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Update Langchains Agent, rename to Monologue (#402)

Browse Source 
* standardize on content vs contents

* remove langchain dep

* rename langchains to monologue

* unused imports

* Update agenthub/planner_agent/prompt.py

* update locks

* fix code editor

* fix agent list in frontend
This commit is contained in:
Robert Brennan
2024-04-01 11:33:39 -04:00
committed by GitHub
parent 26c9ce132b
commit 3e6508b7f1
26 changed files with 13412 additions and 531 deletions
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3
Pipfile
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@@ -14,9 +14,6 @@ fastapi = "*"
uvicorn = {extras = ["standard"], version = "*"}
ruff = "*"
mypy = "*"
langchain = "*"
langchain-core = "*"
langchain-community = "*"
llama-index = "*"
llama-index-vector-stores-chroma = "*"
chromadb = "*"

313
Pipfile.lock generated
View File

@@ -1,11 +1,11 @@
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"python_version": "3.11"
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@@ -211,13 +211,6 @@
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@@ -1210,66 +1196,23 @@
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@@ -1289,11 +1232,11 @@
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@@ -1388,11 +1331,11 @@
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@@ -1427,6 +1370,14 @@
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"sha256:90b9e29824800e90c84e4022dd5cc16eb2d9605ee13f05d47641eb183cd73d45",
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"sha256:c78e1b00a87ce43bb37642c0812315b411e856a905d58d597750eb79802aaaa3",
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"sha256:ca2870d5d10d8726a27396d3ca4cf7976cec0f3cb706debe88e3a5bd4610f7d2",
"sha256:ccce24b7ad89adb5a1e34a6ba96ac2530046763912806ad4c247356a8f33a67b",
"sha256:cd5e14fbf22a87321b24c88669aad3a51ec052eb145315b3da3b7e3cc105b9a2",
"sha256:ce49c67f4ea0609933d01c0731b34b8695a7a748d6c8d186f95e7d085d2fe475",
"sha256:d33891be6df59d93df4d846640f0e46f1a807339f09e79a8040bc887bdcd7ed3",
"sha256:d3b2348a78bc939b4fed6552abfd2e7988e0f81443ef3911a4b8498ca084f6eb",
"sha256:d886f5d353333b4771d21267c7ecc75b710f1a73d72d03ca06df49b09015a9ef",
"sha256:d93480005693d247f8346bc8ee28c72a2191bdf1f6b5db469c096c0c867ac015",
"sha256:dc1a390a82755a8c26c9964d457d4c9cbec5405896cba94cf51f36ea0d855002",
"sha256:dd78700f5788ae180b5ee8902c6aea5a5726bac7c364b202b4b3e3ba2d293170",
"sha256:e46f38133e5a060d46bd630faa4d9fa0202377495df1f068a8299fd78c84de84",
"sha256:e4b878386c4bf293578b48fc570b84ecfe477d3b77ba39a6e87150af77f40c57",
"sha256:f0d0591a0aeaefdaf9a5e545e7485f89910c977087e7de2b6c388aec32011e9f",
"sha256:fdcbb4068117dfd9ce0138d068ac512843c52295ed996ae6dd1faf537b6dbc27",
"sha256:ff61bfd9253c3915e6d41c651d5f962da23eda633cf02262990094a18a55371a"
],
"markers": "python_version >= '3.8'",
"version": "==10.2.0"
"version": "==10.3.0"
},
"portalocker": {
"hashes": [
@@ -2337,10 +2297,11 @@
},
"pycparser": {
"hashes": [
"sha256:8ee45429555515e1f6b185e78100aea234072576aa43ab53aefcae078162fca9",
"sha256:e644fdec12f7872f86c58ff790da456218b10f863970249516d60a5eaca77206"
