id stringlengths 14 16 | text stringlengths 29 2.73k | source stringlengths 49 117 |
|---|---|---|
e6a9b887bc81-0 | Source code for langchain.document_loaders.discord
"""Load from Discord chat dump"""
from __future__ import annotations
from typing import TYPE_CHECKING, List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
if TYPE_CHECKING:
import pandas as pd
[docs]class Dis... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/discord.html |
b7c5a9534d30-0 | Source code for langchain.document_loaders.rtf
"""Loader that loads rich text files."""
from typing import Any, List
from langchain.document_loaders.unstructured import (
UnstructuredFileLoader,
satisfies_min_unstructured_version,
)
[docs]class UnstructuredRTFLoader(UnstructuredFileLoader):
"""Loader that u... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/rtf.html |
7939fd5332c3-0 | Source code for langchain.document_loaders.s3_directory
"""Loading logic for loading documents from an s3 directory."""
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
from langchain.document_loaders.s3_file import S3FileLoader
[docs]class ... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/s3_directory.html |
4b98676b48eb-0 | Source code for langchain.document_loaders.bilibili
import json
import re
import warnings
from typing import List, Tuple
import requests
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class BiliBiliLoader(BaseLoader):
"""Loader that loads bilibili trans... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/bilibili.html |
4b98676b48eb-1 | video_info = sync(v.get_info())
video_info.update({"url": url})
# Get subtitle url
subtitle = video_info.pop("subtitle")
sub_list = subtitle["list"]
if sub_list:
sub_url = sub_list[0]["subtitle_url"]
result = requests.get(sub_url)
raw_sub_title... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/bilibili.html |
43e0c7d5938f-0 | Source code for langchain.document_loaders.arxiv
from typing import List, Optional
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
from langchain.utilities.arxiv import ArxivAPIWrapper
[docs]class ArxivLoader(BaseLoader):
"""Loads a query result from arxiv.org... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/arxiv.html |
52b46dac6df1-0 | Source code for langchain.document_loaders.odt
"""Loader that loads Open Office ODT files."""
from typing import Any, List
from langchain.document_loaders.unstructured import (
UnstructuredFileLoader,
validate_unstructured_version,
)
[docs]class UnstructuredODTLoader(UnstructuredFileLoader):
"""Loader that ... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/odt.html |
3bbb3dfcbc8b-0 | Source code for langchain.document_loaders.college_confidential
"""Loader that loads College Confidential."""
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.web_base import WebBaseLoader
[docs]class CollegeConfidentialLoader(WebBaseLoader):
"""Loader that lo... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/college_confidential.html |
c60ee91afbb4-0 | Source code for langchain.document_loaders.whatsapp_chat
import re
from pathlib import Path
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
def concatenate_rows(date: str, sender: str, text: str) -> str:
"""Combine message information i... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/whatsapp_chat.html |
c60ee91afbb4-1 | text_content += concatenate_rows(date, sender, text)
metadata = {"source": str(p)}
return [Document(page_content=text_content, metadata=metadata)]
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 29, 2023. | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/whatsapp_chat.html |
02f707cebccf-0 | Source code for langchain.document_loaders.stripe
"""Loader that fetches data from Stripe"""
import json
import urllib.request
from typing import List, Optional
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
from langchain.utils import get_from_env, stringify_dic... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/stripe.html |
02f707cebccf-1 | if endpoint is None:
return []
return self._make_request(endpoint)
[docs] def load(self) -> List[Document]:
return self._get_resource()
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 29, 2023. | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/stripe.html |
a7e617cd69f6-0 | Source code for langchain.document_loaders.conllu
"""Load CoNLL-U files."""
import csv
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class CoNLLULoader(BaseLoader):
"""Load CoNLL-U files."""
def __init__(self, file_path: str... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/conllu.html |
f8287d5733a1-0 | Source code for langchain.document_loaders.roam
"""Loader that loads Roam 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 RoamLoader(BaseLoader):
"""Loader that loads Roam files fr... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/roam.html |
4c2a24604655-0 | Source code for langchain.document_loaders.gcs_file
"""Loading logic for loading documents from a GCS 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_loaders.unstructured import Uns... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/gcs_file.html |
6373ddaa31e8-0 | Source code for langchain.document_loaders.azlyrics
"""Loader that loads AZLyrics."""
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.web_base import WebBaseLoader
[docs]class AZLyricsLoader(WebBaseLoader):
"""Loader that loads AZLyrics webpages."""
