langchain[patch]: Make more memory code handle community dependency as optional (#21199)

libs/langchain/langchain/memory/__init__.py

@@ -26,26 +26,9 @@
 
     AIMessage, BaseMessage, HumanMessage
 """  # noqa: E501
-from langchain_community.chat_message_histories import (
+from typing import TYPE_CHECKING, Any
-    AstraDBChatMessageHistory,
-    CassandraChatMessageHistory,
-    ChatMessageHistory,
-    CosmosDBChatMessageHistory,
-    DynamoDBChatMessageHistory,
-    ElasticsearchChatMessageHistory,
-    FileChatMessageHistory,
-    MomentoChatMessageHistory,
-    MongoDBChatMessageHistory,
-    PostgresChatMessageHistory,
-    RedisChatMessageHistory,
-    SingleStoreDBChatMessageHistory,
-    SQLChatMessageHistory,
-    StreamlitChatMessageHistory,
-    UpstashRedisChatMessageHistory,
-    XataChatMessageHistory,
-    ZepChatMessageHistory,
-)
 
+from langchain._api import create_importer
 from langchain.memory.buffer import (
     ConversationBufferMemory,
     ConversationStringBufferMemory,
@@ -59,15 +42,72 @@ from langchain.memory.entity import (
     SQLiteEntityStore,
     UpstashRedisEntityStore,
 )
-from langchain.memory.kg import ConversationKGMemory
-from langchain.memory.motorhead_memory import MotorheadMemory
 from langchain.memory.readonly import ReadOnlySharedMemory
 from langchain.memory.simple import SimpleMemory
 from langchain.memory.summary import ConversationSummaryMemory
 from langchain.memory.summary_buffer import ConversationSummaryBufferMemory
 from langchain.memory.token_buffer import ConversationTokenBufferMemory
 from langchain.memory.vectorstore import VectorStoreRetrieverMemory
-from langchain.memory.zep_memory import ZepMemory
+
+if TYPE_CHECKING:
+    from langchain_community.chat_message_histories import (
+        AstraDBChatMessageHistory,
+        CassandraChatMessageHistory,
+        ChatMessageHistory,
+        CosmosDBChatMessageHistory,
+        DynamoDBChatMessageHistory,
+        ElasticsearchChatMessageHistory,
+        FileChatMessageHistory,
+        MomentoChatMessageHistory,
+        MongoDBChatMessageHistory,
+        PostgresChatMessageHistory,
+        RedisChatMessageHistory,
+        SingleStoreDBChatMessageHistory,
+        SQLChatMessageHistory,
+        StreamlitChatMessageHistory,
+        UpstashRedisChatMessageHistory,
+        XataChatMessageHistory,
+        ZepChatMessageHistory,
+    )
+    from langchain_community.memory.kg import ConversationKGMemory
+    from langchain_community.memory.motorhead_memory import MotorheadMemory
+    from langchain_community.memory.zep_memory import ZepMemory
+
+
+# Create a way to dynamically look up deprecated imports.
+# Used to consolidate logic for raising deprecation warnings and
+# handling optional imports.
+DEPRECATED_LOOKUP = {
+    "MotorheadMemory": "langchain_community.memory.motorhead_memory",
+    "ConversationKGMemory": "langchain_community.memory.kg",
+    "ZepMemory": "langchain_community.memory.zep_memory",
+    "AstraDBChatMessageHistory": "langchain_community.chat_message_histories",
+    "CassandraChatMessageHistory": "langchain_community.chat_message_histories",
+    "ChatMessageHistory": "langchain_community.chat_message_histories",
+    "CosmosDBChatMessageHistory": "langchain_community.chat_message_histories",
+    "DynamoDBChatMessageHistory": "langchain_community.chat_message_histories",
+    "ElasticsearchChatMessageHistory": "langchain_community.chat_message_histories",
+    "FileChatMessageHistory": "langchain_community.chat_message_histories",
+    "MomentoChatMessageHistory": "langchain_community.chat_message_histories",
+    "MongoDBChatMessageHistory": "langchain_community.chat_message_histories",
+    "PostgresChatMessageHistory": "langchain_community.chat_message_histories",
+    "RedisChatMessageHistory": "langchain_community.chat_message_histories",
+    "SingleStoreDBChatMessageHistory": "langchain_community.chat_message_histories",
+    "SQLChatMessageHistory": "langchain_community.chat_message_histories",
+    "StreamlitChatMessageHistory": "langchain_community.chat_message_histories",
+    "UpstashRedisChatMessageHistory": "langchain_community.chat_message_histories",
+    "XataChatMessageHistory": "langchain_community.chat_message_histories",
+    "ZepChatMessageHistory": "langchain_community.chat_message_histories",
+}
+
+
+_import_attribute = create_importer(__package__, deprecated_lookups=DEPRECATED_LOOKUP)
+
+
+def __getattr__(name: str) -> Any:
+    """Look up attributes dynamically."""
+    return _import_attribute(name)
+
 
