update langchain integration (#2388)

This commit is contained in:
LawyZheng
2025-05-19 16:07:02 +08:00
committed by GitHub
parent 19ab386100
commit f9d3f3e2dc
6 changed files with 907 additions and 433 deletions

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@@ -42,7 +42,7 @@ Go to [Langchain Tools](https://python.langchain.com/v0.1/docs/modules/tools/) t
### Run a task(sync) locally in your local environment
> sync task won't return until the task is finished.
:warning: :warning: if you want to run this code block, you need to run `skyvern init --openai-api-key <your_openai_api_key>` command in your terminal to set up skyvern first.
:warning: :warning: if you want to run this code block, you need to run `skyvern init` command in your terminal to set up skyvern first.
```python
@@ -65,7 +65,7 @@ if __name__ == "__main__":
:warning: :warning: if you want to run the task in the background, you need to keep the script running until the task is finished, otherwise the task will be killed when the script is finished.
:warning: :warning: if you want to run this code block, you need to run `skyvern init --openai-api-key <your_openai_api_key>` command in your terminal to set up skyvern first.
:warning: :warning: if you want to run this code block, you need to run `skyvern init` command in your terminal to set up skyvern first.
```python
import asyncio
@@ -88,7 +88,7 @@ if __name__ == "__main__":
### Get a task locally in your local environment
:warning: :warning: if you want to run this code block, you need to run `skyvern init --openai-api-key <your_openai_api_key>` command in your terminal to set up skyvern first.
:warning: :warning: if you want to run this code block, you need to run `skyvern init` command in your terminal to set up skyvern first.
```python
import asyncio
@@ -191,7 +191,7 @@ The following two examples show how to build an agent that executes a specified
> async task will return immediately and the task will be running in the background. You can use `GetTask` tool to poll the task information until the task is finished.
:warning: :warning: if you want to run this code block, you need to run `skyvern init --openai-api-key <your_openai_api_key>` command in your terminal to set up skyvern first.
:warning: :warning: if you want to run this code block, you need to run `skyvern init` command in your terminal to set up skyvern first.
```python
import asyncio

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@@ -1,6 +1,6 @@
[tool.poetry]
name = "skyvern-langchain"
version = "0.1.6"
version = "0.1.7"
description = ""
authors = ["lawyzheng <lawy@skyvern.com>"]
packages = [{ include = "skyvern_langchain" }]
@@ -8,7 +8,7 @@ readme = "README.md"
[tool.poetry.dependencies]
python = "^3.11,<3.12"
skyvern = "^0.1.56"
skyvern = ">=0.1.84"
langchain = "^0.3.19"

