[FEAT][Conversation]

swarms/memory/__init__.py

@@ -1,11 +1,11 @@
-from swarms.memory.base_vectordb import VectorDatabase
+from swarms.memory.base_vectordb import AbstractDatabase
 from swarms.memory.short_term_memory import ShortTermMemory
 from swarms.memory.sqlite import SQLiteDB
 from swarms.memory.weaviate_db import WeaviateDB
 from swarms.memory.visual_memory import VisualShortTermMemory
 
 __all__ = [
-    "VectorDatabase",
+    "AbstractDatabase",
     "ShortTermMemory",
     "SQLiteDB",
     "WeaviateDB",

swarms/memory/base_db.py

@@ -156,4 +156,4 @@ class AbstractDatabase(ABC):
 
         """
 
-        pass
+        pass

swarms/memory/base_vectordatabase.py

@@ -0,0 +1,142 @@
+from abc import ABC, abstractmethod
+
+
+class AbstractVectorDatabase(ABC):
+    """
+    Abstract base class for a database.
+
+    This class defines the interface for interacting with a database.
+    Subclasses must implement the abstract methods to provide the
+    specific implementation details for connecting to a database,
+    executing queries, and performing CRUD operations.
+
+    """
+
+    @abstractmethod
+    def connect(self):
+        """
+        Connect to the database.
+
+        This method establishes a connection to the database.
+
+        """
+
+        pass
+
+    @abstractmethod
+    def close(self):
+        """
+        Close the database connection.
+
+        This method closes the connection to the database.
+
+        """
+
+        pass
+
+    @abstractmethod
+    def query(self, query: str):
+        """
+        Execute a database query.
+
+        This method executes the given query on the database.
+
+        Parameters:
+            query (str): The query to be executed.
+
+        """
+
+        pass
+
+    @abstractmethod
+    def fetch_all(self):
+        """
+        Fetch all rows from the result set.
+
+        This method retrieves all rows from the result set of a query.
+
+        Returns:
+            list: A list of dictionaries representing the rows.
+
+        """
+
+        pass
+
+    @abstractmethod
+    def fetch_one(self):
+        """
+        Fetch one row from the result set.
+
+        This method retrieves one row from the result set of a query.
+
+        Returns:
+            dict: A dictionary representing the row.
+
+        """
+
+        pass
+
+    @abstractmethod
+    def add(self, doc: str):
+        """
+        Add a new record to the database.
+
+        This method adds a new record to the specified table in the database.
+
+        Parameters:
+            table (str): The name of the table.
+            data (dict): A dictionary representing the data to be added.
+
+        """
+
+        pass
+
+
+    @abstractmethod
+    def get(self, query: str):
+        """
+        Get a record from the database.
+
+        This method retrieves a record from the specified table in the database based on the given ID.
+
+        Parameters:
+            table (str): The name of the table.
+            id (int): The ID of the record to be retrieved.
+
+        Returns:
+            dict: A dictionary representing the retrieved record.
+
+        """
+
+        pass
+
+    @abstractmethod
+    def update(self, doc):
+        """
+        Update a record in the database.
+
+        This method updates a record in the specified table in the database based on the given ID.
+
+        Parameters:
+            table (str): The name of the table.
+            id (int): The ID of the record to be updated.
+            data (dict): A dictionary representing the updated data.
+
+        """
+
+        pass
+
+    @abstractmethod
+    def delete(self, message):
+        """
+        Delete a record from the database.
+
+        This method deletes a record from the specified table in the database based on the given ID.
+
+        Parameters:
+            table (str): The name of the table.
+            id (int): The ID of the record to be deleted.
+
+        """
+
+        pass

