT_DIMENSION

Optional task type for which the embeddings will be used. Can only be set for models/embedding-001 Possible values: TASK_TYPE_UNSPECIFIED, RETRIEVAL_QUERY, RETRIEVAL_DOCUMENT, SEMANTIC_SIMILARITY, CLASSIFICATION, CLUSTERING, QUESTION_ANSWERING, FACT_VERIFICATION

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI_EMBEDDING_MODEL_TASK_TYPE

Whether chat model requests should be logged

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI_EMBEDDING_MODEL_LOG_REQUESTS

Whether chat model responses should be logged

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI_EMBEDDING_MODEL_LOG_RESPONSES

Global timeout for requests to gemini APIs

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI_EMBEDDING_MODEL_TIMEOUT

The api key

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI__MODEL_NAME__API_KEY

Publisher of model

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI__MODEL_NAME__PUBLISHER

Meant to be used for testing only in order to override the base URL used by the client

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI__MODEL_NAME__BASE_URL

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

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI__MODEL_NAME__ENABLE_INTEGRATION

Whether the Vertex AI client should log requests

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI__MODEL_NAME__LOG_REQUESTS

Whether the Vertex AI client should log responses

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI__MODEL_NAME__LOG_RESPONSES

Timeout for requests to gemini APIs

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI__MODEL_NAME__TIMEOUT

The id of the model to use.

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI__MODEL_NAME__CHAT_MODEL_MODEL_ID

The temperature is used for sampling during response generation, which occurs when topP and topK are applied. Temperature controls the degree of randomness in token selection. Lower temperatures are good for prompts that require a less open-ended or creative response, while higher temperatures can lead to more diverse or creative results. A temperature of 0 means that the highest probability tokens are always selected. In this case, responses for a given prompt are mostly deterministic, but a small amount of variation is still possible.

If the model returns a response that’s too generic, too short, or the model gives a fallback response, try increasing the temperature.

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI__MODEL_NAME__CHAT_MODEL_TEMPERATURE

Maximum number of tokens that can be generated in the response. A token is approximately four characters. 100 tokens correspond to roughly 60-80 words. Specify a lower value for shorter responses and a higher value for potentially longer responses.

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI__MODEL_NAME__CHAT_MODEL_MAX_OUTPUT_TOKENS

Top-P changes how the model selects tokens for output. Tokens are selected from the most (see top-K) to least probable until the sum of their probabilities equals the top-P value. For example, if tokens A, B, and C have a probability of 0.3, 0.2, and 0.1 and the top-P value is 0.5, then the model will select either A or B as the next token by using temperature and excludes C as a candidate.

Specify a lower value for less random responses and a higher value for more random responses.

Range: 0.0 - 1.0

Default for gemini-2.5-flash: 0.95

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI__MODEL_NAME__CHAT_MODEL_TOP_P

Top-K changes how the model selects tokens for output. A top-K of 1 means the next selected token is the most probable among all tokens in the model’s vocabulary (also called greedy decoding), while a top-K of 3 means that the next token is selected from among the three most probable tokens by using temperature.

For each token selection step, the top-K tokens with the highest probabilities are sampled. Then tokens are further filtered based on top-P with the final token selected using temperature sampling.

Specify a lower value for less random responses and a higher value for more random responses.

Range: 1-40

gemini-2.5-flash doesn’t support topK

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI__MODEL_NAME__CHAT_MODEL_TOP_K

Whether chat model requests should be logged

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI__MODEL_NAME__CHAT_MODEL_LOG_REQUESTS

Whether chat model responses should be logged

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI__MODEL_NAME__CHAT_MODEL_LOG_RESPONSES

Global timeout for requests to gemini APIs

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI__MODEL_NAME__CHAT_MODEL_TIMEOUT

Controls whether thought summaries are enabled. Thought summaries are synthesized versions of the model’s raw thoughts and offer insights into the model’s internal reasoning process.

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI__MODEL_NAME__CHAT_MODEL_THINKING_INCLUDE_THOUGHTS

The thinkingBudget parameter guides the model on the number of thinking tokens to use when generating a response. A higher token count generally allows for more detailed reasoning, which can be beneficial for tackling more complex tasks. If latency is more important, use a lower budget or disable thinking by setting thinkingBudget to 0. Setting the thinkingBudget to -1 turns on dynamic thinking, meaning the model will adjust the budget based on the complexity of the request.

The thinkingBudget is only supported in Gemini 2.5 Flash, 2.5 Pro, and 2.5 Flash-Lite. Depending on the prompt, the model might overflow or underflow the token budget. See Gemini API docs for more details.

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI__MODEL_NAME__CHAT_MODEL_THINKING_THINKING_BUDGET

The id of the model to use.

