id stringlengths 14 16 | text stringlengths 13 2.7k | source stringlengths 57 178 |
|---|---|---|
8d5b453c2c64-1 | yield_keys(*[, prefix])
Get an iterator over keys that match the given prefix.
__init__(store: BaseStore[str, Any], key_encoder: Callable[[K], str], value_serializer: Callable[[V], bytes], value_deserializer: Callable[[Any], V]) → None[source]¶
Initialize an EncodedStore.
mdelete(keys: Sequence[K]) → None[source]¶
Dele... | lang/api.python.langchain.com/en/latest/storage/langchain.storage.encoder_backed.EncoderBackedStore.html |
b95956eebac7-0 | langchain.storage.exceptions.InvalidKeyException¶
class langchain.storage.exceptions.InvalidKeyException[source]¶
Raised when a key is invalid; e.g., uses incorrect characters. | lang/api.python.langchain.com/en/latest/storage/langchain.storage.exceptions.InvalidKeyException.html |
cdac9d96bbde-0 | langchain.storage.upstash_redis.UpstashRedisStore¶
class langchain.storage.upstash_redis.UpstashRedisStore(*, client: Any = None, url: Optional[str] = None, token: Optional[str] = None, ttl: Optional[int] = None, namespace: Optional[str] = None)[source]¶
BaseStore implementation using Upstash Redis as the underlying st... | lang/api.python.langchain.com/en/latest/storage/langchain.storage.upstash_redis.UpstashRedisStore.html |
cdac9d96bbde-1 | namespace – if provided, all keys will be prefixed with this namespace
mdelete(keys: Sequence[str]) → None[source]¶
Delete the given keys.
mget(keys: Sequence[str]) → List[Optional[str]][source]¶
Get the values associated with the given keys.
mset(key_value_pairs: Sequence[Tuple[str, str]]) → None[source]¶
Set the give... | lang/api.python.langchain.com/en/latest/storage/langchain.storage.upstash_redis.UpstashRedisStore.html |
8e24a93086ed-0 | langchain.storage.in_memory.InMemoryStore¶
class langchain.storage.in_memory.InMemoryStore[source]¶
In-memory implementation of the BaseStore using a dictionary.
store¶
The underlying dictionary that stores
the key-value pairs.
Type
Dict[str, Any]
Examples
from langchain.storage import InMemoryStore
store = InMemorySto... | lang/api.python.langchain.com/en/latest/storage/langchain.storage.in_memory.InMemoryStore.html |
8e24a93086ed-1 | Set the values for the given keys.
Parameters
key_value_pairs (Sequence[Tuple[str, V]]) – A sequence of key-value pairs.
Returns
None
yield_keys(prefix: Optional[str] = None) → Iterator[str][source]¶
Get an iterator over keys that match the given prefix.
Parameters
prefix (str, optional) – The prefix to match. Defaults... | lang/api.python.langchain.com/en/latest/storage/langchain.storage.in_memory.InMemoryStore.html |
e1f0f80ccab6-0 | langchain.storage.file_system.LocalFileStore¶
class langchain.storage.file_system.LocalFileStore(root_path: Union[str, Path])[source]¶
BaseStore interface that works on the local file system.
Examples
Create a LocalFileStore instance and perform operations on it:
from langchain.storage import LocalFileStore
# Instantia... | lang/api.python.langchain.com/en/latest/storage/langchain.storage.file_system.LocalFileStore.html |
e1f0f80ccab6-1 | Delete the given keys and their associated values.
Parameters
keys (Sequence[str]) – A sequence of keys to delete.
Returns
None
mget(keys: Sequence[str]) → List[Optional[bytes]][source]¶
Get the values associated with the given keys.
Parameters
keys – A sequence of keys.
Returns
A sequence of optional values associated... | lang/api.python.langchain.com/en/latest/storage/langchain.storage.file_system.LocalFileStore.html |
8bb910f670a1-0 | langchain.storage.redis.RedisStore¶
class langchain.storage.redis.RedisStore(*, client: Any = None, redis_url: Optional[str] = None, client_kwargs: Optional[dict] = None, ttl: Optional[int] = None, namespace: Optional[str] = None)[source]¶
BaseStore implementation using Redis as the underlying store.
