id stringlengths 14 16 | text stringlengths 29 2.73k | source stringlengths 50 116 |
|---|---|---|
6607a9e20659-1 | .. code-block:: python
{
'id': 'text_id',
'vector': 'text_embedding',
'text': 'text_plain',
'metadata': 'metadata_dictionary_in_json',
}... | https:///python.langchain.com/en/latest/_modules/langchain/vectorstores/myscale.html |
6607a9e20659-2 | config: Optional[MyScaleSettings] = None,
**kwargs: Any,
) -> None:
"""MyScale Wrapper to LangChain
embedding_function (Embeddings):
config (MyScaleSettings): Configuration to MyScale Client
Other keyword arguments will pass into
[clickhouse-connect](https://docs.... | https:///python.langchain.com/en/latest/_modules/langchain/vectorstores/myscale.html |
6607a9e20659-3 | CREATE TABLE IF NOT EXISTS {self.config.database}.{self.config.table}(
{self.config.column_map['id']} String,
{self.config.column_map['text']} String,
{self.config.column_map['vector']} Array(Float32),
{self.config.column_map['metadata']} JSON,
... | https:///python.langchain.com/en/latest/_modules/langchain/vectorstores/myscale.html |
6607a9e20659-4 | _data.append(f"({n})")
i_str = f"""
INSERT INTO TABLE
{self.config.database}.{self.config.table}({ks})
VALUES
{','.join(_data)}
"""
return i_str
def _insert(self, transac: Iterable, column_names: Iterable[str]) -> N... | https:///python.langchain.com/en/latest/_modules/langchain/vectorstores/myscale.html |
6607a9e20659-5 | column_names[colmap_["metadata"]] = map(json.dumps, metadatas)
assert len(set(colmap_) - set(column_names)) >= 0
keys, values = zip(*column_names.items())
try:
t = None
for v in self.pgbar(
zip(*values), desc="Inserting data...", total=len(metadatas)
... | https:///python.langchain.com/en/latest/_modules/langchain/vectorstores/myscale.html |
6607a9e20659-6 | texts (Iterable[str]): List or tuple of strings to be added
config (MyScaleSettings, Optional): Myscale configuration
text_ids (Optional[Iterable], optional): IDs for the texts.
Defaults to None.
batch_size (int, optional): Batchsi... | https:///python.langchain.com/en/latest/_modules/langchain/vectorstores/myscale.html |
6607a9e20659-7 | ).named_results():
_repr += (
f"|\033[94m{r['name']:24s}\033[0m|\033[96m{r['type']:24s}\033[0m|\n"
)
_repr += "-" * 51 + "\n"
return _repr
def _build_qstr(
self, q_emb: List[float], topk: int, where_str: Optional[str] = None
) -> str:
q_emb... | https:///python.langchain.com/en/latest/_modules/langchain/vectorstores/myscale.html |
6607a9e20659-8 | of SQL injection. When dealing with metadatas, remember to
use `{self.metadata_column}.attribute` instead of `attribute`
alone. The default name for it is `metadata`.
Returns:
List[Document]: List of Documents
"""
return self.similarity_search_by_v... | https:///python.langchain.com/en/latest/_modules/langchain/vectorstores/myscale.html |
6607a9e20659-9 | ]
except Exception as e:
logger.error(f"\033[91m\033[1m{type(e)}\033[0m \033[95m{str(e)}\033[0m")
return []
[docs] def similarity_search_with_relevance_scores(
self, query: str, k: int = 4, where_str: Optional[str] = None, **kwargs: Any
) -> List[Tuple[Document, float]]:
... | https:///python.langchain.com/en/latest/_modules/langchain/vectorstores/myscale.html |
6607a9e20659-10 | return []
[docs] def drop(self) -> None:
"""
Helper function: Drop data
"""
self.client.command(
f"DROP TABLE IF EXISTS {self.config.database}.{self.config.table}"
)
@property
def metadata_column(self) -> str:
return self.config.column_map["metadata... | https:///python.langchain.com/en/latest/_modules/langchain/vectorstores/myscale.html |
015d3ed426dc-0 | Source code for langchain.vectorstores.tair
"""Wrapper around Tair Vector."""
