id int64 0 190k | prompt stringlengths 21 13.4M | docstring stringlengths 1 12k ⌀ |
|---|---|---|
144,503 | import json
from pathlib import Path
from typing import Any, Union
import yaml
from langchain.chains.api.base import APIChain
from langchain.chains.base import Chain
from langchain.chains.combine_documents.map_reduce import MapReduceDocumentsChain
from langchain.chains.combine_documents.map_rerank import MapRerankDocum... | null |
144,504 | import json
from pathlib import Path
from typing import Any, Union
import yaml
from langchain.chains.api.base import APIChain
from langchain.chains.base import Chain
from langchain.chains.combine_documents.map_reduce import MapReduceDocumentsChain
from langchain.chains.combine_documents.map_rerank import MapRerankDocum... | null |
144,505 | import json
from pathlib import Path
from typing import Any, Union
import yaml
from langchain.chains.api.base import APIChain
from langchain.chains.base import Chain
from langchain.chains.combine_documents.map_reduce import MapReduceDocumentsChain
from langchain.chains.combine_documents.map_rerank import MapRerankDocum... | null |
144,506 | import json
from pathlib import Path
from typing import Any, Union
import yaml
from langchain.chains.api.base import APIChain
from langchain.chains.base import Chain
from langchain.chains.combine_documents.map_reduce import MapReduceDocumentsChain
from langchain.chains.combine_documents.map_rerank import MapRerankDocum... | null |
144,507 | import json
from pathlib import Path
from typing import Any, Union
import yaml
from langchain.chains.api.base import APIChain
from langchain.chains.base import Chain
from langchain.chains.combine_documents.map_reduce import MapReduceDocumentsChain
from langchain.chains.combine_documents.map_rerank import MapRerankDocum... | null |
144,508 | import json
from pathlib import Path
from typing import Any, Union
import yaml
from langchain.chains.api.base import APIChain
from langchain.chains.base import Chain
from langchain.chains.combine_documents.map_reduce import MapReduceDocumentsChain
from langchain.chains.combine_documents.map_rerank import MapRerankDocum... | null |
144,509 | import json
from pathlib import Path
from typing import Any, Union
import yaml
from langchain.chains.api.base import APIChain
from langchain.chains.base import Chain
from langchain.chains.combine_documents.map_reduce import MapReduceDocumentsChain
from langchain.chains.combine_documents.map_rerank import MapRerankDocum... | null |
144,510 | import json
from pathlib import Path
from typing import Any, Union
import yaml
from langchain.chains.api.base import APIChain
from langchain.chains.base import Chain
from langchain.chains.combine_documents.map_reduce import MapReduceDocumentsChain
from langchain.chains.combine_documents.map_rerank import MapRerankDocum... | null |
144,511 | import json
from pathlib import Path
from typing import Any, Union
import yaml
from langchain.chains.api.base import APIChain
from langchain.chains.base import Chain
from langchain.chains.combine_documents.map_reduce import MapReduceDocumentsChain
from langchain.chains.combine_documents.map_rerank import MapRerankDocum... | null |
144,512 | import json
from pathlib import Path
from typing import Any, Union
import yaml
from langchain.chains.api.base import APIChain
from langchain.chains.base import Chain
from langchain.chains.combine_documents.map_reduce import MapReduceDocumentsChain
from langchain.chains.combine_documents.map_rerank import MapRerankDocum... | null |
144,513 | import json
from pathlib import Path
from typing import Any, Union
import yaml
from langchain.chains.api.base import APIChain
from langchain.chains.base import Chain
from langchain.chains.combine_documents.map_reduce import MapReduceDocumentsChain
from langchain.chains.combine_documents.map_rerank import MapRerankDocum... | null |
144,514 | from __future__ import annotations
from typing import Any, Dict, List, Tuple
from pydantic import BaseModel
from langchain.chains.base import Chain
from langchain.chains.chat_vector_db.prompts import CONDENSE_QUESTION_PROMPT, QA_PROMPT
from langchain.chains.combine_documents.base import BaseCombineDocumentsChain
from l... | null |
144,515 | from typing import Any, Dict, List, Optional, Tuple
from pydantic import BaseModel, Extra, Field, root_validator
