id stringlengths 14 15 | text stringlengths 44 2.47k | source stringlengths 61 181 |
|---|---|---|
b8bbb36efad6-1 | """Return history buffer."""
input_key = self._get_prompt_input_key(inputs)
query = inputs[input_key]
docs = self.retriever.get_relevant_documents(query)
result: Union[List[Document], str]
if not self.return_docs:
result = "\n".join([doc.page_content for doc in docs])... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/vectorstore.html |
b9c9ea6ce6f4-0 | Source code for langchain.memory.summary_buffer
from typing import Any, Dict, List
from langchain.memory.chat_memory import BaseChatMemory
from langchain.memory.summary import SummarizerMixin
from langchain.pydantic_v1 import root_validator
from langchain.schema.messages import BaseMessage, get_buffer_string
[docs]clas... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/summary_buffer.html |
b9c9ea6ce6f4-1 | if expected_keys != set(prompt_variables):
raise ValueError(
"Got unexpected prompt input variables. The prompt expects "
f"{prompt_variables}, but it should have {expected_keys}."
)
return values
[docs] def save_context(self, inputs: Dict[str, Any], ou... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/summary_buffer.html |
78b0f8e4d17b-0 | Source code for langchain.memory.zep_memory
from __future__ import annotations
from typing import Any, Dict, Optional
from langchain.memory import ConversationBufferMemory
from langchain.memory.chat_message_histories import ZepChatMessageHistory
[docs]class ZepMemory(ConversationBufferMemory):
"""Persist your chain... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/zep_memory.html |
78b0f8e4d17b-1 | https://docs.getzep.com/deployment/quickstart/
For more information on the zep-python package, see:
https://github.com/getzep/zep-python
"""
chat_memory: ZepChatMessageHistory
def __init__(
self,
session_id: str,
url: str = "http://localhost:8000",
api_key: Optional[s... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/zep_memory.html |
78b0f8e4d17b-2 | Defaults to "history".
Ensure that this matches the key used in
chain's prompt template.
"""
chat_message_history = ZepChatMessageHistory(
session_id=session_id,
url=url,
api_key=api_key,
... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/zep_memory.html |
623a9a456fb3-0 | Source code for langchain.memory.chat_memory
from abc import ABC
from typing import Any, Dict, Optional, Tuple
from langchain.memory.chat_message_histories.in_memory import ChatMessageHistory
from langchain.memory.utils import get_prompt_input_key
from langchain.pydantic_v1 import Field
from langchain.schema import Bas... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_memory.html |
87662a4dfbb2-0 | Source code for langchain.memory.combined
import warnings
from typing import Any, Dict, List, Set
from langchain.memory.chat_memory import BaseChatMemory
from langchain.pydantic_v1 import validator
from langchain.schema import BaseMemory
[docs]class CombinedMemory(BaseMemory):
"""Combining multiple memories' data t... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/combined.html |
87662a4dfbb2-1 | for memory in self.memories:
memory_variables.extend(memory.memory_variables)
return memory_variables
[docs] def load_memory_variables(self, inputs: Dict[str, Any]) -> Dict[str, str]:
"""Load all vars from sub-memories."""
memory_data: Dict[str, Any] = {}
# Collect vars fr... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/combined.html |
b9afd16718e6-0 | Source code for langchain.memory.buffer
from typing import Any, Dict, List, Optional
from langchain.memory.chat_memory import BaseChatMemory, BaseMemory
from langchain.memory.utils import get_prompt_input_key
from langchain.pydantic_v1 import root_validator
from langchain.schema.messages import BaseMessage, get_buffer_... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/buffer.html |
b9afd16718e6-1 | human_prefix: str = "Human"
ai_prefix: str = "AI"
"""Prefix to use for AI generated responses."""
buffer: str = ""
output_key: Optional[str] = None
input_key: Optional[str] = None
memory_key: str = "history" #: :meta private:
@root_validator()
def validate_chains(cls, values: Dict) -> D... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/buffer.html |
b9afd16718e6-2 | ai = f"{self.ai_prefix}: " + outputs[output_key]
self.buffer += "\n" + "\n".join([human, ai])
[docs] def clear(self) -> None:
"""Clear memory contents."""