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI__MODEL_NAME__EMBEDDING_MODEL_MODEL_ID

Reduced dimension for the output embedding

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI__MODEL_NAME__EMBEDDING_MODEL_OUTPUT_DIMENSION

Optional task type for which the embeddings will be used. Can only be set for models/embedding-001 Possible values: TASK_TYPE_UNSPECIFIED, RETRIEVAL_QUERY, RETRIEVAL_DOCUMENT, SEMANTIC_SIMILARITY, CLASSIFICATION, CLUSTERING, QUESTION_ANSWERING, FACT_VERIFICATION

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI__MODEL_NAME__EMBEDDING_MODEL_TASK_TYPE

Whether chat model requests should be logged

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI__MODEL_NAME__EMBEDDING_MODEL_LOG_REQUESTS

Whether chat model responses should be logged

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI__MODEL_NAME__EMBEDDING_MODEL_LOG_RESPONSES

Global timeout for requests to gemini APIs

Environment variable: QUARKUS_LANGCHAIN4J_AI_GEMINI__MODEL_NAME__EMBEDDING_MODEL_TIMEOUT

Whether the model should be enabled

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC_CHAT_MODEL_ENABLED

Base URL of the Anthropic API

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC_BASE_URL

Anthropic API key

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC_API_KEY

The Anthropic version

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC_VERSION

Timeout for Anthropic calls

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC_TIMEOUT

Whether the Anthropic client should log requests

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC_LOG_REQUESTS

Whether the Anthropic client should log responses

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC_LOG_RESPONSES

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

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC_ENABLE_INTEGRATION

Model name to use

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC_CHAT_MODEL_MODEL_NAME

What sampling temperature to use, between 0.0 and 1.0. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.

It is generally recommended to set this or the top-k property but not both.

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC_CHAT_MODEL_TEMPERATURE

The maximum number of tokens to generate in the completion.

The token count of your prompt plus max_tokens cannot exceed the model’s context length

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC_CHAT_MODEL_MAX_TOKENS

Double (0.0-1.0). 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.

It is generally recommended to set this or the temperature property but not both.

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC_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_ANTHROPIC_CHAT_MODEL_TOP_K

The maximum number of times to retry. 1 means exactly one attempt, with retrying disabled.

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC_CHAT_MODEL_MAX_RETRIES

The custom text sequences that will cause the model to stop generating

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC_CHAT_MODEL_STOP_SEQUENCES

Whether chat model requests should be logged

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC_CHAT_MODEL_LOG_REQUESTS

Whether chat model responses should be logged

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC_CHAT_MODEL_LOG_RESPONSES

Cache system messages to reduce costs for repeated prompts. Requires minimum 1024 tokens (Claude Opus/Sonnet) or 2048-4096 tokens (Haiku). Supported models: Claude Opus 4.1, Sonnet 4.5, Haiku 4.5, and later models.

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC_CHAT_MODEL_CACHE_SYSTEM_MESSAGES

Cache tool definitions to reduce costs. Requires minimum 1024 tokens (Claude Opus/Sonnet) or 2048-4096 tokens (Haiku). Supported models: Claude Opus 4.1, Sonnet 4.5, Haiku 4.5, and later models.

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC_CHAT_MODEL_CACHE_TOOLS

The thinking type to enable Claude’s reasoning process

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC_CHAT_MODEL_THINKING_TYPE

The token budget for the model’s thinking process

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC_CHAT_MODEL_THINKING_BUDGET_TOKENS

Whether thinking results should be returned in the response

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC_CHAT_MODEL_THINKING_RETURN_THINKING

Whether previously stored thinking should be sent in follow-up requests

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC_CHAT_MODEL_THINKING_SEND_THINKING

Enable interleaved thinking for Claude 4 models, allowing reasoning between tool calls. Requires Claude 4 model (e.g., claude-opus-4-20250514) and thinking.type: enabled.

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC_CHAT_MODEL_THINKING_INTERLEAVED

Base URL of the Anthropic API

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC__MODEL_NAME__BASE_URL

Anthropic API key

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC__MODEL_NAME__API_KEY

The Anthropic version

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC__MODEL_NAME__VERSION

Timeout for Anthropic calls

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC__MODEL_NAME__TIMEOUT

Whether the Anthropic client should log requests

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC__MODEL_NAME__LOG_REQUESTS

Whether the Anthropic client should log responses

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC__MODEL_NAME__LOG_RESPONSES

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

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC__MODEL_NAME__ENABLE_INTEGRATION

Model name to use

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC__MODEL_NAME__CHAT_MODEL_MODEL_NAME

What sampling temperature to use, between 0.0 and 1.0. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.

It is generally recommended to set this or the top-k property but not both.

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC__MODEL_NAME__CHAT_MODEL_TEMPERATURE

The maximum number of tokens to generate in the completion.

The token count of your prompt plus max_tokens cannot exceed the model’s context length

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC__MODEL_NAME__CHAT_MODEL_MAX_TOKENS

Double (0.0-1.0). 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.

It is generally recommended to set this or the temperature property but not both.

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC__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_ANTHROPIC__MODEL_NAME__CHAT_MODEL_TOP_K

The maximum number of times to retry. 1 means exactly one attempt, with retrying disabled.