"sha256:491c8be9c040f5390f5bf44a5b07752bd07f56edf992381b05c701439eec10f6",
"sha256:c3702b6d3dd8c7abc1afa565d7e63d53a1d0bd86cdc24edd75470f4de499cfcc"
],
"version": "==2.21"
"markers": "python_version >= '3.8'",
"version": "==2.22"
},
"pydantic": {
"hashes": [
@@ -2435,6 +2396,14 @@
"markers": "python_version >= '3.8'",
"version": "==2.16.3"
},
"pygments": {
"hashes": [
"sha256:b27c2826c47d0f3219f29554824c30c5e8945175d888647acd804ddd04af846c",
"sha256:da46cec9fd2de5be3a8a784f434e4c4ab670b4ff54d605c4c2717e9d49c4c367"
],
"markers": "python_version >= '3.7'",
"version": "==2.17.2"
},
"pyjwt": {
"extras": [
"crypto"
@@ -2538,6 +2507,7 @@
"sha256:e324ee90a023d808f1959c46bcbc04446a10ced277783dc6ee09987c37ec10ca",
"sha256:f7b63ef50f1b690dddf550d03497b66d609393b40b564ed0d674909a68ebf16a"
],
"markers": "python_version >= '3.8'",
"version": "==1.0.1"
},
"pytz": {
@@ -2719,6 +2689,13 @@
"markers": "python_version >= '3.4'",
"version": "==2.0.0"
},
"rich": {
"hashes": [
"sha256:4edbae314f59eb482f54e9e30bf00d33350aaa94f4bfcd4e9e3110e64d0d7222",
"sha256:9be308cb1fe2f1f57d67ce99e95af38a1e2bc71ad9813b0e247cf7ffbcc3a432"
],
"version": "==13.7.1"
},
"rsa": {
"hashes": [
"sha256:90260d9058e514786967344d0ef75fa8727eed8a7d2e43ce9f4bcf1b536174f7",
@@ -2950,6 +2927,13 @@
"markers": "python_version >= '3.8'",
"version": "==69.2.0"
},
"shellingham": {
"hashes": [
"sha256:7ecfff8f2fd72616f7481040475a65b2bf8af90a56c89140852d1120324e8686",
"sha256:8dbca0739d487e5bd35ab3ca4b36e11c4078f3a234bfce294b0a0291363404de"
],
"version": "==1.5.4"
},
"six": {
"hashes": [
"sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926",
@@ -3304,11 +3288,30 @@
},
"typer": {
"hashes": [
"sha256:4ce7b2a60b8543816ca97d5ec016026cbe95d1a7a931083b988c1d3682548fe7",
"sha256:f5ae987b97ebbbd59182f8e84407bbc925bc636867fa007bce87a7a71ac81d5c"
"sha256:0441a0bb8962fb4383b8537ada9f7eb2d0deda0caa2cfe7387cc221290f617e4",
"sha256:900fe786ce2d0ea44653d3c8ee4594a22a496a3104370ded770c992c5e3c542d"
],
"markers": "python_version >= '3.7'",
"version": "==0.11.1"
"version": "==0.12.0"
},
"typer-cli": {
"hashes": [
"sha256:603ed3d5a278827bd497e4dc73a39bb714b230371c8724090b0de2abdcdd9f6e",
"sha256:7b7e2dd49f59974bb5a869747045d5444b17bffb851e006cd424f602d3578104"
],
"markers": "python_version >= '3.7'",
"version": "==0.12.0"
},
"typer-slim": {
"extras": [
"standard"
],
"hashes": [
"sha256:3e8a3f17286b173d76dca0fd4e02651c9a2ce1467b3754876b1ac4bd72572beb",
"sha256:ddd7042b29a32140528caa415750bcae54113ba0c32270ca11a6f64069ddadf9"
],
"markers": "python_version >= '3.7'",
"version": "==0.12.0"
},
"typing-extensions": {
"hashes": [

2
agenthub/README.md
View File

@@ -2,7 +2,7 @@
In this folder, there may exist multiple implementations of `Agent` that will be used by the framework.
For example, `agenthub/langchain_agent`, `agenthub/metagpt_agent`, `agenthub/codeact_agent`, etc.
For example, `agenthub/monologue_agent`, `agenthub/metagpt_agent`, `agenthub/codeact_agent`, etc.
Contributors from different backgrounds and interests can choose to contribute to any (or all!) of these directions.
## Constructing an Agent