self.buffer = "" | https://api.python.langchain.com/en/latest/_modules/langchain/memory/buffer.html |
0a57a17d2f5c-0 | Source code for langchain.memory.token_buffer
from typing import Any, Dict, List
from langchain.memory.chat_memory import BaseChatMemory
from langchain.schema.language_model import BaseLanguageModel
from langchain.schema.messages import BaseMessage, get_buffer_string
[docs]class ConversationTokenBufferMemory(BaseChatMe... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/token_buffer.html |
0a57a17d2f5c-1 | """Save context from this conversation to buffer. Pruned."""
super().save_context(inputs, outputs)
# Prune buffer if it exceeds max token limit
buffer = self.chat_memory.messages
curr_buffer_length = self.llm.get_num_tokens_from_messages(buffer)
if curr_buffer_length > self.max_t... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/token_buffer.html |
d2166fe3b8b1-0 | Source code for langchain.memory.motorhead_memory
from typing import Any, Dict, List, Optional
import requests
from langchain.memory.chat_memory import BaseChatMemory
from langchain.schema.messages import get_buffer_string
MANAGED_URL = "https://api.getmetal.io/v1/motorhead"
# LOCAL_URL = "http://localhost:8080"
[docs]... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/motorhead_memory.html |
d2166fe3b8b1-1 | res_data = res_data.get("data", res_data) # Handle Managed Version
messages = res_data.get("messages", [])
context = res_data.get("context", "NONE")
for message in reversed(messages):
if message["role"] == "AI":
self.chat_memory.add_ai_message(message["content"])
... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/motorhead_memory.html |
5a798d71ec0e-0 | Source code for langchain.memory.entity
import logging
from abc import ABC, abstractmethod
from itertools import islice
from typing import Any, Dict, Iterable, List, Optional
from langchain.chains.llm import LLMChain
from langchain.memory.chat_memory import BaseChatMemory
from langchain.memory.prompt import (
ENTIT... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/entity.html |
5a798d71ec0e-1 | """In-memory Entity store."""
store: Dict[str, Optional[str]] = {}
[docs] def get(self, key: str, default: Optional[str] = None) -> Optional[str]:
return self.store.get(key, default)
[docs] def set(self, key: str, value: Optional[str]) -> None:
self.store[key] = value
[docs] def delete(self... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/entity.html |
5a798d71ec0e-2 | raise ImportError(
"Could not import redis python package. "
"Please install it with `pip install redis`."
)
super().__init__(*args, **kwargs)
try:
self.redis_client = get_client(redis_url=url, decode_responses=True)
except redis.exceptions... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/entity.html |
5a798d71ec0e-3 | [docs] def clear(self) -> None:
# iterate a list in batches of size batch_size
def batched(iterable: Iterable[Any], batch_size: int) -> Iterable[Any]:
iterator = iter(iterable)
while batch := list(islice(iterator, batch_size)):
yield batch
for keybatch ... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/entity.html |
5a798d71ec0e-4 | value TEXT
)
"""
with self.conn:
self.conn.execute(create_table_query)
[docs] def get(self, key: str, default: Optional[str] = None) -> Optional[str]:
query = f"""
SELECT value
FROM {self.full_table_name}
WHERE key = ?
"""
... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/entity.html |
5a798d71ec0e-5 | self.conn.execute(query)
[docs]class ConversationEntityMemory(BaseChatMemory):
"""Entity extractor & summarizer memory.
Extracts named entities from the recent chat history and generates summaries.
With a swappable entity store, persisting entities across conversations.
Defaults to an in-memory entity s... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/entity.html |
5a798d71ec0e-6 | New entity name can be found when calling this method, before the entity
summaries are generated, so the entity cache values may be empty if no entity
descriptions are generated yet.