[docs] ... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/azlyrics.html |
10417b1cfaac-0 | Source code for langchain.document_loaders.ifixit
"""Loader that loads iFixit data."""
from typing import List, Optional
import requests
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
from langchain.document_loaders.web_base import WebBaseLoader
IFIXIT_BASE_URL =... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/ifixit.html |
10417b1cfaac-1 | """Teardowns are just guides by a different name"""
self.page_type = pieces[0] if pieces[0] != "Teardown" else "Guide"
if self.page_type == "Guide" or self.page_type == "Answers":
self.id = pieces[2]
else:
self.id = pieces[1]
self.web_path = web_path
[docs] def... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/ifixit.html |
10417b1cfaac-2 | self, url_override: Optional[str] = None
) -> List[Document]:
loader = WebBaseLoader(self.web_path if url_override is None else url_override)
soup = loader.scrape()
output = []
title = soup.find("h1", "post-title").text
output.append("# " + title)
output.append(soup.s... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/ifixit.html |
10417b1cfaac-3 | text = "\n".join(
[
data[key]
for key in ["title", "description", "contents_raw"]
if key in data
]
).strip()
metadata = {"source": self.web_path, "title": data["title"]}
documents.append(Document(page_content=text, metadata=... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/ifixit.html |
10417b1cfaac-4 | doc_parts.append("\n - " + part["text"])
for row in data["steps"]:
doc_parts.append(
"\n\n## "
+ (
row["title"]
if row["title"] != ""
else "Step {}".format(row["orderby"])
)
)
... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/ifixit.html |
2df39d4ce80f-0 | Source code for langchain.document_loaders.azure_blob_storage_container
"""Loading logic for loading documents from an Azure Blob Storage container."""
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.azure_blob_storage_file import (
AzureBlobStorageFileLoader... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/azure_blob_storage_container.html |
99d6de19f29e-0 | Source code for langchain.document_loaders.duckdb_loader
from typing import Dict, List, Optional, cast
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class DuckDBLoader(BaseLoader):
"""Loads a query result from DuckDB into a list of documents.
Each ... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/duckdb_loader.html |
99d6de19f29e-1 | results = query_result.fetchall()
description = cast(list, query_result.description)
field_names = [c[0] for c in description]
if self.page_content_columns is None:
page_content_columns = field_names
else:
page_content_columns = self.page_c... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/duckdb_loader.html |
539472ae2ad3-0 | Source code for langchain.llms.databricks
import os
from abc import ABC, abstractmethod
from typing import Any, Callable, Dict, List, Optional
import requests
from pydantic import BaseModel, Extra, Field, PrivateAttr, root_validator, validator
from langchain.callbacks.manager import CallbackManagerForLLMRun
from langch... | https://python.langchain.com/en/latest/_modules/langchain/llms/databricks.html |
539472ae2ad3-1 | return values
def post(self, request: Any) -> Any:
# See https://docs.databricks.com/machine-learning/model-serving/score-model-serving-endpoints.html
wrapped_request = {"dataframe_records": [request]}
response = self.post_raw(wrapped_request)["predictions"]
# For a single-record que... | https://python.langchain.com/en/latest/_modules/langchain/llms/databricks.html |
539472ae2ad3-2 | def get_default_host() -> str:
"""Gets the default Databricks workspace hostname.
Raises an error if the hostname cannot be automatically determined.
"""
host = os.getenv("DATABRICKS_HOST")
if not host:
try:
host = get_repl_context().browserHostName
if not host:
... | https://python.langchain.com/en/latest/_modules/langchain/llms/databricks.html |
539472ae2ad3-3 | * **Serving endpoint** (recommended for both production and development).
We assume that an LLM was registered and deployed to a serving endpoint.
To wrap it as an LLM you must have "Can Query" permission to the endpoint.
Set ``endpoint_name`` accordingly and do not set ``cluster_id`` and
``clus... | https://python.langchain.com/en/latest/_modules/langchain/llms/databricks.html |
539472ae2ad3-4 | If the endpoint model signature is different or you want to set extra params,
you can use `transform_input_fn` and `transform_output_fn` to apply necessary
transformations before and after the query.
"""
host: str = Field(default_factory=get_default_host)
"""Databricks workspace hostname.
If not... | https://python.langchain.com/en/latest/_modules/langchain/llms/databricks.html |
539472ae2ad3-5 | You must not set both ``endpoint_name`` and ``cluster_id``.
"""
cluster_driver_port: Optional[str] = None
"""The port number used by the HTTP server running on the cluster driver node.
The server should listen on the driver IP address or simply ``0.0.0.0`` to connect.