from langchain.chains.combine_documents.base import BaseCombineDocumentsChain
from langchain.chains.llm import LLMChain
from langchain.docstore.document import Document
from langchain.prompts.base import Bas... | null |
144,516 | from __future__ import annotations
from typing import Any, Dict, List, Tuple
from pydantic import BaseModel, Extra, Field, root_validator
from langchain.chains.combine_documents.base import BaseCombineDocumentsChain
from langchain.chains.llm import LLMChain
from langchain.docstore.document import Document
from langchai... | null |
144,517 | from __future__ import annotations
from typing import Any, Callable, Dict, List, Optional, Protocol, Tuple
from pydantic import BaseModel, Extra, root_validator
from langchain.chains.combine_documents.base import BaseCombineDocumentsChain
from langchain.chains.llm import LLMChain
from langchain.docstore.document import... | null |
144,518 | from __future__ import annotations
from typing import Any, Callable, Dict, List, Optional, Protocol, Tuple
from pydantic import BaseModel, Extra, root_validator
from langchain.chains.combine_documents.base import BaseCombineDocumentsChain
from langchain.chains.llm import LLMChain
from langchain.docstore.document import... | null |
144,519 | from typing import Any, Dict, List, Optional
from pydantic import BaseModel, Field, root_validator
from langchain.chains.base import Memory
from langchain.chains.conversation.prompt import (
ENTITY_EXTRACTION_PROMPT,
ENTITY_SUMMARIZATION_PROMPT,
KNOWLEDGE_TRIPLE_EXTRACTION_PROMPT,
SUMMARY_PROMPT,
)
from... | null |
144,520 | import json
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Any, Dict, List, Optional, Union
import yaml
from pydantic import BaseModel, Extra, Field, validator
import langchain
from langchain.callbacks import get_callback_manager
from langchain.callbacks.base import BaseCallbackManager
... | null |
144,521 | import logging
from pathlib import Path
from typing import List, Type, Union
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
from langchain.document_loaders.text import TextLoader
from langchain.document_loaders.unstructured import UnstructuredFileLoader
def _is_... | null |
144,522 | import json
from pathlib import Path
from typing import Any, List
import pandas as pd
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
The provided code snippet includes necessary dependencies for implementing the `concatenate_cells` function. Write a Python funct... | Combine cells information in a readable format ready to be used. |
144,523 | import json
from pathlib import Path
from typing import Any, List
import pandas as pd
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
The provided code snippet includes necessary dependencies for implementing the `remove_newlines` function. Write a Python functio... | Remove recursivelly newlines, no matter the data structure they are stored in. |
144,524 | import json
from pathlib import Path
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
The provided code snippet includes necessary dependencies for implementing the `concatenate_rows` function. Write a Python function `def concatenate_rows(... | Combine message information in a readable format ready to be used. |
144,525 | import hashlib
from base64 import b64decode
from time import strptime
from typing import Any, Dict, List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
def _parse_note(note: List) -> dict:
note_dict: Dict[str, Any] = {}
resources = []
for elem in note... | Parse Evernote xml. |
144,526 | import datetime
import json
from pathlib import Path
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
The provided code snippet includes necessary dependencies for implementing the `concatenate_rows` function. Write a Python function `def c... | Combine message information in a readable format ready to be used. |
144,527 | from typing import Dict, List, Optional
_TEXT_COLOR_MAPPING = {
"blue": "36;1",
"yellow": "33;1",
"pink": "38;5;200",
"green": "32;1",
"red": "31;1",
}
The provided code snippet includes necessary dependencies for implementing the `get_color_mapping` function. Write a Python function `def get_color... | Get mapping for items to a support color. |
144,528 | from typing import Dict, List, Optional
def get_colored_text(text: str, color: str) -> str:
"""Get colored text."""