"""
# Create an LLMChain for predicting entity names from the recent chat history:
chain = LLMCha... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/entity.html |
5a798d71ec0e-7 | self.entity_cache = entities
# Should we return as message objects or as a string?
if self.return_messages:
# Get last `k` pair of chat messages:
buffer: Any = self.buffer[-self.k * 2 :]
else:
# Reuse the string we made earlier:
buffer = buffer_str... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/entity.html |
5a798d71ec0e-8 | existing_summary = self.entity_store.get(entity, "")
output = chain.predict(
summary=existing_summary,
entity=entity,
history=buffer_string,
input=input_data,
)
# Save the updated summary to the entity store
... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/entity.html |
ce8276672557-0 | Source code for langchain.memory.readonly
from typing import Any, Dict, List
from langchain.schema import BaseMemory
[docs]class ReadOnlySharedMemory(BaseMemory):
"""A memory wrapper that is read-only and cannot be changed."""
memory: BaseMemory
@property
def memory_variables(self) -> List[str]:
... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/readonly.html |
08cd8cd34b60-0 | Source code for langchain.memory.chat_message_histories.cosmos_db
"""Azure CosmosDB Memory History."""
from __future__ import annotations
import logging
from types import TracebackType
from typing import TYPE_CHECKING, Any, List, Optional, Type
from langchain.schema import (
BaseChatMessageHistory,
)
from langchain... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/cosmos_db.html |
08cd8cd34b60-1 | :param credential: The credential to use to authenticate to Azure Cosmos DB.
:param connection_string: The connection string to use to authenticate.
:param ttl: The time to live (in seconds) to use for documents in the container.
:param cosmos_client_kwargs: Additional kwargs to pass to the Cosm... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/cosmos_db.html |
08cd8cd34b60-2 | """Prepare the CosmosDB client.
Use this function or the context manager to make sure your database is ready.
"""
try:
from azure.cosmos import ( # pylint: disable=import-outside-toplevel # noqa: E501
PartitionKey,
)
except ImportError as exc:
... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/cosmos_db.html |
08cd8cd34b60-3 | CosmosHttpResponseError,
)
except ImportError as exc:
raise ImportError(
"You must install the azure-cosmos package to use the CosmosDBChatMessageHistory." # noqa: E501
"Please install it with `pip install azure-cosmos`."
) from exc
tr... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/cosmos_db.html |
4a336a56d1f0-0 | Source code for langchain.memory.chat_message_histories.firestore
"""Firestore Chat Message History."""
from __future__ import annotations
import logging
from typing import TYPE_CHECKING, List, Optional
from langchain.schema import (
BaseChatMessageHistory,
)
from langchain.schema.messages import BaseMessage, messa... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/firestore.html |
4a336a56d1f0-1 | self._document: Optional[DocumentReference] = None
self.messages: List[BaseMessage] = []
self.firestore_client = firestore_client or _get_firestore_client()
self.prepare_firestore()
[docs] def prepare_firestore(self) -> None:
"""Prepare the Firestore client.
Use this function ... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/firestore.html |
0f309697e27c-0 | Source code for langchain.memory.chat_message_histories.dynamodb
from __future__ import annotations
import logging
from typing import TYPE_CHECKING, Dict, List, Optional
from langchain.schema import (
BaseChatMessageHistory,
)
from langchain.schema.messages import (
BaseMessage,
_message_to_dict,
messag... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/dynamodb.html |
0f309697e27c-1 | [docs] def __init__(
self,
table_name: str,
session_id: str,
endpoint_url: Optional[str] = None,
primary_key_name: str = "SessionId",
key: Optional[Dict[str, str]] = None,
boto3_session: Optional[Session] = None,
kms_key_id: Optional[str] = None,
):... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/dynamodb.html |
0f309697e27c-2 | attribute_actions={"History": CryptoAction.ENCRYPT_AND_SIGN},
)
aws_kms_cmp = AwsKmsCryptographicMaterialsProvider(key_id=kms_key_id)
self.table = EncryptedTable(
table=self.table,
materials_provider=aws_kms_cmp,
attribute_actions=actio... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/dynamodb.html |
0f309697e27c-3 | messages.append(_message)
try:
self.table.put_item(Item={**self.key, "History": messages})
except ClientError as err:
logger.error(err)
[docs] def clear(self) -> None:
"""Clear session memory from DynamoDB"""
try:
from botocore.exceptions import Cli... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/dynamodb.html |
dbc206458d68-0 | Source code for langchain.memory.chat_message_histories.xata
import json
from typing import List
from langchain.schema import (
BaseChatMessageHistory,
)
