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" What is the nearest airport to {location}? Please respond with the " " airport's International Air Transport Association (IATA) Location " ' Identifier in the following JSON format. JSON: "iataCode": "IATA ' ' Location Identifier" ' ) llm = ChatOpenAI(temperature=0)...
https://api.python.langchain.com/en/latest/_modules/langchain/tools/amadeus/closest_airport.html
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Source code for langchain.tools.amadeus.utils """O365 tool utils.""" from __future__ import annotations import logging import os from typing import TYPE_CHECKING if TYPE_CHECKING: from amadeus import Client logger = logging.getLogger(__name__) [docs]def authenticate() -> Client: """Authenticate using the Amadeu...
https://api.python.langchain.com/en/latest/_modules/langchain/tools/amadeus/utils.html
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Source code for langchain.tools.office365.events_search """Util that Searches calendar events in Office 365. Free, but setup is required. See link below. https://learn.microsoft.com/en-us/graph/auth/ """ from datetime import datetime as dt from typing import Any, Dict, List, Optional, Type from pydantic import BaseMode...
https://api.python.langchain.com/en/latest/_modules/langchain/tools/office365/events_search.html
f29f59d3783e-1
" components, and the time zone offset is specified as ±hh:mm. " ' For example: "2023-06-09T10:30:00+03:00" represents June 9th, ' " 2023, at 10:30 AM in a time zone with a positive offset of 3 " " hours from Coordinated Universal Time (UTC)." ) ) max_results: int = F...
https://api.python.langchain.com/en/latest/_modules/langchain/tools/office365/events_search.html
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extra = Extra.forbid def _run( self, start_datetime: str, end_datetime: str, max_results: int = 10, truncate: bool = True, run_manager: Optional[CallbackManagerForToolRun] = None, ) -> List[Dict[str, Any]]: TRUNCATE_LIMIT = 150 # Get calendar objec...
https://api.python.langchain.com/en/latest/_modules/langchain/tools/office365/events_search.html
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"%Y-%m-%dT%H:%M:%S%z" ) output_event["end_datetime"] = event.end.astimezone(time_zone).strftime( "%Y-%m-%dT%H:%M:%S%z" ) output_event["modified_date"] = event.modified.astimezone( time_zone ).strftime("%Y-%m-%dT%H:%M:%S%z") ...
https://api.python.langchain.com/en/latest/_modules/langchain/tools/office365/events_search.html
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Source code for langchain.tools.office365.base """Base class for Office 365 tools.""" from __future__ import annotations from typing import TYPE_CHECKING from pydantic import Field from langchain.tools.base import BaseTool from langchain.tools.office365.utils import authenticate if TYPE_CHECKING: from O365 import A...
https://api.python.langchain.com/en/latest/_modules/langchain/tools/office365/base.html
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Source code for langchain.tools.office365.send_message from typing import List, Optional, Type from pydantic import BaseModel, Field from langchain.callbacks.manager import CallbackManagerForToolRun from langchain.tools.office365.base import O365BaseTool [docs]class SendMessageSchema(BaseModel): """Input for SendMe...
https://api.python.langchain.com/en/latest/_modules/langchain/tools/office365/send_message.html
fc213c5eedb6-1
message.body = body message.subject = subject message.to.add(to) if cc is not None: message.cc.add(cc) if bcc is not None: message.bcc.add(cc) message.send() output = "Message sent: " + str(message) return output
https://api.python.langchain.com/en/latest/_modules/langchain/tools/office365/send_message.html
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Source code for langchain.tools.office365.messages_search """Util that Searches email messages in Office 365. Free, but setup is required. See link below. https://learn.microsoft.com/en-us/graph/auth/ """ from typing import Any, Dict, List, Optional, Type from pydantic import BaseModel, Extra, Field from langchain.call...
