Cohere client, over Cohere's OpenAI-compatibility API (https://api.cohere.ai/compatibility/v1/chat/completions).
An OpenAICompatibleClient with CohereDialect, so it has everything the shared client has: completion, streaming (including streamed tool calls and usage), tool calling, structured output and one exchange recorded per call. Until #1132 it was a separate client for the native v2 /v2/chat API that sent text only and whose streamComplete returned a Left (#925). The Compatibility API supports chat, streaming, tools and response_format, so everything that client did carries over, and the rest comes with the shared client rather than a second SSE parser for Cohere's native event format.
Requests go to <baseUrl>/chat/completions, where baseUrl is mapped through org.llm4s.llmconnect.config.CohereConfig.compatibilityBaseUrl, so a config naming the native root still works.
Value parameters
- config
-
Cohere configuration: API key, model, base URL and context settings.
- exchangeLogging
-
where raw request/response exchanges are recorded, if anywhere.
- metrics
-
receives per-call latency and token-usage events.
Attributes
- Companion
- object
- Graph
-
- Supertypes
-
class OpenAICompatibleClienttrait BaseLifecycleLLMClienttrait MetricsRecordingtrait LLMClienttrait AutoCloseableclass Objecttrait Matchableclass AnyShow all
Members list
Value members
Inherited methods
Releases resources and closes connections to the LLM provider.
Releases resources and closes connections to the LLM provider.
Call when the client is no longer needed. After calling close(), the client should not be used. Default implementation is a no-op; override if managing resources like connections or thread pools.
Attributes
- Definition Classes
- Inherited from:
- BaseLifecycleLLMClient
Executes a blocking completion request and returns the full response.
Executes a blocking completion request and returns the full response.
Sends the conversation to the LLM and waits for the complete response. Use when you need the entire response at once or when streaming is not required.
Value parameters
- conversation
-
conversation history including system, user, assistant, and tool messages
- options
-
configuration including temperature, max tokens, tools, etc. (default: CompletionOptions())
Attributes
- Returns
-
Right(Completion) with the model's response, or Left(LLMError) on failure
- Definition Classes
- Inherited from:
- OpenAICompatibleClient
Sends the conversation and parses the response into a typed value using the provided schema.
Sends the conversation and parses the response into a typed value using the provided schema.
Sets ResponseFormat.JsonSchema on the options. OpenAI, Azure OpenAI and Gemini enforce the schema at generation time, as does Ollama 0.5 or later through its format field. Requesty and the OpenAI-compatible providers (including Cohere) send it as response_format, but whether it is enforced is up to the server - for Requesty, a router, the backend model it routes to: one that ignores the field returns unconstrained text. Anthropic falls back to a best-effort system-prompt instruction, which is not schema-enforced. Clients that do not read responseFormat (watsonx, Bedrock) send no schema at all. Because models may wrap JSON in markdown code fences or surround it with prose, the response is normalised (fence stripped, first balanced {...} or [...] extracted) before being deserialised with uPickle into the expected type A.
The reply is '''not''' validated against the schema: it is only deserialised. A constraint the reader does not check - an enum, a numeric or string bound, additionalProperties = false (extra keys are ignored) - can be violated by a reply that still returns Right(A). Check such constraints on the result yourself.
The schema is derived with strict = true, which lists '''every''' property as required, including a property declared optional with required = false. Only responseFormat is overridden: every other option you pass is forwarded unchanged to complete, where the provider client may adjust or drop options the model does not support, as for any other complete call. name and strict on the format are left at their defaults ("response" and true); call complete with your own ResponseFormat.JsonSchema to set them.
Type parameters
- A
-
target type; must have a corresponding
upickle.default.Reader[A]
Value parameters
- conversation
-
conversation history
- options
-
additional completion options (default: CompletionOptions())
- reader
-
implicit uPickle reader for deserialising the JSON into
A - schema
-
JSON-Schema description of the expected response object
Attributes
- Returns
-
Right(A) on success. Left(ValidationError) with field
structured_outputwhen the reply is not JSON, is JSONnull, or cannot be deserialised asA; any other Left is the provider call's own error, returned unchanged - Inherited from:
- LLMClient
Validates that the client is open, executes the operation, and records standard completion metrics (latency, token usage, estimated cost).
