Introduce the LLM session manager classes

conftest.py

@@ -138,3 +138,15 @@ def clear_db(redis):
     redis.flushall()
     yield
     redis.flushall()
+
+@pytest.fixture
+def app_name():
+    return "test_app"
+
+@pytest.fixture
+def session_tag():
+    return "123"
+
+@pytest.fixture
+def user_tag():
+    return "abc"

docs/user_guide/index.md

@@ -17,5 +17,6 @@ llmcache_03
 vectorizers_04
 hash_vs_json_05
 rerankers_06
+session_manager_07
 ```
 

redisvl/extensions/session_manager/__init__.py

@@ -0,0 +1,5 @@
+from redisvl.extensions.session_manager.base_session import BaseSessionManager
+from redisvl.extensions.session_manager.semantic_session import SemanticSessionManager
+from redisvl.extensions.session_manager.standard_session import StandardSessionManager
+
+__all__ = ["BaseSessionManager", "StandardSessionManager", "SemanticSessionManager"]

redisvl/extensions/session_manager/base_session.py

@@ -0,0 +1,173 @@
+from typing import Any, Dict, List, Optional, Union
+
+from redis import Redis
+
+
+class BaseSessionManager:
+    id_field_name: str = "id_field"
+    role_field_name: str = "role"
+    content_field_name: str = "content"
+    tool_field_name: str = "tool_call_id"
+    timestamp_field_name: str = "timestamp"
+
+    def __init__(
+        self,
+        name: str,
+        session_tag: str,
+        user_tag: str,
+    ):
+        """Initialize session memory with index
+
+        Session Manager stores the current and previous user text prompts and
+        LLM responses to allow for enriching future prompts with session
+        context. Session history is stored in individual user or LLM prompts and
+        responses.
+
+        Args:
+            name (str): The name of the session manager index.
+            session_tag (str): Tag to be added to entries to link to a specific
+                session.
+            user_tag (str): Tag to be added to entries to link to a specific user.
+        """
+        self._name = name
+        self._user_tag = user_tag
+        self._session_tag = session_tag
+
+    def set_scope(
+        self,
+        session_tag: Optional[str] = None,
+        user_tag: Optional[str] = None,
+    ) -> None:
+        """Set the filter to apply to querries based on the desired scope.
+
+        This new scope persists until another call to set_scope is made, or if
+        scope specified in calls to get_recent.
+
+        Args:
+            session_tag (str): Id of the specific session to filter to. Default is
+                None.
+            user_tag (str): Id of the specific user to filter to. Default is None.
+        """
+        raise NotImplementedError
+
+    def clear(self) -> None:
+        """Clears the chat session history."""
+        raise NotImplementedError
+
+    def delete(self) -> None:
+        """Clear all conversation history and remove any search indices."""
+        raise NotImplementedError
+
+    def drop(self, id_field: Optional[str] = None) -> None:
+        """Remove a specific exchange from the conversation history.
+
+        Args:
+            id_field (Optional[str]): The id_field of the entry to delete.
+                If None then the last entry is deleted.
+        """
+        raise NotImplementedError
+
+    @property
+    def messages(self) -> Union[List[str], List[Dict[str, str]]]:
+        """Returns the full chat history."""
+        raise NotImplementedError
+
+    def get_recent(
+        self,
+        top_k: int = 5,
+        session_tag: Optional[str] = None,
+        user_tag: Optional[str] = None,
+        as_text: bool = False,
+        raw: bool = False,
+    ) -> Union[List[str], List[Dict[str, str]]]:
+        """Retreive the recent conversation history in sequential order.
+
+        Args:
+            top_k (int): The number of previous exchanges to return. Default is 5.
+                Note that one exchange contains both a prompt and response.
+            session_tag (str): Tag to be added to entries to link to a specific
+                session.
+            user_tag (str): Tag to be added to entries to link to a specific user.
+            as_text (bool): Whether to return the conversation as a single string,
+                or list of alternating prompts and responses.
+            raw (bool): Whether to return the full Redis hash entry or just the
+                prompt and response
+
+        Returns:
+            Union[str, List[str]]: A single string transcription of the session
+                                   or list of strings if as_text is false.
+
+        Raises:
+            ValueError: If top_k is not an integer greater than or equal to 0.
+        """
+        raise NotImplementedError
+
+    def _format_context(
+        self, hits: List[Dict[str, Any]], as_text: bool
+    ) -> Union[List[str], List[Dict[str, str]]]:
+        """Extracts the prompt and response fields from the Redis hashes and
+           formats them as either flat dictionaries or strings.
+
+        Args:
+            hits (List): The hashes containing prompt & response pairs from
+                recent conversation history.
+            as_text (bool): Whether to return the conversation as a single string,
+                or list of alternating prompts and responses.
+        Returns:
+            Union[str, List[str]]: A single string transcription of the session
+                or list of strings if as_text is false.
+        """
+        if as_text:
+            text_statements = []
+            for hit in hits:
+                text_statements.append(hit[self.content_field_name])
+            return text_statements
+        else:
+            statements = []
+            for hit in hits:
+                statements.append(
+                    {
+                        self.role_field_name: hit[self.role_field_name],
+                        self.content_field_name: hit[self.content_field_name],
+                    }
+                )
+                if (
+                    hasattr(hit, self.tool_field_name)
+                    or isinstance(hit, dict)
+                    and self.tool_field_name in hit
+                ):
+                    statements[-1].update(
+                        {self.tool_field_name: hit[self.tool_field_name]}
+                    )
+            return statements
+
+    def store(self, prompt: str, response: str) -> None:
+        """Insert a prompt:response pair into the session memory. A timestamp
+        is associated with each exchange so that they can be later sorted
+        in sequential ordering after retrieval.
+
+        Args:
+            prompt (str): The user prompt to the LLM.
+            response (str): The corresponding LLM response.
+        """
+        raise NotImplementedError
+
+    def add_messages(self, messages: List[Dict[str, str]]) -> None:
+        """Insert a list of prompts and responses into the session memory.
+        A timestamp is associated with each so that they can be later sorted
+        in sequential ordering after retrieval.
+
+        Args:
+            messages (List[Dict[str, str]]): The list of user prompts and LLM responses.
+        """
+        raise NotImplementedError
+
+    def add_message(self, message: Dict[str, str]) -> None:
+        """Insert a single prompt or response into the session memory.
+        A timestamp is associated with it so that it can be later sorted
+        in sequential ordering after retrieval.
+
+        Args:
+            message (Dict[str,str]): The user prompt or LLM response.
+        """
+        raise NotImplementedError