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC__MODEL_NAME__CHAT_MODEL_MAX_RETRIES

The custom text sequences that will cause the model to stop generating

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC__MODEL_NAME__CHAT_MODEL_STOP_SEQUENCES

Whether chat model requests should be logged

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC__MODEL_NAME__CHAT_MODEL_LOG_REQUESTS

Whether chat model responses should be logged

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC__MODEL_NAME__CHAT_MODEL_LOG_RESPONSES

Cache system messages to reduce costs for repeated prompts. Requires minimum 1024 tokens (Claude Opus/Sonnet) or 2048-4096 tokens (Haiku). Supported models: Claude Opus 4.1, Sonnet 4.5, Haiku 4.5, and later models.

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC__MODEL_NAME__CHAT_MODEL_CACHE_SYSTEM_MESSAGES

Cache tool definitions to reduce costs. Requires minimum 1024 tokens (Claude Opus/Sonnet) or 2048-4096 tokens (Haiku). Supported models: Claude Opus 4.1, Sonnet 4.5, Haiku 4.5, and later models.

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC__MODEL_NAME__CHAT_MODEL_CACHE_TOOLS

The thinking type to enable Claude’s reasoning process

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC__MODEL_NAME__CHAT_MODEL_THINKING_TYPE

The token budget for the model’s thinking process

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC__MODEL_NAME__CHAT_MODEL_THINKING_BUDGET_TOKENS

Whether thinking results should be returned in the response

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC__MODEL_NAME__CHAT_MODEL_THINKING_RETURN_THINKING

Whether previously stored thinking should be sent in follow-up requests

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC__MODEL_NAME__CHAT_MODEL_THINKING_SEND_THINKING

Enable interleaved thinking for Claude 4 models, allowing reasoning between tool calls. Requires Claude 4 model (e.g., claude-opus-4-20250514) and thinking.type: enabled.

Environment variable: QUARKUS_LANGCHAIN4J_ANTHROPIC__MODEL_NAME__CHAT_MODEL_THINKING_INTERLEAVED

Whether the model should be enabled

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_CHAT_MODEL_ENABLED

Whether the model should be enabled

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_EMBEDDING_MODEL_ENABLED

Whether the model should be enabled

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_MODERATION_MODEL_ENABLED

Whether the model should be enabled

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_IMAGE_MODEL_ENABLED

The name of your Azure OpenAI Resource. You’re required to first deploy a model before you can make calls.

This and quarkus.langchain4j.azure-openai.deployment-name are required if quarkus.langchain4j.azure-openai.endpoint is not set. If quarkus.langchain4j.azure-openai.endpoint is set then this is never read.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_RESOURCE_NAME

The domain name of your Azure OpenAI Resource. You’re required to first deploy a model before you can make calls.

This and quarkus.langchain4j.azure-openai.domain-name are required if quarkus.langchain4j.azure-openai.endpoint is not set. If quarkus.langchain4j.azure-openai.endpoint is set then this is never read.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_DOMAIN_NAME

The name of your model deployment. You’re required to first deploy a model before you can make calls.

This and quarkus.langchain4j.azure-openai.resource-name are required if quarkus.langchain4j.azure-openai.endpoint is not set. If quarkus.langchain4j.azure-openai.endpoint is set then this is never read.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_DEPLOYMENT_NAME

The endpoint for the Azure OpenAI resource.

If not specified, then quarkus.langchain4j.azure-openai.resource-name, quarkus.langchain4j.azure-openai.domain-name (defaults to "openai.azure.com") and quarkus.langchain4j.azure-openai.deployment-name are required. In this case the endpoint will be set to https://${quarkus.langchain4j.azure-openai.resource-name.${quarkus.langchain4j.azure-openai.domain-name}/openai/deployments/${quarkus.langchain4j.azure-openai.deployment-name}}

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_ENDPOINT

The Azure AD token to use for this operation. If present, then the requests towards OpenAI will include this in the Authorization header. Note that this property overrides the functionality of quarkus.langchain4j.azure-openai.api-key.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_AD_TOKEN

The API version to use for this operation. This follows the YYYY-MM-DD format

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_API_VERSION

Azure OpenAI API key

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_API_KEY

Timeout for OpenAI calls

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_TIMEOUT

The maximum number of times to retry. 1 means exactly one attempt, with retrying disabled.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_MAX_RETRIES

Whether the OpenAI client should log requests

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_LOG_REQUESTS

Whether the OpenAI client should log responses

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_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_AZURE_OPENAI_ENABLE_INTEGRATION

The Proxy type

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_PROXY_TYPE

The Proxy host

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_PROXY_HOST

The Proxy port

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_PROXY_PORT

This property will override the quarkus.langchain4j.azure-openai.resource-name specifically for chat models if it is set.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_CHAT_MODEL_RESOURCE_NAME

This property will override the quarkus.langchain4j.azure-openai.domain-name specifically for chat models if it is set.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_CHAT_MODEL_DOMAIN_NAME

This property will override the quarkus.langchain4j.azure-openai.deployment-name specifically for chat models if it is set.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_CHAT_MODEL_DEPLOYMENT_NAME

This property will override the quarkus.langchain4j.azure-openai.endpoint specifically for chat models if it is set.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_CHAT_MODEL_ENDPOINT

The Azure AD token to use for this operation. If present, then the requests towards OpenAI will include this in the Authorization header. Note that this property overrides the functionality of quarkus.langchain4j.azure-openai.embedding-model.api-key.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_CHAT_MODEL_AD_TOKEN