color_str = _TEXT_COLOR_MAPPING[color]
return f"\u001b[{color_str}m\033[1;3m{text}\u001b[0m"
The provided code snippet includes necessary dependencies for implementing the `print_text` functi... | Print text with highlighting and no end characters. |
144,529 | from typing import Any, Optional, Sequence
from langchain.agents.agent import AgentExecutor
from langchain.agents.loading import AGENT_TO_CLASS, load_agent
from langchain.callbacks.base import BaseCallbackManager
from langchain.llms.base import BaseLLM
from langchain.tools.base import BaseTool
class AgentExecutor(Chai... | Load agent given tools and LLM. Args: tools: List of tools this agent has access to. llm: Language model to use as the agent. agent: The agent to use. Valid options are: `zero-shot-react-description` `react-docstore` `self-ask-with-search` `conversational-react-description` If None and agent_path is also None, will def... |
144,530 | from __future__ import annotations
import re
from typing import Any, Callable, List, NamedTuple, Optional, Sequence, Tuple
from langchain.agents.agent import Agent, AgentExecutor
from langchain.agents.mrkl.prompt import FORMAT_INSTRUCTIONS, PREFIX, SUFFIX
from langchain.agents.tools import Tool
from langchain.callbacks... | Parse out the action and input from the LLM output. Note: if you're specifying a custom prompt for the ZeroShotAgent, you will need to ensure that it meets the following Regex requirements. The string starting with "Action:" and the following string starting with "Action Input:" should be separated by a newline. |
144,531 | from typing import Any, List, Optional
from langchain.agents.tools import Tool
from langchain.callbacks.base import BaseCallbackManager
from langchain.chains.api import news_docs, open_meteo_docs, tmdb_docs
from langchain.chains.api.base import APIChain
from langchain.chains.llm_math.base import LLMMathChain
from langc... | null |
144,532 | from typing import Any, List, Optional
from langchain.agents.tools import Tool
from langchain.callbacks.base import BaseCallbackManager
from langchain.chains.api import news_docs, open_meteo_docs, tmdb_docs
from langchain.chains.api.base import APIChain
from langchain.chains.llm_math.base import LLMMathChain
from langc... | null |
144,533 | from typing import Any, List, Optional
from langchain.agents.tools import Tool
from langchain.callbacks.base import BaseCallbackManager
from langchain.chains.api import news_docs, open_meteo_docs, tmdb_docs
from langchain.chains.api.base import APIChain
from langchain.chains.llm_math.base import LLMMathChain
from langc... | null |
144,534 | from typing import Any, List, Optional
from langchain.agents.tools import Tool
from langchain.callbacks.base import BaseCallbackManager
from langchain.chains.api import news_docs, open_meteo_docs, tmdb_docs
from langchain.chains.api.base import APIChain
from langchain.chains.llm_math.base import LLMMathChain
from langc... | null |
144,535 | from typing import Any, List, Optional
from langchain.agents.tools import Tool
from langchain.callbacks.base import BaseCallbackManager
from langchain.chains.api import news_docs, open_meteo_docs, tmdb_docs
from langchain.chains.api.base import APIChain
from langchain.chains.llm_math.base import LLMMathChain
from langc... | null |
144,536 | from typing import Any, List, Optional
from langchain.agents.tools import Tool
from langchain.callbacks.base import BaseCallbackManager
from langchain.chains.api import news_docs, open_meteo_docs, tmdb_docs
from langchain.chains.api.base import APIChain
from langchain.chains.llm_math.base import LLMMathChain
from langc... | null |
144,537 | from typing import Any, List, Optional
from langchain.agents.tools import Tool
from langchain.callbacks.base import BaseCallbackManager
from langchain.chains.api import news_docs, open_meteo_docs, tmdb_docs
from langchain.chains.api.base import APIChain
from langchain.chains.llm_math.base import LLMMathChain
from langc... | null |
144,538 | from typing import Any, List, Optional
from langchain.agents.tools import Tool
from langchain.callbacks.base import BaseCallbackManager
from langchain.chains.api import news_docs, open_meteo_docs, tmdb_docs
from langchain.chains.api.base import APIChain
from langchain.chains.llm_math.base import LLMMathChain
from langc... | null |
144,539 | from typing import Any, List, Optional