 __all__ = [
     "AstraDBChatMessageHistory",

libs/langchain/langchain/memory/entity.py

@@ -3,7 +3,6 @@ from abc import ABC, abstractmethod
 from itertools import islice
 from typing import Any, Dict, Iterable, List, Optional
 
-from langchain_community.utilities.redis import get_client
 from langchain_core.language_models import BaseLanguageModel
 from langchain_core.messages import BaseMessage, get_buffer_string
 from langchain_core.prompts import BasePromptTemplate
@@ -181,6 +180,14 @@ class RedisEntityStore(BaseEntityStore):
 
         super().__init__(*args, **kwargs)
 
+        try:
+            from langchain_community.utilities.redis import get_client
+        except ImportError:
+            raise ImportError(
+                "Could not import langchain_community.utilities.redis.get_client. "
+                "Please install it with `pip install langchain-community`."
+            )
+
         try:
             self.redis_client = get_client(redis_url=url, decode_responses=True)
         except redis.exceptions.ConnectionError as error:

libs/langchain/langchain/memory/kg.py

@@ -1,133 +1,23 @@
-from typing import Any, Dict, List, Type, Union
+from typing import TYPE_CHECKING, Any
 
-from langchain_community.graphs import NetworkxEntityGraph
+from langchain._api import create_importer
-from langchain_community.graphs.networkx_graph import (
-    KnowledgeTriple,
-    get_entities,
-    parse_triples,
-)
-from langchain_core.language_models import BaseLanguageModel
-from langchain_core.messages import BaseMessage, SystemMessage, get_buffer_string
-from langchain_core.prompts import BasePromptTemplate
-from langchain_core.pydantic_v1 import Field
 
-from langchain.chains.llm import LLMChain
+if TYPE_CHECKING:
-from langchain.memory.chat_memory import BaseChatMemory
+    from langchain_community.memory.kg import ConversationKGMemory
-from langchain.memory.prompt import (
+
-    ENTITY_EXTRACTION_PROMPT,
+# Create a way to dynamically look up deprecated imports.
-    KNOWLEDGE_TRIPLE_EXTRACTION_PROMPT,
+# Used to consolidate logic for raising deprecation warnings and
-)
+# handling optional imports.
-from langchain.memory.utils import get_prompt_input_key
+DEPRECATED_LOOKUP = {"ConversationKGMemory": "langchain_community.memory.kg"}
+
+_import_attribute = create_importer(__package__, deprecated_lookups=DEPRECATED_LOOKUP)
 
 
-class ConversationKGMemory(BaseChatMemory):
+def __getattr__(name: str) -> Any:
-    """Knowledge graph conversation memory.
+    """Look up attributes dynamically."""
+    return _import_attribute(name)
 
-    Integrates with external knowledge graph to store and retrieve
-    information about knowledge triples in the conversation.
-    """
 