Examples
Create a ... | lang/api.python.langchain.com/en/latest/storage/langchain.storage.redis.RedisStore.html |
8bb910f670a1-1 | yield_keys(*[, prefix])
Yield keys in the store.
__init__(*, client: Any = None, redis_url: Optional[str] = None, client_kwargs: Optional[dict] = None, ttl: Optional[int] = None, namespace: Optional[str] = None) → None[source]¶
Initialize the RedisStore with a Redis connection.
Must provide either a Redis client or a r... | lang/api.python.langchain.com/en/latest/storage/langchain.storage.redis.RedisStore.html |
fecdc9b60418-0 | langchain.agents.format_scratchpad.log.format_log_to_str¶
langchain.agents.format_scratchpad.log.format_log_to_str(intermediate_steps: List[Tuple[AgentAction, str]], observation_prefix: str = 'Observation: ', llm_prefix: str = 'Thought: ') → str[source]¶
Construct the scratchpad that lets the agent continue its thought... | lang/api.python.langchain.com/en/latest/agents.format_scratchpad/langchain.agents.format_scratchpad.log.format_log_to_str.html |
0af5685a05d2-0 | langchain.agents.format_scratchpad.log_to_messages.format_log_to_messages¶
langchain.agents.format_scratchpad.log_to_messages.format_log_to_messages(intermediate_steps: List[Tuple[AgentAction, str]], template_tool_response: str = '{observation}') → List[BaseMessage][source]¶
Construct the scratchpad that lets the agent... | lang/api.python.langchain.com/en/latest/agents.format_scratchpad/langchain.agents.format_scratchpad.log_to_messages.format_log_to_messages.html |
73cb3a0be3c2-0 | langchain.agents.format_scratchpad.openai_functions.format_to_openai_function_messages¶
langchain.agents.format_scratchpad.openai_functions.format_to_openai_function_messages(intermediate_steps: Sequence[Tuple[AgentAction, str]]) → List[BaseMessage][source]¶
Convert (AgentAction, tool output) tuples into FunctionMessag... | lang/api.python.langchain.com/en/latest/agents.format_scratchpad/langchain.agents.format_scratchpad.openai_functions.format_to_openai_function_messages.html |
a225ea3598e8-0 | langchain.agents.format_scratchpad.xml.format_xml¶
langchain.agents.format_scratchpad.xml.format_xml(intermediate_steps: List[Tuple[AgentAction, str]]) → str[source]¶
Format the intermediate steps as XML.
Parameters
intermediate_steps – The intermediate steps.
Returns
The intermediate steps as XML. | lang/api.python.langchain.com/en/latest/agents.format_scratchpad/langchain.agents.format_scratchpad.xml.format_xml.html |
c38314461eee-0 | langchain.chat_models.baidu_qianfan_endpoint.QianfanChatEndpoint¶
class langchain.chat_models.baidu_qianfan_endpoint.QianfanChatEndpoint[source]¶
Bases: BaseChatModel
Baidu Qianfan chat models.
To use, you should have the qianfan python package installed, and
the environment variable qianfan_ak and qianfan_sk set with ... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.baidu_qianfan_endpoint.QianfanChatEndpoint.html |
c38314461eee-1 | Default is ERNIE-Bot-turbo.
param model_kwargs: Dict[str, Any] [Optional]¶
param penalty_score: Optional[float] = 1¶
Model params, only supported in ERNIE-Bot and ERNIE-Bot-turbo.
In the case of other model, passing these params will not affect the result.
param qianfan_ak: Optional[str] = None¶
param qianfan_sk: Optio... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.baidu_qianfan_endpoint.QianfanChatEndpoint.html |
c38314461eee-2 | e.g., if the underlying runnable uses an API which supports a batch mode.
async agenerate(messages: List[List[BaseMessage]], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.baidu_qianfan_endpoint.QianfanChatEndpoint.html |
c38314461eee-3 | async ainvoke(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → BaseMessage¶
Default implementation of ainvoke, calls invoke from a thread.
The default implementation allows usage of async code even if
the runnable did not i... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.baidu_qianfan_endpoint.QianfanChatEndpoint.html |
c38314461eee-4 | to the model provider API call.
