Merge branch 'samadpls-ref/move-history-methods-to-working-memory' into develop

Author: pieroit

core/cat/agents/main_agent.py

@@ -116,7 +116,7 @@ def format_agent_input(self, stray):
 
         # format conversation history to be inserted in the prompt
         # TODOV2: take away
-        conversation_history_formatted_content = stray.stringify_chat_history()
+        conversation_history_formatted_content = stray.working_memory.stringify_chat_history()
 
         return BaseModelDict(**{
             "episodic_memory": episodic_memory_formatted_content,

core/cat/agents/memory_agent.py

@@ -24,7 +24,7 @@ def execute(self, stray, prompt_prefix, prompt_suffix) -> AgentOutput:
                 SystemMessagePromptTemplate.from_template(
                     template=sys_prompt
                 ),
-                *(stray.langchainfy_chat_history()),
+                *(stray.working_memory.langchainfy_chat_history()),
             ]
         )
 

core/cat/agents/procedures_agent.py

@@ -116,7 +116,7 @@ def execute_chain(self, stray, procedures_prompt_template, allowed_procedures) -
                 SystemMessagePromptTemplate.from_template(
                     template=procedures_prompt_template
                 ),
-                *(stray.langchainfy_chat_history()),
+                *(stray.working_memory.langchainfy_chat_history()),
             ]
         )
 

core/cat/experimental/form/cat_form.py

@@ -216,7 +216,7 @@ def extract(self):
         return output_model
 
     def extraction_prompt(self):
-        history = self.cat.stringify_chat_history()
+        history = self.cat.working_memory.stringify_chat_history()
 
         # JSON structure
         # BaseModel.__fields__['my_field'].type_

core/cat/looking_glass/stray_cat.py

@@ -551,50 +551,13 @@ def classify(
         # set 0.5 as threshold - let's see if it works properly
         return best_label if score < 0.5 else None
 
-    def stringify_chat_history(self, latest_n: int = 5) -> str:
-        """Serialize chat history.
-        Converts to text the recent conversation turns.
-
-        Parameters
-        ----------
-        latest_n : int
-            Hoe many latest turns to stringify.
-
-        Returns
-        -------
-        history : str
-            String with recent conversation turns.
-
-        Notes
-        -----
-        Such context is placed in the `agent_prompt_suffix` in the place held by {chat_history}.
-
-        The chat history is a dictionary with keys::
-            'who': the name of who said the utterance;
-            'message': the utterance.
-
-        """
-
-        history = self.working_memory.history[-latest_n:]
-
-        history_string = ""
-        for turn in history:
-            history_string += f"\n - {turn.who}: {turn.text}"
-
-        return history_string
-
-    def langchainfy_chat_history(self, latest_n: int = 5) -> List[BaseMessage]: 
-        
-        chat_history = self.working_memory.history[-latest_n:]
-        recent_history = chat_history[-latest_n:]
-        langchain_chat_history = []
-
-        for message in recent_history:
-            langchain_chat_history.append(
-                message.langchainfy()    
-            )
-
-        return langchain_chat_history
+    def langchainfy_chat_history(self, latest_n: int = 10) -> List[BaseMessage]:
+        """Redirects to WorkingMemory.langchainfy_chat_history. Will be removed from this class in v2."""
+        return self.working_memory.langchainfy_chat_history(latest_n)
+    
+    def stringify_chat_history(self, latest_n: int = 10) -> str:
+        """Redirects to WorkingMemory.stringify_chat_history. Will be removed from this class in v2."""
+        return self.working_memory.stringify_chat_history(latest_n)
 
     async def close_connection(self):
         if self.__ws:

core/cat/memory/working_memory.py

@@ -1,4 +1,5 @@
 from typing import List, Optional
+from langchain_core.messages import BaseMessage
 
 from cat.convo.messages import Role, ConversationMessage, UserMessage, CatMessage
 from cat.convo.model_interactions import ModelInteraction
@@ -95,3 +96,51 @@ def update_history(self, message: ConversationMessage):
         """
         self.history.append(message)
 
