Merge branch 'main' into dependabot/github_actions/github/codeql-acti…

…on-2.22.8

.github/dependabot.yml

@@ -9,11 +9,3 @@ updates:
     directory: /
     schedule:
       interval: monthly
-
-  - package-ecosystem: docker
-    directory: /.devcontainer
-    schedule:
-      interval: monthly
-    ignore:
-      - dependency-name: "vscode/devcontainers/python"
-        versions: [">= 3.11"]

.github/workflows/pypi-publish.yml

@@ -28,7 +28,7 @@ jobs:
     runs-on: ubuntu-latest
     environment:
       name: pypi
-      url: https://pypi.org/p/dm-concordia
+      url: https://pypi.org/p/gdm-concordia
     permissions:
       id-token: write
     timeout-minutes: 90

.github/workflows/pypi-test.yml

@@ -56,7 +56,7 @@ jobs:
 
       - name: Install from PyPI
         run: |
-          pip -vvv install dm-concordia
+          pip -vvv install gdm-concordia
           pip list
 
       - name: Test installation

README.md

@@ -2,8 +2,8 @@
 
 *A library for generative social simulation*
 
-[![Python](https://img.shields.io/pypi/pyversions/dm-concordia.svg)](https://pypi.python.org/pypi/dm-concordia)
-[![PyPI version](https://img.shields.io/pypi/v/dm-concordia.svg)](https://pypi.python.org/pypi/dm-concordia)
+[![Python](https://img.shields.io/pypi/pyversions/gdm-concordia.svg)](https://pypi.python.org/pypi/gdm-concordia)
+[![PyPI version](https://img.shields.io/pypi/v/gdm-concordia.svg)](https://pypi.python.org/pypi/gdm-concordia)
 [![PyPI tests](../../actions/workflows/pypi-test.yml/badge.svg)](../../actions/workflows/pypi-test.yml)
 [![Tests](../../actions/workflows/test-concordia.yml/badge.svg)](../../actions/workflows/test-concordia.yml)
 [![Examples](../../actions/workflows/test-examples.yml/badge.svg)](../../actions/workflows/test-examples.yml)

concordia/agents/basic_agent.py

@@ -26,7 +26,7 @@
 import contextlib
 import copy
 import datetime
-
+import threading
 from concordia.associative_memory import associative_memory
 from concordia.document import interactive_document
 from concordia.language_model import language_model
@@ -70,7 +70,7 @@ def __init__(
       update_interval: how often to update components. In game time according to
         the clock argument.
       verbose: whether to print chains of thought or not
-      user_controlled: if True, would query user input for speach and action
+      user_controlled: if True, would query user input for speech and action
       print_colour: which colour to use for printing
     """
     self._verbose = verbose
@@ -86,6 +86,8 @@ def __init__(
     self._update_interval = update_interval
 
     self._under_interrogation = False
+    self._state_lock = threading.Lock()
+    self._state: str | None
 
     self._components = {}
     for comp in components:
@@ -166,10 +168,8 @@ def get_last_log(self):
     return self._last_chain_of_thought
 
   def state(self):
-    return '\n'.join(
-        f"{self._agent_name}'s " + (comp.name() + ':\n' + comp.state())
-        for comp in self._components.values()
-    )
+    with self._state_lock:
+      return self._state
 
   def _maybe_update(self):
     next_update = self._last_update + self._update_interval
@@ -181,6 +181,11 @@ def update(self):
     with concurrent.futures.ThreadPoolExecutor() as executor:
       for comp in self._components.values():
         executor.submit(comp.update)
+    with self._state_lock:
+      self._state = '\n'.join(
+          f"{self._agent_name}'s " + (comp.name() + ':\n' + comp.state())
+          for comp in self._components.values()
+      )
 
   def observe(self, observation: str):
     if observation and not self._under_interrogation:
@@ -257,19 +262,16 @@ def say(self, conversation: str) -> str:
         f'{self._agent_name} is in the following'
         f' conversation:\n{conversation}\n'
     )
-    call_to_speach = (
-        f'Given the above, what should {self._agent_name} say next? Respond in'
-        f' the format `{self._agent_name} says: "..."` For example, '
-        'Cristina says: "Hello! Mighty fine weather today, right?" '
-        'or Ichabod says: "I wonder if the alfalfa is ready to harvest.\n'
+    call_to_speech = agent.DEFAULT_CALL_TO_SPEECH.format(
+        agent_name=self._agent_name,
     )
     if self._user_controlled:
       utterance = self._ask_for_input(
-          convo_context + call_to_speach, f'{self._agent_name}:'
+          convo_context + call_to_speech, f'{self._agent_name}:'
       )
     else:
       utterance = self.act(
-          action_spec=agent.ActionSpec(convo_context + call_to_speach, 'FREE'),
+          action_spec=agent.ActionSpec(convo_context + call_to_speech, 'FREE'),
       )
 
     return utterance

concordia/agents/components/characteristic.py

@@ -14,11 +14,12 @@
 
 
 """Agent characteristic component."""
+import datetime
+from typing import Callable
 
 from concordia.associative_memory import associative_memory
 from concordia.document import interactive_document
 from concordia.language_model import language_model
-from concordia.typing import clock as game_clock
 from concordia.typing import component
 import termcolor
 