https://api.python.langchain.com/en/latest/_modules/langchain/tools/office365/messages_search.html
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"range example: received:2023-06-08..2023-06-09 matching example: " "from:amy OR from:david." ) ) max_results: int = Field( default=10, description="The maximum number of results to return.", ) truncate: bool = Field( default=True, description=( ...
https://api.python.langchain.com/en/latest/_modules/langchain/tools/office365/messages_search.html
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if folder != "": mailbox = mailbox.get_folder(folder_name=folder) # Retrieve messages based on query query = mailbox.q().search(query) messages = mailbox.get_messages(limit=max_results, query=query) # Generate output dict output_messages = [] for message in me...
https://api.python.langchain.com/en/latest/_modules/langchain/tools/office365/messages_search.html
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Source code for langchain.tools.office365.create_draft_message from typing import List, Optional, Type from pydantic import BaseModel, Field from langchain.callbacks.manager import CallbackManagerForToolRun from langchain.tools.office365.base import O365BaseTool [docs]class CreateDraftMessageSchema(BaseModel): """I...
https://api.python.langchain.com/en/latest/_modules/langchain/tools/office365/create_draft_message.html
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message = mailbox.new_message() # Assign message values message.body = body message.subject = subject message.to.add(to) if cc is not None: message.cc.add(cc) if bcc is not None: message.bcc.add(cc) message.save_draft() output = "Dr...
https://api.python.langchain.com/en/latest/_modules/langchain/tools/office365/create_draft_message.html
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Source code for langchain.tools.office365.send_event """Util that sends calendar events in Office 365. Free, but setup is required. See link below. https://learn.microsoft.com/en-us/graph/auth/ """ from datetime import datetime as dt from typing import List, Optional, Type from pydantic import BaseModel, Field from lan...
https://api.python.langchain.com/en/latest/_modules/langchain/tools/office365/send_event.html
7254177581f8-1
" components, and the time zone offset is specified as ±hh:mm. " ' For example: "2023-06-09T10:30:00+03:00" represents June 9th, ' " 2023, at 10:30 AM in a time zone with a positive offset of 3 " " hours from Coordinated Universal Time (UTC).", ) [docs]class O365SendEvent(O365BaseTool): ...
https://api.python.langchain.com/en/latest/_modules/langchain/tools/office365/send_event.html
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Source code for langchain.tools.office365.utils """O365 tool utils.""" from __future__ import annotations import logging import os from typing import TYPE_CHECKING if TYPE_CHECKING: from O365 import Account logger = logging.getLogger(__name__) [docs]def clean_body(body: str) -> str: """Clean body of a message o...
https://api.python.langchain.com/en/latest/_modules/langchain/tools/office365/utils.html
68ac0df7d7bc-1
if account.is_authenticated is False: if not account.authenticate( scopes=[ "https://graph.microsoft.com/Mail.ReadWrite", "https://graph.microsoft.com/Mail.Send", "https://graph.microsoft.com/Calendars.ReadWrite", "https://graph.microso...
https://api.python.langchain.com/en/latest/_modules/langchain/tools/office365/utils.html
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Source code for langchain.tools.bing_search.tool """Tool for the Bing search API.""" from typing import Optional from langchain.callbacks.manager import CallbackManagerForToolRun from langchain.tools.base import BaseTool from langchain.utilities.bing_search import BingSearchAPIWrapper [docs]class BingSearchRun(BaseTool...
https://api.python.langchain.com/en/latest/_modules/langchain/tools/bing_search/tool.html
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Source code for langchain.tools.nuclia.tool """Tool for the Nuclia Understanding API. Installation: ```bash pip install --upgrade protobuf pip install nucliadb-protos ``` """ import asyncio import base64 import logging import mimetypes import os from typing import Any, Dict, Optional, Type, Union import request...
