type stringclasses 5
values | name stringlengths 1 55 | qualified_name stringlengths 5 130 | docstring stringlengths 15 3.11k ⌀ | filepath stringclasses 90
values | is_public bool 2
classes | is_private bool 2
classes | line_start int64 0 1.44k ⌀ | line_end int64 0 1.51k ⌀ | annotation stringclasses 2
values | returns stringclasses 82
values | value stringclasses 66
values | parameters listlengths 0 10 ⌀ | bases listlengths 0 2 ⌀ | parent_class stringclasses 193
values | api_element_summary stringlengths 199 3.43k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
method | check_and_consume_rate_limit | fenic._inference.model_client.RateLimitStrategy.check_and_consume_rate_limit | Checks if there is enough capacity in both token and request rate limit buckets.
If there is sufficient capacity, this method will consume the required tokens
and request quota. This is an abstract method that must be implemented by subclasses.
Args:
token_estimate: A TokenEstimate object containing the estimated input, output,
and total tokens for the request.
Returns:
bool: True if there was enough capacity and it was consumed, False otherwise. | null | true | false | 148 | 162 | null | bool | null | [
"self",
"token_estimate"
] | null | RateLimitStrategy | Type: method
Member Name: check_and_consume_rate_limit
Qualified Name: fenic._inference.model_client.RateLimitStrategy.check_and_consume_rate_limit
Docstring: Checks if there is enough capacity in both token and request rate limit buckets.
If there is sufficient capacity, this method will consume the required tokens
and request quota. This is an abstract method that must be implemented by subclasses.
Args:
token_estimate: A TokenEstimate object containing the estimated input, output,
and total tokens for the request.
Returns:
bool: True if there was enough capacity and it was consumed, False otherwise.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "token_estimate"]
Returns: bool
Parent Class: RateLimitStrategy |
method | context_tokens_per_minute | fenic._inference.model_client.RateLimitStrategy.context_tokens_per_minute | Returns the total token rate limit per minute for this strategy.
This is an abstract method that must be implemented by subclasses to specify
their token rate limiting behavior.
Returns:
int: The total number of tokens allowed per minute. | null | true | false | 164 | 174 | null | int | null | [
"self"
] | null | RateLimitStrategy | Type: method
Member Name: context_tokens_per_minute
Qualified Name: fenic._inference.model_client.RateLimitStrategy.context_tokens_per_minute
Docstring: Returns the total token rate limit per minute for this strategy.
This is an abstract method that must be implemented by subclasses to specify
their token rate limiting behavior.
Returns:
int: The total number of tokens allowed per minute.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self"]
Returns: int
Parent Class: RateLimitStrategy |
class | UnifiedTokenRateLimitStrategy | fenic._inference.model_client.UnifiedTokenRateLimitStrategy | Rate limiting strategy that uses a single token bucket for both input and output tokens.
This strategy enforces both a request rate limit (RPM) and a unified token rate limit (TPM)
where input and output tokens share the same quota.
Attributes:
tpm: Total tokens per minute limit. Must be greater than 0.
unified_tokens_bucket: Token bucket for tracking and limiting total token usage. | null | true | false | 177 | 239 | null | null | null | null | [
"RateLimitStrategy"
] | null | Type: class
Member Name: UnifiedTokenRateLimitStrategy
Qualified Name: fenic._inference.model_client.UnifiedTokenRateLimitStrategy
Docstring: Rate limiting strategy that uses a single token bucket for both input and output tokens.
This strategy enforces both a request rate limit (RPM) and a unified token rate limit (TPM)
where input and output tokens share the same quota.
Attributes:
tpm: Total tokens per minute limit. Must be greater than 0.
unified_tokens_bucket: Token bucket for tracking and limiting total token usage.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
method | __init__ | fenic._inference.model_client.UnifiedTokenRateLimitStrategy.__init__ | null | null | true | false | 187 | 190 | null | null | null | [
"self",
"rpm",
"tpm"
] | null | UnifiedTokenRateLimitStrategy | Type: method
Member Name: __init__
Qualified Name: fenic._inference.model_client.UnifiedTokenRateLimitStrategy.__init__
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "rpm", "tpm"]
Returns: none
Parent Class: UnifiedTokenRateLimitStrategy |
method | backoff | fenic._inference.model_client.UnifiedTokenRateLimitStrategy.backoff | Backoff the request/token rate limit bucket. | null | true | false | 192 | 196 | null | int | null | [
"self",
"curr_time"
] | null | UnifiedTokenRateLimitStrategy | Type: method
Member Name: backoff
Qualified Name: fenic._inference.model_client.UnifiedTokenRateLimitStrategy.backoff
Docstring: Backoff the request/token rate limit bucket.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "curr_time"]
Returns: int
Parent Class: UnifiedTokenRateLimitStrategy |
method | check_and_consume_rate_limit | fenic._inference.model_client.UnifiedTokenRateLimitStrategy.check_and_consume_rate_limit | Checks and consumes rate limits for both requests and total tokens.
This implementation uses a single token bucket for both input and output tokens,
enforcing the total token limit across all token types.
Args:
token_estimate: A TokenEstimate object containing the estimated input, output,
and total tokens for the request.
Returns:
bool: True if there was enough capacity and it was consumed, False otherwise. | null | true | false | 198 | 223 | null | bool | null | [
"self",
"token_estimate"
] | null | UnifiedTokenRateLimitStrategy | Type: method
Member Name: check_and_consume_rate_limit
Qualified Name: fenic._inference.model_client.UnifiedTokenRateLimitStrategy.check_and_consume_rate_limit
Docstring: Checks and consumes rate limits for both requests and total tokens.
This implementation uses a single token bucket for both input and output tokens,
enforcing the total token limit across all token types.
Args:
token_estimate: A TokenEstimate object containing the estimated input, output,
and total tokens for the request.
Returns:
bool: True if there was enough capacity and it was consumed, False otherwise.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "token_estimate"]
Returns: bool
Parent Class: UnifiedTokenRateLimitStrategy |
method | context_tokens_per_minute | fenic._inference.model_client.UnifiedTokenRateLimitStrategy.context_tokens_per_minute | Returns the total token rate limit per minute.
Returns:
int: The total number of tokens allowed per minute (tpm). | null | true | false | 225 | 231 | null | int | null | [
"self"
] | null | UnifiedTokenRateLimitStrategy | Type: method
Member Name: context_tokens_per_minute
Qualified Name: fenic._inference.model_client.UnifiedTokenRateLimitStrategy.context_tokens_per_minute
Docstring: Returns the total token rate limit per minute.
Returns:
int: The total number of tokens allowed per minute (tpm).
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self"]
Returns: int
Parent Class: UnifiedTokenRateLimitStrategy |
method | __str__ | fenic._inference.model_client.UnifiedTokenRateLimitStrategy.__str__ | Returns a string representation of the rate limit strategy.
Returns:
str: A string showing the RPM and TPM limits. | null | true | false | 233 | 239 | null | null | null | [
"self"
] | null | UnifiedTokenRateLimitStrategy | Type: method
Member Name: __str__
Qualified Name: fenic._inference.model_client.UnifiedTokenRateLimitStrategy.__str__
Docstring: Returns a string representation of the rate limit strategy.
Returns:
str: A string showing the RPM and TPM limits.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self"]
Returns: none
Parent Class: UnifiedTokenRateLimitStrategy |
class | SeparatedTokenRateLimitStrategy | fenic._inference.model_client.SeparatedTokenRateLimitStrategy | Rate limiting strategy that uses separate token buckets for input and output tokens.
This strategy enforces both a request rate limit (RPM) and separate token rate limits
for input (input_tpm) and output (output_tpm) tokens.
Attributes:
input_tpm: Input tokens per minute limit. Must be greater than 0.
output_tpm: Output tokens per minute limit. Must be greater than 0.
input_tokens_bucket: Token bucket for tracking and limiting input token usage.
output_tokens_bucket: Token bucket for tracking and limiting output token usage. | null | true | false | 242 | 312 | null | null | null | null | [
"RateLimitStrategy"
] | null | Type: class
Member Name: SeparatedTokenRateLimitStrategy
Qualified Name: fenic._inference.model_client.SeparatedTokenRateLimitStrategy
Docstring: Rate limiting strategy that uses separate token buckets for input and output tokens.
This strategy enforces both a request rate limit (RPM) and separate token rate limits
for input (input_tpm) and output (output_tpm) tokens.