We recommend the server using a... | https://python.langchain.com/en/latest/_modules/langchain/llms/databricks.html |
539472ae2ad3-6 | raise ValueError(
"Neither endpoint_name nor cluster_id was set. "
"And the cluster_id cannot be automatically determined. Received"
f" error: {e}"
)
@validator("cluster_driver_port", always=True)
def set_cluster_driver_port(cls, v: Any... | https://python.langchain.com/en/latest/_modules/langchain/llms/databricks.html |
539472ae2ad3-7 | cluster_driver_port=self.cluster_driver_port,
)
else:
raise ValueError(
"Must specify either endpoint_name or cluster_id/cluster_driver_port."
)
@property
def _llm_type(self) -> str:
"""Return type of llm."""
return "databricks"
def... | https://python.langchain.com/en/latest/_modules/langchain/llms/databricks.html |
4c503841bfd0-0 | Source code for langchain.llms.huggingface_hub
"""Wrapper around HuggingFace APIs."""
from typing import Any, Dict, List, Mapping, Optional
from pydantic import Extra, root_validator
from langchain.callbacks.manager import CallbackManagerForLLMRun
from langchain.llms.base import LLM
from langchain.llms.utils import enf... | https://python.langchain.com/en/latest/_modules/langchain/llms/huggingface_hub.html |
4c503841bfd0-1 | """Configuration for this pydantic object."""
extra = Extra.forbid
@root_validator()
def validate_environment(cls, values: Dict) -> Dict:
"""Validate that api key and python package exists in environment."""
huggingfacehub_api_token = get_from_dict_or_env(
values, "huggingfac... | https://python.langchain.com/en/latest/_modules/langchain/llms/huggingface_hub.html |
4c503841bfd0-2 | self,
prompt: str,
stop: Optional[List[str]] = None,
run_manager: Optional[CallbackManagerForLLMRun] = None,
) -> str:
"""Call out to HuggingFace Hub's inference endpoint.
Args:
prompt: The prompt to pass into the model.
stop: Optional list of stop wor... | https://python.langchain.com/en/latest/_modules/langchain/llms/huggingface_hub.html |
81fd369fd902-0 | Source code for langchain.llms.self_hosted
"""Run model inference on self-hosted remote hardware."""
import importlib.util
import logging
import pickle
from typing import Any, Callable, List, Mapping, Optional
from pydantic import Extra
from langchain.callbacks.manager import CallbackManagerForLLMRun
from langchain.llm... | https://python.langchain.com/en/latest/_modules/langchain/llms/self_hosted.html |
81fd369fd902-1 | )
if device < 0 and cuda_device_count > 0:
logger.warning(
"Device has %d GPUs available. "
"Provide device={deviceId} to `from_model_id` to use available"
"GPUs for execution. deviceId is -1 for CPU and "
"can be a positive integer ass... | https://python.langchain.com/en/latest/_modules/langchain/llms/self_hosted.html |
81fd369fd902-2 | llm = SelfHostedPipeline(
model_load_fn=load_pipeline,
hardware=gpu,
model_reqs=model_reqs, inference_fn=inference_fn
)
Example for <2GB model (can be serialized and sent directly to the server):
.. code-block:: python
from langchain.ll... | https://python.langchain.com/en/latest/_modules/langchain/llms/self_hosted.html |
81fd369fd902-3 | load_fn_kwargs: Optional[dict] = None
"""Key word arguments to pass to the model load function."""
model_reqs: List[str] = ["./", "torch"]
"""Requirements to install on hardware to inference the model."""
class Config:
"""Configuration for this pydantic object."""
extra = Extra.forbid
... | https://python.langchain.com/en/latest/_modules/langchain/llms/self_hosted.html |
81fd369fd902-4 | if not isinstance(pipeline, str):
logger.warning(
"Serializing pipeline to send to remote hardware. "
"Note, it can be quite slow"
"to serialize and send large models with each execution. "
"Consider sending the pipeline"
"to th... | https://python.langchain.com/en/latest/_modules/langchain/llms/self_hosted.html |
330726df3022-0 | Source code for langchain.llms.mosaicml
"""Wrapper around MosaicML APIs."""
from typing import Any, Dict, List, Mapping, Optional
import requests
from pydantic import Extra, root_validator
from langchain.callbacks.manager import CallbackManagerForLLMRun
from langchain.llms.base import LLM
from langchain.llms.utils impo... | https://python.langchain.com/en/latest/_modules/langchain/llms/mosaicml.html |
330726df3022-1 | )
"""
endpoint_url: str = (
"https://models.hosted-on.mosaicml.hosting/mpt-7b-instruct/v1/predict"
)
"""Endpoint URL to use."""
inject_instruction_format: bool = False
"""Whether to inject the instruction format into the prompt."""
model_kwargs: Optional[dict] = None
"""Key word ... | https://python.langchain.com/en/latest/_modules/langchain/llms/mosaicml.html |
330726df3022-2 | instruction=prompt,
)
return prompt
def _call(
self,
prompt: str,
stop: Optional[List[str]] = None,
run_manager: Optional[CallbackManagerForLLMRun] = None,
is_retry: bool = False,
) -> str:
"""Call out to a MosaicML LLM inference endpoint.
