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Source code for langchain.utilities.portkey import json import os from typing import Dict, Optional [docs]class Portkey: """Portkey configuration. Attributes: base: The base URL for the Portkey API. Default: "https://api.portkey.ai/v1/proxy" """ base = "https://api.portkey.ai/v1/proxy"...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/portkey.html
115d2a7a94a4-1
headers = { "x-portkey-api-key": api_key, "x-portkey-mode": "proxy openai", } if trace_id: headers["x-portkey-trace-id"] = trace_id if retry_count: headers["x-portkey-retry-count"] = str(retry_count) if cache: headers["x-portkey...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/portkey.html
afc07acaa362-0
Source code for langchain.utilities.google_scholar """Util that calls Google Scholar Search.""" from typing import Dict, Optional from langchain.pydantic_v1 import BaseModel, Extra, root_validator from langchain.utils import get_from_dict_or_env [docs]class GoogleScholarAPIWrapper(BaseModel): """Wrapper for Google ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/google_scholar.html
afc07acaa362-1
google_scholar = GoogleScholarAPIWrapper() google_scholar.run('langchain') """ top_k_results: int = 10 hl: str = "en" lr: str = "lang_en" serp_api_key: Optional[str] = None class Config: """Configuration for this pydantic object.""" extra = Extra.forbid @root_validato...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/google_scholar.html
afc07acaa362-2
results = ( self.google_scholar_engine( # type: ignore { "q": query, "start": page, "hl": self.hl, "num": min( self.top_k_results, 20 )...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/google_scholar.html
afc07acaa362-3
f"Summary: {result.get('publication_info',{}).get('summary','')}\n" f"Total-Citations: {result.get('inline_links',{}).get('cited_by',{}).get('total','')}" # noqa: E501 for result in total_results ] return "\n\n".join(docs)
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/google_scholar.html
aef74c6edd0d-0
Source code for langchain.utilities.spark_sql from __future__ import annotations from typing import TYPE_CHECKING, Any, Iterable, List, Optional if TYPE_CHECKING: from pyspark.sql import DataFrame, Row, SparkSession [docs]class SparkSQL: """SparkSQL is a utility class for interacting with Spark SQL.""" [docs] ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/spark_sql.html
aef74c6edd0d-1
) if catalog is not None: self._spark.catalog.setCurrentCatalog(catalog) if schema is not None: self._spark.catalog.setCurrentDatabase(schema) self._all_tables = set(self._get_all_table_names()) self._include_tables = set(include_tables) if include_tables else set...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/spark_sql.html
aef74c6edd0d-2
) spark = SparkSession.builder.remote(database_uri).getOrCreate() return cls(spark, **kwargs) [docs] def get_usable_table_names(self) -> Iterable[str]: """Get names of tables available.""" if self._include_tables: return self._include_tables # sorting the result ca...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/spark_sql.html
aef74c6edd0d-3
table_info += "*/" tables.append(table_info) final_str = "\n\n".join(tables) return final_str def _get_sample_spark_rows(self, table: str) -> str: query = f"SELECT * FROM {table} LIMIT {self._sample_rows_in_table_info}" df = self._spark.sql(query) columns_str = "\...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/spark_sql.html
aef74c6edd0d-4
Follows best practices as specified in: Rajkumar et al, 2022 (https://arxiv.org/abs/2204.00498) If `sample_rows_in_table_info`, the specified number of sample rows will be appended to each table description. This can increase performance as demonstrated in the paper. """ ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/spark_sql.html
7675721da6c7-0
Source code for langchain.utilities.bibtex """Util that calls bibtexparser.""" import logging from typing import Any, Dict, List, Mapping from langchain.pydantic_v1 import BaseModel, Extra, root_validator logger = logging.getLogger(__name__) OPTIONAL_FIELDS = [ "annotate", "booktitle", "editor", "howpub...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/bibtex.html
7675721da6c7-1
import bibtexparser with open(path) as file: entries = bibtexparser.load(file).entries return entries [docs] def get_metadata( self, entry: Mapping[str, Any], load_extra: bool = False ) -> Dict[str, Any]: """Get metadata for the given entry.""" publication = en...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/bibtex.html
c92ea5ae7da2-0
Source code for langchain.utilities.gitlab """Util that calls gitlab.""" from __future__ import annotations import json from typing import TYPE_CHECKING, Any, Dict, List, Optional from langchain.pydantic_v1 import BaseModel, Extra, root_validator from langchain.utils import get_from_dict_or_env if TYPE_CHECKING: fr...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/gitlab.html
c92ea5ae7da2-1