from __future__ import annotations
import json
import logging
import uuid
from typing import Any, Iterable, List, Optional, Type
from langchain.docstore.document import Document
from langchain.embeddings.base import Embeddings
from langchain.... | https:///python.langchain.com/en/latest/_modules/langchain/vectorstores/tair.html |
015d3ed426dc-1 | data_type: str,
**kwargs: Any,
) -> bool:
index = self.client.tvs_get_index(self.index_name)
if index is not None:
logger.info("Index already exists")
return False
self.client.tvs_create_index(
self.index_name,
dim,
distance... | https:///python.langchain.com/en/latest/_modules/langchain/vectorstores/tair.html |
015d3ed426dc-2 | Args:
query (str): The query text for which to find similar documents.
k (int): The number of documents to return. Default is 4.
Returns:
List[Document]: A list of documents that are most similar to the query text.
"""
# Creates embedding vector from user quer... | https:///python.langchain.com/en/latest/_modules/langchain/vectorstores/tair.html |
015d3ed426dc-3 | if "tair_url" in kwargs:
kwargs.pop("tair_url")
distance_type = tairvector.DistanceMetric.InnerProduct
if "distance_type" in kwargs:
distance_type = kwargs.pop("distance_typ")
index_type = tairvector.IndexType.HNSW
if "index_type" in kwargs:
index_type... | https:///python.langchain.com/en/latest/_modules/langchain/vectorstores/tair.html |
015d3ed426dc-4 | cls,
documents: List[Document],
embedding: Embeddings,
metadatas: Optional[List[dict]] = None,
index_name: str = "langchain",
content_key: str = "content",
metadata_key: str = "metadata",
**kwargs: Any,
) -> Tair:
texts = [d.page_content for d in docum... | https:///python.langchain.com/en/latest/_modules/langchain/vectorstores/tair.html |
015d3ed426dc-5 | # index not exist
logger.info("Index does not exist")
return False
return True
[docs] @classmethod
def from_existing_index(
cls,
embedding: Embeddings,
index_name: str = "langchain",
content_key: str = "content",
metadata_key: str = "metadat... | https:///python.langchain.com/en/latest/_modules/langchain/vectorstores/tair.html |
9fa7168b2a14-0 | Source code for langchain.output_parsers.regex
from __future__ import annotations
import re
from typing import Dict, List, Optional
from langchain.schema import BaseOutputParser
[docs]class RegexParser(BaseOutputParser):
"""Class to parse the output into a dictionary."""
regex: str
output_keys: List[str]
... | https:///python.langchain.com/en/latest/_modules/langchain/output_parsers/regex.html |
a7ae5da05b20-0 | Source code for langchain.output_parsers.retry
from __future__ import annotations
from typing import TypeVar
from langchain.base_language import BaseLanguageModel
from langchain.chains.llm import LLMChain
from langchain.prompts.base import BasePromptTemplate
from langchain.prompts.prompt import PromptTemplate
from lang... | https:///python.langchain.com/en/latest/_modules/langchain/output_parsers/retry.html |
a7ae5da05b20-1 | chain = LLMChain(llm=llm, prompt=prompt)
return cls(parser=parser, retry_chain=chain)
[docs] def parse_with_prompt(self, completion: str, prompt_value: PromptValue) -> T:
try:
parsed_completion = self.parser.parse(completion)
except OutputParserException:
new_completio... | https:///python.langchain.com/en/latest/_modules/langchain/output_parsers/retry.html |
a7ae5da05b20-2 | ) -> RetryWithErrorOutputParser[T]:
chain = LLMChain(llm=llm, prompt=prompt)
return cls(parser=parser, retry_chain=chain)
[docs] def parse_with_prompt(self, completion: str, prompt_value: PromptValue) -> T:
try:
parsed_completion = self.parser.parse(completion)
except Outp... | https:///python.langchain.com/en/latest/_modules/langchain/output_parsers/retry.html |
be48eff5109e-0 | Source code for langchain.output_parsers.rail_parser
from __future__ import annotations
from typing import Any, Dict
from langchain.schema import BaseOutputParser
[docs]class GuardrailsOutputParser(BaseOutputParser):
guard: Any
@property
def _type(self) -> str:
return "guardrails"
[docs] @classme... | https:///python.langchain.com/en/latest/_modules/langchain/output_parsers/rail_parser.html |
ed436be83145-0 | Source code for langchain.output_parsers.list
from __future__ import annotations
from abc import abstractmethod
from typing import List
from langchain.schema import BaseOutputParser
[docs]class ListOutputParser(BaseOutputParser):
"""Class to parse the output of an LLM call to a list."""
