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closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 674 | test_faiss_with_metadatas: key mismatch in assert | https://github.com/hwchase17/langchain/blob/236ae93610a8538d3d0044fc29379c481acc6789/tests/integration_tests/vectorstores/test_faiss.py#L54
This test will fail because `FAISS.from_texts` will assign uuid4s as keys in its docstore, while `expected_docstore` has string numbers as keys. | https://github.com/langchain-ai/langchain/issues/674 | https://github.com/langchain-ai/langchain/pull/676 | e45f7e40e80d9b47fb51853f0c672e747735b951 | e04b063ff40d7f70eaa91f135729071de60b219d | 2023-01-21T16:02:54 | python | 2023-01-22T00:08:14 | langchain/vectorstores/faiss.py | """Wrapper around FAISS vector database."""
from __future__ import annotations
import uuid
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_... |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 674 | test_faiss_with_metadatas: key mismatch in assert | https://github.com/hwchase17/langchain/blob/236ae93610a8538d3d0044fc29379c481acc6789/tests/integration_tests/vectorstores/test_faiss.py#L54
This test will fail because `FAISS.from_texts` will assign uuid4s as keys in its docstore, while `expected_docstore` has string numbers as keys. | https://github.com/langchain-ai/langchain/issues/674 | https://github.com/langchain-ai/langchain/pull/676 | e45f7e40e80d9b47fb51853f0c672e747735b951 | e04b063ff40d7f70eaa91f135729071de60b219d | 2023-01-21T16:02:54 | python | 2023-01-22T00:08:14 | tests/integration_tests/vectorstores/test_faiss.py | """Test FAISS functionality."""
from typing import List
import pytest
from langchain.docstore.document import Document
from langchain.docstore.in_memory import InMemoryDocstore
from langchain.docstore.wikipedia import Wikipedia
from langchain.embeddings.base import Embeddings
from langchain.vectorstores.faiss import ... |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 897 | Pinecone in docs is outdated | Pinecone default environment was recently changed from `us-west1-gcp` to `us-east1-gcp` ([see here](https://docs.pinecone.io/docs/projects#project-environment)), so new users following the [docs here](https://langchain.readthedocs.io/en/latest/modules/utils/combine_docs_examples/vectorstores.html#pinecone) will hit an ... | https://github.com/langchain-ai/langchain/issues/897 | https://github.com/langchain-ai/langchain/pull/898 | 7658263bfbc9485ebbc85b7d4c2476ea68611e26 | 8217a2f26c94234a1ea99d1b9b815e4da577dcfe | 2023-02-05T18:33:50 | python | 2023-02-05T23:21:56 | docs/modules/utils/combine_docs_examples/vectorstores.ipynb | {
"cells": [
{
"cell_type": "markdown",
"id": "7ef4d402-6662-4a26-b612-35b542066487",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"# VectorStores\n",
"\n",
"This notebook show cases how to use VectorStores. A key part of working with vectorstores is creatin... |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 906 | Error in Pinecone batch selection logic | Current implementation of pinecone vec db finds the batches using:
```
# set end position of batch
i_end = min(i + batch_size, len(texts))
```
[link](https://github.com/hwchase17/langchain/blob/master/langchain/vectorstores/pinecone.py#L199)
But the following lines then go on to use a mix of `[i : i + batch_s... | https://github.com/langchain-ai/langchain/issues/906 | https://github.com/langchain-ai/langchain/pull/907 | 82c080c6e617d4959fb4ee808deeba075f361702 | 3aa53b44dd5f013e35c316d110d340a630b0abd1 | 2023-02-06T07:52:59 | python | 2023-02-06T20:45:56 | langchain/vectorstores/pinecone.py | """Wrapper around Pinecone vector database."""