from langchain.agents.tools import Tool
from langchain.callbacks.base import BaseCallbackManager
from langchain.chains.api import news_docs, open_meteo_docs, tmdb_docs
from langchain.chains.api.base import APIChain
from langchain.chains.llm_math.base import LLMMathChain
from langc... | null |
144,540 | from typing import Any, List, Optional
from langchain.agents.tools import Tool
from langchain.callbacks.base import BaseCallbackManager
from langchain.chains.api import news_docs, open_meteo_docs, tmdb_docs
from langchain.chains.api.base import APIChain
from langchain.chains.llm_math.base import LLMMathChain
from langc... | null |
144,541 | from typing import Any, List, Optional
from langchain.agents.tools import Tool
from langchain.callbacks.base import BaseCallbackManager
from langchain.chains.api import news_docs, open_meteo_docs, tmdb_docs
from langchain.chains.api.base import APIChain
from langchain.chains.llm_math.base import LLMMathChain
from langc... | null |
144,542 | from typing import Any, List, Optional
from langchain.agents.tools import Tool
from langchain.callbacks.base import BaseCallbackManager
from langchain.chains.api import news_docs, open_meteo_docs, tmdb_docs
from langchain.chains.api.base import APIChain
from langchain.chains.llm_math.base import LLMMathChain
from langc... | null |
144,543 | from typing import Any, List, Optional
from langchain.agents.tools import Tool
from langchain.callbacks.base import BaseCallbackManager
from langchain.chains.api import news_docs, open_meteo_docs, tmdb_docs
from langchain.chains.api.base import APIChain
from langchain.chains.llm_math.base import LLMMathChain
from langc... | null |
144,544 | from typing import Any, List, Optional
from langchain.agents.tools import Tool
from langchain.callbacks.base import BaseCallbackManager
from langchain.chains.api import news_docs, open_meteo_docs, tmdb_docs
from langchain.chains.api.base import APIChain
from langchain.chains.llm_math.base import LLMMathChain
from langc... | null |
144,545 | from typing import Any, List, Optional
from langchain.agents.tools import Tool
from langchain.callbacks.base import BaseCallbackManager
from langchain.chains.api import news_docs, open_meteo_docs, tmdb_docs
from langchain.chains.api.base import APIChain
from langchain.chains.llm_math.base import LLMMathChain
from langc... | null |
144,546 | from typing import Any, List, Optional
from langchain.agents.tools import Tool
from langchain.callbacks.base import BaseCallbackManager
from langchain.chains.api import news_docs, open_meteo_docs, tmdb_docs
from langchain.chains.api.base import APIChain
from langchain.chains.llm_math.base import LLMMathChain
from langc... | null |
144,547 | from typing import Any, List, Optional
from langchain.agents.tools import Tool
from langchain.callbacks.base import BaseCallbackManager
from langchain.chains.api import news_docs, open_meteo_docs, tmdb_docs
from langchain.chains.api.base import APIChain
from langchain.chains.llm_math.base import LLMMathChain
from langc... | null |
144,548 | from typing import Any, List, Optional
from langchain.agents.tools import Tool
from langchain.callbacks.base import BaseCallbackManager
from langchain.chains.api import news_docs, open_meteo_docs, tmdb_docs
from langchain.chains.api.base import APIChain
from langchain.chains.llm_math.base import LLMMathChain
from langc... | Load tools based on their name. Args: tool_names: name of tools to load. llm: Optional language model, may be needed to initialize certain tools. callback_manager: Optional callback manager. If not provided, default global callback manager will be used. Returns: List of tools. |
144,549 | from typing import Any, List, Optional
from langchain.agents.tools import Tool
from langchain.callbacks.base import BaseCallbackManager
from langchain.chains.api import news_docs, open_meteo_docs, tmdb_docs
from langchain.chains.api.base import APIChain
from langchain.chains.llm_math.base import LLMMathChain
from langc... | Get a list of all possible tool names. |
144,550 | from typing import List
from langchain.chains.llm import LLMChain
from langchain.llms.base import BaseLLM
from langchain.prompts.few_shot import FewShotPromptTemplate
from langchain.prompts.prompt import PromptTemplate
TEST_GEN_TEMPLATE_SUFFIX = "Add another example."