@property
def _type(... | https:///python.langchain.com/en/latest/_modules/langchain/output_parsers/list.html |
1103ecdbcbeb-0 | Source code for langchain.output_parsers.structured
from __future__ import annotations
import json
from typing import Any, List
from pydantic import BaseModel
from langchain.output_parsers.format_instructions import STRUCTURED_FORMAT_INSTRUCTIONS
from langchain.schema import BaseOutputParser, OutputParserException
line... | https:///python.langchain.com/en/latest/_modules/langchain/output_parsers/structured.html |
1103ecdbcbeb-1 | ) -> StructuredOutputParser:
return cls(response_schemas=response_schemas)
[docs] def get_format_instructions(self) -> str:
schema_str = "\n".join(
[_get_sub_string(schema) for schema in self.response_schemas]
)
return STRUCTURED_FORMAT_INSTRUCTIONS.format(format=schema_st... | https:///python.langchain.com/en/latest/_modules/langchain/output_parsers/structured.html |
65cbe39b8b7c-0 | Source code for langchain.output_parsers.fix
from __future__ import annotations
from typing import TypeVar
from langchain.base_language import BaseLanguageModel
from langchain.chains.llm import LLMChain
from langchain.output_parsers.prompts import NAIVE_FIX_PROMPT
from langchain.prompts.base import BasePromptTemplate
f... | https:///python.langchain.com/en/latest/_modules/langchain/output_parsers/fix.html |
195afb2a4aa0-0 | Source code for langchain.output_parsers.pydantic
import json
import re
from typing import Type, TypeVar
from pydantic import BaseModel, ValidationError
from langchain.output_parsers.format_instructions import PYDANTIC_FORMAT_INSTRUCTIONS
from langchain.schema import BaseOutputParser, OutputParserException
T = TypeVar(... | https:///python.langchain.com/en/latest/_modules/langchain/output_parsers/pydantic.html |
195afb2a4aa0-1 | @property
def _type(self) -> str:
return "pydantic"
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 02, 2023. | https:///python.langchain.com/en/latest/_modules/langchain/output_parsers/pydantic.html |
f236870699f4-0 | Source code for langchain.output_parsers.regex_dict
from __future__ import annotations
import re
from typing import Dict, Optional
from langchain.schema import BaseOutputParser
[docs]class RegexDictParser(BaseOutputParser):
"""Class to parse the output into a dictionary."""
regex_pattern: str = r"{}:\s?([^.'\n'... | https:///python.langchain.com/en/latest/_modules/langchain/output_parsers/regex_dict.html |
eed98336cbda-0 | Source code for langchain.docstore.wikipedia
"""Wrapper around wikipedia API."""
from typing import Union
from langchain.docstore.base import Docstore
from langchain.docstore.document import Document
[docs]class Wikipedia(Docstore):
"""Wrapper around wikipedia API."""
def __init__(self) -> None:
"""Chec... | https:///python.langchain.com/en/latest/_modules/langchain/docstore/wikipedia.html |
034b0e788a8d-0 | Source code for langchain.docstore.in_memory
"""Simple in memory docstore in the form of a dict."""
from typing import Dict, Union
from langchain.docstore.base import AddableMixin, Docstore
from langchain.docstore.document import Document
[docs]class InMemoryDocstore(Docstore, AddableMixin):
"""Simple in memory doc... | https:///python.langchain.com/en/latest/_modules/langchain/docstore/in_memory.html |
fe97a1fe4d22-0 | Source code for langchain.prompts.base
"""BasePrompt schema definition."""