from __future__ import annotations
import uuid
from typing import Any, Callable, Iterable, List, Optional, Tuple
from langchain.docstore.document import Document
from langchain.embeddings.base import Embeddings
from langchain.vectorstores.base import VectorStore
class ... |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 1,087 | Qdrant Wrapper issue: _document_from_score_point exposes incorrect key for content | 
```
pydantic.error_wrappers.ValidationError: 1 validation error for Document
page_content
none is not an allowed value (type=type_error.none.not_allowed)
``` | https://github.com/langchain-ai/langchain/issues/1087 | https://github.com/langchain-ai/langchain/pull/1088 | 774550548242f44df9b219595cd46d9e238351e5 | 5d11e5da4077ad123bfff9f153f577fb5885af53 | 2023-02-16T13:18:41 | python | 2023-02-16T15:06:02 | langchain/vectorstores/qdrant.py | """Wrapper around Qdrant vector database."""
import uuid
from operator import itemgetter
from typing import Any, Callable, Iterable, List, Optional, Tuple
from langchain.docstore.document import Document
from langchain.embeddings.base import Embeddings
from langchain.utils import get_from_dict_or_env
from langchain.ve... |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 1,103 | SQLDatabase chain having issue running queries on the database after connecting | Langchain SQLDatabase and using SQL chain is giving me issues in the recent versions. My goal has been this:
- Connect to a sql server (say, Azure SQL server) using mssql+pyodbc driver (also tried mssql+pymssql driver)
`connection_url = URL.create(
"mssql+pyodbc",
query={"odbc_connect": co... | https://github.com/langchain-ai/langchain/issues/1103 | https://github.com/langchain-ai/langchain/pull/1129 | 1ed708391e80a4de83e859b8364a32cc222df9ef | c39ef70aa457dcfcf8ddcf61f89dd69d55307744 | 2023-02-17T04:18:02 | python | 2023-02-17T21:39:44 | langchain/sql_database.py | """SQLAlchemy wrapper around a database."""
from __future__ import annotations
import ast
from typing import Any, Iterable, List, Optional
from sqlalchemy import create_engine, inspect
from sqlalchemy.engine import Engine
_TEMPLATE_PREFIX = """Table data will be described in the following format:
Table 'table name'... |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 1,186 | max_marginal_relevance_search_by_vector with k > doc size | #1117 didn't seem to fix it? I still get an error `KeyError: -1`
Code to reproduce:
```py
output = docsearch.max_marginal_relevance_search_by_vector(query_vec, k=10)
```
where `k > len(docsearch)`. Pushing PR with unittest/fix shortly. | https://github.com/langchain-ai/langchain/issues/1186 | https://github.com/langchain-ai/langchain/pull/1187 | 159c560c95ed9e11cc740040cc6ee07abb871ded | c5015d77e23b24b3b65d803271f1fa9018d53a05 | 2023-02-20T19:19:29 | python | 2023-02-21T00:39:13 | langchain/vectorstores/faiss.py | """Wrapper around FAISS vector database."""
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 impo... |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 1,186 | max_marginal_relevance_search_by_vector with k > doc size | #1117 didn't seem to fix it? I still get an error `KeyError: -1`
Code to reproduce:
```py
output = docsearch.max_marginal_relevance_search_by_vector(query_vec, k=10)
```
where `k > len(docsearch)`. Pushing PR with unittest/fix shortly. | https://github.com/langchain-ai/langchain/issues/1186 | https://github.com/langchain-ai/langchain/pull/1187 | 159c560c95ed9e11cc740040cc6ee07abb871ded | c5015d77e23b24b3b65d803271f1fa9018d53a05 | 2023-02-20T19:19:29 | python | 2023-02-21T00:39:13 | tests/integration_tests/vectorstores/test_faiss.py | """Test FAISS functionality."""
import tempfile
import pytest
from langchain.docstore.document import Document
from langchain.docstore.in_memory import InMemoryDocstore
from langchain.docstore.wikipedia import Wikipedia
from langchain.vectorstores.faiss import FAISS
from tests.integration_tests.vectorstores.fake_embe... |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 983 | SQLite Cache memory for async agent runs fails in concurrent calls | I have a slack bot using slack bolt for python to handle various request for certain topics.