class LLMChain(Chain, BaseModel):
"""Chain to ... | Return another example given a list of examples for a prompt. |
144,551 | import importlib
import logging
from typing import Any, Callable, List, Optional
from pydantic import BaseModel
from langchain.embeddings.self_hosted import SelfHostedEmbeddings
The provided code snippet includes necessary dependencies for implementing the `_embed_documents` function. Write a Python function `def _emb... | Inference function to send to the remote hardware. Accepts a sentence_transformer model_id and returns a list of embeddings for each document in the batch. |
144,552 | import importlib
import logging
from typing import Any, Callable, List, Optional
from pydantic import BaseModel
from langchain.embeddings.self_hosted import SelfHostedEmbeddings
logger = logging.getLogger(__name__)
The provided code snippet includes necessary dependencies for implementing the `load_embedding_model` fu... | Load the embedding model. |
144,553 | from typing import Any, Callable, List
from pydantic import BaseModel, Extra
from langchain.embeddings.base import Embeddings
from langchain.llms import SelfHostedPipeline
The provided code snippet includes necessary dependencies for implementing the `_embed_documents` function. Write a Python function `def _embed_doc... | Inference function to send to the remote hardware. Accepts a sentence_transformer model_id and returns a list of embeddings for each document in the batch. |
144,554 | from typing import List
import numpy as np
def cosine_similarity(a: np.ndarray, b: np.ndarray) -> float:
"""Calculate cosine similarity with numpy."""
return np.dot(a, b) / (np.linalg.norm(a) * np.linalg.norm(b))
The provided code snippet includes necessary dependencies for implementing the `maximal_marginal_r... | Calculate maximal marginal relevance. |
144,555 | from __future__ import annotations
import pickle
import uuid
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, List, Optional, Tuple
import numpy as np
from langchain.docstore.base import AddableMixin, Docstore
from langchain.docstore.document import Document
from langchain.docstore.in_memory i... | Import faiss if available, otherwise raise error. |
144,556 | from __future__ import annotations
import uuid
from typing import Any, Dict, Iterable, List, Optional
from langchain.docstore.document import Document
from langchain.embeddings.base import Embeddings
from langchain.utils import get_from_dict_or_env
from langchain.vectorstores.base import VectorStore
def _import_opensea... | Get OpenSearch client from the opensearch_url, otherwise raise error. |
144,557 | from __future__ import annotations
import uuid
from typing import Any, Dict, Iterable, List, Optional
from langchain.docstore.document import Document
from langchain.embeddings.base import Embeddings
from langchain.utils import get_from_dict_or_env
from langchain.vectorstores.base import VectorStore
The provided code ... | Validate Embeddings Length and Bulk Size. |
144,558 | from __future__ import annotations
import uuid
from typing import Any, Dict, Iterable, List, Optional
from langchain.docstore.document import Document
from langchain.embeddings.base import Embeddings
from langchain.utils import get_from_dict_or_env
from langchain.vectorstores.base import VectorStore
def _import_bulk() ... | Bulk Ingest Embeddings into given index. |
144,559 | from __future__ import annotations
import uuid
from typing import Any, Dict, Iterable, List, Optional
from langchain.docstore.document import Document
from langchain.embeddings.base import Embeddings
from langchain.utils import get_from_dict_or_env
from langchain.vectorstores.base import VectorStore
The provided code ... | For Painless Scripting or Script Scoring,the default mapping to create index. |
144,560 | from __future__ import annotations
import uuid
from typing import Any, Dict, Iterable, List, Optional
from langchain.docstore.document import Document
from langchain.embeddings.base import Embeddings
from langchain.utils import get_from_dict_or_env
from langchain.vectorstores.base import VectorStore
The provided code ... | For Approximate k-NN Search, this is the default mapping to create index. |
144,561 | from __future__ import annotations
import uuid
from typing import Any, Dict, Iterable, List, Optional
from langchain.docstore.document import Document
from langchain.embeddings.base import Embeddings
from langchain.utils import get_from_dict_or_env
from langchain.vectorstores.base import VectorStore
The provided code ... | For Approximate k-NN Search, this is the default query. |
144,562 | from __future__ import annotations
import uuid
from typing import Any, Dict, Iterable, List, Optional
from langchain.docstore.document import Document
from langchain.embeddings.base import Embeddings