values, "gitlab_personal_access_token", "GITLAB_PERSONAL_ACCESS_TOKEN" ) gitlab_branch = get_from_dict_or_env( values, "gitlab_branch", "GITLAB_BRANCH", default="main" ) gitlab_base_branch = get_from_dict_or_env( values, "gitlab_base_branch", "GITLAB_BASE_BRANCH",...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/gitlab.html
c92ea5ae7da2-2
""" Fetches all open issues from the repo Returns: str: A plaintext report containing the number of issues and each issue's title and number. """ issues = self.gitlab_repo_instance.issues.list(state="opened") if len(issues) > 0: parsed_issues =...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/gitlab.html
c92ea5ae7da2-3
""" Makes a pull request from the bot's branch to the base branch Parameters: pr_query(str): a string which contains the PR title and the PR body. The title is the first line in the string, and the body are the rest of the string. For example, "Updated REA...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/gitlab.html
c92ea5ae7da2-4
""" issue_number = int(comment_query.split("\n\n")[0]) comment = comment_query[len(str(issue_number)) + 2 :] try: issue = self.gitlab_repo_instance.issues.get(issue_number) issue.notes.create({"body": comment}) return "Commented on issue " + str(issue_number) ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/gitlab.html
c92ea5ae7da2-5
Parameters: file_path(str): the file path Returns: str: The file decoded as a string """ file = self.gitlab_repo_instance.files.get(file_path, self.gitlab_branch) return file.decode().decode("utf-8") [docs] def update_file(self, file_query: str) -> str: ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/gitlab.html
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"commit_message": "Create " + file_path, "actions": [ { "action": "update", "file_path": file_path, "content": updated_file_content, } ], } self.gitlab_...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/gitlab.html
c92ea5ae7da2-7
return self.delete_file(query) else: raise ValueError("Invalid mode" + mode)
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/gitlab.html
400e031c6e54-0
Source code for langchain.utilities.clickup """Util that calls clickup.""" import json import warnings from dataclasses import asdict, dataclass, fields from typing import Any, Dict, List, Mapping, Optional, Tuple, Type, Union import requests from langchain.pydantic_v1 import BaseModel, Extra, root_validator from langc...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/clickup.html
400e031c6e54-1
creator_username=data["creator"]["username"], creator_email=data["creator"]["email"], assignees=data["assignees"], watchers=data["watchers"], priority=priority, due_date=data["due_date"], start_date=data["start_date"], points=data["poin...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/clickup.html
400e031c6e54-2
initials=data["user"]["initials"], ) [docs]@dataclass class Team(Component): """Component class for a team.""" id: int name: str members: List[Member] [docs] @classmethod def from_data(cls, data: Dict) -> "Team": members = [Member.from_data(member_data) for member_data in data["me...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/clickup.html
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except Exception as e: if fault_tolerant: warning_str = f"""Error encountered while trying to parse {str(data)}: {str(e)}\n Falling back to returning input data.""" warnings.warn(warning_str) return data else: raise e [docs]def extract_dict_elements_from_c...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/clickup.html
400e031c6e54-4
[docs]def fetch_first_id(data: dict, key: str) -> Optional[int]: """Fetch the first id from a dictionary.""" if key in data and len(data[key]) > 0: if len(data[key]) > 1: warnings.warn(f"Found multiple {key}: {data[key]}. Defaulting to first.") return data[key][0]["id"] return No...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/clickup.html
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return fetch_first_id(data, "folders") [docs]def fetch_list_id(space_id: int, folder_id: int, access_token: str) -> Optional[int]: """Fetch the list id.""" if folder_id: url = f"{DEFAULT_URL}/folder/{folder_id}/list" else: url = f"{DEFAULT_URL}/space/{space_id}/list" data = fetch_data(ur...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/clickup.html
400e031c6e54-6
"""Get the access token.""" url = f"{DEFAULT_URL}/oauth/token" params = { "client_id": oauth_client_id, "client_secret": oauth_client_secret, "code": code, } response = requests.post(url, params=params) data = response.json() if "access...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/clickup.html
400e031c6e54-7
"""Parse appropriate content from the list of teams.""" parsed_teams: Dict[str, List[dict]] = {"teams": []} for team in input_dict["teams"]: try: team = parse_dict_through_component(team, Team, fault_tolerant=False) parsed_teams["teams"].append(team) ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/clickup.html