Returns
Top model prediction as a message.
async astream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → AsyncIterator[BaseMessageChunk]¶
Default implementation of astream, which calls ainvo... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.baidu_qianfan_endpoint.QianfanChatEndpoint.html |
c38314461eee-5 | input is still being generated.
batch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Optional[Any]) → List[Output]¶
Default implementation runs invoke in parallel using a thread pool executor.
The default implementation of batch w... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.baidu_qianfan_endpoint.QianfanChatEndpoint.html |
c38314461eee-6 | Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.baidu_qianfan_endpoint.QianfanChatEndpoint.html |
c38314461eee-7 | API.
Use this method when you want to:
take advantage of batched calls,
need more output from the model than just the top generated value,
are building chains that are agnostic to the underlying language modeltype (e.g., pure text completion models vs chat models).
Parameters
prompts – List of PromptValues. A PromptVal... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.baidu_qianfan_endpoint.QianfanChatEndpoint.html |
c38314461eee-8 | get_num_tokens(text: str) → int¶
Get the number of tokens present in the text.
Useful for checking if an input will fit in a model’s context window.
Parameters
text – The string input to tokenize.
Returns
The integer number of tokens in the text.
get_num_tokens_from_messages(messages: List[BaseMessage]) → int¶
Get the ... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.baidu_qianfan_endpoint.QianfanChatEndpoint.html |
c38314461eee-9 | config – A config to use when invoking the runnable.
The config supports standard keys like ‘tags’, ‘metadata’ for tracing
purposes, ‘max_concurrency’ for controlling how much work to do
in parallel, and other keys. Please refer to the RunnableConfig
for more details.
Returns
The output of the runnable.
classmethod is_... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.baidu_qianfan_endpoint.QianfanChatEndpoint.html |
c38314461eee-10 | classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
predict(text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → str¶
Pass a single string input to t... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.baidu_qianfan_endpoint.QianfanChatEndpoint.html |
c38314461eee-11 | stream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → Iterator[BaseMessageChunk]¶
Default implementation of stream, which calls invoke.
Subclasses should override this method if they support streaming output.
to_json() → ... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.baidu_qianfan_endpoint.QianfanChatEndpoint.html |
c38314461eee-12 | fallback in order, upon failures.
with_listeners(*, on_start: Optional[Listener] = None, on_end: Optional[Listener] = None, on_error: Optional[Listener] = None) → Runnable[Input, Output]¶
Bind lifecycle listeners to a Runnable, returning a new Runnable.
on_start: Called before the runnable starts running, with the Run ... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.baidu_qianfan_endpoint.QianfanChatEndpoint.html |
c38314461eee-13 | List configurable fields for this runnable.
property input_schema: Type[pydantic.main.BaseModel]¶
The type of input this runnable accepts specified as a pydantic model.
property lc_attributes: Dict¶
List of attribute names that should be included in the serialized kwargs.
These attributes must be accepted by the constr... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.baidu_qianfan_endpoint.QianfanChatEndpoint.html |
ba0a3c536927-0 | langchain.chat_models.cohere.ChatCohere¶
class langchain.chat_models.cohere.ChatCohere[source]¶
Bases: BaseChatModel, BaseCohere
Cohere chat large language models.
To use, you should have the cohere python package installed, and the
environment variable COHERE_API_KEY set with your API key, or pass
it as a named parame... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.cohere.ChatCohere.html |
ba0a3c536927-1 | param verbose: bool [Optional]¶
Whether to print out response text.
__call__(messages: List[BaseMessage], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, **kwargs: Any) → BaseMessage¶
Call self as a function.
async abatch(inputs: List[Input], config: ... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.cohere.ChatCohere.html |
ba0a3c536927-2 | need more output from the model than just the top generated value,
are building chains that are agnostic to the underlying language modeltype (e.g., pure text completion models vs chat models).
Parameters
prompts – List of PromptValues. A PromptValue is an object that can be
converted to match the format of any languag... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.cohere.ChatCohere.html |
ba0a3c536927-3 | **kwargs – Arbitrary additional keyword arguments. These are usually passed
to the model provider API call.