Using the SQLite Cache as described in here
https://langchain.readthedocs.io/en/latest/modules/llms/examples/llm_caching.html
Fails when asking the same question mutiple times for the first time with error
> (sqlite3... | https://github.com/langchain-ai/langchain/issues/983 | https://github.com/langchain-ai/langchain/pull/1286 | 81abcae91a3bbd3c90ac9644d232509b3094b54d | 42b892c21be7278689cabdb83101631f286ffc34 | 2023-02-10T19:30:13 | python | 2023-02-27T01:54:43 | langchain/cache.py | """Beta Feature: base interface for cache."""
from abc import ABC, abstractmethod
from typing import Any, Dict, List, Optional, Tuple
from sqlalchemy import Column, Integer, String, create_engine, select
from sqlalchemy.engine.base import Engine
from sqlalchemy.orm import Session
try:
from sqlalchemy.orm import d... |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 1,383 | ValueError: unsupported format character 'b' (0x62) at index 52 | python version 3.9.12, langchain version 0.0.98
Using this code
```
db = SQLDatabase.from_uri(DATABSE_URI, include_tables=['tbl_abc'])
toolkit = SQLDatabaseToolkit(db=db)
agent_executor = create_sql_agent(
llm=OpenAI(temperature=0),
toolkit=toolkit,
verbose=True
)
agent_executor.run("search for th... | https://github.com/langchain-ai/langchain/issues/1383 | https://github.com/langchain-ai/langchain/pull/1408 | 443992c4d58dcb168a21c0f45afb36b84fbdd46a | 882f7964fb0c5364bce0dcfb73abacd8ece525e4 | 2023-03-02T07:22:39 | python | 2023-03-03T00:03:16 | langchain/sql_database.py | """SQLAlchemy wrapper around a database."""
from __future__ import annotations
from typing import Any, Iterable, List, Optional
from sqlalchemy import MetaData, create_engine, inspect, select
from sqlalchemy.engine import Engine
from sqlalchemy.exc import ProgrammingError, SQLAlchemyError
from sqlalchemy.schema impor... |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 1,489 | LLM making its own observation when a tool should be used | I'm playing with the [CSV agent example](https://langchain.readthedocs.io/en/latest/modules/agents/agent_toolkits/csv.html) and notice something strange. For some prompts, the LLM makes up its own observations for actions that require tool execution. For example:
```
agent.run("Summarize the data in one sentence")
... | https://github.com/langchain-ai/langchain/issues/1489 | https://github.com/langchain-ai/langchain/pull/1566 | 30383abb127d7687a82df6593dd74329d00db730 | a9502872069409039c69b41d4857b2c7791c3752 | 2023-03-07T06:41:07 | python | 2023-03-10T00:36:15 | langchain/agents/agent.py | """Chain that takes in an input and produces an action and action input."""
from __future__ import annotations
import json
import logging
from abc import abstractmethod
from pathlib import Path
from typing import Any, Dict, List, Optional, Sequence, Tuple, Union
import yaml
from pydantic import BaseModel, root_valida... |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 1,756 | namespace argument not taken into account when creating Pinecone index | # Quick summary
Using the `namespace` argument in the function `Pinecone.from_existing_index` has no effect. Indeed, it is passed to `pinecone.Index`, which has no `namespace` argument.
# Steps to reproduce a relevant bug
```
import pinecone
from langchain.docstore.document import Document
from langchain.vector... | https://github.com/langchain-ai/langchain/issues/1756 | https://github.com/langchain-ai/langchain/pull/1757 | 280cb4160d9bd6cdb80edb5f766a06216610002c | 3701b2901e76f2f97239c2152a6a7d01754fb666 | 2023-03-18T12:26:39 | python | 2023-03-19T02:55:38 | langchain/vectorstores/pinecone.py | """Wrapper around Pinecone vector database."""
from __future__ import annotations
import uuid
from typing import Any, Callable, Iterable, List, Optional, Tuple
from langchain.docstore.document import Document
from langchain.embeddings.base import Embeddings
from langchain.vectorstores.base import VectorStore
class ... |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 1,756 | namespace argument not taken into account when creating Pinecone index | # Quick summary
Using the `namespace` argument in the function `Pinecone.from_existing_index` has no effect. Indeed, it is passed to `pinecone.Index`, which has no `namespace` argument.