4
agenthub/__init__.py
View File

@@ -2,8 +2,8 @@ from dotenv import load_dotenv
load_dotenv()
# Import agents after environment variables are loaded
from . import langchains_agent # noqa: E402
from . import monologue_agent # noqa: E402
from . import codeact_agent # noqa: E402
from . import planner_agent # noqa: E402
__all__ = ['langchains_agent', 'codeact_agent', 'planner_agent']
__all__ = ['monologue_agent', 'codeact_agent', 'planner_agent']

4
agenthub/langchains_agent/__init__.py
View File

@@ -1,4 +0,0 @@
from opendevin.agent import Agent
from .langchains_agent import LangchainsAgent
Agent.register("LangchainsAgent", LangchainsAgent)

0
agenthub/langchains_agent/.dockerfileignore → agenthub/monologue_agent/.dockerfileignore
View File

0
agenthub/langchains_agent/.dockerignore → agenthub/monologue_agent/.dockerignore
View File

2
agenthub/langchains_agent/README.md → agenthub/monologue_agent/README.md
View File

@@ -4,5 +4,5 @@ This is currently a standalone utility. It will need to be integrated into OpenD
## Usage
```bash
# Run this in project root
./agenthub/langchains_agent/build-and-run.sh "write a bash script that prints 'hello world'"
./agenthub/monologue_agent/build-and-run.sh "write a bash script that prints 'hello world'"
```

0
agenthub/langchains_agent/TODO.md → agenthub/monologue_agent/TODO.md
View File

4
agenthub/monologue_agent/__init__.py Normal file
View File

@@ -0,0 +1,4 @@
from opendevin.agent import Agent
from .agent import MonologueAgent
Agent.register("MonologueAgent", MonologueAgent)

73
agenthub/langchains_agent/langchains_agent.py → agenthub/monologue_agent/agent.py
View File

@@ -1,11 +1,31 @@
from typing import List
from opendevin.agent import Agent
from opendevin.state import State
from opendevin.action import Action
from opendevin.llm.llm import LLM
import agenthub.langchains_agent.utils.prompts as prompts
from agenthub.langchains_agent.utils.monologue import Monologue
from agenthub.langchains_agent.utils.memory import LongTermMemory
from opendevin.action import (
Action,
NullAction,
CmdRunAction,
FileWriteAction,
FileReadAction,
AgentRecallAction,
BrowseURLAction,
AgentThinkAction,
)
from opendevin.observation import (
Observation,
NullObservation,
CmdOutputObservation,
FileReadObservation,
AgentRecallObservation,
BrowserOutputObservation,
)
import agenthub.monologue_agent.utils.prompts as prompts
from agenthub.monologue_agent.utils.monologue import Monologue
from agenthub.monologue_agent.utils.memory import LongTermMemory
MAX_MONOLOGUE_LENGTH = 20000
MAX_OUTPUT_LENGTH = 5000
@@ -56,7 +76,7 @@ INITIAL_THOUGHTS = [
]
class LangchainsAgent(Agent):
class MonologueAgent(Agent):
_initialized = False
def __init__(self, llm: LLM):
@@ -82,40 +102,47 @@ class LangchainsAgent(Agent):
self.monologue = Monologue()
self.memory = LongTermMemory()
next_is_output = False
output_type = ""
for thought in INITIAL_THOUGHTS:
thought = thought.replace("$TASK", task)
if next_is_output:
d = {"action": "output", "args": {"output": thought}}
next_is_output = False
if output_type != "":
observation: Observation = NullObservation(content="")
if output_type == "run":
observation = CmdOutputObservation(content=thought, command_id=0, command="")
elif output_type == "read":
observation = FileReadObservation(content=thought, path="")
elif output_type == "recall":
observation = AgentRecallObservation(content=thought, memories=[])
elif output_type == "browse":
observation = BrowserOutputObservation(content=thought, url="")
self._add_event(observation.to_dict())
output_type = ""
else:
action: Action = NullAction()
if thought.startswith("RUN"):
command = thought.split("RUN ")[1]
d = {"action": "run", "args": {"command": command}}
next_is_output = True
action = CmdRunAction(command)
output_type = "run"
elif thought.startswith("WRITE"):
parts = thought.split("WRITE ")[1].split(" > ")
path = parts[1]
content = parts[0]
d = {"action": "write", "args": {"file": path, "content": content}}
next_is_output = True
action = FileWriteAction(path=path, content=content)
elif thought.startswith("READ"):
path = thought.split("READ ")[1]
d = {"action": "read", "args": {"file": path}}
next_is_output = True
action = FileReadAction(path=path)
output_type = "read"
elif thought.startswith("RECALL"):
query = thought.split("RECALL ")[1]
d = {"action": "recall", "args": {"query": query}}
next_is_output = True
action = AgentRecallAction(query=query)
output_type = "recall"
elif thought.startswith("BROWSE"):
url = thought.split("BROWSE ")[1]
d = {"action": "browse", "args": {"url": url}}
next_is_output = True
action = BrowseURLAction(url=url)
output_type = "browse"
else:
d = {"action": "think", "args": {"thought": thought}}
self._add_event(d)
action = AgentThinkAction(thought=thought)
self._add_event(action.to_dict())
self._initialized = True
def step(self, state: State) -> Action:

0
agenthub/langchains_agent/utils/json.py → agenthub/monologue_agent/utils/json.py
View File

0
agenthub/langchains_agent/utils/memory.py → agenthub/monologue_agent/utils/memory.py
View File

4
agenthub/langchains_agent/utils/monologue.py → agenthub/monologue_agent/utils/monologue.py
View File

@@ -1,7 +1,7 @@
import traceback
import agenthub.langchains_agent.utils.json as json
import agenthub.langchains_agent.utils.prompts as prompts
import agenthub.monologue_agent.utils.json as json
import agenthub.monologue_agent.utils.prompts as prompts
class Monologue:
def __init__(self):

45
agenthub/langchains_agent/utils/prompts.py → agenthub/monologue_agent/utils/prompts.py
View File

@@ -1,13 +1,5 @@
from typing import List
from langchain.prompts import PromptTemplate
from opendevin import config
if config.get_or_default("DEBUG", False):
from langchain.globals import set_debug
set_debug(True)
from . import json
from opendevin.action import (
@@ -19,12 +11,15 @@ from opendevin.observation import (
)
ACTION_PROMPT = """
You're a thoughtful robot. Your main task is to {task}.
You're a thoughtful robot. Your main task is this:
%(task)s
Don't expand the scope of your task--just complete it as written.
This is your internal monologue, in JSON format:
```json
{monologue}
%(monologue)s
```
Your most recent thought is at the bottom of that monologue. Continue your train of thought.
@@ -34,11 +29,11 @@ It must be an object, and it must contain two fields:
* `args`, which is a map of key-value pairs, specifying the arguments for that action
Here are the possible actions:
* `read` - reads the contents of a file. Arguments:
* `read` - reads the content of a file. Arguments:
* `path` - the path of the file to read
* `write` - writes the contents to a file. Arguments:
* `write` - writes the content to a file. Arguments:
* `path` - the path of the file to write
* `contents` - the contents to write to the file
* `content` - the content to write to the file
* `run` - runs a command. Arguments:
* `command` - the command to run
* `background` - if true, run the command in the background, so that other commands can be run concurrently. Useful for e.g. starting a server. You won't be able to see the logs. You don't need to end the command with `&`, just set this to true.
@@ -52,7 +47,7 @@ Here are the possible actions:
* `thought` - the thought to record
* `finish` - if you're absolutely certain that you've completed your task and have tested your work, use the finish action to stop working.
{background_commands}
%(background_commands)s
You MUST take time to think in between read, write, run, browse, and recall actions.
You should never act twice in a row without thinking. But if your last several
@@ -65,7 +60,7 @@ Notes:
What is your next thought or action? Again, you must reply with JSON, and only with JSON.
{hint}
%(hint)s
"""
MONOLOGUE_SUMMARY_PROMPT = """
@@ -77,7 +72,7 @@ internal monologue. You can summarize individual thoughts, and
you can condense related thoughts together with a description
of their content.
```json
{monologue}
%(monologue)s
```
Make the summaries as pithy and informative as possible.
Be specific about what happened and what was learned. The summary
@@ -93,8 +88,9 @@ You can also use the same action and args from the source monologue.
def get_summarize_monologue_prompt(thoughts):
prompt = PromptTemplate.from_template(MONOLOGUE_SUMMARY_PROMPT)
return prompt.format(monologue=json.dumps({'old_monologue': thoughts}, indent=2))
return MONOLOGUE_SUMMARY_PROMPT % {
'monologue': json.dumps({'old_monologue': thoughts}, indent=2),
}
def get_request_action_prompt(
task: str,
@@ -121,13 +117,12 @@ def get_request_action_prompt(
bg_commands_message += "\nYou can end any process by sending a `kill` action with the numerical `id` above."
latest_thought = thoughts[-1]
prompt = PromptTemplate.from_template(ACTION_PROMPT)
return prompt.format(
task=task,
monologue=json.dumps(thoughts, indent=2),
background_commands=bg_commands_message,
hint=hint,
)
return ACTION_PROMPT % {
'task': task,
'monologue': json.dumps(thoughts, indent=2),
'background_commands': bg_commands_message,
'hint': hint,
}
def parse_action_response(response: str) -> Action:
json_start = response.find("{")

