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arch: deprecating recall action and search_memory (OpenHands#2900)
* deprecating recall action * fix integration tests * fix integration tests * remove search memory
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‎agenthub/README.md‎

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@@ -33,7 +33,6 @@ Here is a list of available Actions, which can be returned by `agent.step()`:
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- [`FileReadAction`](../opendevin/events/action/files.py) - Reads the content of a file
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- [`FileWriteAction`](../opendevin/events/action/files.py) - Writes new content to a file
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- [`BrowseURLAction`](../opendevin/events/action/browse.py) - Gets the content of a URL
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- [`AgentRecallAction`](../opendevin/events/action/agent.py) - Searches memory (e.g. a vector database)
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- [`AddTaskAction`](../opendevin/events/action/tasks.py) - Adds a subtask to the plan
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- [`ModifyTaskAction`](../opendevin/events/action/tasks.py) - Changes the state of a subtask.
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- [`AgentFinishAction`](../opendevin/events/action/agent.py) - Stops the control loop, allowing the user/delegator agent to enter a new task
@@ -54,7 +53,6 @@ Here is a list of available Observations:
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- [`BrowserOutputObservation`](../opendevin/events/observation/browse.py)
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- [`FileReadObservation`](../opendevin/events/observation/files.py)
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- [`FileWriteObservation`](../opendevin/events/observation/files.py)
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- [`AgentRecallObservation`](../opendevin/events/observation/recall.py)
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- [`ErrorObservation`](../opendevin/events/observation/error.py)
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- [`SuccessObservation`](../opendevin/events/observation/success.py)
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@@ -72,14 +70,3 @@ def step(self, state: "State") -> "Action"
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`step` moves the agent forward one step towards its goal. This probably means
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sending a prompt to the LLM, then parsing the response into an `Action`.
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### `search_memory`
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```
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def search_memory(self, query: str) -> list[str]:
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```
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`search_memory` should return a list of events that match the query. This will be used
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for the `recall` action.
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You can optionally just return `[]` for this method, meaning the agent has no long-term memory.

‎agenthub/browsing_agent/browsing_agent.py‎

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@@ -213,6 +213,3 @@ def step(self, state: State) -> Action:
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stop=[')```', ')\n```'],
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)
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return self.response_parser.parse(response)
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def search_memory(self, query: str) -> list[str]:
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raise NotImplementedError('Implement this abstract method')

‎agenthub/codeact_agent/codeact_agent.py‎

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@@ -208,9 +208,6 @@ def step(self, state: State) -> Action:
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)
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return self.action_parser.parse(response)
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def search_memory(self, query: str) -> list[str]:
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raise NotImplementedError('Implement this abstract method')
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def _get_messages(self, state: State) -> list[dict[str, str]]:
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messages = [
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{'role': 'system', 'content': self.system_message},

‎agenthub/codeact_swe_agent/codeact_swe_agent.py‎

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@@ -162,9 +162,6 @@ def step(self, state: State) -> Action:
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return self.response_parser.parse(response)
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def search_memory(self, query: str) -> list[str]:
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raise NotImplementedError('Implement this abstract method')
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def _get_messages(self, state: State) -> list[dict[str, str]]:
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messages = [
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{'role': 'system', 'content': self.system_message},

‎agenthub/delegator_agent/agent.py‎

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@@ -82,6 +82,3 @@ def step(self, state: State) -> Action:
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)
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else:
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raise Exception('Invalid delegate state')
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def search_memory(self, query: str) -> list[str]:
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return []

‎agenthub/dummy_agent/agent.py‎

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Action,
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AddTaskAction,
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AgentFinishAction,
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AgentRecallAction,
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AgentRejectAction,
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BrowseInteractiveAction,
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BrowseURLAction,
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ModifyTaskAction,
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)
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from opendevin.events.observation import (
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AgentRecallObservation,
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CmdOutputObservation,
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FileReadObservation,
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FileWriteObservation,
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)
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],
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},
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{
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'action': AgentRecallAction(query='who am I?'),
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'observations': [
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AgentRecallObservation('', memories=['I am a computer.']),
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],
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},
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{
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'action': BrowseURLAction(url='https://google.com'),
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'observations': [
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hist_obs == expected_obs
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), f'Expected observation {expected_obs}, got {hist_obs}'
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return self.steps[state.iteration]['action']
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def search_memory(self, query: str) -> list[str]:
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return ['I am a computer.']