swarms/memory/base_vectordb.py

@@ -1,58 +0,0 @@
-from abc import ABC, abstractmethod
-from typing import Any, Dict
-
-
-class VectorDatabase(ABC):
-    @abstractmethod
-    def add(
-        self, vector: Dict[str, Any], metadata: Dict[str, Any]
-    ) -> None:
-        """
-        add a vector into the database.
-
-        Args:
-            vector (Dict[str, Any]): The vector to add.
-            metadata (Dict[str, Any]): Metadata associated with the vector.
-        """
-        pass
-
-    @abstractmethod
-    def query(self, text: str, num_results: int) -> Dict[str, Any]:
-        """
-        Query the database for vectors similar to the given vector.
-
-        Args:
-            text (Dict[str, Any]): The vector to compare against.
-            num_results (int): The number of similar vectors to return.
-
-        Returns:
-            Dict[str, Any]: The most similar vectors and their associated metadata.
-        """
-        pass
-
-    @abstractmethod
-    def delete(self, vector_id: str) -> None:
-        """
-        Delete a vector from the database.
-
-        Args:
-            vector_id (str): The ID of the vector to delete.
-        """
-        pass
-
-    @abstractmethod
-    def update(
-        self,
-        vector_id: str,
-        vector: Dict[str, Any],
-        metadata: Dict[str, Any],
-    ) -> None:
-        """
-        Update a vector in the database.
-
-        Args:
-            vector_id (str): The ID of the vector to update.
-            vector (Dict[str, Any]): The new vector.
-            metadata (Dict[str, Any]): The new metadata.
-        """
-        pass

swarms/memory/pinecone.py

@@ -1,12 +1,12 @@
 from typing import Optional
-from swarms.memory.base_vectordb import VectorDatabase
+from swarms.memory.base_vectordb import AbstractDatabase
 import pinecone
 from attr import define, field
 from swarms.utils.hash import str_to_hash
 
 
 @define
-class PineconeDB(VectorDatabase):
+class PineconeDB(AbstractDatabase):
     """
     PineconeDB is a vector storage driver that uses Pinecone as the underlying storage engine.
 

swarms/memory/sqlite.py

@@ -1,5 +1,5 @@
 from typing import List, Tuple, Any, Optional
-from swarms.memory.base_vectordb import VectorDatabase
+from swarms.memory.base_vectordb import AbstractDatabase
 
 try:
     import sqlite3
@@ -9,7 +9,7 @@ except ImportError:
     )
 
 
-class SQLiteDB(VectorDatabase):
+class SQLiteDB(AbstractDatabase):
     """
     A reusable class for SQLite database operations with methods for adding,
     deleting, updating, and querying data.

swarms/memory/weaviate_db.py

@@ -4,7 +4,7 @@ Weaviate API Client
 
 from typing import Any, Dict, List, Optional
 
-from swarms.memory.base_vectordb import VectorDatabase
+from swarms.memory.base_vectordb import AbstractDatabase
 
 try:
     import weaviate
@@ -12,7 +12,7 @@ except ImportError:
     print("pip install weaviate-client")
 
 
-class WeaviateDB(VectorDatabase):
+class WeaviateDB(AbstractDatabase):
     """
 
     Weaviate API Client

swarms/structs/agent.py

@@ -9,7 +9,7 @@ from typing import Any, Callable, Dict, List, Optional, Tuple
 
 from termcolor import colored
 
-from swarms.memory.base_vectordb import VectorDatabase
+from swarms.memory.base_vectordb import AbstractDatabase
 from swarms.prompts.agent_system_prompts import (
     AGENT_SYSTEM_PROMPT_3,
 )
@@ -83,7 +83,7 @@ class Agent:
         pdf_path (str): The path to the pdf
         list_of_pdf (str): The list of pdf
         tokenizer (Any): The tokenizer
-        memory (VectorDatabase): The memory
+        memory (AbstractDatabase): The memory
         preset_stopping_token (bool): Enable preset stopping token
         traceback (Any): The traceback
         traceback_handlers (Any): The traceback handlers
@@ -168,7 +168,7 @@ class Agent:
         pdf_path: Optional[str] = None,
         list_of_pdf: Optional[str] = None,
         tokenizer: Optional[Any] = None,
-        long_term_memory: Optional[VectorDatabase] = None,
+        long_term_memory: Optional[AbstractDatabase] = None,
         preset_stopping_token: Optional[bool] = False,
         traceback: Any = None,
         traceback_handlers: Any = None,
@@ -657,7 +657,7 @@ class Agent:
             """
             return agent_history_prompt
 
