This PR adds additional evaluation metrics for data-augmented QA,
resulting in a report like this at the end of the notebook:
The score calculation is based on the
[Critique](https://docs.inspiredco.ai/critique/) toolkit, an API-based
toolkit (like OpenAI) that has minimal dependencies, so it should be
easy for people to run if they choose.
The code could further be simplified by actually adding a chain that
calls Critique directly, but that probably should be saved for another
PR if necessary. Any comments or change requests are welcome!
# Problem
The ChromaDB vecstore only supported local connection. There was no way
to use a chromadb server.
# Fix
Added `client_settings` as Chroma attribute.
# Usage
```
from chromadb.config import Settings
from langchain.vectorstores import Chroma
chroma_settings = Settings(chroma_api_impl="rest",
chroma_server_host="localhost",
chroma_server_http_port="80")
docsearch = Chroma.from_documents(chunks, embeddings, metadatas=metadatas, client_settings=chroma_settings, collection_name=COLLECTION_NAME)
```
Resolves https://github.com/hwchase17/langchain/issues/1510
### Problem
When loading S3 Objects with `/` in the object key (eg.
`folder/some-document.txt`) using `S3FileLoader`, the objects are
downloaded into a temporary directory and saved as a file.
This errors out when the parent directory does not exist within the
temporary directory.
See
https://github.com/hwchase17/langchain/issues/1510#issuecomment-1459583696
on how to reproduce this bug
### What this pr does
Creates parent directories based on object key.
This also works with deeply nested keys:
`folder/subfolder/some-document.txt`
This pull request proposes an update to the Lightweight wrapper
library's documentation. The current documentation provides an example
of how to use the library's requests.run method, as follows:
requests.run("https://www.google.com"). However, this example does not
work for the 0.0.102 version of the library.
Testing:
The changes have been tested locally to ensure they are working as
intended.
Thank you for considering this pull request.
Solves https://github.com/hwchase17/langchain/issues/1412
Currently `OpenAIChat` inherits the way it calculates the number of
tokens, `get_num_token`, from `BaseLLM`.
In the other hand `OpenAI` inherits from `BaseOpenAI`.
`BaseOpenAI` and `BaseLLM` uses different methodologies for doing this.
The first relies on `tiktoken` while the second on `GPT2TokenizerFast`.
The motivation of this PR is:
1. Bring consistency about the way of calculating number of tokens
`get_num_token` to the `OpenAI` family, regardless of `Chat` vs `non
Chat` scenarios.
2. Give preference to the `tiktoken` method as it's serverless friendly.
It doesn't require downloading models which might make it incompatible
with `readonly` filesystems.
Fix an issue that occurs when using OpenAIChat for llm_math, refer to
the code style of the "Final Answer:" in Mrkl。 the reason is I found a
issue when I try OpenAIChat for llm_math, when I try the question in
Chinese, the model generate the format like "\n\nQuestion: What is the
square of 29?\nAnswer: 841", it translate the question first , then
answer. below is my snapshot:
<img width="945" alt="snapshot"
src="https://user-images.githubusercontent.com/82029664/222642193-10ecca77-db7b-4759-bc46-32a8f8ddc48f.png">
Hello! Thank you for the amazing library you've created!
While following the tutorial at [the link(`Using an example
selector`)](https://langchain.readthedocs.io/en/latest/modules/prompts/examples/few_shot_examples.html#using-an-example-selector),
I noticed that passing Chroma as an argument to from_examples results in
a type hint error.
Error message(mypy):
```
Argument 3 to "from_examples" of "SemanticSimilarityExampleSelector" has incompatible type "Type[Chroma]"; expected "VectorStore" [arg-type]mypy(error)
```
This pull request fixes the type hint and allows the VectorStore class
to be specified as an argument.
Different PDF libraries have different strengths and weaknesses. PyMuPDF
does a good job at extracting the most amount of content from the doc,
regardless of the source quality, extremely fast (especially compared to
Unstructured).
https://pymupdf.readthedocs.io/en/latest/index.html
- Added instructions on setting up self hosted searx
- Add notebook example with agent
- Use `localhost:8888` as example url to stay consistent since public
instances are not really usable.
Co-authored-by: blob42 <spike@w530>
% is being misinterpreted by sqlalchemy as parameter passing, so any
`LIKE 'asdf%'` will result in a value error with mysql, mariadb, and
maybe some others. This is one way to fix it - the alternative is to
simply double up %, like `LIKE 'asdf%%'` but this seemed cleaner in
terms of output.
Fixes#1383