... | https://python.langchain.com/en/latest/_modules/langchain/llms/mosaicml.html |
330726df3022-3 | raise ValueError(
f"Error raised by inference API: {parsed_response['error']}"
)
if "data" not in parsed_response:
raise ValueError(
f"Error raised by inference API, no key data: {parsed_response}"
)
generate... | https://python.langchain.com/en/latest/_modules/langchain/llms/mosaicml.html |
de8792fd1356-0 | Source code for langchain.llms.huggingface_text_gen_inference
"""Wrapper around Huggingface text generation inference API."""
from functools import partial
from typing import Any, Dict, List, Optional
from pydantic import Extra, Field, root_validator
from langchain.callbacks.manager import CallbackManagerForLLMRun
from... | https://python.langchain.com/en/latest/_modules/langchain/llms/huggingface_text_gen_inference.html |
de8792fd1356-1 | inference_server_url = "http://localhost:8010/",
max_new_tokens = 512,
top_k = 10,
top_p = 0.95,
typical_p = 0.95,
temperature = 0.01,
repetition_penalty = 1.03,
)
print(llm("What is Deep Learning?"))... | https://python.langchain.com/en/latest/_modules/langchain/llms/huggingface_text_gen_inference.html |
de8792fd1356-2 | @root_validator()
def validate_environment(cls, values: Dict) -> Dict:
"""Validate that python package exists in environment."""
try:
import text_generation
values["client"] = text_generation.Client(
values["inference_server_url"], timeout=values["timeout"]
... | https://python.langchain.com/en/latest/_modules/langchain/llms/huggingface_text_gen_inference.html |
de8792fd1356-3 | text_callback = None
if run_manager:
text_callback = partial(
run_manager.on_llm_new_token, verbose=self.verbose
)
params = {
"stop_sequences": stop,
"max_new_tokens": self.max_new_tokens,
"top_k"... | https://python.langchain.com/en/latest/_modules/langchain/llms/huggingface_text_gen_inference.html |
bade81a56772-0 | Source code for langchain.llms.writer
"""Wrapper around Writer APIs."""
from typing import Any, Dict, List, Mapping, Optional
import requests
from pydantic import Extra, root_validator
from langchain.callbacks.manager import CallbackManagerForLLMRun
from langchain.llms.base import LLM
from langchain.llms.utils import e... | https://python.langchain.com/en/latest/_modules/langchain/llms/writer.html |
bade81a56772-1 | logprobs: bool = False
"""Whether to return log probabilities."""
n: Optional[int] = None
"""How many completions to generate."""
writer_api_key: Optional[str] = None
"""Writer API key."""
base_url: Optional[str] = None
"""Base url to use, if None decides based on model name."""
class Co... | https://python.langchain.com/en/latest/_modules/langchain/llms/writer.html |
bade81a56772-2 | """Get the identifying parameters."""
return {
**{"model_id": self.model_id, "writer_org_id": self.writer_org_id},
**self._default_params,
}
@property
def _llm_type(self) -> str:
"""Return type of llm."""
return "writer"
def _call(
self,
... | https://python.langchain.com/en/latest/_modules/langchain/llms/writer.html |
bade81a56772-3 | text = enforce_stop_tokens(text, stop)
return text
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 29, 2023. | https://python.langchain.com/en/latest/_modules/langchain/llms/writer.html |
da4a92323dd9-0 | Source code for langchain.llms.beam
"""Wrapper around Beam API."""
import base64
import json
import logging
import subprocess
import textwrap
import time
from typing import Any, Dict, List, Mapping, Optional
import requests
from pydantic import Extra, Field, root_validator
from langchain.callbacks.manager import Callba... | https://python.langchain.com/en/latest/_modules/langchain/llms/beam.html |
da4a92323dd9-1 | llm._deploy()
call_result = llm._call(input)
"""
model_name: str = ""
name: str = ""
cpu: str = ""
memory: str = ""
gpu: str = ""
python_version: str = ""
python_packages: List[str] = []
max_length: str = ""
url: str = ""
"""model endpoint to use"""
model_kwargs: ... | https://python.langchain.com/en/latest/_modules/langchain/llms/beam.html |
da4a92323dd9-2 | """Validate that api key and python package exists in environment."""