from __future__ import annotations
import json
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Any, Callable, Dict, List, Mapping, Optional, Set, Union
import yaml
from pydantic import BaseModel, Extra, Field, roo... | https:///python.langchain.com/en/latest/_modules/langchain/prompts/base.html |
fe97a1fe4d22-1 | "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 = meta.find_undeclared_variables(ast)
return variables
DEFAULT_FORMATTER_MAPPING: Dict[str, Callable] = {
... | https:///python.langchain.com/en/latest/_modules/langchain/prompts/base.html |
fe97a1fe4d22-2 | """Base class for all prompt templates, returning a prompt."""
input_variables: List[str]
"""A list of the names of the variables the prompt template expects."""
output_parser: Optional[BaseOutputParser] = None
"""How to parse the output of calling an LLM on this formatted prompt."""
partial_variabl... | https:///python.langchain.com/en/latest/_modules/langchain/prompts/base.html |
fe97a1fe4d22-3 | prompt_dict["input_variables"] = list(
set(self.input_variables).difference(kwargs)
)
prompt_dict["partial_variables"] = {**self.partial_variables, **kwargs}
return type(self)(**prompt_dict)
def _merge_partial_and_user_variables(self, **kwargs: Any) -> Dict[str, Any]:
# G... | https:///python.langchain.com/en/latest/_modules/langchain/prompts/base.html |
fe97a1fe4d22-4 | # Convert file to Path object.
if isinstance(file_path, str):
save_path = Path(file_path)
else:
save_path = file_path
directory_path = save_path.parent
directory_path.mkdir(parents=True, exist_ok=True)
# Fetch dictionary to save
prompt_dict = self.... | https:///python.langchain.com/en/latest/_modules/langchain/prompts/base.html |
cf90ad095927-0 | Source code for langchain.prompts.few_shot
"""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,
check_valid_template,
)
from langcha... | https:///python.langchain.com/en/latest/_modules/langchain/prompts/few_shot.html |
cf90ad095927-1 | """Check that one and only one of examples/example_selector are provided."""
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_select... | https:///python.langchain.com/en/latest/_modules/langchain/prompts/few_shot.html |
cf90ad095927-2 | # Get the examples to use.
examples = self._get_examples(**kwargs)
# Format the examples.
example_strings = [
self.example_prompt.format(**example) for example in examples
]
# Create the overall template.
pieces = [self.prefix, *example_strings, self.suffix]
... | https:///python.langchain.com/en/latest/_modules/langchain/prompts/few_shot.html |
febc24f7b8be-0 | 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, Union
from pydantic import Extra, root_validator
from langchain.prompts.base import (
DEFAULT_FORMATTER_MAPPING,
S... | https:///python.langchain.com/en/latest/_modules/langchain/prompts/prompt.html |
febc24f7b8be-1 | """
kwargs = self._merge_partial_and_user_variables(**kwargs)
return DEFAULT_FORMATTER_MAPPING[self.template_format](self.template, **kwargs)
@root_validator()
def template_is_valid(cls, values: Dict) -> Dict:
"""Check that template and input variables are consistent."""
if value... | https:///python.langchain.com/en/latest/_modules/langchain/prompts/prompt.html |
febc24f7b8be-2 | [docs] @classmethod
def from_file(
cls, template_file: Union[str, Path], input_variables: List[str], **kwargs: Any
) -> PromptTemplate:
"""Load a prompt from a file.
Args:
template_file: The path to the file containing the prompt template.
input_variables: A li... | https:///python.langchain.com/en/latest/_modules/langchain/prompts/prompt.html |
236c67df35b2-0 | Source code for langchain.prompts.loading
"""Load prompts from disk."""
import importlib
import json
import logging
from pathlib import Path
from typing import Union
import yaml
from langchain.output_parsers.regex import RegexParser
from langchain.prompts.base import BasePromptTemplate
from langchain.prompts.few_shot i... | https:///python.langchain.com/en/latest/_modules/langchain/prompts/loading.html |
236c67df35b2-1 | 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_examples(config: dict) -> dict:
... | https:///python.langchain.com/en/latest/_modules/langchain/prompts/loading.html |
236c67df35b2-2 | 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 ValueError(
"Only one of example_prompt and example_prompt_path should "
... | https:///python.langchain.com/en/latest/_modules/langchain/prompts/loading.html |
236c67df35b2-3 | # 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)
elif file_path.suffix == ".py":
spec = importlib.util... | https:///python.langchain.com/en/latest/_modules/langchain/prompts/loading.html |
bc451df98ecd-0 | 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:///python.langchain.com/en/latest/_modules/langchain/prompts/few_shot_with_templates.html |
bc451df98ecd-1 | 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:///python.langchain.com/en/latest/_modules/langchain/prompts/few_shot_with_templates.html |
bc451df98ecd-2 | 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 examples to use.