The API version to use for this operation. This follows the YYYY-MM-DD format

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_CHAT_MODEL_API_VERSION

Azure OpenAI API key

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_CHAT_MODEL_API_KEY

What sampling temperature to use, with values between 0 and 2. Higher values means the model will take more risks. A value of 0.9 is good for more creative applications, while 0 (argmax sampling) is good for ones with a well-defined answer. It is recommended to alter this or topP, but not both.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_CHAT_MODEL_TEMPERATURE

An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with topP probability mass. 0.1 means only the tokens comprising the top 10% probability mass are considered. It is recommended to alter this or temperature, but not both.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_CHAT_MODEL_TOP_P

If specified, our system will make the best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result. Determinism isn’t guaranteed. Support for reproducible output was first added in API version 2023-12-01-preview

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_CHAT_MODEL_SEED

The maximum number of tokens to generate in the completion. The token count of your prompt plus max_tokens can’t exceed the model’s context length. Most models have a context length of 2048 tokens (except for the newest models, which support 4096).

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_CHAT_MODEL_MAX_TOKENS

Number between -2.0 and 2.0. 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.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_CHAT_MODEL_PRESENCE_PENALTY

Number between -2.0 and 2.0. 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.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_CHAT_MODEL_FREQUENCY_PENALTY

Whether chat model requests should be logged

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_CHAT_MODEL_LOG_REQUESTS

Whether chat model responses should be logged

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_CHAT_MODEL_LOG_RESPONSES

The response format the model should use. Some models are not compatible with some response formats, make sure to review OpenAI documentation.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_CHAT_MODEL_RESPONSE_FORMAT

This property will override the quarkus.langchain4j.azure-openai.resource-name specifically for embedding models if it is set.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_EMBEDDING_MODEL_RESOURCE_NAME

This property will override the quarkus.langchain4j.azure-openai.domain-name specifically for embedding models if it is set.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_EMBEDDING_MODEL_DOMAIN_NAME

This property will override the quarkus.langchain4j.azure-openai.deployment-name specifically for embedding models if it is set.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_EMBEDDING_MODEL_DEPLOYMENT_NAME

This property will override the quarkus.langchain4j.azure-openai.endpoint specifically for embedding models if it is set.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_EMBEDDING_MODEL_ENDPOINT

The Azure AD token to use for this operation. If present, then the requests towards OpenAI will include this in the Authorization header. Note that this property overrides the functionality of quarkus.langchain4j.azure-openai.embedding-model.api-key.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_EMBEDDING_MODEL_AD_TOKEN

The API version to use for this operation. This follows the YYYY-MM-DD format

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_EMBEDDING_MODEL_API_VERSION

Azure OpenAI API key

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_EMBEDDING_MODEL_API_KEY

Whether embedding model requests should be logged

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_EMBEDDING_MODEL_LOG_REQUESTS

Whether embedding model responses should be logged

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_EMBEDDING_MODEL_LOG_RESPONSES

This property will override the quarkus.langchain4j.azure-openai.resource-name specifically for image models if it is set.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_IMAGE_MODEL_RESOURCE_NAME

This property will override the quarkus.langchain4j.azure-openai.domain-name specifically for image models if it is set.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_IMAGE_MODEL_DOMAIN_NAME

This property will override the quarkus.langchain4j.azure-openai.deployment-name specifically for image models if it is set.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_IMAGE_MODEL_DEPLOYMENT_NAME

This property will override the quarkus.langchain4j.azure-openai.endpoint specifically for image models if it is set.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_IMAGE_MODEL_ENDPOINT

The Azure AD token to use for this operation. If present, then the requests towards OpenAI will include this in the Authorization header. Note that this property overrides the functionality of quarkus.langchain4j.azure-openai.embedding-model.api-key.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_IMAGE_MODEL_AD_TOKEN

The API version to use for this operation. This follows the YYYY-MM-DD format

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_IMAGE_MODEL_API_VERSION

Azure OpenAI API key

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_IMAGE_MODEL_API_KEY

Model name to use

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_IMAGE_MODEL_MODEL_NAME

Configure whether the generated images will be saved to disk. By default, persisting is disabled, but it is implicitly enabled when quarkus.langchain4j.openai.image-mode.directory is set and this property is not to false

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_IMAGE_MODEL_PERSIST

The path where the generated images will be persisted to disk. This only applies of quarkus.langchain4j.openai.image-mode.persist is not set to false.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_IMAGE_MODEL_PERSIST_DIRECTORY

The format in which the generated images are returned.

Must be one of url or b64_json

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_IMAGE_MODEL_RESPONSE_FORMAT

The size of the generated images.

Must be one of 1024x1024, 1792x1024, or 1024x1792 when the model is dall-e-3.

Must be one of 256x256, 512x512, or 1024x1024 when the model is dall-e-2.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_IMAGE_MODEL_SIZE

The quality of the image that will be generated.

hd creates images with finer details and greater consistency across the image.

This param is only supported for when the model is dall-e-3.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_IMAGE_MODEL_QUALITY

The number of images to generate.