Returns
Top model prediction as a string.
async apredict_messages(messages: List[BaseMessage], *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → BaseMessage¶
Asynchronously pass messages to the model and ... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.cohere.ChatCohere.html |
ba0a3c536927-4 | This includes all inner runs of LLMs, Retrievers, Tools, etc.
Output is streamed as Log objects, which include a list of
jsonpatch ops that describe how the state of the run has changed in each
step, and the final state of the run.
The jsonpatch ops can be applied in order to construct state.
async atransform(input: As... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.cohere.ChatCohere.html |
ba0a3c536927-5 | Returns
A pydantic model that can be used to validate config.
configurable_alternatives(which: ConfigurableField, default_key: str = 'default', **kwargs: Union[Runnable[Input, Output], Callable[[], Runnable[Input, Output]]]) → RunnableSerializable[Input, Output]¶
configurable_fields(**kwargs: Union[ConfigurableField, C... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.cohere.ChatCohere.html |
ba0a3c536927-6 | classmethod from_orm(obj: Any) → Model¶
generate(messages: List[List[BaseMessage]], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, run_name: Optional[str] = None, **kwarg... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.cohere.ChatCohere.html |
ba0a3c536927-7 | Get a pydantic model that can be used to validate input to the runnable.
Runnables that leverage the configurable_fields and configurable_alternatives
methods will have a dynamic input schema that depends on which
configuration the runnable is invoked with.
This method allows to get an input schema for a specific confi... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.cohere.ChatCohere.html |
ba0a3c536927-8 | Parameters
text – The string input to tokenize.
Returns
A list of ids corresponding to the tokens in the text, in order they occurin the text.
invoke(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → BaseMessage¶
Transform a... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.cohere.ChatCohere.html |
ba0a3c536927-9 | to the object.
map() → Runnable[List[Input], List[Output]]¶
Return a new Runnable that maps a list of inputs to a list of outputs,
by calling invoke() with each input.
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool =... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.cohere.ChatCohere.html |
ba0a3c536927-10 | first occurrence of any of these substrings.
**kwargs – Arbitrary additional keyword arguments. These are usually passed
to the model provider API call.
Returns
Top model prediction as a message.
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.cohere.ChatCohere.html |
ba0a3c536927-11 | Add fallbacks to a runnable, returning a new Runnable.
Parameters
fallbacks – A sequence of runnables to try if the original runnable fails.
exceptions_to_handle – A tuple of exception types to handle.
Returns
A new Runnable that will try the original runnable, and then each
fallback in order, upon failures.
with_liste... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.cohere.ChatCohere.html |
ba0a3c536927-12 | Bind input and output types to a Runnable, returning a new Runnable.
property InputType: TypeAlias¶
Get the input type for this runnable.
property OutputType: Any¶
Get the output type for this runnable.
property config_specs: List[langchain.schema.runnable.utils.ConfigurableFieldSpec]¶
List configurable fields for this... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.cohere.ChatCohere.html |
32fbee5e9608-0 | langchain.chat_models.fireworks.convert_dict_to_message¶
langchain.chat_models.fireworks.convert_dict_to_message(_dict: Any) → BaseMessage[source]¶
Convert a dict response to a message. | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fireworks.convert_dict_to_message.html |
f871d18d01c3-0 | langchain.chat_models.tongyi.ChatTongyi¶
class langchain.chat_models.tongyi.ChatTongyi[source]¶
Bases: BaseChatModel
Alibaba Tongyi Qwen chat models API.
To use, you should have the dashscope python package installed,
and set env DASHSCOPE_API_KEY with your API key, or pass
it as a named parameter to the constructor.
E... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.tongyi.ChatTongyi.html |
f871d18d01c3-1 | param tags: Optional[List[str]] = None¶
Tags to add to the run trace.
param top_p: float = 0.8¶
Total probability mass of tokens to consider at each step.
param verbose: bool [Optional]¶
Whether to print out response text.
__call__(messages: List[BaseMessage], stop: Optional[List[str]] = None, callbacks: Optional[Union... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.tongyi.ChatTongyi.html |
f871d18d01c3-2 | API.
Use this method when you want to:
take advantage of batched calls,
need more output from the model than just the top generated value,
are building chains that are agnostic to the underlying language modeltype (e.g., pure text completion models vs chat models).