Attributes:
input_tpm: Input tokens per minute limit. Must be greater than 0.
output_tpm: Output tokens per minute limit. Must be greater than 0.
input_tokens_bucket: Token bucket for tracking and limiting input token usage.
output_tokens_bucket: Token bucket for tracking and limiting output token usage.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
method | __init__ | fenic._inference.model_client.SeparatedTokenRateLimitStrategy.__init__ | null | null | true | false | 254 | 259 | null | null | null | [
"self",
"rpm",
"input_tpm",
"output_tpm"
] | null | SeparatedTokenRateLimitStrategy | Type: method
Member Name: __init__
Qualified Name: fenic._inference.model_client.SeparatedTokenRateLimitStrategy.__init__
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "rpm", "input_tpm", "output_tpm"]
Returns: none
Parent Class: SeparatedTokenRateLimitStrategy |
method | backoff | fenic._inference.model_client.SeparatedTokenRateLimitStrategy.backoff | Backoff the request/token rate limit bucket. | null | true | false | 261 | 266 | null | int | null | [
"self",
"curr_time"
] | null | SeparatedTokenRateLimitStrategy | Type: method
Member Name: backoff
Qualified Name: fenic._inference.model_client.SeparatedTokenRateLimitStrategy.backoff
Docstring: Backoff the request/token rate limit bucket.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "curr_time"]
Returns: int
Parent Class: SeparatedTokenRateLimitStrategy |
method | check_and_consume_rate_limit | fenic._inference.model_client.SeparatedTokenRateLimitStrategy.check_and_consume_rate_limit | Checks and consumes rate limits for requests, input tokens, and output tokens.
This implementation uses separate token buckets for input and output tokens,
enforcing separate limits for each token type.
Args:
token_estimate: A TokenEstimate object containing the estimated input, output,
and total tokens for the request.
Returns:
bool: True if there was enough capacity and it was consumed, False otherwise. | null | true | false | 268 | 296 | null | bool | null | [
"self",
"token_estimate"
] | null | SeparatedTokenRateLimitStrategy | Type: method
Member Name: check_and_consume_rate_limit
Qualified Name: fenic._inference.model_client.SeparatedTokenRateLimitStrategy.check_and_consume_rate_limit
Docstring: Checks and consumes rate limits for requests, input tokens, and output tokens.
This implementation uses separate token buckets for input and output tokens,
enforcing separate limits for each token type.
Args:
token_estimate: A TokenEstimate object containing the estimated input, output,
and total tokens for the request.
Returns:
bool: True if there was enough capacity and it was consumed, False otherwise.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "token_estimate"]
Returns: bool
Parent Class: SeparatedTokenRateLimitStrategy |
method | context_tokens_per_minute | fenic._inference.model_client.SeparatedTokenRateLimitStrategy.context_tokens_per_minute | Returns the total token rate limit per minute.
Returns:
int: The sum of input and output tokens allowed per minute. | null | true | false | 298 | 304 | null | int | null | [
"self"
] | null | SeparatedTokenRateLimitStrategy | Type: method
Member Name: context_tokens_per_minute
Qualified Name: fenic._inference.model_client.SeparatedTokenRateLimitStrategy.context_tokens_per_minute
Docstring: Returns the total token rate limit per minute.
Returns:
int: The sum of input and output tokens allowed per minute.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self"]
Returns: int
Parent Class: SeparatedTokenRateLimitStrategy |
method | __str__ | fenic._inference.model_client.SeparatedTokenRateLimitStrategy.__str__ | Returns a string representation of the rate limit strategy.
Returns:
str: A string showing the RPM, input TPM, and output TPM limits. | null | true | false | 306 | 312 | null | null | null | [
"self"
] | null | SeparatedTokenRateLimitStrategy | Type: method
Member Name: __str__
Qualified Name: fenic._inference.model_client.SeparatedTokenRateLimitStrategy.__str__
Docstring: Returns a string representation of the rate limit strategy.
Returns:
str: A string showing the RPM, input TPM, and output TPM limits.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self"]
Returns: none
Parent Class: SeparatedTokenRateLimitStrategy |
class | ModelClient | fenic._inference.model_client.ModelClient | Base client for interacting with language models.
This abstract base class provides a robust framework for interacting with language models,
handling rate limiting, request queuing, retries, and deduplication. It manages concurrent
requests efficiently using an asynchronous event loop and implements token-based rate limiting.
Type Parameters:
RequestT: The type of request objects this client handles
ResponseT: The type of response objects this client returns
Attributes:
model (str): The name or identifier of the model
model_provider (ModelProvider): The provider of the model (e.g., OPENAI, ANTHROPIC)
rate_limit_strategy (RateLimitStrategy): Strategy for rate limiting requests
token_counter (TiktokenTokenCounter): Counter for estimating token usage | null | true | false | 315 | 863 | null | null | null | null | [
"Generic[RequestT, ResponseT]",
"ABC"
] | null | Type: class
Member Name: ModelClient
Qualified Name: fenic._inference.model_client.ModelClient
Docstring: Base client for interacting with language models.
This abstract base class provides a robust framework for interacting with language models,
handling rate limiting, request queuing, retries, and deduplication. It manages concurrent
requests efficiently using an asynchronous event loop and implements token-based rate limiting.
Type Parameters:
RequestT: The type of request objects this client handles
ResponseT: The type of response objects this client returns
Attributes:
model (str): The name or identifier of the model
model_provider (ModelProvider): The provider of the model (e.g., OPENAI, ANTHROPIC)
rate_limit_strategy (RateLimitStrategy): Strategy for rate limiting requests
token_counter (TiktokenTokenCounter): Counter for estimating token usage
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
method | __init__ | fenic._inference.model_client.ModelClient.__init__ | Initialize the ModelClient with configuration for model interaction.
Args:
model: The name or identifier of the model
model_provider: The model provider (OPENAI, ANTHROPIC)
rate_limit_strategy: Strategy for rate limiting requests
token_counter: Implementation for predicting input token counts
queue_size: Maximum size of the request queue (default: 100)
initial_backoff_seconds: Initial delay for exponential backoff (default: 1)
backoff_factor: Factor by which backoff time increases (default: 2)
max_backoffs: Maximum number of retry attempts (default: 10) | null | true | false | 333 | 386 | null | null | null | [
"self",
"model",
"model_provider",
"rate_limit_strategy",
"token_counter",
"queue_size",
"initial_backoff_seconds",
"backoff_factor",
"max_backoffs"
] | null | ModelClient | Type: method
Member Name: __init__
Qualified Name: fenic._inference.model_client.ModelClient.__init__
Docstring: Initialize the ModelClient with configuration for model interaction.
Args:
model: The name or identifier of the model
model_provider: The model provider (OPENAI, ANTHROPIC)
rate_limit_strategy: Strategy for rate limiting requests
token_counter: Implementation for predicting input token counts
queue_size: Maximum size of the request queue (default: 100)
initial_backoff_seconds: Initial delay for exponential backoff (default: 1)
backoff_factor: Factor by which backoff time increases (default: 2)
max_backoffs: Maximum number of retry attempts (default: 10)
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "model", "model_provider", "rate_limit_strategy", "token_counter", "queue_size", "initial_backoff_seconds", "backoff_factor", "max_backoffs"]
Returns: none
Parent Class: ModelClient |
method | make_single_request | fenic._inference.model_client.ModelClient.make_single_request | Make a single API call to the language model.
This method must be implemented by subclasses to handle the actual API communication
with the language model provider.
Args:
request: The request data to send to the model
Returns:
Union[None, ResponseT, TransientException, FatalException]: The API response,
None if the request was empty, or an exception wrapper indicating either a
transient error (can be retried) or a fatal error (should not be retried) | null | true | false | 388 | 405 | null | Union[None, ResponseT, TransientException, FatalException] | null | [
"self",
"request"
] | null | ModelClient | Type: method
Member Name: make_single_request
Qualified Name: fenic._inference.model_client.ModelClient.make_single_request
Docstring: Make a single API call to the language model.
This method must be implemented by subclasses to handle the actual API communication
with the language model provider.
Args:
request: The request data to send to the model
Returns:
Union[None, ResponseT, TransientException, FatalException]: The API response,
None if the request was empty, or an exception wrapper indicating either a
transient error (can be retried) or a fatal error (should not be retried)
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "request"]
Returns: Union[None, ResponseT, TransientException, FatalException]
Parent Class: ModelClient |
method | estimate_tokens_for_request | fenic._inference.model_client.ModelClient.estimate_tokens_for_request | Estimate the token usage for a given request.
This method must be implemented by subclasses to accurately predict token usage
for both input and output tokens.
Args:
request: The request to estimate tokens for
Returns:
TokenEstimate: Object containing estimated input and output tokens | null | true | false | 407 | 420 | null | TokenEstimate | null | [
"self",
"request"
] | null | ModelClient | Type: method
Member Name: estimate_tokens_for_request
Qualified Name: fenic._inference.model_client.ModelClient.estimate_tokens_for_request
Docstring: Estimate the token usage for a given request.
This method must be implemented by subclasses to accurately predict token usage
for both input and output tokens.
Args:
request: The request to estimate tokens for
Returns:
TokenEstimate: Object containing estimated input and output tokens
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "request"]
Returns: TokenEstimate
Parent Class: ModelClient |
method | count_tokens | fenic._inference.model_client.ModelClient.count_tokens | Count the number of tokens in a tokenizable object.
Args:
messages: The tokenizable object to count tokens for
Returns:
int: The number of tokens in the object | null | true | false | 422 | 431 | null | int | null | [
"self",
"messages"
] | null | ModelClient | Type: method
Member Name: count_tokens
Qualified Name: fenic._inference.model_client.ModelClient.count_tokens
Docstring: Count the number of tokens in a tokenizable object.
Args:
messages: The tokenizable object to count tokens for
Returns:
int: The number of tokens in the object
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "messages"]
Returns: int
Parent Class: ModelClient |
method | get_request_key | fenic._inference.model_client.ModelClient.get_request_key | Generate a unique key for request deduplication.