from langchain.schema.messages import BaseMessage, _message_to_dict, messages_from_dict
[docs]class XataChatMessageHistory(BaseChatMessageHistory):
"""Chat me... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/xata.html |
dbc206458d68-1 | if r.status_code > 299:
raise Exception(f"Error creating table in Xata: {r.status_code} {r}")
r = self._client.table().set_schema(
self._table_name,
payload={
"columns": [
{"name": "sessionId", "type": "string"},
{"name"... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/xata.html |
dbc206458d68-2 | self._table_name,
payload={
"filter": {
"sessionId": self._session_id,
},
"sort": {"xata.createdAt": "asc"},
},
)
if r.status_code != 200:
raise Exception(f"Error running query: {r.status_code} {r}")
... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/xata.html |
74ef6458997a-0 | Source code for langchain.memory.chat_message_histories.file
import json
import logging
from pathlib import Path
from typing import List
from langchain.schema import (
BaseChatMessageHistory,
)
from langchain.schema.messages import BaseMessage, messages_from_dict, messages_to_dict
logger = logging.getLogger(__name_... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/file.html |
951d47398325-0 | Source code for langchain.memory.chat_message_histories.momento
from __future__ import annotations
import json
from datetime import timedelta
from typing import TYPE_CHECKING, Any, Optional
from langchain.schema import (
BaseChatMessageHistory,
)
from langchain.schema.messages import BaseMessage, _message_to_dict, ... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/momento.html |
951d47398325-1 | Note: to instantiate the cache client passed to MomentoChatMessageHistory,
you must have a Momento account at https://gomomento.com/.
Args:
session_id (str): The session ID to use for this chat session.
cache_client (CacheClient): The Momento cache client.
cache_name ... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/momento.html |
951d47398325-2 | def from_client_params(
cls,
session_id: str,
cache_name: str,
ttl: timedelta,
*,
configuration: Optional[momento.config.Configuration] = None,
auth_token: Optional[str] = None,
**kwargs: Any,
) -> MomentoChatMessageHistory:
"""Construct cache ... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/momento.html |
951d47398325-3 | return []
elif isinstance(fetch_response, CacheListFetch.Error):
raise fetch_response.inner_exception
else:
raise Exception(f"Unexpected response: {fetch_response}")
[docs] def add_message(self, message: BaseMessage) -> None:
"""Store a message in the cache.
Ar... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/momento.html |
5abab1f958c2-0 | Source code for langchain.memory.chat_message_histories.in_memory
from typing import List
from langchain.pydantic_v1 import BaseModel, Field
from langchain.schema import (
BaseChatMessageHistory,
)
from langchain.schema.messages import BaseMessage
[docs]class ChatMessageHistory(BaseChatMessageHistory, BaseModel):
... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/in_memory.html |
271ec30800c9-0 | Source code for langchain.memory.chat_message_histories.cassandra
"""Cassandra-based chat message history, based on cassIO."""
from __future__ import annotations
import json
import typing
from typing import List
if typing.TYPE_CHECKING:
from cassandra.cluster import Session
from langchain.schema import (
BaseCh... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/cassandra.html |
271ec30800c9-1 | @property
def messages(self) -> List[BaseMessage]: # type: ignore
"""Retrieve all session messages from DB"""
message_blobs = self.blob_history.retrieve(
self.session_id,
)
items = [json.loads(message_blob) for message_blob in message_blobs]
messages = messages_f... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/cassandra.html |
76b6c52bcf5a-0 | Source code for langchain.memory.chat_message_histories.zep
from __future__ import annotations
import logging
from typing import TYPE_CHECKING, Any, Dict, List, Optional
from langchain.schema import (
BaseChatMessageHistory,
)
from langchain.schema.messages import (
AIMessage,
BaseMessage,
HumanMessage,... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/zep.html |
76b6c52bcf5a-1 | """
[docs] def __init__(
self,
session_id: str,
url: str = "http://localhost:8000",
api_key: Optional[str] = None,
) -> None:
try:
from zep_python import ZepClient
except ImportError:
raise ImportError(
"Could not import zep-... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/zep.html |
76b6c52bcf5a-2 | @property
def zep_messages(self) -> List[Message]:
"""Retrieve summary from Zep memory"""
zep_memory: Optional[Memory] = self._get_memory()
if not zep_memory:
return []
return zep_memory.messages
@property
def zep_summary(self) -> Optional[str]:
"""Retriev... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/zep.html |
76b6c52bcf5a-3 | Args:
message: The string contents of an AI message.
metadata: Optional metadata to attach to the message.