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_config: Dict[str, Any] = {} def __init__(self, enable_ml: bool = False) -> None: zone = os.environ.get("NUCLIA_ZONE", "europe-1") self._config["BACKEND"] = f"https://{zone}.nuclia.cloud/api/v1" key = os.environ.get("NUCLIA_NUA_KEY") if not key: raise ValueError("NUCLIA_N...
https://api.python.langchain.com/en/latest/_modules/langchain/tools/nuclia/tool.html
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if text: self._pushText(id, text) data = None while True: data = self._pull(id) if data: break await asyncio.sleep(15) return data def _pushText(self, id: str, text: str) -> str: field = { "textfield": {"text...
https://api.python.langchain.com/en/latest/_modules/langchain/tools/nuclia/tool.html
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response = requests.post( self._config["BACKEND"] + "/processing/push", headers={ "content-type": "application/json", "x-stf-nuakey": "Bearer " + self._config["NUA_KEY"], }, json=field, ) if response.status_code != 200: ...
https://api.python.langchain.com/en/latest/_modules/langchain/tools/nuclia/tool.html
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"`pip install protobuf`." ) from e res = requests.get( self._config["BACKEND"] + "/processing/pull", headers={ "x-stf-nuakey": "Bearer " + self._config["NUA_KEY"], }, ).json() if res["status"] == "empty": logger.info("Qu...
https://api.python.langchain.com/en/latest/_modules/langchain/tools/nuclia/tool.html
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Source code for langchain.tools.google_places.tool """Tool for the Google search API.""" from typing import Optional, Type from pydantic import BaseModel, Field from langchain.callbacks.manager import CallbackManagerForToolRun from langchain.tools.base import BaseTool from langchain.utilities.google_places_api import G...
https://api.python.langchain.com/en/latest/_modules/langchain/tools/google_places/tool.html
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Source code for langchain.tools.golden_query.tool """Tool for the Golden API.""" from typing import Optional from langchain.callbacks.manager import CallbackManagerForToolRun from langchain.tools.base import BaseTool from langchain.utilities.golden_query import GoldenQueryAPIWrapper [docs]class GoldenQueryRun(BaseTool)...
https://api.python.langchain.com/en/latest/_modules/langchain/tools/golden_query/tool.html
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Source code for langchain.tools.human.tool """Tool for asking human input.""" from typing import Callable, Optional from pydantic import Field from langchain.callbacks.manager import CallbackManagerForToolRun from langchain.tools.base import BaseTool def _print_func(text: str) -> None: print("\n") print(text) [...
https://api.python.langchain.com/en/latest/_modules/langchain/tools/human/tool.html
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Source code for langchain.tools.steamship_image_generation.tool """This tool allows agents to generate images using Steamship. Steamship offers access to different third party image generation APIs using a single API key. Today the following models are supported: - Dall-E - Stable Diffusion To use this tool, you must f...
https://api.python.langchain.com/en/latest/_modules/langchain/tools/steamship_image_generation/tool.html
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"Output: the UUID of a generated image" ) @root_validator(pre=True) def validate_size(cls, values: Dict) -> Dict: if "size" in values: size = values["size"] model_name = values["model_name"] if size not in SUPPORTED_IMAGE_SIZES[model_name]: raise R...
https://api.python.langchain.com/en/latest/_modules/langchain/tools/steamship_image_generation/tool.html
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blocks = task.output.blocks if len(blocks) > 0: if self.return_urls: return make_image_public(self.steamship, blocks[0]) else: return blocks[0].id raise RuntimeError(f"[{self.name}] Tool unable to generate image!")
https://api.python.langchain.com/en/latest/_modules/langchain/tools/steamship_image_generation/tool.html
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Source code for langchain.tools.steamship_image_generation.utils """Steamship Utils.""" from __future__ import annotations import uuid from typing import TYPE_CHECKING if TYPE_CHECKING: from steamship import Block, Steamship [docs]def make_image_public(client: Steamship, block: Block) -> str: """Upload a block ...