This method must be implemented by subclasses to provide a hashable key that
uniquely identifies a request for deduplication purposes.
Args:
request: The request to generate a key for
Returns:
Any: A hashable value that uniquely identifies this request | null | true | false | 433 | 446 | null | Any | null | [
"self",
"request"
] | null | ModelClient | Type: method
Member Name: get_request_key
Qualified Name: fenic._inference.model_client.ModelClient.get_request_key
Docstring: Generate a unique key for request deduplication.
This method must be implemented by subclasses to provide a hashable key that
uniquely identifies a request for deduplication purposes.
Args:
request: The request to generate a key for
Returns:
Any: A hashable value that uniquely identifies this request
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "request"]
Returns: Any
Parent Class: ModelClient |
method | get_metrics | fenic._inference.model_client.ModelClient.get_metrics | Get the current metrics for this model client.
Returns:
LMMetrics: The current metrics for this client | null | true | false | 448 | 455 | null | LMMetrics | null | [
"self"
] | null | ModelClient | Type: method
Member Name: get_metrics
Qualified Name: fenic._inference.model_client.ModelClient.get_metrics
Docstring: Get the current metrics for this model client.
Returns:
LMMetrics: The current metrics for this client
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self"]
Returns: LMMetrics
Parent Class: ModelClient |
method | reset_metrics | fenic._inference.model_client.ModelClient.reset_metrics | Reset all metrics for this model client to their initial values. | null | true | false | 457 | 460 | null | null | null | [
"self"
] | null | ModelClient | Type: method
Member Name: reset_metrics
Qualified Name: fenic._inference.model_client.ModelClient.reset_metrics
Docstring: Reset all metrics for this model client to their initial values.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self"]
Returns: none
Parent Class: ModelClient |
method | shutdown | fenic._inference.model_client.ModelClient.shutdown | Shut down the model client and clean up resources.
This method:
1. Cancels all pending and in-flight requests
2. Unregisters the client from the ModelClientManager
3. Cleans up all associated resources
4. Ensures all threads are properly notified of the shutdown | null | true | false | 465 | 502 | null | null | null | [
"self"
] | null | ModelClient | Type: method
Member Name: shutdown
Qualified Name: fenic._inference.model_client.ModelClient.shutdown
Docstring: Shut down the model client and clean up resources.
This method:
1. Cancels all pending and in-flight requests
2. Unregisters the client from the ModelClientManager
3. Cleans up all associated resources
4. Ensures all threads are properly notified of the shutdown
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self"]
Returns: none
Parent Class: ModelClient |
method | make_batch_requests | fenic._inference.model_client.ModelClient.make_batch_requests | Submit and process a batch of requests asynchronously.
This method handles the submission and processing of multiple requests in parallel,
with automatic deduplication and rate limiting. It provides progress tracking
and handles empty requests appropriately.
Args:
requests: List of requests to process. None entries are handled as empty responses
operation_name: Name for logging purposes to identify the operation
Returns:
List[ResponseT]: List of responses in the same order as the input requests | null | true | false | 504 | 600 | null | List[ResponseT] | null | [
"self",
"requests",
"operation_name"
] | null | ModelClient | Type: method
Member Name: make_batch_requests
Qualified Name: fenic._inference.model_client.ModelClient.make_batch_requests
Docstring: Submit and process a batch of requests asynchronously.
This method handles the submission and processing of multiple requests in parallel,
with automatic deduplication and rate limiting. It provides progress tracking
and handles empty requests appropriately.
Args:
requests: List of requests to process. None entries are handled as empty responses
operation_name: Name for logging purposes to identify the operation
Returns:
List[ResponseT]: List of responses in the same order as the input requests
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "requests", "operation_name"]
Returns: List[ResponseT]
Parent Class: ModelClient |
method | _get_or_create_request_future | fenic._inference.model_client.ModelClient._get_or_create_request_future | Retrieves an existing future for a duplicate request or creates a new one.
Args:
unique_futures: A dictionary mapping request keys to their futures.
request: The current request being processed.
Returns:
A tuple of the future for the request and the estimated number of tokens (0 for duplicates). | null | false | true | 605 | 650 | null | tuple[Future, TokenEstimate | None] | null | [
"self",
"unique_futures",
"request"
] | null | ModelClient | Type: method
Member Name: _get_or_create_request_future
Qualified Name: fenic._inference.model_client.ModelClient._get_or_create_request_future
Docstring: Retrieves an existing future for a duplicate request or creates a new one.
Args:
unique_futures: A dictionary mapping request keys to their futures.
request: The current request being processed.
Returns:
A tuple of the future for the request and the estimated number of tokens (0 for duplicates).
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["self", "unique_futures", "request"]
Returns: tuple[Future, TokenEstimate | None]
Parent Class: ModelClient |
method | _maybe_raise_thread_exception | fenic._inference.model_client.ModelClient._maybe_raise_thread_exception | Surface exceptions from event loop to calling thread immediately. | null | false | true | 652 | 657 | null | null | null | [
"self"
] | null | ModelClient | Type: method
Member Name: _maybe_raise_thread_exception
Qualified Name: fenic._inference.model_client.ModelClient._maybe_raise_thread_exception
Docstring: Surface exceptions from event loop to calling thread immediately.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["self"]
Returns: none
Parent Class: ModelClient |
method | _calculate_backoff_time | fenic._inference.model_client.ModelClient._calculate_backoff_time | Calculates the backoff duration using exponential backoff with a maximum limit.
Args:
backoff_iteration: The current backoff iteration.
Returns:
The backoff time in seconds. | null | false | true | 659 | 671 | null | float | null | [
"self",
"backoff_iteration"
] | null | ModelClient | Type: method
Member Name: _calculate_backoff_time
Qualified Name: fenic._inference.model_client.ModelClient._calculate_backoff_time
Docstring: Calculates the backoff duration using exponential backoff with a maximum limit.
Args:
backoff_iteration: The current backoff iteration.
Returns:
The backoff time in seconds.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["self", "backoff_iteration"]
Returns: float
Parent Class: ModelClient |
method | _check_and_consume_rate_limit | fenic._inference.model_client.ModelClient._check_and_consume_rate_limit | Checks if there is enough capacity in both the token and request rate limit buckets,
and consumes the capacity if so.
Args:
token_amount: A TokenEstimate object containing the estimated input, output, and total tokens.
Returns:
True if there was enough capacity and it was consumed, False otherwise. | null | false | true | 673 | 683 | null | bool | null | [
"self",
"token_amount"
] | null | ModelClient | Type: method
Member Name: _check_and_consume_rate_limit
Qualified Name: fenic._inference.model_client.ModelClient._check_and_consume_rate_limit
Docstring: Checks if there is enough capacity in both the token and request rate limit buckets,
and consumes the capacity if so.
Args:
token_amount: A TokenEstimate object containing the estimated input, output, and total tokens.
Returns:
True if there was enough capacity and it was consumed, False otherwise.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["self", "token_amount"]
Returns: bool
Parent Class: ModelClient |
method | _enqueue_request | fenic._inference.model_client.ModelClient._enqueue_request | Enqueue a request to be processed.
Args:
queue_item: The queue item to enqueue. | null | false | true | 685 | 691 | null | null | null | [
"self",
"queue_item"
] | null | ModelClient | Type: method
Member Name: _enqueue_request
Qualified Name: fenic._inference.model_client.ModelClient._enqueue_request
Docstring: Enqueue a request to be processed.
Args:
queue_item: The queue item to enqueue.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["self", "queue_item"]
Returns: none
Parent Class: ModelClient |
method | _process_queue | fenic._inference.model_client.ModelClient._process_queue | Continuously processes requests from the request and retry queues. This method runs on the shared asyncio event loop. | null | false | true | 696 | 725 | null | null | null | [
"self"
] | null | ModelClient | Type: method
Member Name: _process_queue
Qualified Name: fenic._inference.model_client.ModelClient._process_queue
Docstring: Continuously processes requests from the request and retry queues. This method runs on the shared asyncio event loop.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["self"]
Returns: none
Parent Class: ModelClient |
method | _process_single_request | fenic._inference.model_client.ModelClient._process_single_request | Process a single request from the queues.
Args:
queue_item: The queue item to process. | null | false | true | 727 | 751 | null | null | null | [
"self",
"queue_item"
] | null | ModelClient | Type: method
Member Name: _process_single_request
Qualified Name: fenic._inference.model_client.ModelClient._process_single_request
Docstring: Process a single request from the queues.
Args:
queue_item: The queue item to process.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["self", "queue_item"]
Returns: none
Parent Class: ModelClient |
method | _handle_response | fenic._inference.model_client.ModelClient._handle_response | Handle the response from a request, including retrying if necessary.
Args:
queue_item: The queue item associated with the request.
maybe_response: The response or exception from the request. | null | false | true | 753 | 783 | null | null | null | [
"self",
"queue_item",
"maybe_response"
] | null | ModelClient | Type: method
Member Name: _handle_response
Qualified Name: fenic._inference.model_client.ModelClient._handle_response
Docstring: Handle the response from a request, including retrying if necessary.