"""
self.add_message(AIMessage(content=message), metadata=metadata)
[docs] def add_message(
self, message: BaseMessage, metadata: Optional[Dict[str, Any]] = None
... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/zep.html |
4ebae76a1255-0 | Source code for langchain.memory.chat_message_histories.postgres
import json
import logging
from typing import List
from langchain.schema import (
BaseChatMessageHistory,
)
from langchain.schema.messages import BaseMessage, _message_to_dict, messages_from_dict
logger = logging.getLogger(__name__)
DEFAULT_CONNECTION... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/postgres.html |
4ebae76a1255-1 | items = [record["message"] for record in self.cursor.fetchall()]
messages = messages_from_dict(items)
return messages
[docs] def add_message(self, message: BaseMessage) -> None:
"""Append the message to the record in PostgreSQL"""
from psycopg import sql
query = sql.SQL("INSER... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/postgres.html |
d2b14a43c994-0 | Source code for langchain.memory.chat_message_histories.redis
import json
import logging
from typing import List, Optional
from langchain.schema import (
BaseChatMessageHistory,
)
from langchain.schema.messages import BaseMessage, _message_to_dict, messages_from_dict
from langchain.utilities.redis import get_client... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/redis.html |
d2b14a43c994-1 | [docs] def add_message(self, message: BaseMessage) -> None:
"""Append the message to the record in Redis"""
self.redis_client.lpush(self.key, json.dumps(_message_to_dict(message)))
if self.ttl:
self.redis_client.expire(self.key, self.ttl)
[docs] def clear(self) -> None:
... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/redis.html |
91fe2f6182a2-0 | Source code for langchain.memory.chat_message_histories.mongodb
import json
import logging
from typing import List
from langchain.schema import (
BaseChatMessageHistory,
)
from langchain.schema.messages import BaseMessage, _message_to_dict, messages_from_dict
logger = logging.getLogger(__name__)
DEFAULT_DBNAME = "c... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/mongodb.html |
91fe2f6182a2-1 | except errors.OperationFailure as error:
logger.error(error)
if cursor:
items = [json.loads(document["History"]) for document in cursor]
else:
items = []
messages = messages_from_dict(items)
return messages
[docs] def add_message(self, message: Base... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/mongodb.html |
335770302d75-0 | Source code for langchain.memory.chat_message_histories.rocksetdb
from datetime import datetime
from time import sleep
from typing import Any, Callable, List, Union
from uuid import uuid4
from langchain.schema import BaseChatMessageHistory
from langchain.schema.messages import BaseMessage, _message_to_dict, messages_fr... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/rocksetdb.html |
335770302d75-1 | if (curr - start).total_seconds() * 1000 > timeout:
raise TimeoutError(f"{method} timed out at {timeout} ms")
sleep(RocksetChatMessageHistory.SLEEP_INTERVAL_MS / 1000)
def _query(self, query: str, **query_params: Any) -> List[Any]:
"""Executes an SQL statement and returns the res... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/rocksetdb.html |
335770302d75-2 | """Sleeps until the collection for this message history is ready
to be queried
"""
self._wait_until(
lambda: self._collection_is_ready(),
RocksetChatMessageHistory.CREATE_TIMEOUT_MS,
)
def _wait_until_message_added(self, message_id: str) -> None:
"""Sl... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/rocksetdb.html |
335770302d75-3 | """Constructs a new RocksetChatMessageHistory.