https://api.python.langchain.com/en/latest/_modules/langchain/tools/steamship_image_generation/utils.html
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Source code for langchain.graphs.nebula_graph import logging from string import Template from typing import Any, Dict rel_query = Template( """ MATCH ()-[e:`$edge_type`]->() WITH e limit 1 MATCH (m)-[:`$edge_type`]->(n) WHERE id(m) == src(e) AND id(n) == dst(e) RETURN "(:" + tags(m)[0] + ")-[:$edge_type]->(:" + t...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/nebula_graph.html
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self.schema = "" # Set schema try: self.refresh_schema() except Exception as e: raise ValueError(f"Could not refresh schema. Error: {e}") def _get_session_pool(self) -> Any: assert all( [self.username, self.password, self.address, self.port, self.s...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/nebula_graph.html
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@property def get_schema(self) -> str: """Returns the schema of the NebulaGraph database""" return self.schema [docs] def execute(self, query: str, params: dict = {}, retry: int = 0) -> Any: """Query NebulaGraph database.""" from nebula3.Exception import IOErrorException, NoValidS...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/nebula_graph.html
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raise ValueError(f"Error executing query to NebulaGraph. Error: {e}") except (TTransportException, IOErrorException): # connection issue, try to recreate session pool if retry < RETRY_TIMES: retry += 1 logging.warning( f"Connection issu...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/nebula_graph.html
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edge_types_schema.append(edge_schema) # build relationships types r = self.execute( rel_query.substitute(edge_type=edge_type_name) ).column_values("rels") if len(r) > 0: relationships.append(r[0].cast()) self.schema = ( ...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/nebula_graph.html
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Source code for langchain.graphs.neptune_graph import json from typing import Any, Dict, List, Tuple, Union import requests [docs]class NeptuneQueryException(Exception): """A class to handle queries that fail to execute""" def __init__(self, exception: Union[str, Dict]): if isinstance(exception, dict): ...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/neptune_graph.html
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try: self._refresh_schema() except NeptuneQueryException: raise ValueError("Could not get schema for Neptune database") @property def get_schema(self) -> str: """Returns the schema of the Neptune database""" return self.schema [docs] def query(self, query: str,...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/neptune_graph.html
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n_labels = summary["nodeLabels"] e_labels = summary["edgeLabels"] return n_labels, e_labels def _get_triples(self, e_labels: List[str]) -> List[str]: triple_query = """ MATCH (a)-[e:{e_label}]->(b) WITH a,e,b LIMIT 3000 RETURN DISTINCT labels(a) AS from, type(e) AS ed...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/neptune_graph.html
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"labels": label, } node_properties.append(np) return node_properties def _get_edge_properties(self, e_labels: List[str], types: Dict[str, Any]) -> List: edge_properties_query = """ MATCH ()-[e:{e_label}]->() RETURN properties(e) AS props LIMIT 100 ...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/neptune_graph.html
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The relationships are the following: {triple_schema} """
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/neptune_graph.html
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Source code for langchain.graphs.rdf_graph from __future__ import annotations from typing import ( TYPE_CHECKING, List, Optional, ) if TYPE_CHECKING: import rdflib prefixes = { "owl": """PREFIX owl: <http://www.w3.org/2002/07/owl#>\n""", "rdf": """PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-sy...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/rdf_graph.html
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""" FILTER (isIRI(?cls)) . \n""" """ OPTIONAL { ?cls rdfs:comment ?com } \n""" """}""" ) rel_query_rdf = prefixes["rdfs"] + ( """SELECT DISTINCT ?rel ?com\n""" """WHERE { \n""" """ ?subj ?rel ?obj . \n""" """ OPTIONAL { ?cls rdfs:comment ?com } \n""" """}""" ) rel_query_rdfs = ( ...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/rdf_graph.html
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"""}""" ) ) [docs]class RdfGraph: """ RDFlib wrapper for graph operations. Modes: * local: Local file - can be queried and changed * online: Online file - can only be queried, changes can be stored locally * store: Triple store - can be queried and changed if update_endpoint available To...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/rdf_graph.html
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raise ValueError( "Could not import rdflib python package. " "Please install it with `pip install rdflib`." ) if self.standard not in (supported_standards := ("rdf", "rdfs", "owl")): raise ValueError( f"Invalid standard. Supported standards...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/rdf_graph.html