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return {"response": response} [docs] def get_task(self, query: str, fault_tolerant: bool = True) -> Dict: """ Retrieve a specific task. """ params, error = load_query(query, fault_tolerant=True) if params is None: return {"Error": error} url = f"{DEFAULT_UR...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/clickup.html
400e031c6e54-9
[docs] def get_spaces(self) -> Dict: """ Get all spaces for the team. """ url = f"{DEFAULT_URL}/team/{self.team_id}/space" response = requests.get( url, headers=self.get_headers(), params=self.get_default_params() ) data = response.json() pa...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/clickup.html
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} headers = self.get_headers() payload = {query_dict["attribute_name"]: query_dict["value"]} response = requests.put(url, headers=headers, params=params, json=payload) return {"response": response} [docs] def update_task_assignees(self, query: str) -> Dict: """ Add or ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/clickup.html
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[docs] def create_task(self, query: str) -> Dict: """ Creates a new task. """ query_dict, error = load_query(query, fault_tolerant=True) if query_dict is None: return {"Error": error} list_id = self.list_id url = f"{DEFAULT_URL}/list/{list_id}/task"...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/clickup.html
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self.list_id = parsed_list["id"] return parsed_list [docs] def create_folder(self, query: str) -> Dict: """ Creates a new folder. """ query_dict, error = load_query(query, fault_tolerant=True) if query_dict is None: return {"Error": error} space_id ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/clickup.html
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output = self.update_task(query) elif mode == "update_task_assignees": output = self.update_task_assignees(query) else: output = {"ModeError": f"Got unexpected mode {mode}."} try: return json.dumps(output) except Exception: return str(outpu...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/clickup.html
8a8bf348b1c9-0
Source code for langchain.utilities.vertexai """Utilities to init Vertex AI.""" from importlib import metadata from typing import TYPE_CHECKING, Optional if TYPE_CHECKING: from google.api_core.gapic_v1.client_info import ClientInfo from google.auth.credentials import Credentials [docs]def raise_vertex_import_er...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/vertexai.html
8a8bf348b1c9-1
r"""Returns a custom user agent header. Args: module (Optional[str]): Optional. The module for a custom user agent header. Returns: google.api_core.gapic_v1.client_info.ClientInfo """ try: from google.api_core.gapic_v1.client_info import ClientInfo except ImportEr...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/vertexai.html
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Source code for langchain.utilities.apify from typing import TYPE_CHECKING, Any, Callable, Dict, Optional from langchain.pydantic_v1 import BaseModel, root_validator from langchain.schema.document import Document from langchain.utils import get_from_dict_or_env if TYPE_CHECKING: from langchain.document_loaders impo...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/apify.html
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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: ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/apify.html
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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: ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/apify.html
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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: ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/apify.html
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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...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/apify.html
4ba5c595deec-0
Source code for langchain.utilities.scenexplain """Util that calls SceneXplain. In order to set this up, you need API key for the SceneXplain API. You can obtain a key by following the steps below. - Sign up for a free account at https://scenex.jina.ai/. - Navigate to the API Access page (https://scenex.jina.ai/api) an...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/scenexplain.html
4ba5c595deec-1
"languages": ["en"], } ] } response = requests.post(self.scenex_api_url, headers=headers, json=payload) response.raise_for_status() result = response.json().get("result", []) img = result[0] if result else {} return img.get("text", "") @roo...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/scenexplain.html
68f28c4f559e-0
Source code for langchain.utilities.openweathermap """Util that calls OpenWeatherMap using PyOWM.""" from typing import Any, Dict, Optional from langchain.pydantic_v1 import BaseModel, Extra, root_validator from langchain.utils import get_from_dict_or_env [docs]class OpenWeatherMapAPIWrapper(BaseModel): """Wrapper ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/openweathermap.html
68f28c4f559e-1