Args:
- session_id: The ID of the chat session
- client: The RocksetClient object to use to query
- collection: The name of the collection to use to store chat
messages. If a collection with the given na... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/rocksetdb.html |
335770302d75-4 | self.location = f'"{self.workspace}"."{self.collection}"'
self.rockset = rockset
self.messages_key = messages_key
self.message_uuid_method = message_uuid_method
self.sync = sync
try:
self.client.set_application("langchain")
except AttributeError:
#... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/rocksetdb.html |
335770302d75-5 | value=_message_to_dict(message),
)
],
)
],
)
if self.sync:
self._wait_until_message_added(message.additional_kwargs["id"])
[docs] def clear(self) -> None:
"""Removes all messages from the chat history"""
... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/rocksetdb.html |
cd09fb6ff4bd-0 | Source code for langchain.memory.chat_message_histories.streamlit
from typing import List
from langchain.schema import (
BaseChatMessageHistory,
)
from langchain.schema.messages import BaseMessage
[docs]class StreamlitChatMessageHistory(BaseChatMessageHistory):
"""
Chat message history that stores messages ... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/streamlit.html |
9d499f2a21e3-0 | Source code for langchain.memory.chat_message_histories.sql
import json
import logging
from abc import ABC, abstractmethod
from typing import Any, List, Optional
from sqlalchemy import Column, Integer, Text, create_engine
try:
from sqlalchemy.orm import declarative_base
except ImportError:
from sqlalchemy.ext.d... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/sql.html |
9d499f2a21e3-1 | id = Column(Integer, primary_key=True)
session_id = Column(Text)
message = Column(Text)
return Message
[docs]class DefaultMessageConverter(BaseMessageConverter):
"""The default message converter for SQLChatMessageHistory."""
[docs] def __init__(self, table_name: str):
self.model_class... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/sql.html |
9d499f2a21e3-2 | self._create_table_if_not_exists()
self.session_id = session_id
self.Session = sessionmaker(self.engine)
def _create_table_if_not_exists(self) -> None:
self.sql_model_class.metadata.create_all(self.engine)
@property
def messages(self) -> List[BaseMessage]: # type: ignore
"""... | https://api.python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/sql.html |
25bb86821cd0-0 | Source code for langchain.chains.example_generator
from typing import List
from langchain.chains.llm import LLMChain
from langchain.prompts.few_shot import FewShotPromptTemplate
from langchain.prompts.prompt import PromptTemplate
from langchain.schema.language_model import BaseLanguageModel
TEST_GEN_TEMPLATE_SUFFIX = "... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/example_generator.html |
286330753705-0 | Source code for langchain.chains.sequential
"""Chain pipeline where the outputs of one step feed directly into next."""
from typing import Any, Dict, List, Optional
from langchain.callbacks.manager import (
AsyncCallbackManagerForChainRun,
CallbackManagerForChainRun,
)
from langchain.chains.base import Chain
fr... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/sequential.html |
286330753705-1 | overlapping_keys = set(input_variables) & set(memory_keys)
raise ValueError(
f"The the input key(s) {''.join(overlapping_keys)} are found "
f"in the Memory keys ({memory_keys}) - please use input and "
f"memory keys that don't overlap."
... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/sequential.html |
286330753705-2 | _run_manager = run_manager or CallbackManagerForChainRun.get_noop_manager()
for i, chain in enumerate(self.chains):
callbacks = _run_manager.get_child()
outputs = chain(known_values, return_only_outputs=True, callbacks=callbacks)
known_values.update(outputs)
return {k... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/sequential.html |
286330753705-3 | """Return output key.
:meta private:
"""
return [self.output_key]
@root_validator()
def validate_chains(cls, values: Dict) -> Dict:
"""Validate that chains are all single input/output."""
for chain in values["chains"]:
if len(chain.input_keys) != 1:
... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/sequential.html |
286330753705-4 | run_manager: Optional[AsyncCallbackManagerForChainRun] = None,
) -> Dict[str, Any]:
_run_manager = run_manager or AsyncCallbackManagerForChainRun.get_noop_manager()
_input = inputs[self.input_key]
color_mapping = get_color_mapping([str(i) for i in range(len(self.chains))])
for i, cha... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/sequential.html |
ffe7ddd31003-0 | Source code for langchain.chains.mapreduce
"""Map-reduce chain.
Splits up a document, sends the smaller parts to the LLM with one prompt,
then combines the results with another one.