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@property def get_schema(self) -> str: """ Returns the schema of the graph database. """ return self.schema [docs] def query( self, query: str, ) -> List[rdflib.query.ResultRow]: """ Query the graph. """ from rdflib.exceptions im...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/rdf_graph.html
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return ( "<" + str(res[var]) + "> (" + self._get_local_name(res[var]) + ", " + str(res["com"]) + ")" ) [docs] def load_schema(self) -> None: """ Load the graph schema information. """ def _rdf_...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/rdf_graph.html
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f"In the following, each IRI is followed by the local name and " f"optionally its description in parentheses. \n" f"The OWL graph supports the following node types:\n" f'{", ".join([self._res_to_str(r, "cls") for r in clss])}\n' f"The OWL graph supports th...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/rdf_graph.html
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Source code for langchain.graphs.memgraph_graph from langchain.graphs.neo4j_graph import Neo4jGraph SCHEMA_QUERY = """ CALL llm_util.schema("prompt_ready") YIELD * RETURN * """ [docs]class MemgraphGraph(Neo4jGraph): """Memgraph wrapper for graph operations.""" [docs] def __init__( self, url: str, usernam...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/memgraph_graph.html
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Source code for langchain.graphs.arangodb_graph import os from math import ceil from typing import Any, Dict, List, Optional [docs]class ArangoGraph: """ArangoDB wrapper for graph operations.""" [docs] def __init__(self, db: Any) -> None: """Create a new ArangoDB graph wrapper instance.""" self.s...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/arangodb_graph.html
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""" if not 0 <= sample_ratio <= 1: raise ValueError("**sample_ratio** value must be in between 0 to 1") # Stores the Edge Relationships between each ArangoDB Document Collection graph_schema: List[Dict[str, Any]] = [ {"graph_name": g["name"], "edge_definitions": g["edge_d...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/arangodb_graph.html
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[docs] def query( self, query: str, top_k: Optional[int] = None, **kwargs: Any ) -> List[Dict[str, Any]]: """Query the ArangoDB database.""" import itertools cursor = self.__db.aql.execute(query, **kwargs) return [doc for doc in itertools.islice(cursor, top_k)] [docs] @...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/arangodb_graph.html
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dbname: Optional[str] = None, username: Optional[str] = None, password: Optional[str] = None, ) -> Any: """Get the Arango DB client from credentials. Args: url: Arango DB url. Can be passed in as named arg or set as environment var ``ARANGODB_URL``. Defaults to "http://localhost:8529...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/arangodb_graph.html
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return ArangoClient(_url).db(_dbname, _username, _password, verify=True)
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/arangodb_graph.html
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Source code for langchain.graphs.kuzu_graph from typing import Any, Dict, List [docs]class KuzuGraph: """Kùzu wrapper for graph operations.""" [docs] def __init__(self, db: Any, database: str = "kuzu") -> None: try: import kuzu except ImportError: raise ImportError( ...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/kuzu_graph.html
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for property_name in properties: property_type = properties[property_name]["type"] list_type_flag = "" if properties[property_name]["dimension"] > 0: if "shape" in properties[property_name]: for s in properties[property_name]["s...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/kuzu_graph.html
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Source code for langchain.graphs.neo4j_graph from typing import Any, Dict, List node_properties_query = """ CALL apoc.meta.data() YIELD label, other, elementType, type, property WHERE NOT type = "RELATIONSHIP" AND elementType = "node" WITH label AS nodeLabels, collect({property:property, type:type}) AS properties RETUR...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/neo4j_graph.html
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self._database = database self.schema = "" # Verify connection try: self._driver.verify_connectivity() except neo4j.exceptions.ServiceUnavailable: raise ValueError( "Could not connect to Neo4j database. " "Please ensure that the url...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/neo4j_graph.html
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relationships_properties = self.query(rel_properties_query) relationships = self.query(rel_query) self.schema = f""" Node properties are the following: {[el['output'] for el in node_properties]} Relationship properties are the following: {[el['output'] for el in relations...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/neo4j_graph.html