beam_client_id = get_from_dict_or_env(
values, "beam_client_id", "BEAM_CLIENT_ID"
)
beam_client_secret = get_from_dict_or_env(
values, "beam_client_secret", "BEAM_CLIENT_SECRET"
)
values... | https://python.langchain.com/en/latest/_modules/langchain/llms/beam.html |
da4a92323dd9-3 | outputs={{"text": beam.Types.String()}},
handler="run.py:beam_langchain",
)
"""
)
script_name = "app.py"
with open(script_name, "w") as file:
file.write(
script.format(
name=self.name,
cpu=self.cpu,
... | https://python.langchain.com/en/latest/_modules/langchain/llms/beam.html |
da4a92323dd9-4 | if beam.__path__ == "":
raise ImportError
except ImportError:
raise ImportError(
"Could not import beam python package. "
"Please install it with `curl "
"https://raw.githubusercontent.com/slai-labs"
"/get-beam/main/get-... | https://python.langchain.com/en/latest/_modules/langchain/llms/beam.html |
da4a92323dd9-5 | ) -> str:
"""Call to Beam."""
url = "https://apps.beam.cloud/" + self.app_id if self.app_id else self.url
payload = {"prompt": prompt, "max_length": self.max_length}
headers = {
"Accept": "*/*",
"Accept-Encoding": "gzip, deflate",
"Authorization": "Bas... | https://python.langchain.com/en/latest/_modules/langchain/llms/beam.html |
767415ad4dc3-0 | Source code for langchain.llms.gpt4all
"""Wrapper for the GPT4All model."""
from functools import partial
from typing import Any, Dict, List, Mapping, Optional, Set
from pydantic import Extra, Field, root_validator
from langchain.callbacks.manager import CallbackManagerForLLMRun
from langchain.llms.base import LLM
from... | https://python.langchain.com/en/latest/_modules/langchain/llms/gpt4all.html |
767415ad4dc3-1 | logits_all: bool = Field(False, alias="logits_all")
"""Return logits for all tokens, not just the last token."""
vocab_only: bool = Field(False, alias="vocab_only")
"""Only load the vocabulary, no weights."""
use_mlock: bool = Field(False, alias="use_mlock")
"""Force system to keep model in RAM."""
... | https://python.langchain.com/en/latest/_modules/langchain/llms/gpt4all.html |
767415ad4dc3-2 | starting from beginning if the context has run out."""
client: Any = None #: :meta private:
class Config:
"""Configuration for this pydantic object."""
extra = Extra.forbid
@staticmethod
def _model_param_names() -> Set[str]:
return {
"n_ctx",
"n_predict",... | https://python.langchain.com/en/latest/_modules/langchain/llms/gpt4all.html |
767415ad4dc3-3 | except ImportError:
raise ValueError(
"Could not import gpt4all python package. "
"Please install it with `pip install gpt4all`."
)
return values
@property
def _identifying_params(self) -> Mapping[str, Any]:
"""Get the identifying parameter... | https://python.langchain.com/en/latest/_modules/langchain/llms/gpt4all.html |
767415ad4dc3-4 | text = enforce_stop_tokens(text, stop)
return text
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 29, 2023. | https://python.langchain.com/en/latest/_modules/langchain/llms/gpt4all.html |
9c0819ec9aaf-0 | Source code for langchain.llms.forefrontai
"""Wrapper around ForefrontAI APIs."""
from typing import Any, Dict, List, Mapping, Optional
import requests
from pydantic import Extra, root_validator
from langchain.callbacks.manager import CallbackManagerForLLMRun
from langchain.llms.base import LLM
from langchain.llms.util... | https://python.langchain.com/en/latest/_modules/langchain/llms/forefrontai.html |
9c0819ec9aaf-1 | @root_validator()
def validate_environment(cls, values: Dict) -> Dict:
"""Validate that api key exists in environment."""
forefrontai_api_key = get_from_dict_or_env(
values, "forefrontai_api_key", "FOREFRONTAI_API_KEY"
)
values["forefrontai_api_key"] = forefrontai_api_key... | https://python.langchain.com/en/latest/_modules/langchain/llms/forefrontai.html |
9c0819ec9aaf-2 | """
response = requests.post(
url=self.endpoint_url,
headers={
"Authorization": f"Bearer {self.forefrontai_api_key}",
"Content-Type": "application/json",
},
json={"text": prompt, **self._default_params},
)
response_j... | https://python.langchain.com/en/latest/_modules/langchain/llms/forefrontai.html |
add440674127-0 | Source code for langchain.llms.sagemaker_endpoint
"""Wrapper around Sagemaker InvokeEndpoint API."""