... | https:///python.langchain.com/en/latest/_modules/langchain/prompts/few_shot_with_templates.html |
bc451df98ecd-3 | if self.example_selector:
raise ValueError("Saving an example selector is not currently supported")
return super().dict(**kwargs)
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 02, 2023. | https:///python.langchain.com/en/latest/_modules/langchain/prompts/few_shot_with_templates.html |
e1b143c509fc-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, Union
from pydantic import BaseModel, Field
from langchain.memory.buffer import get_buffer_str... | https:///python.langchain.com/en/latest/_modules/langchain/prompts/chat.html |
e1b143c509fc-1 | def input_variables(self) -> List[str]:
"""Input variables for this prompt template."""
return [self.variable_name]
class BaseStringMessagePromptTemplate(BaseMessagePromptTemplate, ABC):
prompt: StringPromptTemplate
additional_kwargs: dict = Field(default_factory=dict)
@classmethod
def f... | https:///python.langchain.com/en/latest/_modules/langchain/prompts/chat.html |
e1b143c509fc-2 | text = self.prompt.format(**kwargs)
return SystemMessage(content=text, additional_kwargs=self.additional_kwargs)
class ChatPromptValue(PromptValue):
messages: List[BaseMessage]
def to_string(self) -> str:
"""Return prompt as string."""
return get_buffer_string(self.messages)
def to_m... | https:///python.langchain.com/en/latest/_modules/langchain/prompts/chat.html |
e1b143c509fc-3 | for role, template in string_messages
]
return cls.from_messages(messages)
@classmethod
def from_messages(
cls, messages: Sequence[Union[BaseMessagePromptTemplate, BaseMessage]]
) -> ChatPromptTemplate:
input_vars = set()
for message in messages:
if isinst... | https:///python.langchain.com/en/latest/_modules/langchain/prompts/chat.html |
1e228322c399-0 | Source code for langchain.prompts.example_selector.semantic_similarity
"""Example selector that selects examples based on SemanticSimilarity."""
from __future__ import annotations
from typing import Any, Dict, List, Optional, Type
from pydantic import BaseModel, Extra
from langchain.embeddings.base import Embeddings
fr... | https:///python.langchain.com/en/latest/_modules/langchain/prompts/example_selector/semantic_similarity.html |
1e228322c399-1 | return ids[0]
[docs] def select_examples(self, input_variables: Dict[str, str]) -> List[dict]:
"""Select which examples to use based on semantic similarity."""
# Get the docs with the highest similarity.
if self.input_keys:
input_variables = {key: input_variables[key] for key in s... | https:///python.langchain.com/en/latest/_modules/langchain/prompts/example_selector/semantic_similarity.html |
1e228322c399-2 | instead of all variables.
vectorstore_cls_kwargs: optional kwargs containing url for vector store
Returns:
The ExampleSelector instantiated, backed by a vector store.
"""
if input_keys:
string_examples = [
" ".join(sorted_values({k: eg[k] for k... | https:///python.langchain.com/en/latest/_modules/langchain/prompts/example_selector/semantic_similarity.html |
1e228322c399-3 | examples = [dict(e.metadata) for e in example_docs]
# If example keys are provided, filter examples to those keys.
if self.example_keys:
examples = [{k: eg[k] for k in self.example_keys} for eg in examples]
return examples
[docs] @classmethod
def from_examples(
cls,
... | https:///python.langchain.com/en/latest/_modules/langchain/prompts/example_selector/semantic_similarity.html |
1e228322c399-4 | string_examples, embeddings, metadatas=examples, **vectorstore_cls_kwargs
)
return cls(vectorstore=vectorstore, k=k, fetch_k=fetch_k, input_keys=input_keys)
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 02, 2023. | https:///python.langchain.com/en/latest/_modules/langchain/prompts/example_selector/semantic_similarity.html |
f2abe3a384c2-0 | Source code for langchain.prompts.example_selector.length_based
"""Select examples based on length."""