Must be between 1 and 10.

When the model is dall-e-3, only n=1 is supported.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_IMAGE_MODEL_NUMBER

The style of the generated images.

Must be one of vivid or natural. Vivid causes the model to lean towards generating hyper-real and dramatic images. Natural causes the model to produce more natural, less hyper-real looking images.

This param is only supported for when the model is dall-e-3.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_IMAGE_MODEL_STYLE

A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_IMAGE_MODEL_USER

Whether image model requests should be logged

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_IMAGE_MODEL_LOG_REQUESTS

Whether image model responses should be logged

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI_IMAGE_MODEL_LOG_RESPONSES

The name of your Azure OpenAI Resource. You’re required to first deploy a model before you can make calls.

This and quarkus.langchain4j.azure-openai.deployment-name are required if quarkus.langchain4j.azure-openai.endpoint is not set. If quarkus.langchain4j.azure-openai.endpoint is set then this is never read.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__RESOURCE_NAME

The domain name of your Azure OpenAI Resource. You’re required to first deploy a model before you can make calls.

This and quarkus.langchain4j.azure-openai.domain-name are required if quarkus.langchain4j.azure-openai.endpoint is not set. If quarkus.langchain4j.azure-openai.endpoint is set then this is never read.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__DOMAIN_NAME

The name of your model deployment. You’re required to first deploy a model before you can make calls.

This and quarkus.langchain4j.azure-openai.resource-name are required if quarkus.langchain4j.azure-openai.endpoint is not set. If quarkus.langchain4j.azure-openai.endpoint is set then this is never read.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__DEPLOYMENT_NAME

The endpoint for the Azure OpenAI resource.

If not specified, then quarkus.langchain4j.azure-openai.resource-name, quarkus.langchain4j.azure-openai.domain-name (defaults to "openai.azure.com") and quarkus.langchain4j.azure-openai.deployment-name are required. In this case the endpoint will be set to https://${quarkus.langchain4j.azure-openai.resource-name.${quarkus.langchain4j.azure-openai.domain-name}/openai/deployments/${quarkus.langchain4j.azure-openai.deployment-name}}

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__ENDPOINT

The Azure AD token to use for this operation. If present, then the requests towards OpenAI will include this in the Authorization header. Note that this property overrides the functionality of quarkus.langchain4j.azure-openai.api-key.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__AD_TOKEN

The API version to use for this operation. This follows the YYYY-MM-DD format

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__API_VERSION

Azure OpenAI API key

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__API_KEY

Timeout for OpenAI calls

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__TIMEOUT

The maximum number of times to retry. 1 means exactly one attempt, with retrying disabled.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__MAX_RETRIES

Whether the OpenAI client should log requests

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__LOG_REQUESTS

Whether the OpenAI client should log responses

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__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_AZURE_OPENAI__MODEL_NAME__ENABLE_INTEGRATION

The Proxy type

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__PROXY_TYPE

The Proxy host

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__PROXY_HOST

The Proxy port

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__PROXY_PORT

This property will override the quarkus.langchain4j.azure-openai.resource-name specifically for chat models if it is set.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__CHAT_MODEL_RESOURCE_NAME

This property will override the quarkus.langchain4j.azure-openai.domain-name specifically for chat models if it is set.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__CHAT_MODEL_DOMAIN_NAME

This property will override the quarkus.langchain4j.azure-openai.deployment-name specifically for chat models if it is set.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__CHAT_MODEL_DEPLOYMENT_NAME

This property will override the quarkus.langchain4j.azure-openai.endpoint specifically for chat models if it is set.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__CHAT_MODEL_ENDPOINT

The Azure AD token to use for this operation. If present, then the requests towards OpenAI will include this in the Authorization header. Note that this property overrides the functionality of quarkus.langchain4j.azure-openai.embedding-model.api-key.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__CHAT_MODEL_AD_TOKEN

The API version to use for this operation. This follows the YYYY-MM-DD format

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__CHAT_MODEL_API_VERSION

Azure OpenAI API key

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__CHAT_MODEL_API_KEY

What sampling temperature to use, with values between 0 and 2. Higher values means the model will take more risks. A value of 0.9 is good for more creative applications, while 0 (argmax sampling) is good for ones with a well-defined answer. It is recommended to alter this or topP, but not both.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__CHAT_MODEL_TEMPERATURE

An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with topP probability mass. 0.1 means only the tokens comprising the top 10% probability mass are considered. It is recommended to alter this or temperature, but not both.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__CHAT_MODEL_TOP_P

If specified, our system will make the best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result. Determinism isn’t guaranteed. Support for reproducible output was first added in API version 2023-12-01-preview

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__CHAT_MODEL_SEED

The maximum number of tokens to generate in the completion. The token count of your prompt plus max_tokens can’t exceed the model’s context length. Most models have a context length of 2048 tokens (except for the newest models, which support 4096).