from langchain.utils import get_from_dict_or_env
from langchain.vectorstores.base import VectorStore
MATCH_ALL_QUERY = {... | For Script Scoring Search, this is the default query. |
144,563 | from __future__ import annotations
import uuid
from typing import Any, Dict, Iterable, List, Optional
from langchain.docstore.document import Document
from langchain.embeddings.base import Embeddings
from langchain.utils import get_from_dict_or_env
from langchain.vectorstores.base import VectorStore
MATCH_ALL_QUERY = {... | For Painless Scripting Search, this is the default query. |
144,564 | from __future__ import annotations
import uuid
from typing import Any, Dict, Iterable, List, Optional
from langchain.docstore.document import Document
from langchain.embeddings.base import Embeddings
from langchain.utils import get_from_dict_or_env
from langchain.vectorstores.base import VectorStore
The provided code ... | Get the value of the key if present. Else get the default_value. |
144,565 | from __future__ import annotations
import uuid
from typing import Any, Callable, Dict, Iterable, List, Optional
from langchain.docstore.document import Document
from langchain.embeddings.base import Embeddings
from langchain.utils import get_from_dict_or_env
from langchain.vectorstores.base import VectorStore
def _def... | null |
144,566 | from __future__ import annotations
import uuid
from typing import Any, Callable, Dict, Iterable, List, Optional
from langchain.docstore.document import Document
from langchain.embeddings.base import Embeddings
from langchain.utils import get_from_dict_or_env
from langchain.vectorstores.base import VectorStore
def _def... | null |
144,567 | import json
from typing import Any, Dict, List, Optional
import requests
from pydantic import BaseModel, Extra, Field, PrivateAttr, root_validator, validator
from langchain.utils import get_from_dict_or_env
def _get_default_params() -> dict:
return {"language": "en", "format": "json"} | null |
144,568 | import time
from typing import Dict, List, Tuple, Optional
import io
import imagesize
import requests
from pydantic import BaseModel, Extra, root_validator
from langchain.utils import get_from_dict_or_env, download_image, im_downscale, im_upscale
def im_downscale(data, target_size):
output = io.BytesIO()
im = ... | resize if h < 60 or w < 60 or data_len > 1024 * 1024 * 4 |
144,569 | import time
from typing import Dict, List, Tuple, Optional
import io
import imagesize
import requests
from pydantic import BaseModel, Extra, root_validator
from langchain.utils import get_from_dict_or_env, download_image, im_downscale, im_upscale
def _get_box(rect):
rect = rect.get("boundingBox") or rect.get("face... | null |
144,570 | import time
from typing import Dict, List, Tuple, Optional
import io
import imagesize
import requests
from pydantic import BaseModel, Extra, root_validator
from langchain.utils import get_from_dict_or_env, download_image, im_downscale, im_upscale
def _get_person(o):
age = o.get("age") or 25
gender = (o.get("ge... | null |
144,571 | import time
from typing import Dict, List, Tuple, Optional
import io
import imagesize
import requests
from pydantic import BaseModel, Extra, root_validator
from langchain.utils import get_from_dict_or_env, download_image, im_downscale, im_upscale
def _is_handwritten(styles):
handwritten = False
for style in st... | null |
144,572 | import time
from typing import Dict, List, Tuple, Optional
import io
import imagesize
import requests
from pydantic import BaseModel, Extra, root_validator
from langchain.utils import get_from_dict_or_env, download_image, im_downscale, im_upscale
def _isascii(s):
return len(s) == len(s.encode())
def _parse_lines(a... | null |
144,573 | import time
from typing import Dict, List, Tuple, Optional
import io
import imagesize
import requests
from pydantic import BaseModel, Extra, root_validator
from langchain.utils import get_from_dict_or_env, download_image, im_downscale, im_upscale
def _parse_document(analyzeResult:Dict)->List[str]:
content:str = an... | null |
144,574 | import time
from typing import Dict, List, Tuple, Optional
import io
import imagesize
import requests
from pydantic import BaseModel, Extra, root_validator
from langchain.utils import get_from_dict_or_env, download_image, im_downscale, im_upscale
def _parse_table(analyzeResult:Dict)->List[str]:
raw_content = list(... | null |
144,575 | import time
from typing import Dict, List, Tuple, Optional
import io
import imagesize
import requests
from pydantic import BaseModel, Extra, root_validator
from langchain.utils import get_from_dict_or_env, download_image, im_downscale, im_upscale
class InvalidRequest(requests.HTTPError):
pass
class InvalidImageSize... | null |
144,576 | import time
from typing import Dict, List, Tuple, Optional
import io
import imagesize