import re
from typing import Callable, Dict, List
from pydantic import BaseModel, validator
from langchain.prompts.example_selector.base import BaseExampleSelector
from langchain.prompts.prompt import PromptTemplate
d... | https:///python.langchain.com/en/latest/_modules/langchain/prompts/example_selector/length_based.html |
f2abe3a384c2-1 | get_text_length = values["get_text_length"]
string_examples = [example_prompt.format(**eg) for eg in values["examples"]]
return [get_text_length(eg) for eg in string_examples]
[docs] def select_examples(self, input_variables: Dict[str, str]) -> List[dict]:
"""Select which examples to use base... | https:///python.langchain.com/en/latest/_modules/langchain/prompts/example_selector/length_based.html |
b586ef22c35c-0 | Source code for langchain.document_loaders.airbyte_json
"""Loader that loads local airbyte json files."""
import json
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
from langchain.utils import stringify_dict
[docs]class AirbyteJSONLoader(B... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/airbyte_json.html |
164edfff6a5f-0 | Source code for langchain.document_loaders.diffbot
"""Loader that uses Diffbot to load webpages in text format."""
import logging
from typing import Any, List
import requests
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
logger = logging.getLogger(__name__)
[doc... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/diffbot.html |
164edfff6a5f-1 | text = data["objects"][0]["text"] if "objects" in data else ""
metadata = {"source": url}
docs.append(Document(page_content=text, metadata=metadata))
except Exception as e:
if self.continue_on_failure:
logger.error(f"Error fetching or proce... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/diffbot.html |
60039327ea1f-0 | Source code for langchain.document_loaders.modern_treasury
"""Loader that fetches data from Modern Treasury"""
import json
import urllib.request
from base64 import b64encode
from typing import List, Optional
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
from lan... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/modern_treasury.html |
60039327ea1f-1 | self,
resource: str,
organization_id: Optional[str] = None,
api_key: Optional[str] = None,
) -> None:
self.resource = resource
organization_id = organization_id or get_from_env(
"organization_id", "MODERN_TREASURY_ORGANIZATION_ID"
)
api_key = api_k... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/modern_treasury.html |
03e45db6a586-0 | Source code for langchain.document_loaders.bigquery
from typing import List, Optional
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class BigQueryLoader(BaseLoader):
"""Loads a query result from BigQuery into a list of documents.
Each document repr... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/bigquery.html |
03e45db6a586-1 | metadata_columns = []
for row in query_result:
page_content = "\n".join(
f"{k}: {v}" for k, v in row.items() if k in page_content_columns
)
metadata = {k: v for k, v in row.items() if k in metadata_columns}
doc = Document(page_content=page_content,... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/bigquery.html |
601861e2306b-0 | Source code for langchain.document_loaders.readthedocs
"""Loader that loads ReadTheDocs documentation directory dump."""
from pathlib import Path
from typing import Any, List, Optional
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class ReadTheDocsLoader(B... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/readthedocs.html |
601861e2306b-1 | text = text[0].get_text()
else:
text = ""
return "\n".join([t for t in text.split("\n") if t])
docs = []
for p in Path(self.file_path).rglob("*"):
if p.is_dir():
continue
with open(p, encoding=self.encoding, errors=self.erro... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/readthedocs.html |
799e30e4fe4a-0 | Source code for langchain.document_loaders.chatgpt
"""Load conversations from ChatGPT data export"""
import datetime
import json
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
def concatenate_rows(message: dict, title: str) -> str:
if ... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/chatgpt.html |
799e30e4fe4a-1 | documents.append(Document(page_content=text, metadata=metadata))
return documents
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 02, 2023. | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/chatgpt.html |
87c48192991a-0 | Source code for langchain.document_loaders.powerpoint
"""Loader that loads powerpoint files."""