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__CHAT_MODEL_MAX_TOKENS

Number between -2.0 and 2.0. 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.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__CHAT_MODEL_PRESENCE_PENALTY

Number between -2.0 and 2.0. 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.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__CHAT_MODEL_FREQUENCY_PENALTY

Whether chat model requests should be logged

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__CHAT_MODEL_LOG_REQUESTS

Whether chat model responses should be logged

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__CHAT_MODEL_LOG_RESPONSES

The response format the model should use. Some models are not compatible with some response formats, make sure to review OpenAI documentation.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__CHAT_MODEL_RESPONSE_FORMAT

This property will override the quarkus.langchain4j.azure-openai.resource-name specifically for embedding models if it is set.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__EMBEDDING_MODEL_RESOURCE_NAME

This property will override the quarkus.langchain4j.azure-openai.domain-name specifically for embedding models if it is set.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__EMBEDDING_MODEL_DOMAIN_NAME

This property will override the quarkus.langchain4j.azure-openai.deployment-name specifically for embedding models if it is set.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__EMBEDDING_MODEL_DEPLOYMENT_NAME

This property will override the quarkus.langchain4j.azure-openai.endpoint specifically for embedding models if it is set.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__EMBEDDING_MODEL_ENDPOINT

The Azure AD token to use for this operation. If present, then the requests towards OpenAI will include this in the Authorization header. Note that this property overrides the functionality of quarkus.langchain4j.azure-openai.embedding-model.api-key.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__EMBEDDING_MODEL_AD_TOKEN

The API version to use for this operation. This follows the YYYY-MM-DD format

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__EMBEDDING_MODEL_API_VERSION

Azure OpenAI API key

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__EMBEDDING_MODEL_API_KEY

Whether embedding model requests should be logged

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__EMBEDDING_MODEL_LOG_REQUESTS

Whether embedding model responses should be logged

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__EMBEDDING_MODEL_LOG_RESPONSES

This property will override the quarkus.langchain4j.azure-openai.resource-name specifically for image models if it is set.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__IMAGE_MODEL_RESOURCE_NAME

This property will override the quarkus.langchain4j.azure-openai.domain-name specifically for image models if it is set.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__IMAGE_MODEL_DOMAIN_NAME

This property will override the quarkus.langchain4j.azure-openai.deployment-name specifically for image models if it is set.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__IMAGE_MODEL_DEPLOYMENT_NAME

This property will override the quarkus.langchain4j.azure-openai.endpoint specifically for image models if it is set.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__IMAGE_MODEL_ENDPOINT

The Azure AD token to use for this operation. If present, then the requests towards OpenAI will include this in the Authorization header. Note that this property overrides the functionality of quarkus.langchain4j.azure-openai.embedding-model.api-key.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__IMAGE_MODEL_AD_TOKEN

The API version to use for this operation. This follows the YYYY-MM-DD format

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__IMAGE_MODEL_API_VERSION

Azure OpenAI API key

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__IMAGE_MODEL_API_KEY

Model name to use

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__IMAGE_MODEL_MODEL_NAME

Configure whether the generated images will be saved to disk. By default, persisting is disabled, but it is implicitly enabled when quarkus.langchain4j.openai.image-mode.directory is set and this property is not to false

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__IMAGE_MODEL_PERSIST

The path where the generated images will be persisted to disk. This only applies of quarkus.langchain4j.openai.image-mode.persist is not set to false.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__IMAGE_MODEL_PERSIST_DIRECTORY

The format in which the generated images are returned.

Must be one of url or b64_json

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__IMAGE_MODEL_RESPONSE_FORMAT

The size of the generated images.

Must be one of 1024x1024, 1792x1024, or 1024x1792 when the model is dall-e-3.

Must be one of 256x256, 512x512, or 1024x1024 when the model is dall-e-2.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__IMAGE_MODEL_SIZE

The quality of the image that will be generated.

hd creates images with finer details and greater consistency across the image.

This param is only supported for when the model is dall-e-3.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__IMAGE_MODEL_QUALITY

The number of images to generate.

Must be between 1 and 10.

When the model is dall-e-3, only n=1 is supported.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__IMAGE_MODEL_NUMBER

The style of the generated images.

Must be one of vivid or natural. Vivid causes the model to lean towards generating hyper-real and dramatic images. Natural causes the model to produce more natural, less hyper-real looking images.

This param is only supported for when the model is dall-e-3.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__IMAGE_MODEL_STYLE

A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse.

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__IMAGE_MODEL_USER

Whether image model requests should be logged

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__IMAGE_MODEL_LOG_REQUESTS

Whether image model responses should be logged

Environment variable: QUARKUS_LANGCHAIN4J_AZURE_OPENAI__MODEL_NAME__IMAGE_MODEL_LOG_RESPONSES

Whether the model should be enabled

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_ENABLED

Whether the model should be enabled

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_EMBEDDING_MODEL_ENABLED

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

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_ENABLE_INTEGRATION

Whether the Bedrock client should log requests

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_LOG_REQUESTS

Whether the Bedrock client should log responses

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_LOG_RESPONSES

Whether chat model body in request and response should be logged

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_LOG_BODY

Region used by the bedrock runtime api. See Regions Supported.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_AWS_REGION