# Steps to reproduce a relevant bug
```
import pinecone
from langchain.docstore.document import Document
from langchain.vector... | https://github.com/langchain-ai/langchain/issues/1756 | https://github.com/langchain-ai/langchain/pull/1757 | 280cb4160d9bd6cdb80edb5f766a06216610002c | 3701b2901e76f2f97239c2152a6a7d01754fb666 | 2023-03-18T12:26:39 | python | 2023-03-19T02:55:38 | tests/integration_tests/vectorstores/test_pinecone.py | """Test Pinecone functionality."""
import pinecone
from langchain.docstore.document import Document
from langchain.vectorstores.pinecone import Pinecone
from tests.integration_tests.vectorstores.fake_embeddings import FakeEmbeddings
pinecone.init(api_key="YOUR_API_KEY", environment="YOUR_ENV")
index = pinecone.Index... |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 1,339 | UT test_bash.py broken on MacOS dev environment | I forked & cloned the project to my dev env on MacOS, then ran 'make test', the test case 'test_incorrect_command_return_err_output' from test_bash.py failed with the following output:
<img width="1139" alt="image" src="https://user-images.githubusercontent.com/64731944/221828313-4c3f6284-9fd4-4bb5-b489-8d7e911ada03... | https://github.com/langchain-ai/langchain/issues/1339 | https://github.com/langchain-ai/langchain/pull/1837 | b706966ebc7e17cef3ced81c8e59c8f2d648a8c8 | a92344f476fc3f18599442790a1423505eec9eb4 | 2023-02-28T10:51:39 | python | 2023-03-21T16:06:52 | tests/unit_tests/test_bash.py | """Test the bash utility."""
import subprocess
from pathlib import Path
from langchain.utilities.bash import BashProcess
def test_pwd_command() -> None:
"""Test correct functionality."""
session = BashProcess()
commands = ["pwd"]
output = session.run(commands)
assert output == subprocess.check_o... |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 1,805 | Document loader for Azure Blob storage | Lots of customers is asking if langchain have a document loader like AWS S3 or GCS for Azure Blob Storage as well. As you know Microsoft is a big partner for OpenAI , so there is a real need to have native document loader for Azure Blob storage as well. We will be very happy to see this feature ASAP. | https://github.com/langchain-ai/langchain/issues/1805 | https://github.com/langchain-ai/langchain/pull/1890 | 42d725223ea3765a7699e19d46a6e0c70b4baa79 | c1a9d83b34441592d063c4d0753029c187b1c16a | 2023-03-20T02:39:16 | python | 2023-03-27T15:17:14 | docs/modules/document_loaders/examples/azure_blob_storage_container.ipynb | |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 1,805 | Document loader for Azure Blob storage | Lots of customers is asking if langchain have a document loader like AWS S3 or GCS for Azure Blob Storage as well. As you know Microsoft is a big partner for OpenAI , so there is a real need to have native document loader for Azure Blob storage as well. We will be very happy to see this feature ASAP. | https://github.com/langchain-ai/langchain/issues/1805 | https://github.com/langchain-ai/langchain/pull/1890 | 42d725223ea3765a7699e19d46a6e0c70b4baa79 | c1a9d83b34441592d063c4d0753029c187b1c16a | 2023-03-20T02:39:16 | python | 2023-03-27T15:17:14 | docs/modules/document_loaders/examples/azure_blob_storage_file.ipynb | |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 1,805 | Document loader for Azure Blob storage | Lots of customers is asking if langchain have a document loader like AWS S3 or GCS for Azure Blob Storage as well. As you know Microsoft is a big partner for OpenAI , so there is a real need to have native document loader for Azure Blob storage as well. We will be very happy to see this feature ASAP. | https://github.com/langchain-ai/langchain/issues/1805 | https://github.com/langchain-ai/langchain/pull/1890 | 42d725223ea3765a7699e19d46a6e0c70b4baa79 | c1a9d83b34441592d063c4d0753029c187b1c16a | 2023-03-20T02:39:16 | python | 2023-03-27T15:17:14 | langchain/document_loaders/__init__.py | """All different types of document loaders."""