from abc import abstractmethod
from typing import Any, Dict, Generic, List, Mapping, Optional, TypeVar, Union
from pydantic import Extra, root_validator
from langchain.callbacks.manager import CallbackManagerForLLMRun
f... | https://python.langchain.com/en/latest/_modules/langchain/llms/sagemaker_endpoint.html |
add440674127-1 | """The MIME type of the response data returned from endpoint"""
@abstractmethod
def transform_input(self, prompt: INPUT_TYPE, model_kwargs: Dict) -> bytes:
"""Transforms the input to a format that model can accept
as the request Body. Should return bytes or seekable file
like object in t... | https://python.langchain.com/en/latest/_modules/langchain/llms/sagemaker_endpoint.html |
add440674127-2 | )
credentials_profile_name = (
"default"
)
se = SagemakerEndpoint(
endpoint_name=endpoint_name,
region_name=region_name,
credentials_profile_name=credentials_profile_name
)
"""
client: Any #: :meta p... | https://python.langchain.com/en/latest/_modules/langchain/llms/sagemaker_endpoint.html |
add440674127-3 | def transform_output(self, output: bytes) -> str:
response_json = json.loads(output.read().decode("utf-8"))
return response_json[0]["generated_text"]
"""
model_kwargs: Optional[Dict] = None
"""Key word arguments to pass to the model."""
endpoint_kwargs: Optional[D... | https://python.langchain.com/en/latest/_modules/langchain/llms/sagemaker_endpoint.html |
add440674127-4 | @property
def _identifying_params(self) -> Mapping[str, Any]:
"""Get the identifying parameters."""
_model_kwargs = self.model_kwargs or {}
return {
**{"endpoint_name": self.endpoint_name},
**{"model_kwargs": _model_kwargs},
}
@property
def _llm_type(s... | https://python.langchain.com/en/latest/_modules/langchain/llms/sagemaker_endpoint.html |
add440674127-5 | text = self.content_handler.transform_output(response["Body"])
if stop is not None:
# This is a bit hacky, but I can't figure out a better way to enforce
# stop tokens when making calls to the sagemaker endpoint.
text = enforce_stop_tokens(text, stop)
return text
By H... | https://python.langchain.com/en/latest/_modules/langchain/llms/sagemaker_endpoint.html |
8fbffb8dbec8-0 | Source code for langchain.llms.huggingface_pipeline
"""Wrapper around HuggingFace Pipeline APIs."""
import importlib.util
import logging
from typing import Any, List, Mapping, Optional
from pydantic import Extra
from langchain.callbacks.manager import CallbackManagerForLLMRun
from langchain.llms.base import LLM
from la... | https://python.langchain.com/en/latest/_modules/langchain/llms/huggingface_pipeline.html |
8fbffb8dbec8-1 | """
pipeline: Any #: :meta private:
model_id: str = DEFAULT_MODEL_ID
"""Model name to use."""
model_kwargs: Optional[dict] = None
"""Key word arguments passed to the model."""
pipeline_kwargs: Optional[dict] = None
"""Key word arguments passed to the pipeline."""
class Config:
"... | https://python.langchain.com/en/latest/_modules/langchain/llms/huggingface_pipeline.html |
8fbffb8dbec8-2 | else:
raise ValueError(
f"Got invalid task {task}, "
f"currently only {VALID_TASKS} are supported"
)
except ImportError as e:
raise ValueError(
f"Could not load the {task} model due to missing dependencies."
... | https://python.langchain.com/en/latest/_modules/langchain/llms/huggingface_pipeline.html |
8fbffb8dbec8-3 | )
return cls(
pipeline=pipeline,
model_id=model_id,
model_kwargs=_model_kwargs,
pipeline_kwargs=_pipeline_kwargs,
**kwargs,
)
@property
def _identifying_params(self) -> Mapping[str, Any]:
"""Get the identifying parameters."""