‎agenthub/micro/agent.py‎

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action_resp = resp['choices'][0]['message']['content']
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action = parse_response(action_resp)
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return action
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def search_memory(self, query: str) -> list[str]:
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return []

‎agenthub/monologue_agent/agent.py‎

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from opendevin.core.schema import ActionType
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from opendevin.events.action import (
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Action,
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AgentRecallAction,
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BrowseURLAction,
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CmdRunAction,
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FileReadAction,
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NullAction,
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)
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from opendevin.events.observation import (
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AgentRecallObservation,
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BrowserOutputObservation,
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CmdOutputObservation,
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FileReadObservation,
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)
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elif previous_action == ActionType.READ:
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observation = FileReadObservation(content=thought, path='')
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elif previous_action == ActionType.RECALL:
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observation = AgentRecallObservation(content=thought, memories=[])
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elif previous_action == ActionType.BROWSE:
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observation = BrowserOutputObservation(
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content=thought, url='', screenshot=''
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path = thought.split('READ ')[1]
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action = FileReadAction(path=path)
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previous_action = ActionType.READ
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elif thought.startswith('RECALL'):
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query = thought.split('RECALL ')[1]
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action = AgentRecallAction(query=query)
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previous_action = ActionType.RECALL
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elif thought.startswith('BROWSE'):
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url = thought.split('BROWSE ')[1]
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action = BrowseURLAction(url=url)
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self.latest_action = action
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return action
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def search_memory(self, query: str) -> list[str]:
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"""
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Uses VectorIndexRetriever to find related memories within the long term memory.
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Uses search to produce top 10 results.
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Parameters:
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- The query that we want to find related memories for
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Returns:
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- A list of top 10 text results that matched the query
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"""
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if self.memory is None:
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return []
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return self.memory.search(query)
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def reset(self) -> None:
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super().reset()
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‎agenthub/monologue_agent/utils/prompts.py‎

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* `owner` - the owner of the repo to push to
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* `repo` - the name of the repo to push to
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* `branch` - the name of the branch to push
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* `recall` - recalls a past memory. Arguments:
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* `query` - the query to search for
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* `message` - make a plan, set a goal, record your thoughts, or ask for more input from the user. Arguments:
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* `content` - the message to record
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* `wait_for_response` - set to `true` to wait for the user to respond before proceeding
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* `finish` - if you're absolutely certain that you've completed your task and have tested your work, use the finish action to stop working.
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You MUST take time to think in between read, write, run, browse, push, and recall actions--do this with the `message` action.
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You MUST take time to think in between read, write, run, browse, and push actions--do this with the `message` action.
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You should never act twice in a row without thinking. But if your last several
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actions are all `message` actions, you should consider taking a different action.
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'It seems like I have some kind of short term memory.',
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'Each of my thoughts seems to be stored in a JSON array.',
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'It seems whatever I say next will be added as an object to the list.',
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'But no one has perfect short-term memory. My list of thoughts will be summarized and condensed over time, losing information in the process.',
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'Fortunately I have long term memory!',
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'I can just perform a recall action, followed by the thing I want to remember. And then related thoughts just spill out!',
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"Sometimes they're random thoughts that don't really have to do with what I wanted to remember. But usually they're exactly what I need!",
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"Let's try it out!",
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'RECALL what it is I want to do',
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"Here's what I want to do: $TASK",
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'How am I going to get there though?',
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"Neat! And it looks like it's easy for me to use the command line too! I just have to perform a run action and include the command I want to run in the command argument. The command output just jumps into my head!",
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"It looks like it's easy for me to use the command line too! I just have to perform a run action and include the command I want to run in the command argument. The command output just jumps into my head!",
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'RUN echo "hello world"',
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'hello world',
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'Cool! I bet I can write files too using the write action.',

‎agenthub/planner_agent/agent.py‎

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messages = [{'content': prompt, 'role': 'user'}]
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resp = self.llm.completion(messages=messages)
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return self.response_parser.parse(resp)
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def search_memory(self, query: str) -> list[str]:
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return []

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