Parameters
prompts – List of PromptValues. A PromptVal... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.tongyi.ChatTongyi.html |
f871d18d01c3-3 | stop – Stop words to use when generating. Model output is cut off at the
first occurrence of any of these substrings.
**kwargs – Arbitrary additional keyword arguments. These are usually passed
to the model provider API call.
Returns
Top model prediction as a string.
async apredict_messages(messages: List[BaseMessage],... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.tongyi.ChatTongyi.html |
f871d18d01c3-4 | Stream all output from a runnable, as reported to the callback system.
This includes all inner runs of LLMs, Retrievers, Tools, etc.
Output is streamed as Log objects, which include a list of
jsonpatch ops that describe how the state of the run has changed in each
step, and the final state of the run.
The jsonpatch ops... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.tongyi.ChatTongyi.html |
f871d18d01c3-5 | The type of config this runnable accepts specified as a pydantic model.
To mark a field as configurable, see the configurable_fields
and configurable_alternatives methods.
Parameters
include – A list of fields to include in the config schema.
Returns
A pydantic model that can be used to validate config.
configurable_al... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.tongyi.ChatTongyi.html |
f871d18d01c3-6 | Returns
new model instance
dict(**kwargs: Any) → Dict¶
Return a dictionary of the LLM.
classmethod from_orm(obj: Any) → Model¶
generate(messages: List[List[BaseMessage]], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = N... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.tongyi.ChatTongyi.html |
f871d18d01c3-7 | to the model provider API call.
Returns
An LLMResult, which contains a list of candidate Generations for each inputprompt and additional model provider-specific output.
get_input_schema(config: Optional[RunnableConfig] = None) → Type[BaseModel]¶
Get a pydantic model that can be used to validate input to the runnable.
R... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.tongyi.ChatTongyi.html |
f871d18d01c3-8 | Runnables that leverage the configurable_fields and configurable_alternatives
methods will have a dynamic output schema that depends on which
configuration the runnable is invoked with.
This method allows to get an output schema for a specific configuration.
Parameters
config – A config to use when generating the schem... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.tongyi.ChatTongyi.html |
f871d18d01c3-9 | classmethod is_lc_serializable() → bool¶
Is this class serializable?
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defa... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.tongyi.ChatTongyi.html |
f871d18d01c3-10 | Pass a single string input to the model and return a string prediction.
Use this method when passing in raw text. If you want to pass in specifictypes of chat messages, use predict_messages.
Parameters
text – String input to pass to the model.
stop – Stop words to use when generating. Model output is cut off at the
fir... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.tongyi.ChatTongyi.html |
f871d18d01c3-11 | Subclasses should override this method if they support streaming output.
stream_completion_with_retry(run_manager: Optional[CallbackManagerForLLMRun] = None, **kwargs: Any) → Any[source]¶
Use tenacity to retry the completion call.
to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶
to_json_not_implement... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.tongyi.ChatTongyi.html |
f871d18d01c3-12 | Bind lifecycle listeners to a Runnable, returning a new Runnable.
on_start: Called before the runnable starts running, with the Run object.
on_end: Called after the runnable finishes running, with the Run object.
on_error: Called if the runnable throws an error, with the Run object.
The Run object contains information ... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.tongyi.ChatTongyi.html |
f871d18d01c3-13 | List of attribute names that should be included in the serialized kwargs.
These attributes must be accepted by the constructor.
property lc_secrets: Dict[str, str]¶
A map of constructor argument names to secret ids.
For example,{“openai_api_key”: “OPENAI_API_KEY”}
property lc_serializable: bool¶
property output_schema:... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.tongyi.ChatTongyi.html |
27e062735ae5-0 | langchain.chat_models.anthropic.convert_messages_to_prompt_anthropic¶
langchain.chat_models.anthropic.convert_messages_to_prompt_anthropic(messages: List[BaseMessage], *, human_prompt: str = '\n\nHuman:', ai_prompt: str = '\n\nAssistant:') → str[source]¶
Format a list of messages into a full prompt for the Anthropic mo... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.anthropic.convert_messages_to_prompt_anthropic.html |
2b629bb98d29-0 | langchain.chat_models.fireworks.ChatFireworks¶
class langchain.chat_models.fireworks.ChatFireworks[source]¶
Bases: BaseChatModel
Fireworks Chat models.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param c... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fireworks.ChatFireworks.html |
2b629bb98d29-1 | Default implementation runs ainvoke in parallel using asyncio.gather.