Args:
queue_item: The queue item associated with the request.
maybe_response: The response or exception from the request.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["self", "queue_item", "maybe_response"]
Returns: none
Parent Class: ModelClient |
method | _maybe_backoff | fenic._inference.model_client.ModelClient._maybe_backoff | Manages the backoff period after encountering a transient exception. | null | false | true | 785 | 801 | null | null | null | [
"self"
] | null | ModelClient | Type: method
Member Name: _maybe_backoff
Qualified Name: fenic._inference.model_client.ModelClient._maybe_backoff
Docstring: Manages the backoff period after encountering a transient exception.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["self"]
Returns: none
Parent Class: ModelClient |
method | _get_queued_requests | fenic._inference.model_client.ModelClient._get_queued_requests | Asynchronously retrieves items from the retry queue or the request queue,
prioritizing the retry queue. Returns None if a shutdown is signaled.
Returns:
A list of queue items, or None if a shutdown is signaled. | null | false | true | 804 | 833 | null | List[QueueItem[RequestT]] | null | [
"self"
] | null | ModelClient | Type: method
Member Name: _get_queued_requests
Qualified Name: fenic._inference.model_client.ModelClient._get_queued_requests
Docstring: Asynchronously retrieves items from the retry queue or the request queue,
prioritizing the retry queue. Returns None if a shutdown is signaled.
Returns:
A list of queue items, or None if a shutdown is signaled.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["self"]
Returns: List[QueueItem[RequestT]]
Parent Class: ModelClient |
method | _track_inflight_task | fenic._inference.model_client.ModelClient._track_inflight_task | Adds a task to the set of inflight requests and removes it upon completion.
Args:
task: The task to track. | null | false | true | 835 | 842 | null | null | null | [
"self",
"task"
] | null | ModelClient | Type: method
Member Name: _track_inflight_task
Qualified Name: fenic._inference.model_client.ModelClient._track_inflight_task
Docstring: Adds a task to the set of inflight requests and removes it upon completion.
Args:
task: The task to track.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["self", "task"]
Returns: none
Parent Class: ModelClient |
method | _register_thread_exception | fenic._inference.model_client.ModelClient._register_thread_exception | Registers an exception that occurred on the event loop to be raised in the originating thread.
Args:
queue_item: The queue item associated with the exception.
exception: The exception that occurred. | null | false | true | 844 | 857 | null | null | null | [
"self",
"queue_item",
"exception"
] | null | ModelClient | Type: method
Member Name: _register_thread_exception
Qualified Name: fenic._inference.model_client.ModelClient._register_thread_exception
Docstring: Registers an exception that occurred on the event loop to be raised in the originating thread.
Args:
queue_item: The queue item associated with the exception.
exception: The exception that occurred.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["self", "queue_item", "exception"]
Returns: none
Parent Class: ModelClient |
method | _cancel_in_flight_requests | fenic._inference.model_client.ModelClient._cancel_in_flight_requests | Cancels all inflight tasks and gathers their results. | null | false | true | 859 | 863 | null | null | null | [
"self"
] | null | ModelClient | Type: method
Member Name: _cancel_in_flight_requests
Qualified Name: fenic._inference.model_client.ModelClient._cancel_in_flight_requests
Docstring: Cancels all inflight tasks and gathers their results.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["self"]
Returns: none
Parent Class: ModelClient |
class | ModelClientManager | fenic._inference.model_client.ModelClientManager | Manages a shared asyncio event loop for multiple ModelClient instances.
Ensures that all clients run on the same loop for efficient resource management. | null | true | false | 866 | 936 | null | null | null | null | [] | null | Type: class
Member Name: ModelClientManager
Qualified Name: fenic._inference.model_client.ModelClientManager
Docstring: Manages a shared asyncio event loop for multiple ModelClient instances.
Ensures that all clients run on the same loop for efficient resource management.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
method | __new__ | fenic._inference.model_client.ModelClientManager.__new__ | null | null | true | false | 874 | 879 | null | null | null | [
"cls"
] | null | ModelClientManager | Type: method
Member Name: __new__
Qualified Name: fenic._inference.model_client.ModelClientManager.__new__
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["cls"]
Returns: none
Parent Class: ModelClientManager |
method | _initialize | fenic._inference.model_client.ModelClientManager._initialize | Initializes the ModelClientManager, creating the event loop if it doesn't exist. | null | false | true | 881 | 886 | null | null | null | [
"self"
] | null | ModelClientManager | Type: method
Member Name: _initialize
Qualified Name: fenic._inference.model_client.ModelClientManager._initialize
Docstring: Initializes the ModelClientManager, creating the event loop if it doesn't exist.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["self"]
Returns: none
Parent Class: ModelClientManager |
method | register_client | fenic._inference.model_client.ModelClientManager.register_client | Registers a ModelClient with the manager and starts its processing task on the shared event loop.
Args:
client: The client to register. | null | true | false | 888 | 897 | null | null | null | [
"self",
"client"
] | null | ModelClientManager | Type: method
Member Name: register_client
Qualified Name: fenic._inference.model_client.ModelClientManager.register_client
Docstring: Registers a ModelClient with the manager and starts its processing task on the shared event loop.
Args:
client: The client to register.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "client"]
Returns: none
Parent Class: ModelClientManager |
method | unregister_client | fenic._inference.model_client.ModelClientManager.unregister_client | Unregisters a ModelClient from the manager and shuts down the event loop if no clients remain.
Args:
client: The client to unregister. | null | true | false | 899 | 927 | null | null | null | [
"self",
"client"
] | null | ModelClientManager | Type: method
Member Name: unregister_client
Qualified Name: fenic._inference.model_client.ModelClientManager.unregister_client
Docstring: Unregisters a ModelClient from the manager and shuts down the event loop if no clients remain.
Args:
client: The client to unregister.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "client"]
Returns: none
Parent Class: ModelClientManager |
method | _maybe_create_event_loop | fenic._inference.model_client.ModelClientManager._maybe_create_event_loop | Creates and starts a dedicated event loop in a background thread if one doesn't exist. | null | false | true | 929 | 936 | null | null | null | [
"self"
] | null | ModelClientManager | Type: method
Member Name: _maybe_create_event_loop
Qualified Name: fenic._inference.model_client.ModelClientManager._maybe_create_event_loop
Docstring: Creates and starts a dedicated event loop in a background thread if one doesn't exist.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["self"]
Returns: none
Parent Class: ModelClientManager |
function | _cancel_event_loop_tasks | fenic._inference.model_client._cancel_event_loop_tasks | Cancels all pending tasks in the given asyncio event loop, except the current task.
Args:
loop: The event loop to cancel tasks for. | null | false | true | 939 | 949 | null | null | null | [
"loop"
] | null | null | Type: function
Member Name: _cancel_event_loop_tasks
Qualified Name: fenic._inference.model_client._cancel_event_loop_tasks
Docstring: Cancels all pending tasks in the given asyncio event loop, except the current task.
Args:
loop: The event loop to cancel tasks for.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["loop"]
Returns: none
Parent Class: none |
module | types | fenic._inference.types | null | /private/var/folders/w2/dyfkx_354cqghs4b74vb_x380000gn/T/fenic-clone-0.0.0-y6d85svd/fenic/src/fenic/_inference/types.py | true | false | null | null | null | null | null | null | null | null | Type: module
Member Name: types
Qualified Name: fenic._inference.types
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
class | FewShotExample | fenic._inference.types.FewShotExample | null | null | true | false | 5 | 8 | null | null | null | null | [] | null | Type: class
Member Name: FewShotExample
Qualified Name: fenic._inference.types.FewShotExample
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
method | __init__ | fenic._inference.types.FewShotExample.__init__ | null | null | true | false | 0 | 0 | null | None | null | [
"self",
"user",
"assistant"
] | null | FewShotExample | Type: method
Member Name: __init__
Qualified Name: fenic._inference.types.FewShotExample.__init__
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "user", "assistant"]
Returns: None
Parent Class: FewShotExample |
class | LMRequestMessages | fenic._inference.types.LMRequestMessages | null | null | true | false | 10 | 24 | null | null | null | null | [] | null | Type: class
Member Name: LMRequestMessages
Qualified Name: fenic._inference.types.LMRequestMessages
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
method | to_message_list | fenic._inference.types.LMRequestMessages.to_message_list | null | null | true | false | 16 | 24 | null | List[Dict[str, str]] | null | [
"self"
] | null | LMRequestMessages | Type: method
Member Name: to_message_list
Qualified Name: fenic._inference.types.LMRequestMessages.to_message_list
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self"]
Returns: List[Dict[str, str]]
Parent Class: LMRequestMessages |
method | __init__ | fenic._inference.types.LMRequestMessages.__init__ | null | null | true | false | 0 | 0 | null | None | null | [
"self",
"system",
"examples",
"user"
] | null | LMRequestMessages | Type: method
Member Name: __init__
Qualified Name: fenic._inference.types.LMRequestMessages.__init__
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "system", "examples", "user"]
Returns: None
Parent Class: LMRequestMessages |
module | model_catalog | fenic._inference.model_catalog | null | /private/var/folders/w2/dyfkx_354cqghs4b74vb_x380000gn/T/fenic-clone-0.0.0-y6d85svd/fenic/src/fenic/_inference/model_catalog.py | true | false | null | null | null | null | null | null | null | null | Type: module
Member Name: model_catalog
Qualified Name: fenic._inference.model_catalog
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
class | ModelProvider | fenic._inference.model_catalog.ModelProvider | Enum representing different model providers supported by the system. | null | true | false | 5 | 9 | null | null | null | null | [
"Enum"
] | null | Type: class
Member Name: ModelProvider
Qualified Name: fenic._inference.model_catalog.ModelProvider
Docstring: Enum representing different model providers supported by the system.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
class | TieredTokenCost | fenic._inference.model_catalog.TieredTokenCost | null | null | true | false | 11 | 23 | null | null | null | null | [] | null | Type: class
Member Name: TieredTokenCost
Qualified Name: fenic._inference.model_catalog.TieredTokenCost
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
method | __init__ | fenic._inference.model_catalog.TieredTokenCost.__init__ | null | null | true | false | 13 | 23 | null | null | null | [
"self",
"input_token_cost",
"cached_input_token_read_cost",
"output_token_cost",
"cached_input_token_write_cost"
] | null | TieredTokenCost | Type: method
Member Name: __init__
Qualified Name: fenic._inference.model_catalog.TieredTokenCost.__init__
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "input_token_cost", "cached_input_token_read_cost", "output_token_cost", "cached_input_token_write_cost"]
Returns: none
Parent Class: TieredTokenCost |
class | CompletionModelParameters | fenic._inference.model_catalog.CompletionModelParameters | Parameters for completion models including costs and context window size.