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@@ -1,4 +1,4 @@
from typing import Any, Literal, Type
from typing import Any, Type
from langchain.tools import BaseTool
from litellm import BaseModel
@@ -6,52 +6,33 @@ from pydantic import Field
from skyvern_langchain.schema import CreateTaskInput, GetTaskInput
from skyvern_langchain.settings import settings
from skyvern.agent import SkyvernAgent
from skyvern.forge import app
from skyvern.forge.prompts import prompt_engine
from skyvern.forge.sdk.schemas.task_generations import TaskGenerationBase
from skyvern.forge.sdk.schemas.task_v2 import TaskV2, TaskV2Request
from skyvern.forge.sdk.schemas.tasks import CreateTaskResponse, TaskRequest, TaskResponse
from skyvern import Skyvern
from skyvern.client.agent.types.agent_get_run_response import AgentGetRunResponse
from skyvern.client.types.task_run_response import TaskRunResponse
from skyvern.schemas.runs import RunEngine
class SkyvernTaskBaseTool(BaseTool):
engine: Literal["TaskV1", "TaskV2"] = Field(default=settings.engine)
engine: RunEngine = Field(default=settings.engine)
run_task_timeout_seconds: int = Field(default=settings.run_task_timeout_seconds)
agent: SkyvernAgent = SkyvernAgent()
agent: Skyvern = Skyvern(base_url=None, api_key=None)
def _run(self, *args: Any, **kwargs: Any) -> None:
raise NotImplementedError("skyvern task tool does not support sync")
# TODO: agent haven't exposed the task v1 generate function, we can migrate to use agent interface when it's available
async def _generate_v1_task_request(self, user_prompt: str) -> TaskGenerationBase:
llm_prompt = prompt_engine.load_prompt("generate-task", user_prompt=user_prompt)
llm_response = await app.LLM_API_HANDLER(prompt=llm_prompt, prompt_name="generate-task")
return TaskGenerationBase.model_validate(llm_response)
class RunTask(SkyvernTaskBaseTool):
name: str = "run-skyvern-agent-task"
description: str = """Use Skyvern agent to run a task. This function won't return until the task is finished."""
args_schema: Type[BaseModel] = CreateTaskInput
async def _arun(self, user_prompt: str, url: str | None = None) -> TaskResponse | TaskV2:
if self.engine == "TaskV1":
return await self._arun_task_v1(user_prompt=user_prompt, url=url)
else:
return await self._arun_task_v2(user_prompt=user_prompt, url=url)
async def _arun_task_v1(self, user_prompt: str, url: str | None = None) -> TaskResponse:
task_generation = await self._generate_v1_task_request(user_prompt=user_prompt)
task_request = TaskRequest.model_validate(task_generation, from_attributes=True)
if url is not None:
task_request.url = url
return await self.agent.run_task_v1(task_request=task_request, timeout_seconds=self.run_task_timeout_seconds)
async def _arun_task_v2(self, user_prompt: str, url: str | None = None) -> TaskV2:
task_request = TaskV2Request(user_prompt=user_prompt, url=url)
return await self.agent.run_observer_task_v_2(
task_request=task_request, timeout_seconds=self.run_task_timeout_seconds
async def _arun(self, user_prompt: str, url: str | None = None) -> TaskRunResponse:
return await self.agent.run_task(
prompt=user_prompt,
url=url,
engine=self.engine,
timeout=self.run_task_timeout_seconds,
wait_for_completion=True,
)
@@ -60,23 +41,14 @@ class DispatchTask(SkyvernTaskBaseTool):
description: str = """Use Skyvern agent to dispatch a task. This function will return immediately and the task will be running in the background."""
args_schema: Type[BaseModel] = CreateTaskInput
async def _arun(self, user_prompt: str, url: str | None = None) -> CreateTaskResponse | TaskV2:
if self.engine == "TaskV1":
return await self._arun_task_v1(user_prompt=user_prompt, url=url)
else:
return await self._arun_task_v2(user_prompt=user_prompt, url=url)
async def _arun_task_v1(self, user_prompt: str, url: str | None = None) -> CreateTaskResponse:
task_generation = await self._generate_v1_task_request(user_prompt=user_prompt)
task_request = TaskRequest.model_validate(task_generation, from_attributes=True)
if url is not None:
task_request.url = url
return await self.agent.create_task_v1(task_request=task_request)
async def _arun_task_v2(self, user_prompt: str, url: str | None = None) -> TaskV2:
task_request = TaskV2Request(user_prompt=user_prompt, url=url)
return await self.agent.observer_task_v_2(task_request=task_request)
async def _arun(self, user_prompt: str, url: str | None = None) -> TaskRunResponse:
return await self.agent.run_task(
prompt=user_prompt,
url=url,
engine=self.engine,
timeout=self.run_task_timeout_seconds,
wait_for_completion=False,
)
class GetTask(SkyvernTaskBaseTool):
@@ -84,14 +56,5 @@ class GetTask(SkyvernTaskBaseTool):
description: str = """Use Skyvern agent to get a task."""
args_schema: Type[BaseModel] = GetTaskInput
async def _arun(self, task_id: str) -> TaskResponse | TaskV2 | None:
if self.engine == "TaskV1":
return await self._arun_task_v1(task_id=task_id)
else:
return await self._arun_task_v2(task_id=task_id)
async def _arun_task_v1(self, task_id: str) -> TaskResponse | None:
return await self.agent.get_task(task_id=task_id)
async def _arun_task_v2(self, task_id: str) -> TaskV2 | None:
return await self.agent.get_observer_task_v_2(task_id=task_id)
async def _arun(self, task_id: str) -> AgentGetRunResponse | None:
return await self.agent.get_run(run_id=task_id)