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Source code for langchain.graphs.hugegraph from typing import Any, Dict, List [docs]class HugeGraph: """HugeGraph wrapper for graph operations""" [docs] def __init__( self, username: str = "default", password: str = "default", address: str = "127.0.0.1", port: int = 8081, ...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/hugegraph.html
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self.schema = ( f"Node properties: {vertex_schema}\n" f"Edge properties: {edge_schema}\n" f"Relationships: {relationships}\n" ) [docs] def query(self, query: str) -> List[Dict[str, Any]]: g = self.client.gremlin() res = g.exec(query) return res["dat...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/hugegraph.html
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Source code for langchain.graphs.networkx_graph """Networkx wrapper for graph operations.""" from __future__ import annotations from typing import Any, List, NamedTuple, Optional, Tuple KG_TRIPLE_DELIMITER = "<|>" [docs]class KnowledgeTriple(NamedTuple): """A triple in the graph.""" subject: str predicate: ...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/networkx_graph.html
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"""Create a new graph.""" try: import networkx as nx except ImportError: raise ImportError( "Could not import networkx python package. " "Please install it with `pip install networkx`." ) if graph is not None: if not...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/networkx_graph.html
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if self._graph.has_edge(knowledge_triple.subject, knowledge_triple.object_): self._graph.remove_edge(knowledge_triple.subject, knowledge_triple.object_) [docs] def get_triples(self) -> List[Tuple[str, str, str]]: """Get all triples in the graph.""" return [(u, v, d["relation"]) for u, v, ...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/networkx_graph.html
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Usage in a jupyter notebook: >>> from IPython.display import SVG >>> self.draw_graphviz_svg(layout="dot", filename="web.svg") >>> SVG('web.svg') """ from networkx.drawing.nx_agraph import to_agraph try: import pygraphviz # noqa: F401 excep...
https://api.python.langchain.com/en/latest/_modules/langchain/graphs/networkx_graph.html
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Source code for langchain.prompts.base """BasePrompt schema definition.""" from __future__ import annotations import warnings from abc import ABC from typing import Any, Callable, Dict, List, Set from langchain.formatting import formatter from langchain.schema.messages import BaseMessage, HumanMessage from langchain.sc...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/base.html
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try: from jinja2 import Environment, meta except ImportError: raise ImportError( "jinja2 not installed, which is needed to use the jinja2_formatter. " "Please install it with `pip install jinja2`." ) env = Environment() ast = env.parse(template) variables ...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/base.html
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"""Return prompt as string.""" return self.text [docs] def to_messages(self) -> List[BaseMessage]: """Return prompt as messages.""" return [HumanMessage(content=self.text)] [docs]class StringPromptTemplate(BasePromptTemplate, ABC): """String prompt that exposes the format method, returnin...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/base.html
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Source code for langchain.prompts.pipeline from typing import Any, Dict, List, Tuple from pydantic import root_validator from langchain.prompts.chat import BaseChatPromptTemplate from langchain.schema import BasePromptTemplate, PromptValue def _get_inputs(inputs: dict, input_variables: List[str]) -> dict: return {k...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/pipeline.html
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for k, prompt in self.pipeline_prompts: _inputs = _get_inputs(kwargs, prompt.input_variables) if isinstance(prompt, BaseChatPromptTemplate): kwargs[k] = prompt.format_messages(**_inputs) else: kwargs[k] = prompt.format(**_inputs) _inputs = _get...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/pipeline.html
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Source code for langchain.prompts.loading """Load prompts.""" import json import logging from pathlib import Path from typing import Union import yaml from langchain.output_parsers.regex import RegexParser from langchain.prompts.few_shot import FewShotPromptTemplate from langchain.prompts.prompt import PromptTemplate f...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/loading.html
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# Load the template. if template_path.suffix == ".txt": with open(template_path) as f: template = f.read() else: raise ValueError # Set the template variable to the extracted variable. config[var_name] = template return config def _load_example...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/loading.html