Attributes:
input_token_cost: Cost per input token in USD
cached_input_token_read_cost: Cost per cached input token read in USD
cached_input_token_write_cost: Cost per cached input token write in USD
output_token_cost: Cost per output token in USD
context_window_length: Maximum number of tokens in the context window
max_output_tokens: Maximum number of tokens the model can generate in a single request. | null | true | false | 25 | 57 | null | null | null | null | [] | null | Type: class
Member Name: CompletionModelParameters
Qualified Name: fenic._inference.model_catalog.CompletionModelParameters
Docstring: Parameters for completion models including costs and context window size.
Attributes:
input_token_cost: Cost per input token in USD
cached_input_token_read_cost: Cost per cached input token read in USD
cached_input_token_write_cost: Cost per cached input token write in USD
output_token_cost: Cost per output token in USD
context_window_length: Maximum number of tokens in the context window
max_output_tokens: Maximum number of tokens the model can generate in a single request.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
method | __init__ | fenic._inference.model_catalog.CompletionModelParameters.__init__ | null | null | true | false | 36 | 57 | null | null | null | [
"self",
"input_token_cost",
"output_token_cost",
"context_window_length",
"max_output_tokens",
"max_temperature",
"cached_input_token_write_cost",
"cached_input_token_read_cost",
"tiered_token_costs",
"requires_reasoning_effort"
] | null | CompletionModelParameters | Type: method
Member Name: __init__
Qualified Name: fenic._inference.model_catalog.CompletionModelParameters.__init__
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "input_token_cost", "output_token_cost", "context_window_length", "max_output_tokens", "max_temperature", "cached_input_token_write_cost", "cached_input_token_read_cost", "tiered_token_costs", "requires_reasoning_effort"]
Returns: none
Parent Class: CompletionModelParameters |
class | EmbeddingModelParameters | fenic._inference.model_catalog.EmbeddingModelParameters | Parameters for embedding models including costs and output dimensions.
Attributes:
input_token_cost: Cost per input token in USD
output_dimensions: Number of dimensions in the embedding output | null | true | false | 60 | 69 | null | null | null | null | [] | null | Type: class
Member Name: EmbeddingModelParameters
Qualified Name: fenic._inference.model_catalog.EmbeddingModelParameters
Docstring: Parameters for embedding models including costs and output dimensions.
Attributes:
input_token_cost: Cost per input token in USD
output_dimensions: Number of dimensions in the embedding output
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
method | __init__ | fenic._inference.model_catalog.EmbeddingModelParameters.__init__ | null | null | true | false | 67 | 69 | null | null | null | [
"self",
"input_token_cost",
"output_dimensions"
] | null | EmbeddingModelParameters | Type: method
Member Name: __init__
Qualified Name: fenic._inference.model_catalog.EmbeddingModelParameters.__init__
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "input_token_cost", "output_dimensions"]
Returns: none
Parent Class: EmbeddingModelParameters |
attribute | CompletionModelCollection | fenic._inference.model_catalog.CompletionModelCollection | null | null | true | false | 71 | 71 | TypeAlias | null | Dict[str, CompletionModelParameters] | null | null | null | Type: attribute
Member Name: CompletionModelCollection
Qualified Name: fenic._inference.model_catalog.CompletionModelCollection
Docstring: none
Value: Dict[str, CompletionModelParameters]
Annotation: TypeAlias
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
attribute | EmbeddingModelCollection | fenic._inference.model_catalog.EmbeddingModelCollection | null | null | true | false | 72 | 72 | TypeAlias | null | Dict[str, EmbeddingModelParameters] | null | null | null | Type: attribute
Member Name: EmbeddingModelCollection
Qualified Name: fenic._inference.model_catalog.EmbeddingModelCollection
Docstring: none
Value: Dict[str, EmbeddingModelParameters]
Annotation: TypeAlias
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
attribute | OPENAI_AVAILABLE_LANGUAGE_MODELS | fenic._inference.model_catalog.OPENAI_AVAILABLE_LANGUAGE_MODELS | null | null | true | false | 73 | 91 | null | null | Literal['gpt-4.1', 'gpt-4.1-mini', 'gpt-4.1-nano', 'gpt-4.1-2025-04-14', 'gpt-4.1-mini-2025-04-14', 'gpt-4.1-nano-2025-04-14', 'gpt-4o', 'gpt-4o-2024-11-20', 'gpt-4o-2024-08-06', 'gpt-4o-2024-05-13', 'gpt-4o-mini', 'gpt-4o-mini-2024-07-18', 'gpt-4-turbo', 'gpt-4-turbo-2024-04-09', 'gpt-4', 'gpt-4-0314', 'gpt-4-0613'] | null | null | null | Type: attribute
Member Name: OPENAI_AVAILABLE_LANGUAGE_MODELS
Qualified Name: fenic._inference.model_catalog.OPENAI_AVAILABLE_LANGUAGE_MODELS
Docstring: none
Value: Literal['gpt-4.1', 'gpt-4.1-mini', 'gpt-4.1-nano', 'gpt-4.1-2025-04-14', 'gpt-4.1-mini-2025-04-14', 'gpt-4.1-nano-2025-04-14', 'gpt-4o', 'gpt-4o-2024-11-20', 'gpt-4o-2024-08-06', 'gpt-4o-2024-05-13', 'gpt-4o-mini', 'gpt-4o-mini-2024-07-18', 'gpt-4-turbo', 'gpt-4-turbo-2024-04-09', 'gpt-4', 'gpt-4-0314', 'gpt-4-0613']
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
attribute | OPENAI_AVAILABLE_EMBEDDING_MODELS | fenic._inference.model_catalog.OPENAI_AVAILABLE_EMBEDDING_MODELS | null | null | true | false | 93 | 96 | null | null | Literal['text-embedding-3-small', 'text-embedding-3-large'] | null | null | null | Type: attribute
Member Name: OPENAI_AVAILABLE_EMBEDDING_MODELS
Qualified Name: fenic._inference.model_catalog.OPENAI_AVAILABLE_EMBEDDING_MODELS
Docstring: none
Value: Literal['text-embedding-3-small', 'text-embedding-3-large']
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
attribute | ANTHROPIC_AVAILABLE_LANGUAGE_MODELS | fenic._inference.model_catalog.ANTHROPIC_AVAILABLE_LANGUAGE_MODELS | null | null | true | false | 98 | 115 | null | null | Literal['claude-3-7-sonnet-latest', 'claude-3-7-sonnet-20250219', 'claude-3-5-haiku-latest', 'claude-3-5-haiku-20241022', 'claude-sonnet-4-20250514', 'claude-sonnet-4-0', 'claude-4-sonnet-20250514', 'claude-3-5-sonnet-latest', 'claude-3-5-sonnet-20241022', 'claude-3-5-sonnet-20240620', 'claude-opus-4-0', 'claude-opus-4-20250514', 'claude-4-opus-20250514', 'claude-3-opus-latest', 'claude-3-opus-20240229', 'claude-3-haiku-20240307'] | null | null | null | Type: attribute
Member Name: ANTHROPIC_AVAILABLE_LANGUAGE_MODELS
Qualified Name: fenic._inference.model_catalog.ANTHROPIC_AVAILABLE_LANGUAGE_MODELS
Docstring: none
Value: Literal['claude-3-7-sonnet-latest', 'claude-3-7-sonnet-20250219', 'claude-3-5-haiku-latest', 'claude-3-5-haiku-20241022', 'claude-sonnet-4-20250514', 'claude-sonnet-4-0', 'claude-4-sonnet-20250514', 'claude-3-5-sonnet-latest', 'claude-3-5-sonnet-20241022', 'claude-3-5-sonnet-20240620', 'claude-opus-4-0', 'claude-opus-4-20250514', 'claude-4-opus-20250514', 'claude-3-opus-latest', 'claude-3-opus-20240229', 'claude-3-haiku-20240307']
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
attribute | GOOGLE_GLA_AVAILABLE_MODELS | fenic._inference.model_catalog.GOOGLE_GLA_AVAILABLE_MODELS | null | null | true | false | 117 | 125 | null | null | Literal['gemini-2.5-pro-preview-06-05', 'gemini-2.5-flash-preview-05-20', 'gemini-2.0-flash-lite', 'gemini-2.0-flash-lite-001', 'gemini-2.0-flash', 'gemini-2.0-flash-001', 'gemini-2.0-flash-exp'] | null | null | null | Type: attribute
Member Name: GOOGLE_GLA_AVAILABLE_MODELS
Qualified Name: fenic._inference.model_catalog.GOOGLE_GLA_AVAILABLE_MODELS
Docstring: none
Value: Literal['gemini-2.5-pro-preview-06-05', 'gemini-2.5-flash-preview-05-20', 'gemini-2.0-flash-lite', 'gemini-2.0-flash-lite-001', 'gemini-2.0-flash', 'gemini-2.0-flash-001', 'gemini-2.0-flash-exp']
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
attribute | AVAILABLE_LANGUAGE_MODELS | fenic._inference.model_catalog.AVAILABLE_LANGUAGE_MODELS | null | null | true | false | 127 | 127 | null | null | Union[OPENAI_AVAILABLE_LANGUAGE_MODELS, ANTHROPIC_AVAILABLE_LANGUAGE_MODELS, GOOGLE_GLA_AVAILABLE_MODELS] | null | null | null | Type: attribute
Member Name: AVAILABLE_LANGUAGE_MODELS
Qualified Name: fenic._inference.model_catalog.AVAILABLE_LANGUAGE_MODELS
Docstring: none
Value: Union[OPENAI_AVAILABLE_LANGUAGE_MODELS, ANTHROPIC_AVAILABLE_LANGUAGE_MODELS, GOOGLE_GLA_AVAILABLE_MODELS]