@@ -50,7 +51,7 @@ def __init__(
       memory: associative_memory.AssociativeMemory,
       agent_name: str,
       characteristic_name: str,
-      state_clock: game_clock.GameClock | None = None,
+      state_clock_now: Callable[[], datetime.datetime] | None = None,
       extra_instructions: str = '',
       num_memories_to_retrieve: int = 25,
       verbose: bool = False,
@@ -62,7 +63,7 @@ def __init__(
       memory: an associative memory
       agent_name: the name of the agent
       characteristic_name: the string to use in similarity search of memory
-      state_clock: if None then consider this component as representing a
+      state_clock_now: if None then consider this component as representing a
         `trait`. If a clock is used then consider this component to represent a
         `state`. A state is temporary whereas a trait is meant to endure.
       extra_instructions: append additional instructions when asking the model
@@ -77,7 +78,7 @@ def __init__(
     self._characteristic_name = characteristic_name
     self._agent_name = agent_name
     self._extra_instructions = extra_instructions
-    self._clock = state_clock
+    self._clock_now = state_clock_now
     self._num_memories_to_retrieve = num_memories_to_retrieve
 
   def name(self) -> str:
@@ -88,13 +89,13 @@ def state(self) -> str:
 
   def update(self) -> None:
     query = f"{self._agent_name}'s {self._characteristic_name}"
-    if self._clock is not None:
-      query = f'[{self._clock.now()}] {query}'
+    if self._clock_now is not None:
+      query = f'[{self._clock_now()}] {query}'
 
     mems = '\n'.join(
-        self._memory.retrieve_associative(query,
-                                          self._num_memories_to_retrieve,
-                                          add_time=True)
+        self._memory.retrieve_associative(
+            query, self._num_memories_to_retrieve, add_time=True
+        )
     )
 
     prompt = interactive_document.InteractiveDocument(self._model)
@@ -105,8 +106,8 @@ def update(self) -> None:
         f'{self._extra_instructions}'
         f'Start the answer with "{self._agent_name} is"'
     )
-    if self._clock is not None:
-      question = f'Current time: {self._clock.now()}.\n{question}'
+    if self._clock_now is not None:
+      question = f'Current time: {self._clock_now()}.\n{question}'
 
     self._cache = prompt.open_question(
         '\n'.join([question, f'Statements:\n{mems}']),

concordia/agents/components/person_by_situation.py

@@ -13,12 +13,13 @@
 # limitations under the License.
 
 """Agent component for self perception."""
-
+import datetime
+from typing import Callable
 from typing import Sequence
+
 from concordia.associative_memory import associative_memory
 from concordia.document import interactive_document
 from concordia.language_model import language_model
-from concordia.typing import clock
 from concordia.typing import component
 import termcolor
 
@@ -33,7 +34,7 @@ def __init__(
       memory: associative_memory.AssociativeMemory,
       agent_name: str,
       components=Sequence[component.Component] | None,
-      state_clock: clock.GameClock | None = None,
+      clock_now: Callable[[], datetime.datetime] | None = None,
       num_memories_to_retrieve: int = 25,
       verbose: bool = False,
   ):
@@ -45,7 +46,7 @@ def __init__(
       memory: The memory to use.
       agent_name: The name of the agent.
       components: The components to condition the answer on.
-      state_clock: The clock to use.
+      clock_now: time callback to use for the state.
       num_memories_to_retrieve: The number of memories to retrieve.
       verbose: Whether to print the state of the component.
     """
@@ -56,7 +57,7 @@ def __init__(
     self._state = ''
     self._components = components or []
     self._agent_name = agent_name
-    self._clock = state_clock
+    self._clock_now = clock_now
     self._num_memories_to_retrieve = num_memories_to_retrieve
     self._name = name
 
@@ -77,21 +78,19 @@ def update(self) -> None:
 
     prompt.statement(f'Memories of {self._agent_name}:\n{mems}')
 
-    component_states = '\n'.join(
-        [
-            f"{self._agent_name}'s "
-            + (construct.name() + ':\n' + construct.state())
-            for construct in self._components
-        ]
-    )
+    component_states = '\n'.join([
+        f"{self._agent_name}'s "
+        + (construct.name() + ':\n' + construct.state())
+        for construct in self._components
+    ])
 
     prompt.statement(component_states)
     question = (
         f'What would a person like {self._agent_name} do in a situation like'
         ' this?'
     )
-    if self._clock is not None:
-      question = f'Current time: {self._clock.now()}.\n{question}'
+    if self._clock_now is not None:
+      question = f'Current time: {self._clock_now()}.\n{question}'
 
     self._state = prompt.open_question(
         question,

concordia/agents/components/report_state.py

@@ -15,19 +15,18 @@
 
 """This components report what the get_state returns at the moment.
 
