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Code Issues Packages Projects Releases Wiki Activity

Harrison/official pre release (#8106)

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This commit is contained in:
Harrison Chase
2023-07-21 18:44:32 -07:00
committed by GitHub
parent 95bcf68802
commit aa0e69bc98
65 changed files with 210 additions and 602 deletions
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51
libs/langchain/langchain/agents/agent_toolkits/github/toolkit.py
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@@ -1,8 +1,17 @@
"""GitHub Toolkit."""
from typing import List
from typing import Dict, List
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.tools import BaseTool
from langchain.tools.github.prompt import (
COMMENT_ON_ISSUE_PROMPT,
CREATE_FILE_PROMPT,
DELETE_FILE_PROMPT,
GET_ISSUE_PROMPT,
GET_ISSUES_PROMPT,
READ_FILE_PROMPT,
UPDATE_FILE_PROMPT,
)
from langchain.tools.github.tool import GitHubAction
from langchain.utilities.github import GitHubAPIWrapper
@@ -16,7 +25,43 @@ class GitHubToolkit(BaseToolkit):
def from_github_api_wrapper(
cls, github_api_wrapper: GitHubAPIWrapper
) -> "GitHubToolkit":
actions = github_api_wrapper.list()
operations: List[Dict] = [
{
"mode": "get_issues",
"name": "Get Issues",
"description": GET_ISSUES_PROMPT,
},
{
"mode": "get_issue",
"name": "Get Issue",
"description": GET_ISSUE_PROMPT,
},
{
"mode": "comment_on_issue",
"name": "Comment on Issue",
"description": COMMENT_ON_ISSUE_PROMPT,
},
{
"mode": "create_file",
"name": "Create File",
"description": CREATE_FILE_PROMPT,
},
{
"mode": "read_file",
"name": "Read File",
"description": READ_FILE_PROMPT,
},
{
"mode": "update_file",
"name": "Update File",
"description": UPDATE_FILE_PROMPT,
},
{
"mode": "delete_file",
"name": "Delete File",
"description": DELETE_FILE_PROMPT,
},
]
tools = [
GitHubAction(
name=action["name"],
@@ -24,7 +69,7 @@ class GitHubToolkit(BaseToolkit):
mode=action["mode"],
api_wrapper=github_api_wrapper,
)
for action in actions
for action in operations
]
return cls(tools=tools)

39
libs/langchain/langchain/agents/agent_toolkits/jira/toolkit.py
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@@ -1,7 +1,14 @@
from typing import List
from typing import Dict, List
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.tools import BaseTool
from langchain.tools.jira.prompt import (
JIRA_CATCH_ALL_PROMPT,
JIRA_CONFLUENCE_PAGE_CREATE_PROMPT,
JIRA_GET_ALL_PROJECTS_PROMPT,
JIRA_ISSUE_CREATE_PROMPT,
JIRA_JQL_PROMPT,
)
from langchain.tools.jira.tool import JiraAction
from langchain.utilities.jira import JiraAPIWrapper
@@ -13,7 +20,33 @@ class JiraToolkit(BaseToolkit):
@classmethod
def from_jira_api_wrapper(cls, jira_api_wrapper: JiraAPIWrapper) -> "JiraToolkit":
actions = jira_api_wrapper.list()
operations: List[Dict] = [
{
"mode": "jql",
"name": "JQL Query",
"description": JIRA_JQL_PROMPT,
},
{
"mode": "get_projects",
"name": "Get Projects",
"description": JIRA_GET_ALL_PROJECTS_PROMPT,
},
{
"mode": "create_issue",
"name": "Create Issue",
"description": JIRA_ISSUE_CREATE_PROMPT,
},
{
"mode": "other",
"name": "Catch all Jira API call",
"description": JIRA_CATCH_ALL_PROMPT,
},
{
"mode": "create_page",
"name": "Create confluence page",
"description": JIRA_CONFLUENCE_PAGE_CREATE_PROMPT,
},
]
tools = [
JiraAction(
name=action["name"],
@@ -21,7 +54,7 @@ class JiraToolkit(BaseToolkit):
mode=action["mode"],
api_wrapper=jira_api_wrapper,
)
for action in actions
for action in operations
]
return cls(tools=tools)