The default implementation of batch works well for IO bound runnables.
Subclasses should override this method if they can batch more efficiently;
e.g., if the underlying runnable uses an API which supports a batch mode.
async agenerate(messages: List... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fireworks.ChatFireworks.html |
2b629bb98d29-2 | **kwargs – Arbitrary additional keyword arguments. These are usually passed
to the model provider API call.
Returns
An LLMResult, which contains a list of candidate Generations for each inputprompt and additional model provider-specific output.
async ainvoke(input: Union[PromptValue, str, List[BaseMessage]], config: Op... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fireworks.ChatFireworks.html |
2b629bb98d29-3 | **kwargs – Arbitrary additional keyword arguments. These are usually passed
to the model provider API call.
Returns
Top model prediction as a message.
async astream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → AsyncIter... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fireworks.ChatFireworks.html |
2b629bb98d29-4 | input is still being generated.
batch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Optional[Any]) → List[Output]¶
Default implementation runs invoke in parallel using a thread pool executor.
The default implementation of batch w... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fireworks.ChatFireworks.html |
2b629bb98d29-5 | Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fireworks.ChatFireworks.html |
2b629bb98d29-6 | API.
Use this method when you want to:
take advantage of batched calls,
need more output from the model than just the top generated value,
are building chains that are agnostic to the underlying language modeltype (e.g., pure text completion models vs chat models).
Parameters
prompts – List of PromptValues. A PromptVal... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fireworks.ChatFireworks.html |
2b629bb98d29-7 | get_num_tokens(text: str) → int¶
Get the number of tokens present in the text.
Useful for checking if an input will fit in a model’s context window.
Parameters
text – The string input to tokenize.
Returns
The integer number of tokens in the text.
get_num_tokens_from_messages(messages: List[BaseMessage]) → int¶
Get the ... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fireworks.ChatFireworks.html |
2b629bb98d29-8 | config – A config to use when invoking the runnable.
The config supports standard keys like ‘tags’, ‘metadata’ for tracing
purposes, ‘max_concurrency’ for controlling how much work to do
in parallel, and other keys. Please refer to the RunnableConfig
for more details.
Returns
The output of the runnable.
classmethod is_... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fireworks.ChatFireworks.html |
2b629bb98d29-9 | classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
predict(text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → str¶
Pass a single string input to t... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fireworks.ChatFireworks.html |
2b629bb98d29-10 | stream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → Iterator[BaseMessageChunk]¶
Default implementation of stream, which calls invoke.
Subclasses should override this method if they support streaming output.
to_json() → ... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fireworks.ChatFireworks.html |
2b629bb98d29-11 | fallback in order, upon failures.
with_listeners(*, on_start: Optional[Listener] = None, on_end: Optional[Listener] = None, on_error: Optional[Listener] = None) → Runnable[Input, Output]¶
Bind lifecycle listeners to a Runnable, returning a new Runnable.
on_start: Called before the runnable starts running, with the Run ... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fireworks.ChatFireworks.html |
2b629bb98d29-12 | List configurable fields for this runnable.
property input_schema: Type[pydantic.main.BaseModel]¶
The type of input this runnable accepts specified as a pydantic model.
property lc_attributes: Dict¶
List of attribute names that should be included in the serialized kwargs.
These attributes must be accepted by the constr... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fireworks.ChatFireworks.html |
a6834ad372fe-0 | langchain.chat_models.base.BaseChatModel¶
class langchain.chat_models.base.BaseChatModel[source]¶
Bases: BaseLanguageModel[BaseMessage], ABC
Base class for Chat models.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a val... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.BaseChatModel.html |
a6834ad372fe-1 | e.g., if the underlying runnable uses an API which supports a batch mode.
async agenerate(messages: List[List[BaseMessage]], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.BaseChatModel.html |
a6834ad372fe-2 | async ainvoke(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → BaseMessage[source]¶
Default implementation of ainvoke, calls invoke from a thread.
The default implementation allows usage of async code even if
the runnable d... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.BaseChatModel.html |
a6834ad372fe-3 | to the model provider API call.