Override the endpoint used by the bedrock client

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_AWS_ENDPOINT_OVERRIDE

Specify a custom credentials provider to use for the bedrock client. Identified by bean name.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_AWS_CREDENTIALS_PROVIDER

The maximum number retries the aws sdk client will attempt.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_AWS_MAX_RETRIES

Configure the amount of time to allow the client to complete the execution of an API call. This timeout covers the entire client execution except for marshalling. This includes request handler execution, all HTTP requests including retries, unmarshalling, etc. This value should always be positive, if present.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_AWS_API_CALL_TIMEOUT

Connect Timeout for Bedrock calls

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CLIENT_CONNECT_TIMEOUT

Read Timeout for Bedrock calls

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CLIENT_TIMEOUT

A string value in the form of : that specifies the HTTP proxy server hostname (or IP address) and port for requests of clients to use.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CLIENT_PROXY_ADDRESS

Proxy username, equivalent to the http.proxy or https.proxy JVM settings.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CLIENT_PROXY_USER

Proxy password, equivalent to the http.proxyPassword or https.proxyPassword JVM settings.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CLIENT_PROXY_PASSWORD

Hosts to access without proxy, similar to the http.nonProxyHosts or https.nonProxyHosts JVM settings. Please note that unlike the JVM settings, this property is empty by default.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CLIENT_NON_PROXY_HOSTS

If true, the REST clients will not provide additional contextual information (like REST client class and method names) when exception occurs during a client invocation.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CLIENT_DISABLE_CONTEXTUAL_ERROR_MESSAGES

The time in ms for which a connection remains unused in the connection pool before being evicted and closed. A timeout of 0 means there is no timeout.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CLIENT_CONNECTION_TTL

The size of the connection pool for this client.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CLIENT_CONNECTION_POOL_SIZE

If set to false disables the keep alive completely.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CLIENT_KEEP_ALIVE_ENABLED

The class name of the host name verifier. The class must have a public no-argument constructor.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CLIENT_HOSTNAME_VERIFIER

Set whether hostname verification is enabled. Default is enabled. This setting should not be disabled in production as it makes the client vulnerable to MITM attacks.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CLIENT_VERIFY_HOST

The trust store location. Can point to either a classpath resource or a file.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CLIENT_TRUST_STORE

The trust store password.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CLIENT_TRUST_STORE_PASSWORD

The type of the trust store. Defaults to "JKS".

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CLIENT_TRUST_STORE_TYPE

The key store location. Can point to either a classpath resource or a file.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CLIENT_KEY_STORE

The key store password.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CLIENT_KEY_STORE_PASSWORD

The type of the key store. Defaults to "JKS".

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CLIENT_KEY_STORE_TYPE

The name of the TLS configuration to use.

If not set and the default TLS configuration is configured (quarkus.tls.*) then that will be used. If a name is configured, it uses the configuration from quarkus.tls.<name>.* If a name is configured, but no TLS configuration is found with that name then an error will be thrown.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CLIENT_TLS_CONFIGURATION_NAME

Whether chat model requests should be logged

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_LOG_REQUESTS

Whether chat model responses should be logged

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_LOG_RESPONSES

Whether chat model body in request and response should be logged

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_LOG_BODY

Region used by the bedrock runtime api. See Regions Supported.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_AWS_REGION

Override the endpoint used by the bedrock client

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_AWS_ENDPOINT_OVERRIDE

Specify a custom credentials provider to use for the bedrock client. Identified by bean name.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_AWS_CREDENTIALS_PROVIDER

The maximum number retries the aws sdk client will attempt.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_AWS_MAX_RETRIES

Configure the amount of time to allow the client to complete the execution of an API call. This timeout covers the entire client execution except for marshalling. This includes request handler execution, all HTTP requests including retries, unmarshalling, etc. This value should always be positive, if present.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_AWS_API_CALL_TIMEOUT

Model id to use. See Models Supported

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_MODEL_ID

What sampling temperature to use, between 0.0 and 1.0. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.

It is generally recommended to set this or the top-k property but not both.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_TEMPERATURE

The maximum number of tokens to generate in the completion.

The token count of your prompt plus max_tokens cannot exceed the model’s context length

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_MAX_TOKENS

Double (0.0-1.0). 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.

It is generally recommended to set this or the temperature property but not both.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_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_BEDROCK_CHAT_MODEL_TOP_K

The custom text sequences that will cause the model to stop generating

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_STOP_SEQUENCES

Connect Timeout for Bedrock calls

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_CLIENT_CONNECT_TIMEOUT

Read Timeout for Bedrock calls

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_CLIENT_TIMEOUT

A string value in the form of : that specifies the HTTP proxy server hostname (or IP address) and port for requests of clients to use.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_CLIENT_PROXY_ADDRESS

Proxy username, equivalent to the http.proxy or https.proxy JVM settings.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_CLIENT_PROXY_USER

Proxy password, equivalent to the http.proxyPassword or https.proxyPassword JVM settings.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_CLIENT_PROXY_PASSWORD

Hosts to access without proxy, similar to the http.nonProxyHosts or https.nonProxyHosts JVM settings. Please note that unlike the JVM settings, this property is empty by default.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_CLIENT_NON_PROXY_HOSTS