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
attribute | AVAILABLE_EMBEDDING_MODELS | fenic._inference.model_catalog.AVAILABLE_EMBEDDING_MODELS | null | null | true | false | 128 | 128 | null | null | Union[OPENAI_AVAILABLE_EMBEDDING_MODELS] | null | null | null | Type: attribute
Member Name: AVAILABLE_EMBEDDING_MODELS
Qualified Name: fenic._inference.model_catalog.AVAILABLE_EMBEDDING_MODELS
Docstring: none
Value: Union[OPENAI_AVAILABLE_EMBEDDING_MODELS]
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
class | ModelCatalog | fenic._inference.model_catalog.ModelCatalog | Catalog of supported models and their parameters for different providers.
This class maintains a registry of all supported models across different providers,
including their costs, context windows, and other parameters. It provides methods
to query model information and calculate costs for different operations. | null | true | false | 130 | 569 | null | null | null | null | [] | null | Type: class
Member Name: ModelCatalog
Qualified Name: fenic._inference.model_catalog.ModelCatalog
Docstring: Catalog of supported models and their parameters for different providers.
This class maintains a registry of all supported models across different providers,
including their costs, context windows, and other parameters. It provides methods
to query model information and calculate costs for different operations.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
method | __init__ | fenic._inference.model_catalog.ModelCatalog.__init__ | null | null | true | false | 137 | 368 | null | null | null | [
"self"
] | null | ModelCatalog | Type: method
Member Name: __init__
Qualified Name: fenic._inference.model_catalog.ModelCatalog.__init__
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self"]
Returns: none
Parent Class: ModelCatalog |
method | get_completion_model_parameters | fenic._inference.model_catalog.ModelCatalog.get_completion_model_parameters | Gets the parameters for a specific completion model.
Args:
model_provider: The provider of the model
model_name: The name of the model
Returns:
Model parameters if found, None otherwise | null | true | false | 371 | 382 | null | CompletionModelParameters | None | null | [
"self",
"model_provider",
"model_name"
] | null | ModelCatalog | Type: method
Member Name: get_completion_model_parameters
Qualified Name: fenic._inference.model_catalog.ModelCatalog.get_completion_model_parameters
Docstring: Gets the parameters for a specific completion model.
Args:
model_provider: The provider of the model
model_name: The name of the model
Returns:
Model parameters if found, None otherwise
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "model_provider", "model_name"]
Returns: CompletionModelParameters | None
Parent Class: ModelCatalog |
method | get_embedding_model_parameters | fenic._inference.model_catalog.ModelCatalog.get_embedding_model_parameters | Gets the parameters for a specific embedding model.
Args:
model_provider: The provider of the model
model_name: The name of the model
Returns:
Model parameters if found, None otherwise | null | true | false | 384 | 394 | null | EmbeddingModelParameters | None | null | [
"self",
"model_provider",
"model_name"
] | null | ModelCatalog | Type: method
Member Name: get_embedding_model_parameters
Qualified Name: fenic._inference.model_catalog.ModelCatalog.get_embedding_model_parameters
Docstring: Gets the parameters for a specific embedding model.
Args:
model_provider: The provider of the model
model_name: The name of the model
Returns:
Model parameters if found, None otherwise
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "model_provider", "model_name"]
Returns: EmbeddingModelParameters | None
Parent Class: ModelCatalog |
method | generate_unsupported_completion_model_error_message | fenic._inference.model_catalog.ModelCatalog.generate_unsupported_completion_model_error_message | Generates an error message for unsupported completion models.
Args:
model_provider: The provider of the unsupported model
model_name: The name of the unsupported model
Returns:
Error message string | null | true | false | 396 | 407 | null | str | null | [
"self",
"model_provider",
"model_name"
] | null | ModelCatalog | Type: method
Member Name: generate_unsupported_completion_model_error_message
Qualified Name: fenic._inference.model_catalog.ModelCatalog.generate_unsupported_completion_model_error_message
Docstring: Generates an error message for unsupported completion models.
Args:
model_provider: The provider of the unsupported model
model_name: The name of the unsupported model
Returns:
Error message string
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "model_provider", "model_name"]
Returns: str
Parent Class: ModelCatalog |
method | generate_unsupported_embedding_model_error_message | fenic._inference.model_catalog.ModelCatalog.generate_unsupported_embedding_model_error_message | Generates an error message for unsupported embedding models.
Args:
model_provider: The provider of the unsupported model
model_name: The name of the unsupported model
Returns:
Error message string | null | true | false | 409 | 419 | null | str | null | [
"self",
"model_provider",
"model_name"
] | null | ModelCatalog | Type: method
Member Name: generate_unsupported_embedding_model_error_message
Qualified Name: fenic._inference.model_catalog.ModelCatalog.generate_unsupported_embedding_model_error_message
Docstring: Generates an error message for unsupported embedding models.
Args:
model_provider: The provider of the unsupported model
model_name: The name of the unsupported model
Returns:
Error message string
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "model_provider", "model_name"]
Returns: str
Parent Class: ModelCatalog |
method | get_supported_completions_models_as_string | fenic._inference.model_catalog.ModelCatalog.get_supported_completions_models_as_string | Returns a comma-separated string of all supported completion models.
Returns:
Comma-separated string of model names in format 'provider:model' | null | true | false | 421 | 431 | null | str | null | [
"self"
] | null | ModelCatalog | Type: method
Member Name: get_supported_completions_models_as_string
Qualified Name: fenic._inference.model_catalog.ModelCatalog.get_supported_completions_models_as_string
Docstring: Returns a comma-separated string of all supported completion models.
Returns:
Comma-separated string of model names in format 'provider:model'
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self"]
Returns: str
Parent Class: ModelCatalog |
method | get_supported_embeddings_models_as_string | fenic._inference.model_catalog.ModelCatalog.get_supported_embeddings_models_as_string | Returns a comma-separated string of all supported embedding models.
Returns:
Comma-separated string of model names | null | true | false | 433 | 443 | null | str | null | [
"self"
] | null | ModelCatalog | Type: method
Member Name: get_supported_embeddings_models_as_string
Qualified Name: fenic._inference.model_catalog.ModelCatalog.get_supported_embeddings_models_as_string
Docstring: Returns a comma-separated string of all supported embedding models.
Returns:
Comma-separated string of model names
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self"]
Returns: str
Parent Class: ModelCatalog |
method | calculate_completion_model_cost | fenic._inference.model_catalog.ModelCatalog.calculate_completion_model_cost | Calculates the total cost for a completion model operation.
Args:
model_provider: The provider of the model
model_name: The name of the model
uncached_input_tokens: Number of uncached input tokens
cached_input_tokens_read: Number of cached input tokens read
output_tokens: Number of output tokens
cached_input_tokens_written: Number of cached input tokens written
Returns:
Total cost in USD
Raises:
ValueError: If the model is not supported | null | true | false | 445 | 489 | null | float | null | [
"self",
"model_provider",
"model_name",
"uncached_input_tokens",
"cached_input_tokens_read",
"output_tokens",
"cached_input_tokens_written"
] | null | ModelCatalog | Type: method
Member Name: calculate_completion_model_cost
Qualified Name: fenic._inference.model_catalog.ModelCatalog.calculate_completion_model_cost
Docstring: Calculates the total cost for a completion model operation.