"""
from __future__ import annotations
from typing import Any, Dict, List, Mapping, Optional
from langchain.callbacks.manager import Callb... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/mapreduce.html |
ffe7ddd31003-1 | **kwargs: Any,
) -> MapReduceChain:
"""Construct a map-reduce chain that uses the chain for map and reduce."""
llm_chain = LLMChain(llm=llm, prompt=prompt, callbacks=callbacks)
stuff_chain = StuffDocumentsChain(
llm_chain=llm_chain,
callbacks=callbacks,
**... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/mapreduce.html |
ffe7ddd31003-2 | # Split the larger text into smaller chunks.
doc_text = inputs.pop(self.input_key)
texts = self.text_splitter.split_text(doc_text)
docs = [Document(page_content=text) for text in texts]
_inputs: Dict[str, Any] = {
**inputs,
self.combine_documents_chain.input_key: ... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/mapreduce.html |
2f8b542e2393-0 | Source code for langchain.chains.transform
"""Chain that runs an arbitrary python function."""
import functools
import logging
from typing import Any, Awaitable, Callable, Dict, List, Optional
from langchain.callbacks.manager import (
AsyncCallbackManagerForChainRun,
CallbackManagerForChainRun,
)
from langchain... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/transform.html |
2f8b542e2393-1 | """Return output keys.
:meta private:
"""
return self.output_variables
def _call(
self,
inputs: Dict[str, str],
run_manager: Optional[CallbackManagerForChainRun] = None,
) -> Dict[str, str]:
return self.transform_cb(inputs)
async def _acall(
se... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/transform.html |
86aa1fb083c2-0 | Source code for langchain.chains.llm
"""Chain that just formats a prompt and calls an LLM."""
from __future__ import annotations
import warnings
from typing import Any, Dict, List, Optional, Sequence, Tuple, Union
from langchain.callbacks.manager import (
AsyncCallbackManager,
AsyncCallbackManagerForChainRun,
... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/llm.html |
86aa1fb083c2-1 | output_key: str = "text" #: :meta private:
output_parser: BaseLLMOutputParser = Field(default_factory=StrOutputParser)
"""Output parser to use.
Defaults to one that takes the most likely string but does not change it
otherwise."""
return_final_only: bool = True
"""Whether to return only the fi... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/llm.html |
86aa1fb083c2-2 | ) -> LLMResult:
"""Generate LLM result from inputs."""
prompts, stop = self.prep_prompts(input_list, run_manager=run_manager)
return self.llm.generate_prompt(
prompts,
stop,
callbacks=run_manager.get_child() if run_manager else None,
**self.llm_kwa... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/llm.html |
86aa1fb083c2-3 | _text = "Prompt after formatting:\n" + _colored_text
if run_manager:
run_manager.on_text(_text, end="\n", verbose=self.verbose)
if "stop" in inputs and inputs["stop"] != stop:
raise ValueError(
"If `stop` is present in any inputs, should be pre... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/llm.html |
86aa1fb083c2-4 | self, input_list: List[Dict[str, Any]], callbacks: Callbacks = None
) -> List[Dict[str, str]]:
"""Utilize the LLM generate method for speed gains."""
callback_manager = CallbackManager.configure(
callbacks, self.callbacks, self.verbose
)
run_manager = callback_manager.on_... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/llm.html |
86aa1fb083c2-5 | """Create outputs from response."""
result = [
# Get the text of the top generated string.
{
self.output_key: self.output_parser.parse_result(generation),
"full_generation": generation,
}
for generation in llm_result.generations
... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/llm.html |
86aa1fb083c2-6 | completion = llm.predict(adjective="funny")
"""
return (await self.acall(kwargs, callbacks=callbacks))[self.output_key]
[docs] def predict_and_parse(
self, callbacks: Callbacks = None, **kwargs: Any
) -> Union[str, List[str], Dict[str, Any]]:
"""Call predict and then parse the res... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/llm.html |
86aa1fb083c2-7 | "instead pass an output parser directly to LLMChain."