If true, the REST clients will not provide additional contextual information (like REST client class and method names) when exception occurs during a client invocation.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_CLIENT_DISABLE_CONTEXTUAL_ERROR_MESSAGES

The time in ms for which a connection remains unused in the connection pool before being evicted and closed. A timeout of 0 means there is no timeout.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_CLIENT_CONNECTION_TTL

The size of the connection pool for this client.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_CLIENT_CONNECTION_POOL_SIZE

If set to false disables the keep alive completely.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_CLIENT_KEEP_ALIVE_ENABLED

The class name of the host name verifier. The class must have a public no-argument constructor.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_CLIENT_HOSTNAME_VERIFIER

Set whether hostname verification is enabled. Default is enabled. This setting should not be disabled in production as it makes the client vulnerable to MITM attacks.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_CLIENT_VERIFY_HOST

The trust store location. Can point to either a classpath resource or a file.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_CLIENT_TRUST_STORE

The trust store password.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_CLIENT_TRUST_STORE_PASSWORD

The type of the trust store. Defaults to "JKS".

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_CLIENT_TRUST_STORE_TYPE

The key store location. Can point to either a classpath resource or a file.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_CLIENT_KEY_STORE

The key store password.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_CLIENT_KEY_STORE_PASSWORD

The type of the key store. Defaults to "JKS".

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_CLIENT_KEY_STORE_TYPE

The name of the TLS configuration to use.

If not set and the default TLS configuration is configured (quarkus.tls.*) then that will be used. If a name is configured, it uses the configuration from quarkus.tls.<name>.* If a name is configured, but no TLS configuration is found with that name then an error will be thrown.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_CHAT_MODEL_CLIENT_TLS_CONFIGURATION_NAME

Whether embedding model requests should be logged

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_EMBEDDING_MODEL_LOG_REQUESTS

Whether embedding model responses should be logged

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_EMBEDDING_MODEL_LOG_RESPONSES

Whether embedding model body in request and response should be logged

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_EMBEDDING_MODEL_LOG_BODY

Region used by the bedrock runtime api. See Regions Supported.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_EMBEDDING_MODEL_AWS_REGION

Override the endpoint used by the bedrock client

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_EMBEDDING_MODEL_AWS_ENDPOINT_OVERRIDE

Specify a custom credentials provider to use for the bedrock client. Identified by bean name.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_EMBEDDING_MODEL_AWS_CREDENTIALS_PROVIDER

The maximum number retries the aws sdk client will attempt.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_EMBEDDING_MODEL_AWS_MAX_RETRIES

Configure the amount of time to allow the client to complete the execution of an API call. This timeout covers the entire client execution except for marshalling. This includes request handler execution, all HTTP requests including retries, unmarshalling, etc. This value should always be positive, if present.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_EMBEDDING_MODEL_AWS_API_CALL_TIMEOUT

Model name to use

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_EMBEDDING_MODEL_MODEL_ID

The number of dimensions the output embedding should have

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_EMBEDDING_MODEL_TITAN_DIMENSIONS

Flag indicating whether to normalize the output embedding

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_EMBEDDING_MODEL_TITAN_NORMALIZE

Prepends special tokens to differentiate each type from one another. You should not mix different types together, except when mixing types for search and retrieval. In this case, embed your corpus with the search_document type and embedded queries with type search_query type.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_EMBEDDING_MODEL_COHERE_INPUT_TYPE

Specifies how the API handles inputs longer than the maximum token length

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_EMBEDDING_MODEL_COHERE_TRUNCATE

Connect Timeout for Bedrock calls

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_EMBEDDING_MODEL_CLIENT_CONNECT_TIMEOUT

Read Timeout for Bedrock calls

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_EMBEDDING_MODEL_CLIENT_TIMEOUT

A string value in the form of : that specifies the HTTP proxy server hostname (or IP address) and port for requests of clients to use.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_EMBEDDING_MODEL_CLIENT_PROXY_ADDRESS

Proxy username, equivalent to the http.proxy or https.proxy JVM settings.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_EMBEDDING_MODEL_CLIENT_PROXY_USER

Proxy password, equivalent to the http.proxyPassword or https.proxyPassword JVM settings.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_EMBEDDING_MODEL_CLIENT_PROXY_PASSWORD

Hosts to access without proxy, similar to the http.nonProxyHosts or https.nonProxyHosts JVM settings. Please note that unlike the JVM settings, this property is empty by default.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_EMBEDDING_MODEL_CLIENT_NON_PROXY_HOSTS

If true, the REST clients will not provide additional contextual information (like REST client class and method names) when exception occurs during a client invocation.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_EMBEDDING_MODEL_CLIENT_DISABLE_CONTEXTUAL_ERROR_MESSAGES

The time in ms for which a connection remains unused in the connection pool before being evicted and closed. A timeout of 0 means there is no timeout.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_EMBEDDING_MODEL_CLIENT_CONNECTION_TTL

The size of the connection pool for this client.

Environment variable: QUARKUS_LANGCHAIN4J_BEDROCK_EMBEDDING_MODEL_CLIENT_CONNECTION_POOL_SIZE