import os
from typing import List
from langchain.document_loaders.unstructured import UnstructuredFileLoader
[docs]class UnstructuredPowerPointLoader(UnstructuredFileLoader):
"""Loader that uses unstructured to load powe... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/powerpoint.html |
87c48192991a-1 | return partition_pptx(filename=self.file_path, **self.unstructured_kwargs)
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 02, 2023. | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/powerpoint.html |
e7780cf76cd5-0 | Source code for langchain.document_loaders.epub
"""Loader that loads EPub files."""
from typing import List
from langchain.document_loaders.unstructured import (
UnstructuredFileLoader,
satisfies_min_unstructured_version,
)
[docs]class UnstructuredEPubLoader(UnstructuredFileLoader):
"""Loader that uses unst... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/epub.html |
ba171a18b925-0 | Source code for langchain.document_loaders.python
import tokenize
from langchain.document_loaders.text import TextLoader
[docs]class PythonLoader(TextLoader):
"""
Load Python files, respecting any non-default encoding if specified.
"""
def __init__(self, file_path: str):
with open(file_path, "rb... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/python.html |
faef20befc5d-0 | Source code for langchain.document_loaders.azure_blob_storage_file
"""Loading logic for loading documents from an Azure Blob Storage file."""
import os
import tempfile
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
from langchain.document_... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/azure_blob_storage_file.html |
cf7f7f3356e1-0 | Source code for langchain.document_loaders.git
import os
from typing import Callable, List, Optional
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class GitLoader(BaseLoader):
"""Loads files from a Git repository into a list of documents.
Repositor... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/git.html |
cf7f7f3356e1-1 | else:
repo = Repo(self.repo_path)
repo.git.checkout(self.branch)
docs: List[Document] = []
for item in repo.tree().traverse():
if not isinstance(item, Blob):
continue
file_path = os.path.join(self.repo_path, item.path)
ignored_f... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/git.html |
b025a69f3fbe-0 | Source code for langchain.document_loaders.text
from typing import List, Optional
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class TextLoader(BaseLoader):
"""Load text files."""
def __init__(self, file_path: str, encoding: Optional[str] = None):... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/text.html |
290bdf020951-0 | Source code for langchain.document_loaders.image
"""Loader that loads image files."""
from typing import List
from langchain.document_loaders.unstructured import UnstructuredFileLoader
[docs]class UnstructuredImageLoader(UnstructuredFileLoader):
"""Loader that uses unstructured to load image files, such as PNGs and... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/image.html |
07f20d10e310-0 | Source code for langchain.document_loaders.srt
"""Loader for .srt (subtitle) files."""
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class SRTLoader(BaseLoader):
"""Loader for .srt (subtitle) files."""
def __init__(self, fil... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/srt.html |
944be3304458-0 | Source code for langchain.document_loaders.url_selenium
"""Loader that uses Selenium to load a page, then uses unstructured to load the html.
"""
import logging
from typing import TYPE_CHECKING, List, Literal, Optional, Union
if TYPE_CHECKING:
from selenium.webdriver import Chrome, Firefox
from langchain.docstore.d... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/url_selenium.html |
944be3304458-1 | raise ValueError(
"unstructured package not found, please install it with "
"`pip install unstructured`"
)
self.urls = urls
self.continue_on_failure = continue_on_failure
self.browser = browser
self.executable_path = executable_path
sel... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/url_selenium.html |
944be3304458-2 | """Load the specified URLs using Selenium and create Document instances.
Returns:
List[Document]: A list of Document instances with loaded content.
"""
from unstructured.partition.html import partition_html
docs: List[Document] = list()
driver = self._get_driver()
... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/url_selenium.html |
6e15690eb8d2-0 | Source code for langchain.document_loaders.notion
"""Loader that loads Notion directory dump."""
from pathlib import Path
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class NotionDirectoryLoader(BaseLoader):
"""Loader that load... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/notion.html |
cd4ae848bd75-0 | Source code for langchain.document_loaders.evernote
"""Load documents from Evernote.
https://gist.github.com/foxmask/7b29c43a161e001ff04afdb2f181e31c
"""
import hashlib
from base64 import b64decode
from time import strptime
from typing import Any, Dict, List
from langchain.docstore.document import Document
from langcha... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/evernote.html |
cd4ae848bd75-1 | else:
note_dict[elem.tag] = elem.text
note_dict["resource"] = resources
return note_dict
def _parse_note_xml(xml_file: str) -> str:
"""Parse Evernote xml."""