from langchain.document_loaders.airbyte_json import AirbyteJSONLoader
from langchain.document_loaders.azlyrics import AZLyricsLoader
from langchain.document_loaders.blackboard import BlackboardLoader
from langchain.document_loaders.college_confidential import CollegeConfi... |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 1,805 | Document loader for Azure Blob storage | Lots of customers is asking if langchain have a document loader like AWS S3 or GCS for Azure Blob Storage as well. As you know Microsoft is a big partner for OpenAI , so there is a real need to have native document loader for Azure Blob storage as well. We will be very happy to see this feature ASAP. | https://github.com/langchain-ai/langchain/issues/1805 | https://github.com/langchain-ai/langchain/pull/1890 | 42d725223ea3765a7699e19d46a6e0c70b4baa79 | c1a9d83b34441592d063c4d0753029c187b1c16a | 2023-03-20T02:39:16 | python | 2023-03-27T15:17:14 | langchain/document_loaders/azure_blob_storage_container.py | |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 1,805 | Document loader for Azure Blob storage | Lots of customers is asking if langchain have a document loader like AWS S3 or GCS for Azure Blob Storage as well. As you know Microsoft is a big partner for OpenAI , so there is a real need to have native document loader for Azure Blob storage as well. We will be very happy to see this feature ASAP. | https://github.com/langchain-ai/langchain/issues/1805 | https://github.com/langchain-ai/langchain/pull/1890 | 42d725223ea3765a7699e19d46a6e0c70b4baa79 | c1a9d83b34441592d063c4d0753029c187b1c16a | 2023-03-20T02:39:16 | python | 2023-03-27T15:17:14 | langchain/document_loaders/azure_blob_storage_file.py | |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 1,801 | Poetry 1.4.0 installation fails | `poetry install -E all` fails with Poetry >=1.4.0 due to upstream incompatibility between `poetry>=1.4.0` and `pydata_sphinx_theme`.
This is a tracking issue. I've already created an issue upstream here: https://github.com/pydata/pydata-sphinx-theme/issues/1253 | https://github.com/langchain-ai/langchain/issues/1801 | https://github.com/langchain-ai/langchain/pull/1935 | 3d3e52352005aef549f9e19ad6ab18428887865c | c50fafb35d22f0f2b4e39ebb24a5ee6177c8f44e | 2023-03-19T23:42:55 | python | 2023-03-27T15:27:54 | poetry.toml | [virtualenvs]
in-project = true
|
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 1,838 | How metadata is being used during similarity search and query? | I have 3 pdf files in my directory and I "documentized", added metadata, split, embed and store them in pinecone, like this:
```
loader = DirectoryLoader('data/dir', glob="**/*.pdf", loader_cls=UnstructuredPDFLoader)
data = loader.load()
#I added company names explicitly for now
data[0].metadata["company"]="Ap... | https://github.com/langchain-ai/langchain/issues/1838 | https://github.com/langchain-ai/langchain/pull/1964 | f257b08406563af9ffb044da45b829d0707d755b | 953e58d0040773c76f68e633c3db3cd371c9c350 | 2023-03-21T01:32:20 | python | 2023-03-27T22:04:53 | langchain/vectorstores/chroma.py | """Wrapper around ChromaDB embeddings platform."""
from __future__ import annotations
import logging
import uuid
from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Optional, Tuple
from langchain.docstore.document import Document
from langchain.embeddings.base import Embeddings
from langchain.vectorstores.ba... |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 1,712 | bug(QA with Sources): source parsing is not reliable | I was going through [Vectorstore Agent](https://langchain.readthedocs.io/en/latest/modules/agents/agent_toolkits/vectorstore.html?highlight=vectorstore%20agent#vectorstore-agent) tutorial and I am facing issues with the `VectorStoreQAWithSourcesTool`.