import requests
from pydantic import BaseModel, Extra, root_validator
from langchain.utils import get_from_dict_or_env, download_image, im_downscale, im_upscale
IMUN_PROMPT_DESCRIPTION = "Image description is: {description}.\n"
IMUN_P... | Create the final prompt output |
144,577 | import importlib
import json
import logging
from pathlib import Path
from typing import Union
import yaml
from langchain.prompts.base import BasePromptTemplate, RegexParser
from langchain.prompts.few_shot import FewShotPromptTemplate
from langchain.prompts.prompt import PromptTemplate
from langchain.utilities.loading i... | Load the few shot prompt from the config. |
144,578 | import importlib
import json
import logging
from pathlib import Path
from typing import Union
import yaml
from langchain.prompts.base import BasePromptTemplate, RegexParser
from langchain.prompts.few_shot import FewShotPromptTemplate
from langchain.prompts.prompt import PromptTemplate
from langchain.utilities.loading i... | Load the prompt template from config. |
144,579 | from __future__ import annotations
from typing import Any, Dict, List, Optional
from pydantic import BaseModel, Extra
from langchain.embeddings.base import Embeddings
from langchain.prompts.example_selector.base import BaseExampleSelector
from langchain.vectorstores.base import VectorStore
The provided code snippet in... | Return a list of values in dict sorted by key. |
144,580 | from typing import Dict, List
import numpy as np
from pydantic import BaseModel, root_validator
from langchain.prompts.example_selector.base import BaseExampleSelector
from langchain.prompts.prompt import PromptTemplate
The provided code snippet includes necessary dependencies for implementing the `ngram_overlap_score... | Compute ngram overlap score of source and example as sentence_bleu score. Use sentence_bleu with method1 smoothing function and auto reweighting. Return float value between 0.0 and 1.0 inclusive. https://www.nltk.org/_modules/nltk/translate/bleu_score.html https://aclanthology.org/P02-1040.pdf |
144,581 | import json
import re
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Any, Callable, Dict, List, Optional, Union
import yaml
from pydantic import BaseModel, Extra, root_validator
from langchain.formatting import formatter
The provided code snippet includes necessary dependencies for imp... | Format a template using jinja2. |
144,582 | import json
import re
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Any, Callable, Dict, List, Optional, Union
import yaml
from pydantic import BaseModel, Extra, root_validator
from langchain.formatting import formatter
DEFAULT_FORMATTER_MAPPING: Dict[str, Callable] = {
"f-string":... | Check that template string is valid. |
144,583 | from typing import List, NamedTuple, Tuple
KG_TRIPLE_DELIMITER = "<|>"
class KnowledgeTriple(NamedTuple):
"""A triple in the graph."""
subject: str
predicate: str
object_: str
def from_string(cls, triple_string: str) -> "KnowledgeTriple":
"""Create a KnowledgeTriple from a string."""
... | Parse knowledge triples from the knowledge string. |
144,584 | from typing import List, NamedTuple, Tuple
The provided code snippet includes necessary dependencies for implementing the `get_entities` function. Write a Python function `def get_entities(entity_str: str) -> List[str]` to solve the following problem:
Extract entities from entity string.
Here is the function:
def ge... | Extract entities from entity string. |
144,585 | import asyncio
import json
import logging
from collections import OrderedDict
from datetime import timedelta
from functools import partial
from typing import Optional
import async_timeout
import homeassistant.helpers.config_validation as cv
import voluptuous as vol
from aiohttp import ClientSession
from homeassistant.c... | null |
144,586 | import asyncio
import json
import logging
from collections import OrderedDict
from datetime import timedelta
from functools import partial
from typing import Optional
import async_timeout
import homeassistant.helpers.config_validation as cv
import voluptuous as vol
from aiohttp import ClientSession
from homeassistant.c... | null |
144,587 | import asyncio
import base64
import hashlib
import hmac
import json
import locale
import logging
import os
import random
import string
import time
from aiohttp import ClientSession, ClientConnectorError
def get_random_string(length: int):
seq = string.ascii_uppercase + string.digits
return ''.join((random.choi... | null |
144,588 | import asyncio
import base64
import hashlib
import hmac
import json
import locale
import logging
import os
import random
import string
import time
from aiohttp import ClientSession, ClientConnectorError
The provided code snippet includes necessary dependencies for implementing the `gen_nonce` function. Write a Python ... | Time based nonce. |