Returns
Top model prediction as a message.
async astream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → AsyncIterator[BaseMessageChunk][source]¶
Default implementation of astream, which cal... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.BaseChatModel.html |
a6834ad372fe-4 | input is still being generated.
batch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Optional[Any]) → List[Output]¶
Default implementation runs invoke in parallel using a thread pool executor.
The default implementation of batch w... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.BaseChatModel.html |
a6834ad372fe-5 | Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.BaseChatModel.html |
a6834ad372fe-6 | API.
Use this method when you want to:
take advantage of batched calls,
need more output from the model than just the top generated value,
are building chains that are agnostic to the underlying language modeltype (e.g., pure text completion models vs chat models).
Parameters
prompts – List of PromptValues. A PromptVal... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.BaseChatModel.html |
a6834ad372fe-7 | get_num_tokens(text: str) → int¶
Get the number of tokens present in the text.
Useful for checking if an input will fit in a model’s context window.
Parameters
text – The string input to tokenize.
Returns
The integer number of tokens in the text.
get_num_tokens_from_messages(messages: List[BaseMessage]) → int¶
Get the ... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.BaseChatModel.html |
a6834ad372fe-8 | config – A config to use when invoking the runnable.
The config supports standard keys like ‘tags’, ‘metadata’ for tracing
purposes, ‘max_concurrency’ for controlling how much work to do
in parallel, and other keys. Please refer to the RunnableConfig
for more details.
Returns
The output of the runnable.
classmethod is_... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.BaseChatModel.html |
a6834ad372fe-9 | classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
predict(text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → str[source]¶
Pass a single string in... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.BaseChatModel.html |
a6834ad372fe-10 | stream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → Iterator[BaseMessageChunk][source]¶
Default implementation of stream, which calls invoke.
Subclasses should override this method if they support streaming output.
to_j... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.BaseChatModel.html |
a6834ad372fe-11 | fallback in order, upon failures.
with_listeners(*, on_start: Optional[Listener] = None, on_end: Optional[Listener] = None, on_error: Optional[Listener] = None) → Runnable[Input, Output]¶
Bind lifecycle listeners to a Runnable, returning a new Runnable.
on_start: Called before the runnable starts running, with the Run ... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.BaseChatModel.html |
a6834ad372fe-12 | List configurable fields for this runnable.
property input_schema: Type[pydantic.main.BaseModel]¶
The type of input this runnable accepts specified as a pydantic model.
property lc_attributes: Dict¶
List of attribute names that should be included in the serialized kwargs.
These attributes must be accepted by the constr... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.BaseChatModel.html |
655a72473bb7-0 | langchain.chat_models.openai.ChatOpenAI¶
class langchain.chat_models.openai.ChatOpenAI[source]¶
Bases: BaseChatModel
OpenAI Chat large language models API.
To use, you should have the openai python package installed, and the
environment variable OPENAI_API_KEY set with your API key.
Any parameters that are valid to be ... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.openai.ChatOpenAI.html |
655a72473bb7-1 | Model name to use.
param n: int = 1¶
Number of chat completions to generate for each prompt.
param openai_api_base: Optional[str] = None (alias 'base_url')¶
Base URL path for API requests, leave blank if not using a proxy or service
emulator.
param openai_api_key: Optional[str] = None (alias 'api_key')¶
Automatically i... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.openai.ChatOpenAI.html |
655a72473bb7-2 | API but with different models. In those cases, in order to avoid erroring
when tiktoken is called, you can specify a model name to use here.
param verbose: bool [Optional]¶
Whether to print out response text.
__call__(messages: List[BaseMessage], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCall... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.openai.ChatOpenAI.html |
655a72473bb7-3 | API.
Use this method when you want to:
take advantage of batched calls,
need more output from the model than just the top generated value,
are building chains that are agnostic to the underlying language modeltype (e.g., pure text completion models vs chat models).
Parameters
prompts – List of PromptValues. A PromptVal... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.openai.ChatOpenAI.html |
655a72473bb7-4 | stop – Stop words to use when generating. Model output is cut off at the
first occurrence of any of these substrings.
**kwargs – Arbitrary additional keyword arguments. These are usually passed
to the model provider API call.