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"""Load the "few shot" prompt from the config.""" # Load the suffix and prefix templates. config = _load_template("suffix", config) config = _load_template("prefix", config) # Load the example prompt. if "example_prompt_path" in config: if "example_prompt" in config: raise ValueE...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/loading.html
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file_path = Path(file) else: file_path = file # Load from either json or yaml. if file_path.suffix == ".json": with open(file_path) as f: config = json.load(f) elif file_path.suffix == ".yaml": with open(file_path, "r") as f: config = yaml.safe_load(f) ...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/loading.html
cc03e0eae319-0
Source code for langchain.prompts.chat """Chat prompt template.""" from __future__ import annotations from abc import ABC, abstractmethod from pathlib import Path from typing import Any, Callable, List, Sequence, Tuple, Type, TypeVar, Union from pydantic import Field, root_validator from langchain.load.serializable imp...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/chat.html
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Combined prompt template. """ prompt = ChatPromptTemplate(messages=[self]) return prompt + other [docs]class MessagesPlaceholder(BaseMessagePromptTemplate): """Prompt template that assumes variable is already list of messages.""" variable_name: str """Name of variable to use as messa...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/chat.html
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"""Additional keyword arguments to pass to the prompt template.""" [docs] @classmethod def from_template( cls: Type[MessagePromptTemplateT], template: str, template_format: str = "f-string", **kwargs: Any, ) -> MessagePromptTemplateT: """Create a class from a string te...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/chat.html
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"""Format messages from kwargs. Args: **kwargs: Keyword arguments to use for formatting. Returns: List of BaseMessages. """ return [self.format(**kwargs)] @property def input_variables(self) -> List[str]: """ Input variables for this prompt...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/chat.html
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"""Format the prompt template. Args: **kwargs: Keyword arguments to use for formatting. Returns: Formatted message. """ text = self.prompt.format(**kwargs) return AIMessage(content=text, additional_kwargs=self.additional_kwargs) [docs]class SystemMessagePr...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/chat.html
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formatted string """ return self.format_prompt(**kwargs).to_string() [docs] def format_prompt(self, **kwargs: Any) -> PromptValue: """ Format prompt. Should return a PromptValue. Args: **kwargs: Keyword arguments to use for formatting. Returns: ...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/chat.html
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"""Combine two prompt templates. Args: other: Another prompt template. Returns: Combined prompt template. """ # Allow for easy combining if isinstance(other, ChatPromptTemplate): return ChatPromptTemplate(messages=self.messages + other.messages...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/chat.html
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else: values["input_variables"] = list(input_vars) return values [docs] @classmethod def from_template(cls, template: str, **kwargs: Any) -> ChatPromptTemplate: """Create a chat prompt template from a template string. Creates a chat template consisting of a single message assu...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/chat.html
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[docs] @classmethod def from_messages( cls, messages: Sequence[ Union[ BaseMessagePromptTemplate, BaseChatPromptTemplate, BaseMessage, Tuple[str, str], Tuple[Type, str], str, ] ...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/chat.html
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_message, (BaseChatPromptTemplate, BaseMessagePromptTemplate) ): input_vars.update(_message.input_variables) return cls(input_variables=sorted(input_vars), messages=_messages) [docs] def format(self, **kwargs: Any) -> str: """Format the chat template into a string. ...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/chat.html
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filled in. Args: **kwargs: keyword arguments to use for filling in template variables. Ought to be a subset of the input variables. Returns: A new ChatPromptTemplate. Example: .. code-block:: python from langchain.prompt...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/chat.html
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template: str the template string. Returns: a message prompt template of the appropriate type. """ if message_type == "human": message: BaseMessagePromptTemplate = HumanMessagePromptTemplate.from_template( template ) elif message_type == "ai": message = AIMess...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/chat.html