2
libs/langchain/langchain/utilities/__init__.py
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@@ -1,6 +1,5 @@
"""General utilities."""
from langchain.requests import TextRequestsWrapper
from langchain.utilities.apify import ApifyWrapper
from langchain.utilities.arxiv import ArxivAPIWrapper
from langchain.utilities.awslambda import LambdaWrapper
from langchain.utilities.bash import BashProcess
@@ -32,7 +31,6 @@ from langchain.utilities.wolfram_alpha import WolframAlphaAPIWrapper
from langchain.utilities.zapier import ZapierNLAWrapper
__all__ = [
"ApifyWrapper",
"ArxivAPIWrapper",
"GoldenQueryAPIWrapper",
"BashProcess",

205
libs/langchain/langchain/utilities/apify.py
View File

@@ -1,205 +0,0 @@
from typing import Any, Callable, Dict, Optional
from pydantic import BaseModel, root_validator
from langchain.document_loaders import ApifyDatasetLoader
from langchain.document_loaders.base import Document
from langchain.utils import get_from_dict_or_env
class ApifyWrapper(BaseModel):
"""Wrapper around Apify.
To use, you should have the ``apify-client`` python package installed,
and the environment variable ``APIFY_API_TOKEN`` set with your API key, or pass
`apify_api_token` as a named parameter to the constructor.
"""
apify_client: Any
apify_client_async: Any
@root_validator()
def validate_environment(cls, values: Dict) -> Dict:
"""Validate environment.
Validate that an Apify API token is set and the apify-client
Python package exists in the current environment.
"""
apify_api_token = get_from_dict_or_env(
values, "apify_api_token", "APIFY_API_TOKEN"
)
try:
from apify_client import ApifyClient, ApifyClientAsync
values["apify_client"] = ApifyClient(apify_api_token)
values["apify_client_async"] = ApifyClientAsync(apify_api_token)
except ImportError:
raise ValueError(
"Could not import apify-client Python package. "
"Please install it with `pip install apify-client`."
)
return values
def call_actor(
self,
actor_id: str,
run_input: Dict,
dataset_mapping_function: Callable[[Dict], Document],
*,
build: Optional[str] = None,
memory_mbytes: Optional[int] = None,
timeout_secs: Optional[int] = None,
) -> ApifyDatasetLoader:
"""Run an Actor on the Apify platform and wait for results to be ready.
Args:
actor_id (str): The ID or name of the Actor on the Apify platform.
run_input (Dict): The input object of the Actor that you're trying to run.
dataset_mapping_function (Callable): A function that takes a single
dictionary (an Apify dataset item) and converts it to an
instance of the Document class.
build (str, optional): Optionally specifies the actor build to run.
It can be either a build tag or build number.
memory_mbytes (int, optional): Optional memory limit for the run,
in megabytes.
timeout_secs (int, optional): Optional timeout for the run, in seconds.
Returns:
ApifyDatasetLoader: A loader that will fetch the records from the
Actor run's default dataset.
"""
actor_call = self.apify_client.actor(actor_id).call(
run_input=run_input,
build=build,
memory_mbytes=memory_mbytes,
timeout_secs=timeout_secs,
)
return ApifyDatasetLoader(
dataset_id=actor_call["defaultDatasetId"],
dataset_mapping_function=dataset_mapping_function,
)
async def acall_actor(
self,
actor_id: str,
run_input: Dict,
dataset_mapping_function: Callable[[Dict], Document],
*,
build: Optional[str] = None,
memory_mbytes: Optional[int] = None,
timeout_secs: Optional[int] = None,
) -> ApifyDatasetLoader:
"""Run an Actor on the Apify platform and wait for results to be ready.
Args:
actor_id (str): The ID or name of the Actor on the Apify platform.
run_input (Dict): The input object of the Actor that you're trying to run.
dataset_mapping_function (Callable): A function that takes a single
dictionary (an Apify dataset item) and converts it to
an instance of the Document class.
build (str, optional): Optionally specifies the actor build to run.
It can be either a build tag or build number.
memory_mbytes (int, optional): Optional memory limit for the run,
in megabytes.
timeout_secs (int, optional): Optional timeout for the run, in seconds.
Returns:
ApifyDatasetLoader: A loader that will fetch the records from the
Actor run's default dataset.
"""
actor_call = await self.apify_client_async.actor(actor_id).call(
run_input=run_input,
build=build,
memory_mbytes=memory_mbytes,
timeout_secs=timeout_secs,
)
return ApifyDatasetLoader(
dataset_id=actor_call["defaultDatasetId"],
dataset_mapping_function=dataset_mapping_function,
)
def call_actor_task(
self,
task_id: str,
task_input: Dict,
dataset_mapping_function: Callable[[Dict], Document],
*,
build: Optional[str] = None,
memory_mbytes: Optional[int] = None,
timeout_secs: Optional[int] = None,
) -> ApifyDatasetLoader:
"""Run a saved Actor task on Apify and wait for results to be ready.
Args:
task_id (str): The ID or name of the task on the Apify platform.
task_input (Dict): The input object of the task that you're trying to run.
Overrides the task's saved input.
dataset_mapping_function (Callable): A function that takes a single
dictionary (an Apify dataset item) and converts it to an
instance of the Document class.
build (str, optional): Optionally specifies the actor build to run.
It can be either a build tag or build number.
memory_mbytes (int, optional): Optional memory limit for the run,
in megabytes.
timeout_secs (int, optional): Optional timeout for the run, in seconds.
Returns:
ApifyDatasetLoader: A loader that will fetch the records from the
task run's default dataset.
"""
task_call = self.apify_client.task(task_id).call(
task_input=task_input,
build=build,
memory_mbytes=memory_mbytes,
timeout_secs=timeout_secs,
)
return ApifyDatasetLoader(
dataset_id=task_call["defaultDatasetId"],
dataset_mapping_function=dataset_mapping_function,
)
async def acall_actor_task(
self,
task_id: str,
task_input: Dict,
dataset_mapping_function: Callable[[Dict], Document],
*,
build: Optional[str] = None,
memory_mbytes: Optional[int] = None,
timeout_secs: Optional[int] = None,
) -> ApifyDatasetLoader:
"""Run a saved Actor task on Apify and wait for results to be ready.
Args:
task_id (str): The ID or name of the task on the Apify platform.
task_input (Dict): The input object of the task that you're trying to run.
Overrides the task's saved input.
dataset_mapping_function (Callable): A function that takes a single
dictionary (an Apify dataset item) and converts it to an
instance of the Document class.
build (str, optional): Optionally specifies the actor build to run.
It can be either a build tag or build number.
memory_mbytes (int, optional): Optional memory limit for the run,
in megabytes.
timeout_secs (int, optional): Optional timeout for the run, in seconds.
Returns:
ApifyDatasetLoader: A loader that will fetch the records from the
task run's default dataset.
"""
task_call = await self.apify_client_async.task(task_id).call(
task_input=task_input,
build=build,
memory_mbytes=memory_mbytes,
timeout_secs=timeout_secs,
)
return ApifyDatasetLoader(
dataset_id=task_call["defaultDatasetId"],
dataset_mapping_function=dataset_mapping_function,
)