10
agenthub/planner_agent/prompt.py
View File

@@ -97,11 +97,11 @@ It must be an object, and it must contain two fields:
* `action`, which is one of the actions below
* `args`, which is a map of key-value pairs, specifying the arguments for that action
* `read` - reads the contents of a file. Arguments:
* `read` - reads the content of a file. Arguments:
* `path` - the path of the file to read
* `write` - writes the contents to a file. Arguments:
* `write` - writes the content to a file. Arguments:
* `path` - the path of the file to write
* `contents` - the contents to write to the file
* `content` - the content to write to the file
* `run` - runs a command on the command line in a Linux shell. Arguments:
* `command` - the command to run
* `background` - if true, run the command in the background, so that other commands can be run concurrently. Useful for e.g. starting a server. You won't be able to see the logs. You don't need to end the command with `&`, just set this to true.
@@ -192,9 +192,9 @@ def parse_response(response: str) -> Action:
json_end = response.rfind("}") + 1
response = response[json_start:json_end]
action_dict = json.loads(response)
if 'content' in action_dict:
if 'contents' in action_dict:
# The LLM gets confused here. Might as well be robust
action_dict['contents'] = action_dict.pop('content')
action_dict['content'] = action_dict.pop('contents')
action = action_from_dict(action_dict)
return action

13438
frontend/package-lock.json generated
View File

File diff suppressed because it is too large Load Diff

9
frontend/src/components/SettingModal.tsx
View File

@@ -17,6 +17,7 @@ import {
changeDirectory as sendChangeDirectorySocketMessage,
changeModel,
fetchModels,
fetchAgents,
INITIAL_MODELS,
} from "../services/settingsService";
@@ -43,9 +44,9 @@ function SettingModal({ isOpen, onClose }: Props): JSX.Element {
cachedModels.length > 0 ? cachedModels : INITIAL_MODELS,
);
const [agent, setAgent] = useState(
localStorage.getItem("agent") || "LangchainsAgent",
localStorage.getItem("agent") || "MonologueAgent",
);
const [supportedAgents] = useState(
const [supportedAgents, setSupportedAgents] = useState(
cachedAgents.length > 0 ? cachedAgents : INITIAL_AGENTS,
);
@@ -54,6 +55,10 @@ function SettingModal({ isOpen, onClose }: Props): JSX.Element {
setSupportedModels(fetchedModels);
localStorage.setItem("supportedModels", JSON.stringify(fetchedModels));
});
fetchAgents().then((fetchedAgents) => {
setSupportedAgents(fetchedAgents);
localStorage.setItem("supportedAgents", JSON.stringify(fetchedAgents));
});
}, []);
const handleSaveCfg = () => {

2
frontend/src/services/settingsService.ts
View File

@@ -23,7 +23,7 @@ export const INITIAL_MODELS = [
export type Model = (typeof INITIAL_MODELS)[number];
export const INITIAL_AGENTS = ["LangchainsAgent", "CodeActAgent"];
export const INITIAL_AGENTS = ["MonologueAgent", "CodeActAgent"];
export type Agent = (typeof INITIAL_AGENTS)[number];