Args:
model_provider: The provider of the model
model_name: The name of the model
uncached_input_tokens: Number of uncached input tokens
cached_input_tokens_read: Number of cached input tokens read
output_tokens: Number of output tokens
cached_input_tokens_written: Number of cached input tokens written
Returns:
Total cost in USD
Raises:
ValueError: If the model is not supported
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "model_provider", "model_name", "uncached_input_tokens", "cached_input_tokens_read", "output_tokens", "cached_input_tokens_written"]
Returns: float
Parent Class: ModelCatalog |
method | calculate_embedding_model_cost | fenic._inference.model_catalog.ModelCatalog.calculate_embedding_model_cost | Calculates the total cost for an embedding model operation.
Args:
model_provider: The provider of the model
model_name: The name of the model
tokens: Number of tokens to embed
Returns:
Total cost in USD
Raises:
ValueError: If the model is not supported | null | true | false | 491 | 512 | null | float | null | [
"self",
"model_provider",
"model_name",
"tokens"
] | null | ModelCatalog | Type: method
Member Name: calculate_embedding_model_cost
Qualified Name: fenic._inference.model_catalog.ModelCatalog.calculate_embedding_model_cost
Docstring: Calculates the total cost for an embedding model operation.
Args:
model_provider: The provider of the model
model_name: The name of the model
tokens: Number of tokens to embed
Returns:
Total cost in USD
Raises:
ValueError: If the model is not supported
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "model_provider", "model_name", "tokens"]
Returns: float
Parent Class: ModelCatalog |
method | _create_complete_model_collection | fenic._inference.model_catalog.ModelCatalog._create_complete_model_collection | Creates a complete model collection including snapshots.
Args:
base_models: Dictionary of base model parameters
snapshots: Dictionary mapping (provider, base_model) to list of snapshot names
provider: The provider to create the collection for
Returns:
Complete model collection including snapshots | null | false | true | 515 | 536 | null | Dict[str, Union[CompletionModelParameters, EmbeddingModelParameters]] | null | [
"self",
"base_models",
"snapshots",
"provider"
] | null | ModelCatalog | Type: method
Member Name: _create_complete_model_collection
Qualified Name: fenic._inference.model_catalog.ModelCatalog._create_complete_model_collection
Docstring: Creates a complete model collection including snapshots.
Args:
base_models: Dictionary of base model parameters
snapshots: Dictionary mapping (provider, base_model) to list of snapshot names
provider: The provider to create the collection for
Returns:
Complete model collection including snapshots
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["self", "base_models", "snapshots", "provider"]
Returns: Dict[str, Union[CompletionModelParameters, EmbeddingModelParameters]]
Parent Class: ModelCatalog |
method | _get_supported_completions_models_by_provider | fenic._inference.model_catalog.ModelCatalog._get_supported_completions_models_by_provider | Returns the collection of completion models for a specific provider.
Args:
model_provider: The provider to get models for
Returns:
Collection of completion models for the specified provider, including snapshots | null | false | true | 538 | 547 | null | CompletionModelCollection | null | [
"self",
"model_provider"
] | null | ModelCatalog | Type: method
Member Name: _get_supported_completions_models_by_provider
Qualified Name: fenic._inference.model_catalog.ModelCatalog._get_supported_completions_models_by_provider
Docstring: Returns the collection of completion models for a specific provider.
Args:
model_provider: The provider to get models for
Returns:
Collection of completion models for the specified provider, including snapshots
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["self", "model_provider"]
Returns: CompletionModelCollection
Parent Class: ModelCatalog |
method | _get_supported_embeddings_models_by_provider | fenic._inference.model_catalog.ModelCatalog._get_supported_embeddings_models_by_provider | Returns the collection of embedding models for a specific provider.
Args:
model_provider: The provider to get models for
Returns:
Collection of embedding models for the specified provider, including snapshots | null | false | true | 549 | 558 | null | EmbeddingModelCollection | null | [
"self",
"model_provider"
] | null | ModelCatalog | Type: method
Member Name: _get_supported_embeddings_models_by_provider
Qualified Name: fenic._inference.model_catalog.ModelCatalog._get_supported_embeddings_models_by_provider
Docstring: Returns the collection of embedding models for a specific provider.
Args:
model_provider: The provider to get models for
Returns:
Collection of embedding models for the specified provider, including snapshots
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["self", "model_provider"]
Returns: EmbeddingModelCollection
Parent Class: ModelCatalog |
method | _get_supported_completions_models_by_provider_as_string | fenic._inference.model_catalog.ModelCatalog._get_supported_completions_models_by_provider_as_string | Returns a comma-separated string of supported completion model names for a provider.
Args:
model_provider: The provider to get model names for
Returns:
Comma-separated string of model names | null | false | true | 560 | 569 | null | str | null | [
"self",
"model_provider"
] | null | ModelCatalog | Type: method
Member Name: _get_supported_completions_models_by_provider_as_string
Qualified Name: fenic._inference.model_catalog.ModelCatalog._get_supported_completions_models_by_provider_as_string
Docstring: Returns a comma-separated string of supported completion model names for a provider.
Args:
model_provider: The provider to get model names for
Returns:
Comma-separated string of model names
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["self", "model_provider"]
Returns: str
Parent Class: ModelCatalog |
attribute | model_catalog | fenic._inference.model_catalog.model_catalog | null | null | true | false | 572 | 572 | null | null | ModelCatalog() | null | null | null | Type: attribute
Member Name: model_catalog
Qualified Name: fenic._inference.model_catalog.model_catalog
Docstring: none
Value: ModelCatalog()
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
module | google | fenic._inference.google | null | /private/var/folders/w2/dyfkx_354cqghs4b74vb_x380000gn/T/fenic-clone-0.0.0-y6d85svd/fenic/src/fenic/_inference/google/__init__.py | true | false | null | null | null | null | null | null | null | null | Type: module
Member Name: google
Qualified Name: fenic._inference.google
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
module | gemini_oai_chat_completions_client | fenic._inference.google.gemini_oai_chat_completions_client | Client for making requests to Google's Gemini model using OpenAI compatibility layer or Vertex AI. | /private/var/folders/w2/dyfkx_354cqghs4b74vb_x380000gn/T/fenic-clone-0.0.0-y6d85svd/fenic/src/fenic/_inference/google/gemini_oai_chat_completions_client.py | true | false | null | null | null | null | null | null | null | null | Type: module
Member Name: gemini_oai_chat_completions_client
Qualified Name: fenic._inference.google.gemini_oai_chat_completions_client
Docstring: Client for making requests to Google's Gemini model using OpenAI compatibility layer or Vertex AI.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
class | GeminiOAIChatCompletionsClient | fenic._inference.google.gemini_oai_chat_completions_client.GeminiOAIChatCompletionsClient | Client for making requests to Google's Gemini model using OpenAI compatibility layer or Vertex AI. | null | true | false | 32 | 128 | null | null | null | null | [
"ModelClient[FenicCompletionsRequest, FenicCompletionsResponse]"
] | null | Type: class
Member Name: GeminiOAIChatCompletionsClient
Qualified Name: fenic._inference.google.gemini_oai_chat_completions_client.GeminiOAIChatCompletionsClient
Docstring: Client for making requests to Google's Gemini model using OpenAI compatibility layer or Vertex AI.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
method | __init__ | fenic._inference.google.gemini_oai_chat_completions_client.GeminiOAIChatCompletionsClient.__init__ | Initialize the Gemini client with OpenAI compatibility layer or Vertex AI.
Args:
rate_limit_strategy: Strategy for handling rate limits
model: The Gemini model to use
queue_size: Size of the request queue
max_backoffs: Maximum number of backoff attempts
reasoning_effort: Reasoning effort level for thinking models (Gemini 2.5 only) | null | true | false | 35 | 80 | null | null | null | [
"self",
"rate_limit_strategy",
"model",
"queue_size",
"max_backoffs",
"reasoning_effort"
] | null | GeminiOAIChatCompletionsClient | Type: method
Member Name: __init__
Qualified Name: fenic._inference.google.gemini_oai_chat_completions_client.GeminiOAIChatCompletionsClient.__init__
Docstring: Initialize the Gemini client with OpenAI compatibility layer or Vertex AI.
Args:
rate_limit_strategy: Strategy for handling rate limits
model: The Gemini model to use
queue_size: Size of the request queue
max_backoffs: Maximum number of backoff attempts
reasoning_effort: Reasoning effort level for thinking models (Gemini 2.5 only)
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "rate_limit_strategy", "model", "queue_size", "max_backoffs", "reasoning_effort"]
Returns: none
Parent Class: GeminiOAIChatCompletionsClient |
method | make_single_request | fenic._inference.google.gemini_oai_chat_completions_client.GeminiOAIChatCompletionsClient.make_single_request | Make a single request to the Gemini API.