50
libs/langchain/langchain/utilities/github.py
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@@ -4,15 +4,6 @@ from typing import Any, Dict, List, Optional
from pydantic import BaseModel, Extra, root_validator
from langchain.tools.github.prompt import (
COMMENT_ON_ISSUE_PROMPT,
CREATE_FILE_PROMPT,
DELETE_FILE_PROMPT,
GET_ISSUE_PROMPT,
GET_ISSUES_PROMPT,
READ_FILE_PROMPT,
UPDATE_FILE_PROMPT,
)
from langchain.utils import get_from_dict_or_env
@@ -26,52 +17,11 @@ class GitHubAPIWrapper(BaseModel):
github_app_private_key: Optional[str] = None
github_branch: Optional[str] = None
operations: List[Dict] = [
{
"mode": "get_issues",
"name": "Get Issues",
"description": GET_ISSUES_PROMPT,
},
{
"mode": "get_issue",
"name": "Get Issue",
"description": GET_ISSUE_PROMPT,
},
{
"mode": "comment_on_issue",
"name": "Comment on Issue",
"description": COMMENT_ON_ISSUE_PROMPT,
},
{
"mode": "create_file",
"name": "Create File",
"description": CREATE_FILE_PROMPT,
},
{
"mode": "read_file",
"name": "Read File",
"description": READ_FILE_PROMPT,
},
{
"mode": "update_file",
"name": "Update File",
"description": UPDATE_FILE_PROMPT,
},
{
"mode": "delete_file",
"name": "Delete File",
"description": DELETE_FILE_PROMPT,
},
]
class Config:
"""Configuration for this pydantic object."""
extra = Extra.forbid
def list(self) -> List[Dict]:
return self.operations
@root_validator()
def validate_environment(cls, values: Dict) -> Dict:
"""Validate that api key and python package exists in environment."""

38
libs/langchain/langchain/utilities/jira.py
View File

@@ -3,13 +3,6 @@ from typing import Any, Dict, List, Optional
from pydantic import BaseModel, Extra, root_validator
from langchain.tools.jira.prompt import (
JIRA_CATCH_ALL_PROMPT,
JIRA_CONFLUENCE_PAGE_CREATE_PROMPT,
JIRA_GET_ALL_PROJECTS_PROMPT,
JIRA_ISSUE_CREATE_PROMPT,
JIRA_JQL_PROMPT,
)
from langchain.utils import get_from_dict_or_env
@@ -23,42 +16,11 @@ class JiraAPIWrapper(BaseModel):
jira_api_token: Optional[str] = None
jira_instance_url: Optional[str] = None
operations: List[Dict] = [
{
"mode": "jql",
"name": "JQL Query",
"description": JIRA_JQL_PROMPT,
},
{
"mode": "get_projects",
"name": "Get Projects",
"description": JIRA_GET_ALL_PROJECTS_PROMPT,
},
{
"mode": "create_issue",
"name": "Create Issue",
"description": JIRA_ISSUE_CREATE_PROMPT,
},
{
"mode": "other",
"name": "Catch all Jira API call",
"description": JIRA_CATCH_ALL_PROMPT,
},
{
"mode": "create_page",
"name": "Create confluence page",
"description": JIRA_CONFLUENCE_PAGE_CREATE_PROMPT,
},
]
class Config:
"""Configuration for this pydantic object."""
extra = Extra.forbid
def list(self) -> List[Dict]:
return self.operations
@root_validator()
def validate_environment(cls, values: Dict) -> Dict:
"""Validate that api key and python package exists in environment."""

3
libs/langchain/langchain/utilities/openweathermap.py
View File

@@ -1,9 +1,8 @@
"""Util that calls OpenWeatherMap using PyOWM."""
from typing import Any, Dict, Optional
from pydantic import Extra, root_validator
from pydantic import BaseModel, Extra, root_validator
from langchain.tools.base import BaseModel
from langchain.utils import get_from_dict_or_env

2
libs/langchain/pyproject.toml
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@@ -1,6 +1,6 @@
[tool.poetry]
name = "langchain"
version = "0.0.240rc0"
version = "0.0.240rc4"
description = "Building applications with LLMs through composability"
authors = []
license = "MIT"