)
result = self.apply(input_list, callbacks=callbacks)
return self._parse_generation(result)
def _parse_generation(
self, generation: List[Dict[str, str]]
) -> Sequence[Union[str, List[str], Dict[str, str]]]:
if self.p... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/llm.html |
37232718fcd2-0 | Source code for langchain.chains.moderation
"""Pass input through a moderation endpoint."""
from typing import Any, Dict, List, Optional
from langchain.callbacks.manager import CallbackManagerForChainRun
from langchain.chains.base import Chain
from langchain.pydantic_v1 import root_validator
from langchain.utils import... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/moderation.html |
37232718fcd2-1 | values,
"openai_organization",
"OPENAI_ORGANIZATION",
default="",
)
try:
import openai
openai.api_key = openai_api_key
if openai_organization:
openai.organization = openai_organization
values["client"] = ... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/moderation.html |
0c3ea932b161-0 | Source code for langchain.chains.base
"""Base interface that all chains should implement."""
import asyncio
import inspect
import json
import logging
import warnings
from abc import ABC, abstractmethod
from functools import partial
from pathlib import Path
from typing import Any, Dict, List, Optional, Type, Union
impor... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/base.html |
0c3ea932b161-1 | Chains with other components, including other Chains.
The main methods exposed by chains are:
- `__call__`: Chains are callable. The `__call__` method is the primary way to
execute a Chain. This takes inputs as a dictionary and returns a
dictionary output.
- `run`: A convenie... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/base.html |
0c3ea932b161-2 | )
[docs] async def ainvoke(
self,
input: Dict[str, Any],
config: Optional[RunnableConfig] = None,
**kwargs: Any,
) -> Dict[str, Any]:
if type(self)._acall == Chain._acall:
# If the chain does not implement async, fall back to default implementation
... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/base.html |
0c3ea932b161-3 | verbose: bool = Field(default_factory=_get_verbosity)
"""Whether or not run in verbose mode. In verbose mode, some intermediate logs
will be printed to the console. Defaults to `langchain.verbose` value."""
tags: Optional[List[str]] = None
"""Optional list of tags associated with the chain. Defaults to ... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/base.html |
0c3ea932b161-4 | DeprecationWarning,
)
values["callbacks"] = values.pop("callback_manager", None)
return values
@validator("verbose", pre=True, always=True)
def set_verbose(cls, verbose: Optional[bool]) -> bool:
"""Set the chain verbosity.
Defaults to the global setting if not spe... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/base.html |
0c3ea932b161-5 | callbacks configuration and some input/output processing.
Args:
inputs: A dict of named inputs to the chain. Assumed to contain all inputs
specified in `Chain.input_keys`, including any inputs added by memory.
run_manager: The callbacks manager that contains the callback ... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/base.html |
0c3ea932b161-6 | include_run_info: bool = False,
) -> Dict[str, Any]:
"""Execute the chain.
Args:
inputs: Dictionary of inputs, or single input if chain expects
only one param. Should contain all inputs specified in
`Chain.input_keys` except for inputs that will be set by ... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/base.html |
0c3ea932b161-7 | name=run_name,
)
try:
outputs = (
self._call(inputs, run_manager=run_manager)
if new_arg_supported
else self._call(inputs)
)
except BaseException as e:
run_manager.on_chain_error(e)
raise e
ru... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/base.html |
0c3ea932b161-8 | addition to callbacks passed to the chain during construction, but only
these runtime callbacks will propagate to calls to other objects.
tags: List of string tags to pass to all callbacks. These will be passed in
addition to tags passed to the chain during construction, but ... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/base.html |
0c3ea932b161-9 | self,
inputs: Dict[str, str],
outputs: Dict[str, str],
return_only_outputs: bool = False,
) -> Dict[str, str]:
"""Validate and prepare chain outputs, and save info about this run to memory.
Args:
inputs: Dictionary of chain inputs, including any inputs added by ch... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/base.html |
0c3ea932b161-10 | _input_keys = _input_keys.difference(self.memory.memory_variables)
if len(_input_keys) != 1:
raise ValueError(
f"A single string input was passed in, but this chain expects "
f"multiple inputs ({_input_keys}). When a chain expects "
... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/base.html |
0c3ea932b161-11 | sole positional argument.
callbacks: Callbacks to use for this chain run. These will be called in
addition to callbacks passed to the chain during construction, but only
these runtime callbacks will propagate to calls to other objects.
tags: List of string tags to... | https://api.python.langchain.com/en/latest/_modules/langchain/chains/base.html |
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