heat_index = w.heat_index clouds = w.clouds return ( f"In {location}, the current weather is as follows:\n" f"Detailed status: {detailed_status}\n" f"Wind speed: {wind['speed']} m/s, direction: {wind['deg']}°\n" f"Humidity: {humidity}%\n" f"Tem...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/openweathermap.html
fd9d6aca7567-0
Source code for langchain.utilities.anthropic from typing import Any, List def _get_anthropic_client() -> Any: try: import anthropic except ImportError: raise ImportError( "Could not import anthropic python package. " "This is needed in order to accurately tokenize the te...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/anthropic.html
d50f2d5f1ea0-0
Source code for langchain.utilities.twilio """Util that calls Twilio.""" from typing import Any, Dict, Optional from langchain.pydantic_v1 import BaseModel, Extra, root_validator from langchain.utils import get_from_dict_or_env [docs]class TwilioAPIWrapper(BaseModel): """Messaging Client using Twilio. To use, y...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/twilio.html
d50f2d5f1ea0-1
that is enabled for the type of message you want to send. Phone numbers or [short codes](https://www.twilio.com/docs/sms/api/short-code) purchased from Twilio also work here. You cannot, for example, spoof messages from a private cell phone number. If you are using `messaging_service_sid`, th...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/twilio.html
d50f2d5f1ea0-2
characters in length. to: The destination phone number in [E.164](https://www.twilio.com/docs/glossary/what-e164) format for SMS/MMS or [Channel user address](https://www.twilio.com/docs/sms/channels#channel-addresses) for other 3rd-party chann...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/twilio.html
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Source code for langchain.utilities.requests """Lightweight wrapper around requests library, with async support.""" from contextlib import asynccontextmanager from typing import Any, AsyncGenerator, Dict, Optional import aiohttp import requests from langchain.pydantic_v1 import BaseModel, Extra [docs]class Requests(Bas...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/requests.html
cc5493f88733-1
"""PUT the URL and return the text.""" return requests.put( url, json=data, headers=self.headers, auth=self.auth, **kwargs ) [docs] def delete(self, url: str, **kwargs: Any) -> requests.Response: """DELETE the URL and return the text.""" return requests.delete(url, headers...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/requests.html
cc5493f88733-2
yield response [docs] @asynccontextmanager async def apatch( self, url: str, data: Dict[str, Any], **kwargs: Any ) -> AsyncGenerator[aiohttp.ClientResponse, None]: """PATCH the URL and return the text asynchronously.""" async with self._arequest("PATCH", url, json=data, **kwargs) as r...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/requests.html
cc5493f88733-3
headers=self.headers, aiosession=self.aiosession, auth=self.auth ) [docs] def get(self, url: str, **kwargs: Any) -> str: """GET the URL and return the text.""" return self.requests.get(url, **kwargs).text [docs] def post(self, url: str, data: Dict[str, Any], **kwargs: Any) -> str: ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/requests.html
cc5493f88733-4
return await response.text() [docs] async def apatch(self, url: str, data: Dict[str, Any], **kwargs: Any) -> str: """PATCH the URL and return the text asynchronously.""" async with self.requests.apatch(url, data, **kwargs) as response: return await response.text() [docs] async def aput...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/requests.html
c53f1c832fc0-0
Source code for langchain.utilities.max_compute from __future__ import annotations from typing import TYPE_CHECKING, Iterator, List, Optional from langchain.utils import get_from_env if TYPE_CHECKING: from odps import ODPS [docs]class MaxComputeAPIWrapper: """Interface for querying Alibaba Cloud MaxCompute tabl...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/max_compute.html
c53f1c832fc0-1
"https://pyodps.readthedocs.io/." ) from ex access_id = access_id or get_from_env("access_id", "MAX_COMPUTE_ACCESS_ID") secret_access_key = secret_access_key or get_from_env( "secret_access_key", "MAX_COMPUTE_SECRET_ACCESS_KEY" ) client = ODPS( access_...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/max_compute.html
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Source code for langchain.utilities.python import functools import logging import multiprocessing import sys from io import StringIO from typing import Dict, Optional from langchain.pydantic_v1 import BaseModel, Field logger = logging.getLogger(__name__) @functools.lru_cache(maxsize=None) def warn_once() -> None: "...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/python.html
0097bd10ff7e-1
# create a Process p = multiprocessing.Process( target=self.worker, args=(command, self.globals, self.locals, queue) ) # start it p.start() # wait for the process to finish or kill it after timeout seconds p.join(timeout) ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/python.html
cfda5880b057-0