Looking closely at the code https://github.com/hwchase17/langchai... | https://github.com/langchain-ai/langchain/issues/1712 | https://github.com/langchain-ai/langchain/pull/2118 | c33e055f17d59e225cc009c49b28d4400d56e709 | 859502b16c132e6d2f02d5233233f20f78847bdb | 2023-03-16T15:47:53 | python | 2023-03-28T22:28:20 | langchain/chains/qa_with_sources/base.py | """Question answering with sources over documents."""
from __future__ import annotations
from abc import ABC, abstractmethod
from typing import Any, Dict, List, Optional
from pydantic import BaseModel, Extra, root_validator
from langchain.chains.base import Chain
from langchain.chains.combine_documents.base import ... |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 1,834 | LLMMathChain to allow ChatOpenAI as an llm | 1. Cannot initialize match chain with ChatOpenAI LLM
llm_math = LLMMathChain(llm=ChatOpenAI(temperature=0))
---------------------------------------------------------------------------
ValidationError Traceback (most recent call last)
Cell In[33], line 1
----> 1 llm_math = LLMMathChai... | https://github.com/langchain-ai/langchain/issues/1834 | https://github.com/langchain-ai/langchain/pull/2183 | 3207a7482915a658cf8f473ae0a81ba9998c8531 | fd1fcb5a7d48cbe18b480b1493b66540e4709745 | 2023-03-20T23:12:24 | python | 2023-03-30T14:52:58 | langchain/chains/llm_math/base.py | """Chain that interprets a prompt and executes python code to do math."""
from typing import Dict, List
from pydantic import BaseModel, Extra
from langchain.chains.base import Chain
from langchain.chains.llm import LLMChain
from langchain.chains.llm_math.prompt import PROMPT
from langchain.llms.base import BaseLLM
fr... |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 2,245 | Wrong PromptLayer Dashboard hyperlink | In the docs, in https://python.langchain.com/en/latest/modules/models/llms/integrations/promptlayer_openai.html there is a hyperlink to the PromptLayer dashboard that links to "https://ww.promptlayer.com", which is incorrect. | https://github.com/langchain-ai/langchain/issues/2245 | https://github.com/langchain-ai/langchain/pull/2246 | e57b045402b52c2a602f4895c5b06fa2c22b745a | 632c2b49dabbccab92e37d01e4d1d86b6fa68457 | 2023-03-31T20:33:41 | python | 2023-03-31T23:16:23 | docs/modules/models/llms/integrations/promptlayer_openai.ipynb | {
"cells": [
{
"attachments": {},
"cell_type": "markdown",
"id": "959300d4",
"metadata": {},
"source": [
"# PromptLayer OpenAI\n",
"\n",
"This example showcases how to connect to [PromptLayer](https://www.promptlayer.com) to start recording your OpenAI requests."
]
},
{
"attachme... |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 2,174 | failed tests on Windows platform | NOTE: fixed in #2238 PR.
I'm running `tests/unit_tests` on the Windows platform and several tests related to `bash` failed.
>test_llm_bash/
test_simple_question
and
>test_bash/
test_pwd_command
test_incorrect_command
test_incorrect_command_return_err_output
test_create_directory_and_file... | https://github.com/langchain-ai/langchain/issues/2174 | https://github.com/langchain-ai/langchain/pull/2238 | 609b14a57004b4679341a05729577ec5dbcaff7d | 579ad85785a4011bdcb9fc316d2c1bcddfb9d427 | 2023-03-30T03:43:17 | python | 2023-04-01T19:52:21 | tests/unit_tests/chains/test_llm_bash.py | """Test LLM Bash functionality."""
import pytest
from langchain.chains.llm_bash.base import LLMBashChain
from langchain.chains.llm_bash.prompt import _PROMPT_TEMPLATE
from tests.unit_tests.llms.fake_llm import FakeLLM
@pytest.fixture
def fake_llm_bash_chain() -> LLMBashChain:
"""Fake LLM Bash chain for testing.... |
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