+
+    def stringify_chat_history(self, latest_n: int = 10) -> str:
+        """Serialize chat history.
+        Converts to text the recent conversation turns.
+        Useful for retrocompatibility with old non-chat models, and to easily insert convo into a prompt without using dedicated objects and libraries.
+
+        Parameters
+        ----------
+        latest_n : int
+            How many latest turns to stringify.
+
+        Returns
+        -------
+        history : str
+            String with recent conversation turns.
+        """
+
+        history = self.history[-latest_n:]
+
+        history_string = ""
+        for turn in history:
+            history_string += f"\n - {turn.who}: {turn.text}"
+
+        return history_string
+
+    def langchainfy_chat_history(self, latest_n: int = 10) -> List[BaseMessage]: 
+        """Convert chat history in working memory to langchain objects.
+
+        Parameters
+        ----------
+        latest_n : int
+            How many latest turns to convert.
+
+        Returns
+        -------
+        history : List[BaseMessage]
+            List of langchain HumanMessage / AIMessage.
+        """
+        chat_history = self.history[-latest_n:]
+        recent_history = chat_history[-latest_n:]
+        langchain_chat_history = []
+
+        for message in recent_history:
+            langchain_chat_history.append(
+                message.langchainfy()    
+            )
+
+        return langchain_chat_history

core/tests/memory/test_class_working_memory.py

@@ -0,0 +1,68 @@
+from langchain_core.messages import AIMessage, HumanMessage
+
+from cat.convo.messages import Role, ConversationMessage, UserMessage, CatMessage
+from cat.memory.working_memory import WorkingMemory
+
+def create_working_memory_with_convo_history():
+    """Utility to create a working memory and populate its convo history."""
+
+    working_memory = WorkingMemory()
+    human_message = UserMessage(user_id="123", who="Human", text="Hi")
+    working_memory.update_history(human_message)
+    cat_message = CatMessage(user_id="123", who="AI", text="Meow")
+    working_memory.update_history(cat_message)
+    return working_memory
+
+def test_create_working_memory():
+
+    wm = WorkingMemory()
+    assert wm.history == []
+    assert wm.user_message_json == None
+    assert wm.active_form == None
+    assert wm.recall_query == ""
+    assert wm.episodic_memories == []
+    assert wm.declarative_memories == []
+    assert wm.procedural_memories == []
+    assert wm.model_interactions == []
+
+
+def test_update_history():
+
+    wm = create_working_memory_with_convo_history()
+
+    assert len(wm.history) == 2
+
+    assert isinstance(wm.history[0], UserMessage)
+    assert wm.history[0].who == "Human"
+    assert wm.history[0].role == Role.Human
+    assert wm.history[0].text == "Hi"
+
+    assert isinstance(wm.history[1], CatMessage)
+    assert wm.history[1].who == "AI"
+    assert wm.history[1].role == Role.AI
+    assert wm.history[1].text == "Meow"
+
+
+def test_stringify_chat_history():
+
+    wm = create_working_memory_with_convo_history()
+    assert wm.stringify_chat_history() == "\n - Human: Hi\n - AI: Meow"
+
+
+def test_langchainfy_chat_history():
+
+    wm = create_working_memory_with_convo_history()
+    langchain_convo = wm.langchainfy_chat_history()
+
+    assert len(langchain_convo) == len(wm.history)
+
+    assert isinstance(langchain_convo[0], HumanMessage)
+    assert langchain_convo[0].name == "Human"
+    assert isinstance(langchain_convo[0].content, list)
+    assert langchain_convo[0].content[0] == {"type": "text", "text": "Hi"}
+
+    assert isinstance(langchain_convo[1], AIMessage)
+    assert langchain_convo[1].name == "AI"
+    assert langchain_convo[1].content == "Meow"
+
+# TODOV2: add tests for multimodal messages!