Source code for langchain.utilities.github """Util that calls GitHub.""" from __future__ import annotations import json from typing import TYPE_CHECKING, Any, Dict, List, Optional from langchain.pydantic_v1 import BaseModel, Extra, root_validator from langchain.utils import get_from_dict_or_env if TYPE_CHECKING: fr...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/github.html
cfda5880b057-1
) try: from github import Auth, GithubIntegration except ImportError: raise ImportError( "PyGithub is not installed. " "Please install it with `pip install PyGithub`" ) with open(github_app_private_key, "r") as f: pr...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/github.html
cfda5880b057-2
and each issue's title and number. """ issues = self.github_repo_instance.get_issues(state="open") if issues.totalCount > 0: parsed_issues = self.parse_issues(issues) parsed_issues_str = ( "Found " + str(len(parsed_issues)) + " issues:\n" + str(parsed_issu...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/github.html
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in the string, and the body are the rest of the string. For example, "Updated README\nmade changes to add info" Returns: str: A success or failure message """ if self.github_base_branch == self.github_branch: return """Cannot make a pull request because ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/github.html
cfda5880b057-4
return "Unable to make comment due to error:\n" + str(e) [docs] def create_file(self, file_query: str) -> str: """ Creates a new file on the Github repo Parameters: file_query(str): a string which contains the file path and the file contents. The file path is the first...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/github.html
cfda5880b057-5
""" Updates a file with new content. Parameters: file_query(str): Contains the file path and the file contents. The old file contents is wrapped in OLD <<<< and >>>> OLD The new file contents is wrapped in NEW <<<< and >>>> NEW For example: ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/github.html
cfda5880b057-6
""" Deletes a file from the repo Parameters: file_path(str): Where the file is Returns: str: Success or failure message """ try: file = self.github_repo_instance.get_contents(file_path) self.github_repo_instance.delete_file( ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/github.html
0a09325f35a6-0
Source code for langchain.utilities.graphql import json from typing import Any, Callable, Dict, Optional from langchain.pydantic_v1 import BaseModel, Extra, root_validator [docs]class GraphQLAPIWrapper(BaseModel): """Wrapper around GraphQL API. To use, you should have the ``gql`` python package installed. T...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/graphql.html
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return json.dumps(result, indent=2) def _execute_query(self, query: str) -> Dict[str, Any]: """Execute a GraphQL query and return the results.""" document_node = self.gql_function(query) result = self.gql_client.execute(document_node) return result
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/graphql.html
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Source code for langchain.utilities.awslambda """Util that calls Lambda.""" import json from typing import Any, Dict, Optional from langchain.pydantic_v1 import BaseModel, Extra, root_validator [docs]class LambdaWrapper(BaseModel): """Wrapper for AWS Lambda SDK. To use, you should have the ``boto3`` package ins...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/awslambda.html
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Invokes the lambda function and returns the result. Args: query: an input to passed to the lambda function as the ``body`` of a JSON object. """ # noqa: E501 res = self.lambda_client.invoke( FunctionName=self.function_name, ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/awslambda.html
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Source code for langchain.utilities.searchapi from typing import Any, Dict, Optional import aiohttp import requests from langchain.pydantic_v1 import BaseModel, root_validator from langchain.utils import get_from_dict_or_env [docs]class SearchApiAPIWrapper(BaseModel): """ Wrapper around SearchApi API. To us...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/searchapi.html
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results = await self.aresults(query, **kwargs) return self._result_as_string(results) [docs] def results(self, query: str, **kwargs: Any) -> dict: results = self._search_api_results(query, **kwargs) return results [docs] async def aresults(self, query: str, **kwargs: Any) -> dict: ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/searchapi.html
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url=request_details["url"], headers=request_details["headers"], params=request_details["params"], raise_for_status=True, ) as response: results = await response.json() else: async with self.aiosession.get...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/searchapi.html