2
frontend/src/socket/actions.ts
View File

@@ -20,7 +20,7 @@ const messageActions = {
store.dispatch(setScreenshotSrc(screenshotSrc));
},
write: (message: ActionMessage) => {
store.dispatch(setCode(message.args.contents));
store.dispatch(setCode(message.args.content));
},
think: (message: ActionMessage) => {
store.dispatch(appendAssistantMessage(message.args.thought));

4
opendevin/action/fileop.py
View File

@@ -33,13 +33,13 @@ class FileReadAction(ExecutableAction):
@dataclass
class FileWriteAction(ExecutableAction):
path: str
contents: str
content: str
action: str = "write"
def run(self, controller) -> FileWriteObservation:
path = resolve_path(controller.workdir, self.path)
with open(path, 'w', encoding='utf-8') as file:
file.write(self.contents)
file.write(self.content)
return FileWriteObservation(content="", path=self.path)
@property

4
opendevin/main.py
View File

@@ -4,7 +4,7 @@ import sys
from typing import Type
import agenthub # noqa F401 (we import this to get the agents registered)
from opendevin import config
from opendevin import config
from opendevin.agent import Agent
from opendevin.controller import AgentController
from opendevin.llm.llm import LLM
@@ -24,7 +24,7 @@ def parse_arguments():
parser.add_argument("-d", "--directory", required=True, type=str, help="The working directory for the agent")
parser.add_argument("-t", "--task", type=str, default="", help="The task for the agent to perform")
parser.add_argument("-f", "--file", type=str, help="Path to a file containing the task. Overrides -t if both are provided.")
parser.add_argument("-c", "--agent-cls", default="LangchainsAgent", type=str, help="The agent class to use")
parser.add_argument("-c", "--agent-cls", default="MonologueAgent", type=str, help="The agent class to use")
parser.add_argument("-m", "--model-name", default=config.get_or_default("LLM_MODEL", "gpt-4-0125-preview"), type=str, help="The (litellm) model name to use")
parser.add_argument("-i", "--max-iterations", default=100, type=int, help="The maximum number of iterations to run the agent")
return parser.parse_args()

10
opendevin/server/README.md
View File

@@ -60,11 +60,11 @@ This list may grow over time.
* `agent_cls` - the class of the agent to use
* `start` - starts a new development task. Only sent by the client.
* `task` - the task to start
* `read` - reads the contents of a file.
* `read` - reads the content of a file.
* `path` - the path of the file to read
* `write` - writes the contents to a file.
* `write` - writes the content to a file.
* `path` - the path of the file to write
* `contents` - the contents to write to the file
* `content` - the content to write to the file
* `run` - runs a command.
* `command` - the command to run
* `background` - if true, run the command in the background
@@ -87,9 +87,9 @@ An observation has four parts:
There are several kinds of observations. Their extras are listed below.
This list may grow over time.
* `read` - the contents of a file
* `read` - the content of a file
* `path` - the path of the file read
* `browse` - the HTML contents of a url
* `browse` - the HTML content of a url
* `url` - the URL opened
* `run` - the output of a command
* `command` - the command run

4
opendevin/server/schema/action.py
View File

@@ -11,11 +11,11 @@ class ActionType(str, Enum):
"""
READ = "read"
"""Reads the contents of a file.
"""Reads the content of a file.
"""
WRITE = "write"
"""Writes the contents to a file.
"""Writes the content to a file.
"""
RUN = "run"

4
opendevin/server/schema/observation.py
View File

@@ -3,11 +3,11 @@ from enum import Enum
class ObservationType(str, Enum):
READ = "read"
"""The contents of a file
"""The content of a file
"""
BROWSE = "browse"
"""The HTML contents of a URL
"""The HTML content of a URL
"""
RUN = "run"

2
opendevin/server/session.py
View File

@@ -112,7 +112,7 @@ class Session:
directory = DEFAULT_WORKSPACE_DIR
if start_event and "directory" in start_event["args"]:
directory = start_event["args"]["directory"]
agent_cls = "LangchainsAgent"
agent_cls = "MonologueAgent"
if start_event and "agent_cls" in start_event["args"]:
agent_cls = start_event["args"]["agent_cls"]
model = LLM_MODEL