Args:
request: The request to make
Returns:
The response from the API or an exception | null | true | false | 83 | 94 | null | Union[None, FenicCompletionsResponse, TransientException, FatalException] | null | [
"self",
"request"
] | null | GeminiOAIChatCompletionsClient | Type: method
Member Name: make_single_request
Qualified Name: fenic._inference.google.gemini_oai_chat_completions_client.GeminiOAIChatCompletionsClient.make_single_request
Docstring: Make a single request to the Gemini API.
Args:
request: The request to make
Returns:
The response from the API or an exception
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "request"]
Returns: Union[None, FenicCompletionsResponse, TransientException, FatalException]
Parent Class: GeminiOAIChatCompletionsClient |
method | estimate_tokens_for_request | fenic._inference.google.gemini_oai_chat_completions_client.GeminiOAIChatCompletionsClient.estimate_tokens_for_request | Estimate the number of tokens for a request.
Args:
request: The request to estimate tokens for
Returns:
TokenEstimate with input and output token counts | null | true | false | 96 | 105 | null | TokenEstimate | null | [
"self",
"request"
] | null | GeminiOAIChatCompletionsClient | Type: method
Member Name: estimate_tokens_for_request
Qualified Name: fenic._inference.google.gemini_oai_chat_completions_client.GeminiOAIChatCompletionsClient.estimate_tokens_for_request
Docstring: Estimate the number of tokens for a request.
Args:
request: The request to estimate tokens for
Returns:
TokenEstimate with input and output token counts
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "request"]
Returns: TokenEstimate
Parent Class: GeminiOAIChatCompletionsClient |
method | get_request_key | fenic._inference.google.gemini_oai_chat_completions_client.GeminiOAIChatCompletionsClient.get_request_key | Generate a unique key for request deduplication.
Args:
request: The request to generate a key for
Returns:
A unique key for the request | null | true | false | 107 | 116 | null | str | null | [
"self",
"request"
] | null | GeminiOAIChatCompletionsClient | Type: method
Member Name: get_request_key
Qualified Name: fenic._inference.google.gemini_oai_chat_completions_client.GeminiOAIChatCompletionsClient.get_request_key
Docstring: Generate a unique key for request deduplication.
Args:
request: The request to generate a key for
Returns:
A unique key for the request
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "request"]
Returns: str
Parent Class: GeminiOAIChatCompletionsClient |
method | reset_metrics | fenic._inference.google.gemini_oai_chat_completions_client.GeminiOAIChatCompletionsClient.reset_metrics | Reset all metrics to their initial values. | null | true | false | 118 | 120 | null | null | null | [
"self"
] | null | GeminiOAIChatCompletionsClient | Type: method
Member Name: reset_metrics
Qualified Name: fenic._inference.google.gemini_oai_chat_completions_client.GeminiOAIChatCompletionsClient.reset_metrics
Docstring: Reset all metrics to their initial values.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self"]
Returns: none
Parent Class: GeminiOAIChatCompletionsClient |
method | get_metrics | fenic._inference.google.gemini_oai_chat_completions_client.GeminiOAIChatCompletionsClient.get_metrics | Get the current metrics.
Returns:
The current metrics | null | true | false | 122 | 128 | null | LMMetrics | null | [
"self"
] | null | GeminiOAIChatCompletionsClient | Type: method
Member Name: get_metrics
Qualified Name: fenic._inference.google.gemini_oai_chat_completions_client.GeminiOAIChatCompletionsClient.get_metrics
Docstring: Get the current metrics.
Returns:
The current metrics
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self"]
Returns: LMMetrics
Parent Class: GeminiOAIChatCompletionsClient |
module | anthropic | fenic._inference.anthropic | null | /private/var/folders/w2/dyfkx_354cqghs4b74vb_x380000gn/T/fenic-clone-0.0.0-y6d85svd/fenic/src/fenic/_inference/anthropic/__init__.py | true | false | null | null | null | null | null | null | null | null | Type: module
Member Name: anthropic
Qualified Name: fenic._inference.anthropic
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
module | anthropic_batch_chat_completions_client | fenic._inference.anthropic.anthropic_batch_chat_completions_client | null | /private/var/folders/w2/dyfkx_354cqghs4b74vb_x380000gn/T/fenic-clone-0.0.0-y6d85svd/fenic/src/fenic/_inference/anthropic/anthropic_batch_chat_completions_client.py | true | false | null | null | null | null | null | null | null | null | Type: module
Member Name: anthropic_batch_chat_completions_client
Qualified Name: fenic._inference.anthropic.anthropic_batch_chat_completions_client
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
attribute | EPHEMERAL_CACHE_CONTROL | fenic._inference.anthropic.anthropic_batch_chat_completions_client.EPHEMERAL_CACHE_CONTROL | null | null | true | false | 40 | 40 | null | null | CacheControlEphemeralParam(type='ephemeral') | null | null | null | Type: attribute
Member Name: EPHEMERAL_CACHE_CONTROL
Qualified Name: fenic._inference.anthropic.anthropic_batch_chat_completions_client.EPHEMERAL_CACHE_CONTROL
Docstring: none
Value: CacheControlEphemeralParam(type='ephemeral')
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
class | AnthropicBatchCompletionsClient | fenic._inference.anthropic.anthropic_batch_chat_completions_client.AnthropicBatchCompletionsClient | null | null | true | false | 42 | 198 | null | null | null | null | [
"ModelClient[FenicCompletionsRequest, FenicCompletionsResponse]"
] | null | Type: class
Member Name: AnthropicBatchCompletionsClient
Qualified Name: fenic._inference.anthropic.anthropic_batch_chat_completions_client.AnthropicBatchCompletionsClient
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
method | __init__ | fenic._inference.anthropic.anthropic_batch_chat_completions_client.AnthropicBatchCompletionsClient.__init__ | null | null | true | false | 45 | 67 | null | null | null | [
"self",
"rate_limit_strategy",
"queue_size",
"model",
"max_backoffs"
] | null | AnthropicBatchCompletionsClient | Type: method
Member Name: __init__
Qualified Name: fenic._inference.anthropic.anthropic_batch_chat_completions_client.AnthropicBatchCompletionsClient.__init__
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "rate_limit_strategy", "queue_size", "model", "max_backoffs"]
Returns: none
Parent Class: AnthropicBatchCompletionsClient |
method | validate_request | fenic._inference.anthropic.anthropic_batch_chat_completions_client.AnthropicBatchCompletionsClient.validate_request | Validate the request before making it to the Anthropic API. | null | true | false | 69 | 73 | null | Optional[FatalException] | null | [
"self",
"request"
] | null | AnthropicBatchCompletionsClient | Type: method
Member Name: validate_request
Qualified Name: fenic._inference.anthropic.anthropic_batch_chat_completions_client.AnthropicBatchCompletionsClient.validate_request
Docstring: Validate the request before making it to the Anthropic API.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "request"]
Returns: Optional[FatalException]
Parent Class: AnthropicBatchCompletionsClient |
method | make_single_request | fenic._inference.anthropic.anthropic_batch_chat_completions_client.AnthropicBatchCompletionsClient.make_single_request | null | null | true | false | 75 | 134 | null | Union[None, FenicCompletionsResponse, TransientException, FatalException] | null | [
"self",
"request"
] | null | AnthropicBatchCompletionsClient | Type: method
Member Name: make_single_request
Qualified Name: fenic._inference.anthropic.anthropic_batch_chat_completions_client.AnthropicBatchCompletionsClient.make_single_request
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "request"]
Returns: Union[None, FenicCompletionsResponse, TransientException, FatalException]
Parent Class: AnthropicBatchCompletionsClient |
method | estimate_response_format_tokens | fenic._inference.anthropic.anthropic_batch_chat_completions_client.AnthropicBatchCompletionsClient.estimate_response_format_tokens | null | null | true | false | 138 | 151 | null | int | null | [
"self",
"response_format"
] | null | AnthropicBatchCompletionsClient | Type: method
Member Name: estimate_response_format_tokens
Qualified Name: fenic._inference.anthropic.anthropic_batch_chat_completions_client.AnthropicBatchCompletionsClient.estimate_response_format_tokens
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "response_format"]
Returns: int
Parent Class: AnthropicBatchCompletionsClient |
method | estimate_tokens_for_request | fenic._inference.anthropic.anthropic_batch_chat_completions_client.AnthropicBatchCompletionsClient.estimate_tokens_for_request | null | null | true | false | 153 | 159 | null | TokenEstimate | null | [
"self",
"request"
] | null | AnthropicBatchCompletionsClient | Type: method
Member Name: estimate_tokens_for_request
Qualified Name: fenic._inference.anthropic.anthropic_batch_chat_completions_client.AnthropicBatchCompletionsClient.estimate_tokens_for_request
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "request"]
Returns: TokenEstimate
Parent Class: AnthropicBatchCompletionsClient |
method | count_tokens | fenic._inference.anthropic.anthropic_batch_chat_completions_client.AnthropicBatchCompletionsClient.count_tokens | null | null | true | false | 163 | 164 | null | int | null | [
"self",
"messages"
] | null | AnthropicBatchCompletionsClient | Type: method
Member Name: count_tokens
Qualified Name: fenic._inference.anthropic.anthropic_batch_chat_completions_client.AnthropicBatchCompletionsClient.count_tokens
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "messages"]
Returns: int
Parent Class: AnthropicBatchCompletionsClient |
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