-For example, can be used for reporting current time 
+For example, can be used for reporting current time
 current_time_component = ReportState(
-    'Current time', 
+    'Current time',
     get_state=clock.current_time_interval_str)
-    
 """
 
 from typing import Callable
 from concordia.typing import component
 
 
 class ReportState(component.Component):
-  """A component that shows the current time interval."""
+  """A component that reports what the get_state returns at the moment."""
 
   def __init__(self, get_state: Callable[[], str], name: str = 'State'):
     """Initializes the component.

concordia/agents/components/self_perception.py

@@ -13,11 +13,12 @@
 # limitations under the License.
 
 """Agent component for self perception."""
+import datetime
+from typing import Callable
 
 from concordia.associative_memory import associative_memory
 from concordia.document import interactive_document
 from concordia.language_model import language_model
-from concordia.typing import clock
 from concordia.typing import component
 import termcolor
 
@@ -31,7 +32,7 @@ def __init__(
       model: language_model.LanguageModel,
       memory: associative_memory.AssociativeMemory,
       agent_name: str,
-      state_clock: clock.GameClock | None = None,
+      clock_now: Callable[[], datetime.datetime] | None = None,
       num_memories_to_retrieve: int = 100,
       verbose: bool = False,
   ):
@@ -42,7 +43,7 @@ def __init__(
       model: Language model.
       memory: Associative memory.
       agent_name: Name of the agent.
-      state_clock: Clock to use for the state.
+      clock_now: time callback to use for the state.
       num_memories_to_retrieve: Number of memories to retrieve.
       verbose: Whether to print the state.
     """
@@ -52,7 +53,7 @@ def __init__(
     self._memory = memory
     self._state = ''
     self._agent_name = agent_name
-    self._clock = state_clock
+    self._clock_now = clock_now
     self._num_memories_to_retrieve = num_memories_to_retrieve
     self._name = name
 
@@ -72,8 +73,8 @@ def update(self) -> None:
     prompt = interactive_document.InteractiveDocument(self._model)
     prompt.statement(f'Memories of {self._agent_name}:\n{mems}')
 
-    if self._clock is not None:
-      prompt.statement(f'Current time: {self._clock.now()}.\n')
+    if self._clock_now is not None:
+      prompt.statement(f'Current time: {self._clock_now()}.\n')
 
     question = (
         f'Given the memories above, what kind of person is {self._agent_name}?'

concordia/agents/components/situation_perception.py

@@ -13,11 +13,12 @@
 # limitations under the License.
 
 """Agent component for situation perception."""
+import datetime
+from typing import Callable
 
 from concordia.associative_memory import associative_memory
 from concordia.document import interactive_document
 from concordia.language_model import language_model
-from concordia.typing import clock
 from concordia.typing import component
 import termcolor
 
@@ -31,7 +32,7 @@ def __init__(
       model: language_model.LanguageModel,
       memory: associative_memory.AssociativeMemory,
       agent_name: str,
-      state_clock: clock.GameClock | None = None,
+      clock_now: Callable[[], datetime.datetime] | None = None,
       num_memories_to_retrieve: int = 25,
       verbose: bool = False,
   ):
@@ -42,7 +43,7 @@ def __init__(
       model: The language model to use.
       memory: The memory to use.
       agent_name: The name of the agent.
-      state_clock: The clock to use.
+      clock_now: time callback to use for the state.
       num_memories_to_retrieve: The number of memories to retrieve.
       verbose: Whether to print the last chain.
     """
@@ -51,7 +52,7 @@ def __init__(
     self._memory = memory
     self._state = ''
     self._agent_name = agent_name
-    self._clock = state_clock
+    self._clock_now = clock_now
     self._num_memories_to_retrieve = num_memories_to_retrieve
     self._name = name
 
@@ -71,8 +72,8 @@ def update(self) -> None:
     prompt = interactive_document.InteractiveDocument(self._model)
     prompt.statement(f'Memories of {self._agent_name}:\n{mems}')
 
-    if self._clock is not None:
-      prompt.statement(f'Current time: {self._clock.now()}.\n')
+    if self._clock_now is not None:
+      prompt.statement(f'Current time: {self._clock_now()}.\n')
 
     question = (
         'Given the memories above, what kind of situation is'