Validates that the client is open, executes the operation, and records standard completion metrics (latency, token usage, estimated cost).
Use this in complete and streamComplete implementations to avoid repeating the lifecycle-check + metrics-wrapping boilerplate.
An interrupted call - one that throws InterruptedException, or fails while the thread is interrupted - is returned as Left(CancelledError) with the interrupt flag kept, whatever the provider SDK did with it. A call made with the flag already set returns Left(CancelledError) at once, without running operation: an SDK that ignores the flag would otherwise send the (billed) request anyway.
Value parameters
- operation
-
The provider-specific completion logic to execute. Called only when the client is open and the thread is not interrupted.
Attributes
- Returns
-
The completion result with metrics recorded as a side-effect.
- Inherited from:
- BaseLifecycleLLMClient
Calculates available token budget for prompts after accounting for completion reserve and headroom.
Calculates available token budget for prompts after accounting for completion reserve and headroom.
Formula: (contextWindow - reserveCompletion) * (1 - headroom)
Headroom provides a safety margin for tokenization variations and message formatting overhead.
Value parameters
- headroom
-
safety margin as percentage of prompt budget (default: HeadroomPercent.Standard ~10%)
Attributes
- Returns
-
maximum tokens available for prompt content
- Inherited from:
- LLMClient
Returns the maximum context window size supported by this model in tokens.
Returns the maximum context window size supported by this model in tokens.
The context window is the total tokens (prompt + completion) the model can process in a single request, including all conversation messages and the generated response.
Attributes
- Returns
-
total context window size in tokens (e.g., 4096, 8192, 128000)
- Definition Classes
- Inherited from:
- OpenAICompatibleClient
Returns the number of tokens reserved for the model's completion response.
Returns the number of tokens reserved for the model's completion response.
This value is subtracted from the context window when calculating available tokens for prompts. Corresponds to the max_tokens or completion token limit configured for the model.
Attributes
- Returns
-
number of tokens reserved for completion
- Definition Classes
- Inherited from:
- OpenAICompatibleClient
Executes a streaming completion request, invoking a callback for each chunk as it arrives.
Executes a streaming completion request, invoking a callback for each chunk as it arrives.
Streams the response incrementally, calling onChunk for each token/chunk received. Enables real-time display of responses. Returns the final accumulated completion on success.
Value parameters
- conversation
-
conversation history including system, user, assistant, and tool messages
- onChunk
-
callback invoked for each chunk; called synchronously, avoid blocking operations
- options
-
configuration including temperature, max tokens, tools, etc. (default: CompletionOptions())
Attributes
- Returns
-
Right(Completion) with the complete accumulated response, or Left(LLMError) on failure
- Definition Classes
- Inherited from:
- OpenAICompatibleClient
Validates client configuration and connectivity to the LLM provider.
Validates client configuration and connectivity to the LLM provider.
May perform checks such as verifying API credentials, testing connectivity, and validating configuration. Default implementation returns success; override for provider-specific validation.
Attributes
- Returns
-
Right(()) if validation succeeds, Left(LLMError) with details on failure
- Inherited from:
- LLMClient
Attributes
- Inherited from:
- BaseLifecycleLLMClient
Executes operation and records metrics for the call.
Executes operation and records metrics for the call.
Latency and outcome (success or classified error) are recorded for every call regardless of result. Token counts and cost are recorded only on success — a Left result emits an org.llm4s.metrics.Outcome.Error event whose kind is derived from the org.llm4s.error.LLMError subtype via ErrorKind.fromLLMError.
Value parameters
- extractCost
-
Extracts the pre-computed cost (USD) from a successful result; return
Noneto skip cost recording. - extractUsage
-
Extracts prompt/completion token counts from a successful result; return
Noneto skip token recording. - model
-
Model identifier forwarded to the collector.
- operation
-
The LLM call to time and observe.
- provider
-
Provider label forwarded to the collector (e.g.
"openai").
Attributes
- Returns
-
The result of
operation, unchanged. - Inherited from:
- MetricsRecording
Givens
Inherited givens
Attributes
- Inherited from:
- OpenAICompatibleClient