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if "title" in r.keys() ] toret = "\n".join(videos) elif "images" in result.keys(): images = [ f"""Title: "{r["title"]}" Link: {r["original"]["link"]}""" for r in result["images"] if "original" in r.keys() ] ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/searchapi.html
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Source code for langchain.utilities.zapier """Util that can interact with Zapier NLA. Full docs here: https://nla.zapier.com/start/ Note: this wrapper currently only implemented the `api_key` auth method for testing and server-side production use cases (using the developer's connected accounts on Zapier.com) For use-ca...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/zapier.html
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your own provider and generate credentials. """ zapier_nla_api_key: str zapier_nla_oauth_access_token: str zapier_nla_api_base: str = "https://nla.zapier.com/api/v1/" class Config: """Configuration for this pydantic object.""" extra = Extra.forbid def _format_headers(self) -> Dic...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/zapier.html
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{ "instructions": instructions, } ) if preview_only: data.update({"preview_only": True}) return data def _create_action_url(self, action_id: str) -> str: """Create a url for an action.""" return self.zapier_nla_api_base + f"exposed/{act...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/zapier.html
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return values [docs] async def alist(self) -> List[Dict]: """Returns a list of all exposed (enabled) actions associated with current user (associated with the set api_key). Change your exposed actions here: https://nla.zapier.com/demo/start/ The return list can be empty if no actions ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/zapier.html
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""" session = self._get_session() try: response = session.get(self.zapier_nla_api_base + "exposed/") response.raise_for_status() except requests.HTTPError as http_err: if response.status_code == 401: if self.zapier_nla_oauth_access_token: ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/zapier.html
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) -> Dict: """Executes an action that is identified by action_id, must be exposed (enabled) by the current user (associated with the set api_key). Change your exposed actions here: https://nla.zapier.com/demo/start/ The return JSON is guaranteed to be less than ~500 words (350 to...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/zapier.html
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response = await self._arequest( "POST", self._create_action_url(action_id), json=self._create_action_payload(instructions, params, preview_only=True), ) return response["result"] [docs] def run_as_str(self, *args, **kwargs) -> str: # type: ignore[no-untyped-def] ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/zapier.html
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"""Same as list, but returns a stringified version of the JSON for insertting back into an LLM.""" actions = self.list() return json.dumps(actions) [docs] async def alist_as_str(self) -> str: # type: ignore[no-untyped-def] """Same as list, but returns a stringified version of the JSO...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/zapier.html
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Source code for langchain.utilities.jira """Util that calls Jira.""" from typing import Any, Dict, List, Optional from langchain.pydantic_v1 import BaseModel, Extra, root_validator from langchain.utils import get_from_dict_or_env # TODO: think about error handling, more specific api specs, and jql/project limits [docs]...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/jira.html
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) jira = Jira( url=jira_instance_url, username=jira_username, password=jira_api_token, cloud=True, ) confluence = Confluence( url=jira_instance_url, username=jira_username, password=jira_api_token, cl...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/jira.html
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parsed.append( { "key": key, "summary": summary, "created": created, "assignee": assignee, "priority": priority, "status": status, "related_issues": rel_issues, ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/jira.html
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) params = json.loads(query) return self.jira.issue_create(fields=dict(params)) [docs] def page_create(self, query: str) -> str: try: import json except ImportError: raise ImportError( "json is not installed. Please install it with `pip install ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/jira.html