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BaseMessage, BaseMessagePromptTemplate, BaseChatPromptTemplate ] = message elif isinstance(message, BaseMessage): _message = message elif isinstance(message, str): _message = _create_template_from_message_type("human", message) elif isinstance(message, tuple): if len(message)...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/chat.html
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Source code for langchain.prompts.prompt """Prompt schema definition.""" from __future__ import annotations from pathlib import Path from string import Formatter from typing import Any, Dict, List, Optional, Union from pydantic import root_validator from langchain.prompts.base import ( DEFAULT_FORMATTER_MAPPING, ...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/prompt.html
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def __add__(self, other: Any) -> PromptTemplate: """Override the + operator to allow for combining prompt templates.""" # Allow for easy combining if isinstance(other, PromptTemplate): if self.template_format != "f-string": raise ValueError( "Addin...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/prompt.html
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Args: kwargs: Any arguments to be passed to the prompt template. Returns: A formatted string. Example: .. code-block:: python prompt.format(variable1="foo") """ kwargs = self._merge_partial_and_user_variables(**kwargs) return DE...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/prompt.html
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Returns: The final prompt generated. """ template = example_separator.join([prefix, *examples, suffix]) return cls(input_variables=input_variables, template=template, **kwargs) [docs] @classmethod def from_file( cls, template_file: Union[str, Path], input_variables: Li...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/prompt.html
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`"foo {variable2}"`. Returns: The prompt template loaded from the template. """ if template_format == "jinja2": # Get the variables for the template input_variables = _get_jinja2_variables_from_template(template) elif template_format == "f-string": ...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/prompt.html
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Source code for langchain.prompts.few_shot_with_templates """Prompt template that contains few shot examples.""" from typing import Any, Dict, List, Optional from pydantic import Extra, root_validator from langchain.prompts.base import DEFAULT_FORMATTER_MAPPING, StringPromptTemplate from langchain.prompts.example_selec...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/few_shot_with_templates.html
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examples = values.get("examples", None) example_selector = values.get("example_selector", None) if examples and example_selector: raise ValueError( "Only one of 'examples' and 'example_selector' should be provided" ) if examples is None and example_selecto...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/few_shot_with_templates.html
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Args: kwargs: Any arguments to be passed to the prompt template. Returns: A formatted string. Example: .. code-block:: python prompt.format(variable1="foo") """ kwargs = self._merge_partial_and_user_variables(**kwargs) # Get the example...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/few_shot_with_templates.html
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"""Return a dictionary of the prompt.""" if self.example_selector: raise ValueError("Saving an example selector is not currently supported") return super().dict(**kwargs)
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/few_shot_with_templates.html
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Source code for langchain.prompts.few_shot """Prompt template that contains few shot examples.""" from __future__ import annotations from typing import Any, Dict, List, Optional, Union from pydantic import BaseModel, Extra, Field, root_validator from langchain.prompts.base import ( DEFAULT_FORMATTER_MAPPING, St...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/few_shot.html
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) return values def _get_examples(self, **kwargs: Any) -> List[dict]: """Get the examples to use for formatting the prompt. Args: **kwargs: Keyword arguments to be passed to the example selector. Returns: List of examples. """ if self.examples ...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/few_shot.html
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def template_is_valid(cls, values: Dict) -> Dict: """Check that prefix, suffix, and input variables are consistent.""" if values["validate_template"]: check_valid_template( values["prefix"] + values["suffix"], values["template_format"], values[...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/few_shot.html
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[docs] def dict(self, **kwargs: Any) -> Dict: """Return a dictionary of the prompt.""" if self.example_selector: raise ValueError("Saving an example selector is not currently supported") return super().dict(**kwargs) [docs]class FewShotChatMessagePromptTemplate( BaseChatPrompt...
https://api.python.langchain.com/en/latest/_modules/langchain/prompts/few_shot.html