... | https://python.langchain.com/en/latest/_modules/langchain/llms/huggingface_pipeline.html |
8fbffb8dbec8-4 | By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 29, 2023. | https://python.langchain.com/en/latest/_modules/langchain/llms/huggingface_pipeline.html |
bbfcb1372975-0 | Source code for langchain.llms.anyscale
"""Wrapper around Anyscale"""
from typing import Any, Dict, List, Mapping, Optional
import requests
from pydantic import Extra, root_validator
from langchain.callbacks.manager import CallbackManagerForLLMRun
from langchain.llms.base import LLM
from langchain.llms.utils import enf... | https://python.langchain.com/en/latest/_modules/langchain/llms/anyscale.html |
bbfcb1372975-1 | @root_validator()
def validate_environment(cls, values: Dict) -> Dict:
"""Validate that api key and python package exists in environment."""
anyscale_service_url = get_from_dict_or_env(
values, "anyscale_service_url", "ANYSCALE_SERVICE_URL"
)
anyscale_service_route = get_... | https://python.langchain.com/en/latest/_modules/langchain/llms/anyscale.html |
bbfcb1372975-2 | ) -> str:
"""Call out to Anyscale Service endpoint.
Args:
prompt: The prompt to pass into the model.
stop: Optional list of stop words to use when generating.
Returns:
The string generated by the model.
Example:
.. code-block:: python
... | https://python.langchain.com/en/latest/_modules/langchain/llms/anyscale.html |
02df57adee24-0 | Source code for langchain.llms.stochasticai
"""Wrapper around StochasticAI APIs."""
import logging
import time
from typing import Any, Dict, List, Mapping, Optional
import requests
from pydantic import Extra, Field, root_validator
from langchain.callbacks.manager import CallbackManagerForLLMRun
from langchain.llms.base... | https://python.langchain.com/en/latest/_modules/langchain/llms/stochasticai.html |
02df57adee24-1 | raise ValueError(f"Found {field_name} supplied twice.")
logger.warning(
f"""{field_name} was transfered to model_kwargs.
Please confirm that {field_name} is what you intended."""
)
extra[field_name] = values.pop(field_name)
... | https://python.langchain.com/en/latest/_modules/langchain/llms/stochasticai.html |
02df57adee24-2 | """
params = self.model_kwargs or {}
response_post = requests.post(
url=self.api_url,
json={"prompt": prompt, "params": params},
headers={
"apiKey": f"{self.stochasticai_api_key}",
"Accept": "application/json",
"Content-... | https://python.langchain.com/en/latest/_modules/langchain/llms/stochasticai.html |
560028662917-0 | Source code for langchain.llms.self_hosted_hugging_face
"""Wrapper around HuggingFace Pipeline API to run on self-hosted remote hardware."""
import importlib.util
import logging
from typing import Any, Callable, List, Mapping, Optional
from pydantic import Extra
from langchain.callbacks.manager import CallbackManagerFo... | https://python.langchain.com/en/latest/_modules/langchain/llms/self_hosted_hugging_face.html |
560028662917-1 | text = enforce_stop_tokens(text, stop)
return text
def _load_transformer(
model_id: str = DEFAULT_MODEL_ID,
task: str = DEFAULT_TASK,
device: int = 0,
model_kwargs: Optional[dict] = None,
) -> Any:
"""Inference function to send to the remote hardware.
Accepts a huggingface model_id and retur... | https://python.langchain.com/en/latest/_modules/langchain/llms/self_hosted_hugging_face.html |
560028662917-2 | )
if device < 0 and cuda_device_count > 0:
logger.warning(
"Device has %d GPUs available. "
"Provide device={deviceId} to `from_model_id` to use available"
"GPUs for execution. deviceId is -1 for CPU and "
"can be a positive integer ass... | https://python.langchain.com/en/latest/_modules/langchain/llms/self_hosted_hugging_face.html |
560028662917-3 | hf = SelfHostedHuggingFaceLLM(
model_id="google/flan-t5-large", task="text2text-generation",
hardware=gpu
)
Example passing fn that generates a pipeline (bc the pipeline is not serializable):
.. code-block:: python
from langchain.llms import SelfHosted... | https://python.langchain.com/en/latest/_modules/langchain/llms/self_hosted_hugging_face.html |
560028662917-4 | """Function to load the model remotely on the server."""
inference_fn: Callable = _generate_text #: :meta private:
"""Inference function to send to the remote hardware."""
class Config:
"""Configuration for this pydantic object."""
extra = Extra.forbid
def __init__(self, **kwargs: Any):... | https://python.langchain.com/en/latest/_modules/langchain/llms/self_hosted_hugging_face.html |
560028662917-5 | By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 29, 2023. | https://python.langchain.com/en/latest/_modules/langchain/llms/self_hosted_hugging_face.html |
b190571a777f-0 | Source code for langchain.llms.cohere
"""Wrapper around Cohere APIs."""
