openai_gpt
langroid/language_models/openai_gpt.py
OpenAICallParams
¶
Bases: BaseModel
Various params that can be sent to an OpenAI API chat-completion call. When specified, any param here overrides the one with same name in the OpenAIGPTConfig. See OpenAI API Reference for details on the params: https://platform.openai.com/docs/api-reference/chat
LiteLLMProxyConfig
¶
Bases: BaseSettings
Configuration for LiteLLM proxy connection.
OpenAIGPTConfig(**kwargs)
¶
Bases: LLMConfig
Class for any LLM with an OpenAI-like API: besides the OpenAI models this includes: (a) locally-served models behind an OpenAI-compatible API (b) non-local models, using a proxy adaptor lib like litellm that provides an OpenAI-compatible API. (We could rename this class to OpenAILikeConfig, but we keep it as-is for now)
Important Note:
Due to the env_prefix = "OPENAI_"
defined below,
all of the fields below can be set AND OVERRIDDEN via env vars,
by upper-casing the name and prefixing with OPENAI_, e.g.¶
OPENAI_MAX_OUTPUT_TOKENS=1000.¶
If any of these is defined in this way in the environment¶
(either via explicit setenv or export or via .env file + load_dotenv()),¶
the environment variable takes precedence over the value in the config.¶
Source code in langroid/language_models/openai_gpt.py
create(prefix)
classmethod
¶
Create a config class whose params can be set via a desired prefix from the .env file or env vars. E.g., using
you can have a group of params prefixed by "OLLAMA_", to be used with models served viaollama
.
This way, you can maintain several setting-groups in your .env file,
one per model type.
Source code in langroid/language_models/openai_gpt.py
OpenAIResponse
¶
Bases: BaseModel
OpenAI response model, either completion or chat.
OpenAIGPT(config=OpenAIGPTConfig())
¶
Bases: LanguageModel
Class for OpenAI LLMs
Source code in langroid/language_models/openai_gpt.py
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|
is_gemini_model()
¶
unsupported_params()
¶
List of params that are not supported by the current model
Source code in langroid/language_models/openai_gpt.py
rename_params()
¶
Map of param name -> new name for specific models. Currently main troublemaker is o1* series.
chat_context_length()
¶
Context-length for chat-completion models/endpoints. Get it from the config if explicitly given, otherwise use model_info based on model name, and fall back to generic model_info if there's no match.
Source code in langroid/language_models/openai_gpt.py
completion_context_length()
¶
Context-length for completion models/endpoints. Get it from the config if explicitly given, otherwise use model_info based on model name, and fall back to generic model_info if there's no match.
Source code in langroid/language_models/openai_gpt.py
chat_cost()
¶
(Prompt, Cached, Generation) cost per 1000 tokens, for chat-completion models/endpoints. Get it from the dict, otherwise fail-over to general method
Source code in langroid/language_models/openai_gpt.py
set_stream(stream)
¶
Enable or disable streaming output from API. Args: stream: enable streaming output from API Returns: previous value of stream
Source code in langroid/language_models/openai_gpt.py
get_stream()
¶
tool_deltas_to_tools(tools)
staticmethod
¶
Convert accumulated tool-call deltas to OpenAIToolCall objects. Adapted from this excellent code: https://community.openai.com/t/help-for-function-calls-with-streaming/627170/2
Parameters:
Name | Type | Description | Default |
---|---|---|---|
tools
|
List[Dict[str, Any]]
|
list of tool deltas received from streaming API |
required |
Returns:
Name | Type | Description |
---|---|---|
str |
str
|
plain text corresponding to tool calls that failed to parse |
List[OpenAIToolCall]
|
List[OpenAIToolCall]: list of OpenAIToolCall objects |
|
List[Dict[str, Any]]
|
List[Dict[str, Any]]: list of tool dicts (to reconstruct OpenAI API response, so it can be cached) |
Source code in langroid/language_models/openai_gpt.py
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noop()
¶
litellm_logging_fn(model_call_dict)
¶
Logging function for litellm