144,589 | import asyncio
import base64
import hashlib
import hmac
import json
import locale
import logging
import os
import random
import string
import time
from aiohttp import ClientSession, ClientConnectorError
The provided code snippet includes necessary dependencies for implementing the `gen_signed_nonce` function. Write a ... | Nonce signed with ssecret. |
144,590 | import asyncio
import base64
import hashlib
import hmac
import json
import locale
import logging
import os
import random
import string
import time
from aiohttp import ClientSession, ClientConnectorError
The provided code snippet includes necessary dependencies for implementing the `gen_signature` function. Write a Pyt... | Request signature based on url, signed_nonce, nonce and data. |
144,591 | import json
import re
from dataclasses import dataclass
import logging
from .const import MAP
from .special_devices import SPECIAL_DEVICES
_LOGGER = logging.getLogger(__name__)
def get_id_by_instance(s:dict):
if 'type' not in s:
return ''
try:
type_ = f'{s["type"]}:::'.split(':')[3]
r =... | null |
144,592 | import json
import re
from dataclasses import dataclass
import logging
from .const import MAP
from .special_devices import SPECIAL_DEVICES
MAP = {
"sensor": {
"air_fryer",
"air_monitor",
"battery",
"bed",
"chair",
"chair_customize",
"coffee_machine",
... | null |
144,593 | import json
import re
from dataclasses import dataclass
import logging
from .const import MAP
from .special_devices import SPECIAL_DEVICES
_LOGGER = logging.getLogger(__name__)
def get_range_by_list(value_list: list):
l = [item['value'] for item in value_list]
l.sort()
if len(l) <= 1:
_LOGGER.error... | null |
144,594 | import asyncio
import json
import logging
from collections import OrderedDict
from datetime import timedelta
from functools import partial
from typing import Optional
import async_timeout
import homeassistant.helpers.config_validation as cv
import voluptuous as vol
from aiohttp import ClientSession
from homeassistant.c... | null |
144,595 | import asyncio
import json
import logging
from collections import OrderedDict
from datetime import timedelta
from functools import partial
from typing import Optional
import async_timeout
import homeassistant.helpers.config_validation as cv
import voluptuous as vol
from aiohttp import ClientSession
from homeassistant.c... | null |
144,596 | import asyncio
import logging
from collections import defaultdict
from functools import partial
import homeassistant.helpers.config_validation as cv
import voluptuous as vol
from homeassistant.components.sensor import PLATFORM_SCHEMA
from homeassistant.const import (ATTR_ENTITY_ID, CONF_HOST, CONF_NAME,
... | null |
144,597 | import asyncio
import logging
from collections import defaultdict
from functools import partial
import homeassistant.helpers.config_validation as cv
import voluptuous as vol
from homeassistant.components.sensor import PLATFORM_SCHEMA
from homeassistant.const import (ATTR_ENTITY_ID, CONF_HOST, CONF_NAME,
... | null |
144,598 | import asyncio
import logging
from functools import partial
from datetime import timedelta
import json
from collections import OrderedDict
import homeassistant.helpers.config_validation as cv
import voluptuous as vol
from homeassistant.components.binary_sensor import PLATFORM_SCHEMA, BinarySensorEntity
from homeassista... | null |
144,599 | from collections import OrderedDict
from datetime import timedelta
from functools import partial
from dataclasses import dataclass
import homeassistant.helpers.config_validation as cv
import homeassistant.util.dt as dt_util
import voluptuous as vol
from homeassistant.components import media_player
from homeassistant.co... | null |
144,600 | from yarl import URL
from homeassistant.components import system_health
from homeassistant.core import HomeAssistant, callback
from .deps.const import DOMAIN
async def system_health_info(hass):
"""Get info for the info page."""
is_logged_in = bool(hass.data[DOMAIN]['cloud_instance_list'])
data = {
"... | Register system health callbacks. |
144,601 | import asyncio
import json
import logging
from datetime import timedelta
from functools import partial
from typing import Optional
from collections import OrderedDict
import async_timeout
import homeassistant.helpers.config_validation as cv
import voluptuous as vol
from aiohttp import ClientSession
from homeassistant.c... | null |
144,602 | import asyncio
import json
import logging
from collections import OrderedDict
from datetime import timedelta
from functools import partial
from typing import Optional
import async_timeout
import homeassistant.helpers.config_validation as cv
import voluptuous as vol
from aiohttp import ClientSession
from homeassistant.c... | null |
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