import logging
from typing import Any, Dict, List, Optional
from pydantic import Extra, root_validator
from langchain.callbacks.manager import CallbackManagerForLLMRun
from langchain.llms.base import LLM
from langchain.llms.utils import enforce_sto... | https://python.langchain.com/en/latest/_modules/langchain/llms/cohere.html |
b190571a777f-1 | """Penalizes repeated tokens. Between 0 and 1."""
truncate: Optional[str] = None
"""Specify how the client handles inputs longer than the maximum token
length: Truncate from START, END or NONE"""
cohere_api_key: Optional[str] = None
stop: Optional[List[str]] = None
class Config:
"""Confi... | https://python.langchain.com/en/latest/_modules/langchain/llms/cohere.html |
b190571a777f-2 | def _llm_type(self) -> str:
"""Return type of llm."""
return "cohere"
def _call(
self,
prompt: str,
stop: Optional[List[str]] = None,
run_manager: Optional[CallbackManagerForLLMRun] = None,
) -> str:
"""Call out to Cohere's generate endpoint.
Args:... | https://python.langchain.com/en/latest/_modules/langchain/llms/cohere.html |
963db9fb425f-0 | Source code for langchain.llms.aleph_alpha
"""Wrapper around Aleph Alpha APIs."""
from typing import Any, Dict, List, Optional, Sequence
from pydantic import Extra, root_validator
from langchain.callbacks.manager import CallbackManagerForLLMRun
from langchain.llms.base import LLM
from langchain.llms.utils import enforc... | https://python.langchain.com/en/latest/_modules/langchain/llms/aleph_alpha.html |
963db9fb425f-1 | """Total probability mass of tokens to consider at each step."""
presence_penalty: float = 0.0
"""Penalizes repeated tokens."""
frequency_penalty: float = 0.0
"""Penalizes repeated tokens according to frequency."""
repetition_penalties_include_prompt: Optional[bool] = False
"""Flag deciding whet... | https://python.langchain.com/en/latest/_modules/langchain/llms/aleph_alpha.html |
963db9fb425f-2 | """Echo the prompt in the completion."""
use_multiplicative_frequency_penalty: bool = False
sequence_penalty: float = 0.0
sequence_penalty_min_length: int = 2
use_multiplicative_sequence_penalty: bool = False
completion_bias_inclusion: Optional[Sequence[str]] = None
completion_bias_inclusion_fir... | https://python.langchain.com/en/latest/_modules/langchain/llms/aleph_alpha.html |
963db9fb425f-3 | """Validate that api key and python package exists in environment."""
aleph_alpha_api_key = get_from_dict_or_env(
values, "aleph_alpha_api_key", "ALEPH_ALPHA_API_KEY"
)
try:
import aleph_alpha_client
values["client"] = aleph_alpha_client.Client(token=aleph_alp... | https://python.langchain.com/en/latest/_modules/langchain/llms/aleph_alpha.html |
963db9fb425f-4 | "minimum_tokens": self.minimum_tokens,
"echo": self.echo,
"use_multiplicative_frequency_penalty": self.use_multiplicative_frequency_penalty, # noqa: E501
"sequence_penalty": self.sequence_penalty,
"sequence_penalty_min_length": self.sequence_penalty_min_length,
... | https://python.langchain.com/en/latest/_modules/langchain/llms/aleph_alpha.html |
963db9fb425f-5 | Args:
prompt: The prompt to pass into the model.
stop: Optional list of stop words to use when generating.
Returns:
The string generated by the model.
Example:
.. code-block:: python
response = alpeh_alpha("Tell me a joke.")
"""
... | https://python.langchain.com/en/latest/_modules/langchain/llms/aleph_alpha.html |
42414b45b1c1-0 | Source code for langchain.llms.deepinfra
"""Wrapper around DeepInfra APIs."""
from typing import Any, Dict, List, Mapping, Optional
import requests
from pydantic import Extra, root_validator
from langchain.callbacks.manager import CallbackManagerForLLMRun
from langchain.llms.base import LLM
from langchain.llms.utils im... | https://python.langchain.com/en/latest/_modules/langchain/llms/deepinfra.html |
42414b45b1c1-1 | return values
@property
def _identifying_params(self) -> Mapping[str, Any]:
"""Get the identifying parameters."""
return {
**{"model_id": self.model_id},
**{"model_kwargs": self.model_kwargs},
}
@property
def _llm_type(self) -> str:
"""Return type ... | https://python.langchain.com/en/latest/_modules/langchain/llms/deepinfra.html |
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