# Without huge_tree set to True, parser may complain about huge text node
# Try to recover, because there may be " ", which w... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/evernote.html |
92807198b598-0 | Source code for langchain.document_loaders.reddit
"""Reddit document loader."""
from __future__ import annotations
from typing import TYPE_CHECKING, Iterable, List, Optional, Sequence
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
if TYPE_CHECKING:
import pra... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/reddit.html |
92807198b598-1 | if self.mode == "subreddit":
for search_query in self.search_queries:
for category in self.categories:
docs = self._subreddit_posts_loader(
search_query=search_query, category=category, reddit=reddit
)
result... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/reddit.html |
92807198b598-2 | method = getattr(user.submissions, category)
cat_posts = method(limit=self.number_posts)
"""Format reddit posts into a string."""
for post in cat_posts:
metadata = {
"post_subreddit": post.subreddit_name_prefixed,
"post_category": category,
... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/reddit.html |
cf919d9b47b9-0 | Source code for langchain.document_loaders.url_playwright
"""Loader that uses Playwright to load a page, then uses unstructured to load the html.
"""
import logging
from typing import List, Optional
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
logger = logging.... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/url_playwright.html |
cf919d9b47b9-1 | [docs] def load(self) -> List[Document]:
"""Load the specified URLs using Playwright and create Document instances.
Returns:
List[Document]: A list of Document instances with loaded content.
"""
from playwright.sync_api import sync_playwright
from unstructured.part... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/url_playwright.html |
2adc2373df1d-0 | Source code for langchain.document_loaders.twitter
"""Twitter document loader."""
from __future__ import annotations
from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Optional, Sequence, Union
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
if TYPE_CHEC... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/twitter.html |
2adc2373df1d-1 | user = api.get_user(screen_name=username)
docs = self._format_tweets(tweets, user)
results.extend(docs)
return results
def _format_tweets(
self, tweets: List[Dict[str, Any]], user_info: dict
) -> Iterable[Document]:
"""Format tweets into a string."""
for t... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/twitter.html |
2adc2373df1d-2 | access_token=access_token,
access_token_secret=access_token_secret,
consumer_key=consumer_key,
consumer_secret=consumer_secret,
)
return cls(
auth_handler=auth,
twitter_users=twitter_users,
number_tweets=number_tweets,
)
By ... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/twitter.html |
5ecff278ae21-0 | Source code for langchain.document_loaders.gcs_directory
"""Loading logic for loading documents from an GCS directory."""
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
from langchain.document_loaders.gcs_file import GCSFileLoader
[docs]cl... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/gcs_directory.html |
0eefa3edbbb3-0 | Source code for langchain.document_loaders.html
"""Loader that uses unstructured to load HTML files."""
from typing import List
from langchain.document_loaders.unstructured import UnstructuredFileLoader
[docs]class UnstructuredHTMLLoader(UnstructuredFileLoader):
"""Loader that uses unstructured to load HTML files."... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/html.html |
f032db217422-0 | Source code for langchain.document_loaders.confluence
"""Load Data from a Confluence Space"""
import logging
from typing import Any, Callable, List, Optional, Union
from tenacity import (
before_sleep_log,
retry,
stop_after_attempt,
wait_exponential,
)
from langchain.docstore.document import Document
fr... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
f032db217422-1 | :param url: _description_
:type url: str
:param api_key: _description_, defaults to None
:type api_key: str, optional
:param username: _description_, defaults to None
:type username: str, optional
:param oauth2: _description_, defaults to {}
:type oauth2: dict, optional
:param cloud: _de... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
f032db217422-2 | if errors:
raise ValueError(f"Error(s) while validating input: {errors}")
self.base_url = url
self.number_of_retries = number_of_retries
self.min_retry_seconds = min_retry_seconds
self.max_retry_seconds = max_retry_seconds
try:
from atlassian import Conflu... | https:///python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
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