Returns
Top model prediction as a string.
async apredict_messages(messages: List[BaseMessage],... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.openai.ChatOpenAI.html |
655a72473bb7-5 | Stream all output from a runnable, as reported to the callback system.
This includes all inner runs of LLMs, Retrievers, Tools, etc.
Output is streamed as Log objects, which include a list of
jsonpatch ops that describe how the state of the run has changed in each
step, and the final state of the run.
The jsonpatch ops... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.openai.ChatOpenAI.html |
655a72473bb7-6 | Can be a dictionary, pydantic model, or callable. Pydantic
models and callables will be automatically converted to
their schema dictionary representation.
function_call – Which function to require the model to call.
Must be the name of the single provided function or
“auto” to automatically determine which function to... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.openai.ChatOpenAI.html |
655a72473bb7-7 | Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.openai.ChatOpenAI.html |
655a72473bb7-8 | API.
Use this method when you want to:
take advantage of batched calls,
need more output from the model than just the top generated value,
are building chains that are agnostic to the underlying language modeltype (e.g., pure text completion models vs chat models).
Parameters
prompts – List of PromptValues. A PromptVal... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.openai.ChatOpenAI.html |
655a72473bb7-9 | get_num_tokens(text: str) → int¶
Get the number of tokens present in the text.
Useful for checking if an input will fit in a model’s context window.
Parameters
text – The string input to tokenize.
Returns
The integer number of tokens in the text.
get_num_tokens_from_messages(messages: List[BaseMessage]) → int[source]¶
... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.openai.ChatOpenAI.html |
655a72473bb7-10 | purposes, ‘max_concurrency’ for controlling how much work to do
in parallel, and other keys. Please refer to the RunnableConfig
for more details.
Returns
The output of the runnable.
classmethod is_lc_serializable() → bool[source]¶
Return whether this model can be serialized by Langchain.
json(*, include: Optional[Union... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.openai.ChatOpenAI.html |
655a72473bb7-11 | predict(text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → str¶
Pass a single string input to the model and return a string prediction.
Use this method when passing in raw text. If you want to pass in specifictypes of chat messages, use predict_messages.
Parameters
text – String input to pass to the m... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.openai.ChatOpenAI.html |
655a72473bb7-12 | Default implementation of stream, which calls invoke.
Subclasses should override this method if they support streaming output.
to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶
to_json_not_implemented() → SerializedNotImplemented¶
transform(input: Iterator[Input], config: Optional[RunnableConfig] = No... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.openai.ChatOpenAI.html |
655a72473bb7-13 | on_start: Called before the runnable starts running, with the Run object.
on_end: Called after the runnable finishes running, with the Run object.
on_error: Called if the runnable throws an error, with the Run object.
The Run object contains information about the run, including its id,
type, input, output, error, start... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.openai.ChatOpenAI.html |
655a72473bb7-14 | List of attribute names that should be included in the serialized kwargs.
These attributes must be accepted by the constructor.
property lc_secrets: Dict[str, str]¶
A map of constructor argument names to secret ids.
For example,{“openai_api_key”: “OPENAI_API_KEY”}
property output_schema: Type[pydantic.main.BaseModel]¶
... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.openai.ChatOpenAI.html |
655a72473bb7-15 | Use LangChain, GPT and Activeloop’s Deep Lake to work with code base
Structure answers with OpenAI functions
QA using Activeloop’s DeepLake
Neptune Open Cypher QA Chain
NebulaGraphQAChain
Memgraph QA chain
KuzuQAChain
HugeGraph QA Chain
GraphSparqlQAChain
Diffbot Graph Transformer
ArangoDB QA chain
Neo4j DB QA chain
Fa... | lang/api.python.langchain.com/en/latest/chat_models/langchain.chat_models.openai.ChatOpenAI.html |
7e6a7dcc4d8f-0 | langchain_experimental.chat_models.llm_wrapper.Llama2Chat¶
class langchain_experimental.chat_models.llm_wrapper.Llama2Chat[source]¶
Bases: ChatWrapper
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param ai... | lang/api.python.langchain.com/en/latest/chat_models/langchain_experimental.chat_models.llm_wrapper.Llama2Chat.html |
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