-    k: int = 2
+__all__ = [
-    human_prefix: str = "Human"
+    "ConversationKGMemory",
-    ai_prefix: str = "AI"
+]
-    kg: NetworkxEntityGraph = Field(default_factory=NetworkxEntityGraph)
-    knowledge_extraction_prompt: BasePromptTemplate = KNOWLEDGE_TRIPLE_EXTRACTION_PROMPT
-    entity_extraction_prompt: BasePromptTemplate = ENTITY_EXTRACTION_PROMPT
-    llm: BaseLanguageModel
-    summary_message_cls: Type[BaseMessage] = SystemMessage
-    """Number of previous utterances to include in the context."""
-    memory_key: str = "history"  #: :meta private:
-
-    def load_memory_variables(self, inputs: Dict[str, Any]) -> Dict[str, Any]:
-        """Return history buffer."""
-        entities = self._get_current_entities(inputs)
-
-        summary_strings = []
-        for entity in entities:
-            knowledge = self.kg.get_entity_knowledge(entity)
-            if knowledge:
-                summary = f"On {entity}: {'. '.join(knowledge)}."
-                summary_strings.append(summary)
-        context: Union[str, List]
-        if not summary_strings:
-            context = [] if self.return_messages else ""
-        elif self.return_messages:
-            context = [
-                self.summary_message_cls(content=text) for text in summary_strings
-            ]
-        else:
-            context = "\n".join(summary_strings)
-
-        return {self.memory_key: context}
-
-    @property
-    def memory_variables(self) -> List[str]:
-        """Will always return list of memory variables.
-
-        :meta private:
-        """
-        return [self.memory_key]
-
-    def _get_prompt_input_key(self, inputs: Dict[str, Any]) -> str:
-        """Get the input key for the prompt."""
-        if self.input_key is None:
-            return get_prompt_input_key(inputs, self.memory_variables)
-        return self.input_key
-
-    def _get_prompt_output_key(self, outputs: Dict[str, Any]) -> str:
-        """Get the output key for the prompt."""
-        if self.output_key is None:
-            if len(outputs) != 1:
-                raise ValueError(f"One output key expected, got {outputs.keys()}")
-            return list(outputs.keys())[0]
-        return self.output_key
-
-    def get_current_entities(self, input_string: str) -> List[str]:
-        chain = LLMChain(llm=self.llm, prompt=self.entity_extraction_prompt)
-        buffer_string = get_buffer_string(
-            self.chat_memory.messages[-self.k * 2 :],
-            human_prefix=self.human_prefix,
-            ai_prefix=self.ai_prefix,
-        )
-        output = chain.predict(
-            history=buffer_string,
-            input=input_string,
-        )
-        return get_entities(output)
-
-    def _get_current_entities(self, inputs: Dict[str, Any]) -> List[str]:
-        """Get the current entities in the conversation."""
-        prompt_input_key = self._get_prompt_input_key(inputs)
-        return self.get_current_entities(inputs[prompt_input_key])
-
-    def get_knowledge_triplets(self, input_string: str) -> List[KnowledgeTriple]:
-        chain = LLMChain(llm=self.llm, prompt=self.knowledge_extraction_prompt)
-        buffer_string = get_buffer_string(
-            self.chat_memory.messages[-self.k * 2 :],
-            human_prefix=self.human_prefix,
-            ai_prefix=self.ai_prefix,
-        )
-        output = chain.predict(
-            history=buffer_string,
-            input=input_string,
-            verbose=True,
-        )
-        knowledge = parse_triples(output)
-        return knowledge
-
-    def _get_and_update_kg(self, inputs: Dict[str, Any]) -> None:
-        """Get and update knowledge graph from the conversation history."""
-        prompt_input_key = self._get_prompt_input_key(inputs)
-        knowledge = self.get_knowledge_triplets(inputs[prompt_input_key])
-        for triple in knowledge:
-            self.kg.add_triple(triple)
-
-    def save_context(self, inputs: Dict[str, Any], outputs: Dict[str, str]) -> None:
-        """Save context from this conversation to buffer."""
-        super().save_context(inputs, outputs)
-        self._get_and_update_kg(inputs)
-
-    def clear(self) -> None:
-        """Clear memory contents."""
-        super().clear()
-        self.kg.clear()

libs/langchain/langchain/memory/motorhead_memory.py

@@ -1,3 +1,23 @@
-from langchain_community.memory.motorhead_memory import MotorheadMemory
+from typing import TYPE_CHECKING, Any
 
-__all__ = ["MotorheadMemory"]
+from langchain._api import create_importer
+
+if TYPE_CHECKING:
+    from langchain_community.memory.motorhead_memory import MotorheadMemory
+
+# Create a way to dynamically look up deprecated imports.
+# Used to consolidate logic for raising deprecation warnings and
+# handling optional imports.
+DEPRECATED_LOOKUP = {"MotorheadMemory": "langchain_community.memory.motorhead_memory"}
+
+_import_attribute = create_importer(__package__, deprecated_lookups=DEPRECATED_LOOKUP)
+
+
+def __getattr__(name: str) -> Any:
+    """Look up attributes dynamically."""
+    return _import_attribute(name)
+
+
+__all__ = [
+    "MotorheadMemory",
+]

libs/langchain/langchain/memory/zep_memory.py

@@ -1,3 +1,23 @@
-from langchain_community.memory.zep_memory import ZepMemory
+from typing import TYPE_CHECKING, Any
 
-__all__ = ["ZepMemory"]
+from langchain._api import create_importer
+
+if TYPE_CHECKING:
+    from langchain_community.memory.zep_memory import ZepMemory
+
+# Create a way to dynamically look up deprecated imports.
+# Used to consolidate logic for raising deprecation warnings and
+# handling optional imports.
+DEPRECATED_LOOKUP = {"ZepMemory": "langchain_community.memory.zep_memory"}
+
+_import_attribute = create_importer(__package__, deprecated_lookups=DEPRECATED_LOOKUP)
+
+
+def __getattr__(name: str) -> Any:
+    """Look up attributes dynamically."""
+    return _import_attribute(name)
+
+
+__all__ = [
+    "ZepMemory",
+]