-    def long_term_memory_prompt(self, query: str, prompt: str):
+    def long_term_memory_prompt(self, query: str):
         """
         Generate the agent long term memory prompt
 
@@ -671,7 +671,7 @@ class Agent:
         ltr = self.long_term_memory.query(query)
 
         context = f"""
-            {prompt}
+            {query}
             ####### Long Term Memory ################
             {ltr}
         """

swarms/structs/conversation.py

@@ -60,6 +60,7 @@ class Conversation(BaseStructure):
 
     def __init__(
         self,
+        system_prompt: str,
         time_enabled: bool = False,
         database: AbstractDatabase = None,
         autosave: bool = False,
@@ -68,11 +69,16 @@ class Conversation(BaseStructure):
         **kwargs,
     ):
         super().__init__()
+        self.system_prompt = system_prompt
         self.time_enabled = time_enabled
         self.database = database
         self.autosave = autosave
         self.save_filepath = save_filepath
         self.conversation_history = []
+        
+        # If system prompt is not None, add it to the conversation history
+        if self.system_prompt:
+            self.add("system", self.system_prompt)
 
     def add(self, role: str, content: str, *args, **kwargs):
         """Add a message to the conversation history

swarms/structs/multi_agent_rag.py

@@ -0,0 +1,97 @@
+from dataclasses import dataclass
+from typing import List, Optional
+
+from swarms.memory.base_vectordatabase import AbstractVectorDatabase
+from swarms.structs.agent import Agent
+
+
+@dataclass
+class MultiAgentRag:
+    """
+    Represents a multi-agent RAG (Relational Agent Graph) structure.
+    
+    Attributes:
+        agents (List[Agent]): List of agents in the multi-agent RAG.
+        db (AbstractVectorDatabase): Database used for querying.
+        verbose (bool): Flag indicating whether to print verbose output.
+    """
+    agents: List[Agent]
+    db: AbstractVectorDatabase
+    verbose: bool = False
+    
+    
+    def query_database(self, query: str):
+        """
+        Queries the database using the given query string.
+        
+        Args:
+            query (str): The query string.
+        
+        Returns:
+            List: The list of results from the database.
+        """
+        results = []
+        for agent in self.agents:
+            agent_results = agent.long_term_memory_prompt(query)
+            results.extend(agent_results)
+        return results
+    
+    
+    def get_agent_by_id(self, agent_id) -> Optional[Agent]:
+        """
+        Retrieves an agent from the multi-agent RAG by its ID.
+        
+        Args:
+            agent_id: The ID of the agent to retrieve.
+        
+        Returns:
+            Agent or None: The agent with the specified ID, or None if not found.
+        """
+        for agent in self.agents:
+            if agent.agent_id == agent_id:
+                return agent
+        return None
+    
+    def add_message(
+        self,
+        sender: Agent,
+        message: str,
+        *args,
+        **kwargs
+    ):
+        """
+        Adds a message to the database.
+        
+        Args:
+            sender (Agent): The agent sending the message.
+            message (str): The message to add.
+            *args: Additional positional arguments.
+            **kwargs: Additional keyword arguments.
+        
+        Returns:
+            int: The ID of the added message.
+        """
+        doc = f"{sender.ai_name}: {message}"
+        
+        return self.db.add(doc)
+    
+    def query(
+        self,
+        message: str,
+        *args,
+        **kwargs
+    ):
+        """
+        Queries the database using the given message.
+        
+        Args:
+            message (str): The message to query.
+            *args: Additional positional arguments.
+            **kwargs: Additional keyword arguments.
+        
+        Returns:
+            List: The list of results from the database.
+        """
+        return self.db.query(message)
+    
+