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Source code for langchain.utilities.arcee # This module contains utility classes and functions for interacting with Arcee API. # For more information and updates, refer to the Arcee utils page: # [https://github.com/arcee-ai/arcee-python/blob/main/arcee/dalm.py] from enum import Enum from typing import Any, Dict, List,...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/arcee.html
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'strict_search' means that the exact string must appear in the provided field. This is NOT an exact eq filter. ie a document with content "the happy dog crossed the street" will match on a strict_search of "dog" but won't match on "the dog". Python equivalent ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/arcee.html
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"source_id": arcee_document.source.id, # arcee document metadata "index": arcee_document.index, "id": arcee_document.id, "score": arcee_document.score, }, ) [docs]class ArceeWrapper: """Wrapper for Arcee API.""" [docs] def __init...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/arcee.html
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raise Exception( f"Model {self.model_id} is not ready. " "Please wait for training to complete." ) def _make_request( self, method: Literal["post", "get"], route: Union[ArceeRoute, str], body: Optional[Mapping[str, Any]] = None, par...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/arcee.html
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self, prompt: str, **kwargs: Mapping[str, Any] ) -> Mapping[str, Any]: """Make the request body for generate/retrieve models endpoint""" _model_kwargs = self.model_kwargs or {} _params = {**_model_kwargs, **kwargs} filters = [DALMFilter(**f) for f in _params.get("filters", [])] ...
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filters: Filters to apply to the context dataset. """ response = self._make_request( method="post", route=ArceeRoute.retrieve.value, body=self._make_request_body_for_models( prompt=query, **kwargs, ), ) retur...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/arcee.html
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Source code for langchain.utilities.arxiv """Util that calls Arxiv.""" import logging import os import re from typing import Any, Dict, List, Optional from langchain.pydantic_v1 import BaseModel, root_validator from langchain.schema import Document logger = logging.getLogger(__name__) [docs]class ArxivAPIWrapper(BaseMo...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/arxiv.html
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content Example: .. code-block:: python from langchain.utilities.arxiv import ArxivAPIWrapper arxiv = ArxivAPIWrapper( top_k_results = 3, ARXIV_MAX_QUERY_LENGTH = 300, load_max_docs = 3, load_all_available_meta = False, ...
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import arxiv values["arxiv_search"] = arxiv.Search values["arxiv_exceptions"] = ( arxiv.ArxivError, arxiv.UnexpectedEmptyPageError, arxiv.HTTPError, ) values["arxiv_result"] = arxiv.Result except ImportError: ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/arxiv.html
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}, ) for result in results ] return docs [docs] def run(self, query: str) -> str: """ Performs an arxiv search and A single string with the publish date, title, authors, and summary for each article separated by two newlines. If an error...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/arxiv.html
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""" Run Arxiv search and get the article texts plus the article meta information. See https://lukasschwab.me/arxiv.py/index.html#Search Returns: a list of documents with the document.page_content in text format Performs an arxiv search, downloads the top k results as PDFs, loads ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/arxiv.html
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logger.debug(f_ex) continue if self.load_all_available_meta: extra_metadata = { "entry_id": result.entry_id, "published_first_time": str(result.published.date()), "comment": result.comment, "journ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/arxiv.html
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Source code for langchain.utilities.wolfram_alpha """Util that calls WolframAlpha.""" from typing import Any, Dict, Optional from langchain.pydantic_v1 import BaseModel, Extra, root_validator from langchain.utils import get_from_dict_or_env [docs]class WolframAlphaAPIWrapper(BaseModel): """Wrapper for Wolfram Alpha...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/wolfram_alpha.html
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"""Run query through WolframAlpha and parse result.""" res = self.wolfram_client.query(query) try: assumption = next(res.pods).text answer = next(res.results).text except StopIteration: return "Wolfram Alpha wasn't able to answer it" if answer is None ...
lang/api.python.langchain.com/en/latest/_modules/langchain/utilities/wolfram_alpha.html