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@@ -1,30 +1,23 @@
from typing import Any, Dict, Literal, Type
from typing import Any, Type
from httpx import AsyncClient
from langchain.tools import BaseTool
from pydantic import BaseModel, Field
from skyvern_langchain.schema import CreateTaskInput, GetTaskInput
from skyvern_langchain.settings import settings
from skyvern.client import AsyncSkyvern
from skyvern.forge.sdk.schemas.task_v2 import TaskV2Request
from skyvern.forge.sdk.schemas.tasks import CreateTaskResponse, TaskRequest, TaskResponse
from skyvern import Skyvern
from skyvern.client.types.task_run_response import TaskRunResponse
from skyvern.schemas.runs import RunEngine
class SkyvernTaskBaseTool(BaseTool):
api_key: str = Field(default=settings.api_key)
base_url: str = Field(default=settings.base_url)
engine: Literal["TaskV1", "TaskV2"] = Field(default=settings.engine)
engine: RunEngine = Field(default=settings.engine)
run_task_timeout_seconds: int = Field(default=settings.run_task_timeout_seconds)
def get_client(self) -> AsyncSkyvern:
httpx_client = AsyncClient(
headers={
"Content-Type": "application/json",
"x-api-key": self.api_key,
},
)
return AsyncSkyvern(base_url=self.base_url, httpx_client=httpx_client)
def get_client(self) -> Skyvern:
return Skyvern(base_url=self.base_url, api_key=self.api_key)
def _run(self, *args: Any, **kwargs: Any) -> None:
raise NotImplementedError("skyvern task tool does not support sync")
@@ -35,41 +28,13 @@ class RunTask(SkyvernTaskBaseTool):
description: str = """Use Skyvern client to run a task. This function won't return until the task is finished."""
args_schema: Type[BaseModel] = CreateTaskInput
async def _arun(self, user_prompt: str, url: str | None = None) -> TaskResponse | Dict[str, Any | None]:
if self.engine == "TaskV1":
return await self._arun_task_v1(user_prompt=user_prompt, url=url)
else:
return await self._arun_task_v2(user_prompt=user_prompt, url=url)
async def _arun_task_v1(self, user_prompt: str, url: str | None = None) -> TaskResponse:
task_generation = await self.get_client().agent.generate_task(
async def _arun(self, user_prompt: str, url: str | None = None) -> TaskRunResponse:
return await self.get_client().run_task(
timeout=self.run_task_timeout_seconds,
url=url,
prompt=user_prompt,
)
task_request = TaskRequest.model_validate(task_generation, from_attributes=True)
if url is not None:
task_request.url = url
return await self.get_client().agent.run_task_v1(
timeout_seconds=self.run_task_timeout_seconds,
url=task_request.url,
title=task_request.title,
navigation_goal=task_request.navigation_goal,
data_extraction_goal=task_request.data_extraction_goal,
navigation_payload=task_request.navigation_goal,
error_code_mapping=task_request.error_code_mapping,
extracted_information_schema=task_request.extracted_information_schema,
complete_criterion=task_request.complete_criterion,
terminate_criterion=task_request.terminate_criterion,
)
async def _arun_task_v2(self, user_prompt: str, url: str | None = None) -> TaskResponse:
task_request = TaskV2Request(url=url, user_prompt=user_prompt)
return await self.get_client().agent.run_observer_task_v_2(
timeout_seconds=self.run_task_timeout_seconds,
user_prompt=task_request.user_prompt,
url=task_request.url,
browser_session_id=task_request.browser_session_id,
engine=self.engine,
wait_for_completion=True,
)
@@ -78,39 +43,13 @@ class DispatchTask(SkyvernTaskBaseTool):
description: str = """Use Skyvern client to dispatch a task. This function will return immediately and the task will be running in the background."""
args_schema: Type[BaseModel] = CreateTaskInput
async def _arun(self, user_prompt: str, url: str | None = None) -> CreateTaskResponse | Dict[str, Any | None]:
if self.engine == "TaskV1":
return await self._arun_task_v1(user_prompt=user_prompt, url=url)
else:
return await self._arun_task_v2(user_prompt=user_prompt, url=url)
async def _arun_task_v1(self, user_prompt: str, url: str | None = None) -> CreateTaskResponse:
task_generation = await self.get_client().agent.generate_task(
async def _arun(self, user_prompt: str, url: str | None = None) -> TaskRunResponse:
return await self.get_client().run_task(
timeout=self.run_task_timeout_seconds,
url=url,
prompt=user_prompt,
)
task_request = TaskRequest.model_validate(task_generation, from_attributes=True)
if url is not None:
task_request.url = url
return await self.get_client().agent.create_task(
url=task_request.url,
title=task_request.title,
navigation_goal=task_request.navigation_goal,
data_extraction_goal=task_request.data_extraction_goal,
navigation_payload=task_request.navigation_goal,
error_code_mapping=task_request.error_code_mapping,
extracted_information_schema=task_request.extracted_information_schema,
complete_criterion=task_request.complete_criterion,
terminate_criterion=task_request.terminate_criterion,
)
async def _arun_task_v2(self, user_prompt: str, url: str | None = None) -> Dict[str, Any | None]:
task_request = TaskV2Request(url=url, user_prompt=user_prompt)
return await self.get_client().agent.observer_task_v_2(
user_prompt=task_request.user_prompt,
url=task_request.url,
browser_session_id=task_request.browser_session_id,
engine=self.engine,
wait_for_completion=False,
)
@@ -119,14 +58,5 @@ class GetTask(SkyvernTaskBaseTool):
description: str = """Use Skyvern client to get a task."""
args_schema: Type[BaseModel] = GetTaskInput
async def _arun(self, task_id: str) -> Dict[str, Any | None]:
if self.engine == "TaskV1":
return await self._arun_task_v1(task_id=task_id)
else:
return await self._arun_task_v2(task_id=task_id)
async def _arun_task_v1(self, task_id: str) -> TaskResponse:
return await self.get_client().agent.get_task(task_id=task_id)
async def _arun_task_v2(self, task_id: str) -> Dict[str, Any | None]:
return await self.get_client().agent.get_observer_task_v_2(task_id=task_id)
async def _arun(self, task_id: str) -> TaskRunResponse:
return await self.get_client().get_run(run_id=task_id)

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@@ -1,13 +1,13 @@
from typing import Literal
from dotenv import load_dotenv
from pydantic_settings import BaseSettings
from skyvern.schemas.runs import RunEngine
class Settings(BaseSettings):
api_key: str = ""
base_url: str = "https://api.skyvern.com"
engine: Literal["TaskV1", "TaskV2"] = "TaskV2"
engine: RunEngine = RunEngine.skyvern_v2
run_task_timeout_seconds: int = 60 * 60
class Config: