In the `FORMAT_INSTRUCTIONS` template, 4 curly braces (escaping) are
used to get single curly brace after formatting:
```
"{{{ ... }}}}" -> format_instructions.format() -> "{{ ... }}" -> template.format() -> "{ ... }".
```
Tool's `args_schema` string contains single braces `{ ... }`, and is
also transformed to `{{{{ ... }}}}` form. But this is not really correct
since there is only one `format()` call:
```
"{{{{ ... }}}}" -> template.format() -> "{{ ... }}".
```
As a result we get double curly braces in the prompt:
````
Respond to the human as helpfully and accurately as possible. You have access to the following tools:
foo: Test tool FOO, args: {{'tool_input': {{'type': 'string'}}}} # <--- !!!
...
Provide only ONE action per $JSON_BLOB, as shown:
```
{
"action": $TOOL_NAME,
"action_input": $INPUT
}
```
````
This PR fixes curly braces escaping in the `args_schema` to have single
braces in the final prompt:
````
Respond to the human as helpfully and accurately as possible. You have access to the following tools:
foo: Test tool FOO, args: {'tool_input': {'type': 'string'}} # <--- !!!
...
Provide only ONE action per $JSON_BLOB, as shown:
```
{
"action": $TOOL_NAME,
"action_input": $INPUT
}
```
````
---------
Co-authored-by: Sergey Kozlov <sergey.kozlov@ludditelabs.io>
Hi 👋 We are working with Llama2 on Bedrock, and would like to add it to
Langchain. We saw a [pull
request](https://github.com/langchain-ai/langchain/pull/13322) to add it
to the `llm.Bedrock` class, but since it concerns a chat model, we would
like to add it to `BedrockChat` as well.
- **Description:** Add support for Llama2 to `BedrockChat` in
`chat_models`
- **Issue:** the issue # it fixes (if applicable)
[#13316](https://github.com/langchain-ai/langchain/issues/13316)
- **Dependencies:** any dependencies required for this change `None`
- **Tag maintainer:** /
- **Twitter handle:** `@SimonBockaert @WouterDurnez`
---------
Co-authored-by: wouter.durnez <wouter.durnez@showpad.com>
Co-authored-by: Simon Bockaert <simon.bockaert@showpad.com>
- **Description:** This change adds an agent to the Azure Cognitive
Services toolkit for identifying healthcare entities
- **Dependencies:** azure-ai-textanalytics (Optional)
---------
Co-authored-by: James Beck <James.Beck@sa.gov.au>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Hi!
This short PR aims at:
* Fixing `OpenAIEmbeddings`' check on `chunk_size` when used with Azure
OpenAI (thus with openai < 1.0). Azure OpenAI embeddings support at most
16 chunks per batch, I believe we are supposed to take the min between
the passed value/default value and 16, not the max - which, I suppose,
was introduced by accident while refactoring the previous version of
this check from this other PR of mine: #10707
* Porting this fix to the newest class (`AzureOpenAIEmbeddings`) for
openai >= 1.0
This fixes#13539 (closed but the issue persists).
@baskaryan @hwchase17
- **Description:** There are several mistakes in the sample code in the
doc-string of `DashVector` class, and this pull request aims to correct
them.
The correction code has been tested against latest version (at the time
of creation of this pull request) of: `langchain==0.0.336`
`dashvector==1.0.6` .
- **Issue:** No issue is created for this.
- **Dependencies:** No dependency is required for this change,
<!-- - **Tag maintainer:** for a quicker response, tag the relevant
maintainer (see below), -->
- **Twitter handle:** `zeyanglin`
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submitting. Run `make format`, `make lint` and `make test` to check this
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See contribution guidelines for more information on how to write/run
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1. a test for the integration, preferably unit tests that do not rely on
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@baskaryan, @eyurtsev, @hwchase17.
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- **Description:** AstraDB is going to deprecate the `$similarity`
projection property in favor of the ´includeSimilarity´ option flag. I
moved all the queries to the new format.
- **Tag maintainer:** @hemidactylus
- **Twitter handle:** nicoloboschi
Added a `search_kwargs` field to BingSearchAPIWrapper in
`bing_search.py,` enabling users to include extra keyword arguments in
Bing search queries. This update, like specifying language preferences,
adds more customization to searches. The `search_kwargs` seamlessly
merge with standard parameters in `_bing_search_results` method.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
- **Description:** Fix Astra integration tests that are failing. The
`delete` always return True as the deletion is successful if no errors
are thrown. I aligned the test to verify this behaviour
- **Tag maintainer:** @hemidactylus
- **Twitter handle:** nicoloboschi
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
The issue was accuring because of `openai` update in Completions. its
not accepting `api_key` and 'api_base' args.
The fix is we check for the openai version and if ats v1 then remove
these keys from args before passing them to `Compilation.create(...)`
when sending from `VLLMOpenAI`
Fixed: #13507
@eyu
@efriis
@hwchase17
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
- **Description:** In this pull request, we address an issue related to
assigning a schema to the SQLDatabase class when utilizing an Oracle
database. The current implementation encounters a bug where, upon
attempting to execute a query, the alter session parse is not
appropriately defined for Oracle, leading to an error,
- **Issue:** #7928,
- **Dependencies:** No dependencies,
- **Tag maintainer:** @baskaryan,
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
- **Description:** This change allows for the `MWDumpLoader` to load all
namespaces including custom by default instead of only loading the
[default
namespaces](https://www.mediawiki.org/wiki/Help:Namespaces#Localisation).
- **Tag maintainer:** @hwchase17
**Description:**
This commit adds embedchain retriever along with tests and docs.
Embedchain is a RAG framework to create data pipelines.
**Twitter handle:**
- [Taranjeet's twitter](https://twitter.com/taranjeetio) and
[Embedchain's twitter](https://twitter.com/embedchain)
**Reviewer**
@hwchase17
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
**Description:**
Enhance the functionality of YoutubeLoader to enable the translation of
available transcripts by refining the existing logic.
**Issue:**
Encountering a problem with YoutubeLoader (#13523) where the translation
feature is not functioning as expected.
Tag maintainers/contributors who might be interested:
@eyurtsev
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
BUG: langchain.agents.openai_assistant has a reference as
`from langchain_experimental.openai_assistant.base import
OpenAIAssistantRunnable`
should be
`from langchain.agents.openai_assistant.base import
OpenAIAssistantRunnable`
This prevents building of the API Reference docs
## Update 2023-09-08
This PR now supports further models in addition to Lllama-2 chat models.
See [this comment](#issuecomment-1668988543) for further details. The
title of this PR has been updated accordingly.
## Original PR description
This PR adds a generic `Llama2Chat` model, a wrapper for LLMs able to
serve Llama-2 chat models (like `LlamaCPP`,
`HuggingFaceTextGenInference`, ...). It implements `BaseChatModel`,
converts a list of chat messages into the [required Llama-2 chat prompt
format](https://huggingface.co/blog/llama2#how-to-prompt-llama-2) and
forwards the formatted prompt as `str` to the wrapped `LLM`. Usage
example:
```python
# uses a locally hosted Llama2 chat model
llm = HuggingFaceTextGenInference(
inference_server_url="http://127.0.0.1:8080/",
max_new_tokens=512,
top_k=50,
temperature=0.1,
repetition_penalty=1.03,
)
# Wrap llm to support Llama2 chat prompt format.
# Resulting model is a chat model
model = Llama2Chat(llm=llm)
messages = [
SystemMessage(content="You are a helpful assistant."),
MessagesPlaceholder(variable_name="chat_history"),
HumanMessagePromptTemplate.from_template("{text}"),
]
prompt = ChatPromptTemplate.from_messages(messages)
memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)
chain = LLMChain(llm=model, prompt=prompt, memory=memory)
# use chat model in a conversation
# ...
```
Also part of this PR are tests and a demo notebook.
- Tag maintainer: @hwchase17
- Twitter handle: `@mrt1nz`
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
- **Description:** Added a method `fetch_valid_documents` to
`WebResearchRetriever` class that will test the connection for every url
in `new_urls` and remove those that raise a `ConnectionError`.
- **Issue:** [Previous
PR](https://github.com/langchain-ai/langchain/pull/13353),
- **Dependencies:** None,
- **Tag maintainer:** @efriis
Please make sure your PR is passing linting and testing before
submitting. Run `make format`, `make lint` and `make test` to check this
locally.
See contribution guidelines for more information on how to write/run
tests, lint, etc:
https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md
If you're adding a new integration, please include:
1. a test for the integration, preferably unit tests that do not rely on
network access,
2. an example notebook showing its use. It lives in `docs/extras`
directory.
If no one reviews your PR within a few days, please @-mention one of
@baskaryan, @eyurtsev, @hwchase17.
## Description
This PR adds an option to allow unsigned requests to the Neptune
database when using the `NeptuneGraph` class.
```python
graph = NeptuneGraph(
host='<my-cluster>',
port=8182,
sign=False
)
```
Also, added is an option in the `NeptuneOpenCypherQAChain` to provide
additional domain instructions to the graph query generation prompt.
This will be injected in the prompt as-is, so you should include any
provider specific tags, for example `<instructions>` or `<INSTR>`.
```python
chain = NeptuneOpenCypherQAChain.from_llm(
llm=llm,
graph=graph,
extra_instructions="""
Follow these instructions to build the query:
1. Countries contain airports, not the other way around
2. Use the airport code for identifying airports
"""
)
```
<!-- Thank you for contributing to LangChain!
Replace this entire comment with:
- **Description:** a description of the change,
- **Issue:** the issue # it fixes (if applicable),
- **Dependencies:** any dependencies required for this change,
- **Tag maintainer:** for a quicker response, tag the relevant
maintainer (see below),
- **Twitter handle:** we announce bigger features on Twitter. If your PR
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Please make sure your PR is passing linting and testing before
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See contribution guidelines for more information on how to write/run
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If you're adding a new integration, please include:
1. a test for the integration, preferably unit tests that do not rely on
network access,
2. an example notebook showing its use. It lives in `docs/extras`
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If no one reviews your PR within a few days, please @-mention one of
@baskaryan, @eyurtsev, @hwchase17.
-->
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
**Description**
MongoDB drivers are used in various flavors and languages. Making sure
we exercise our due diligence in identifying the "origin" of the library
calls makes it best to understand how our Atlas servers get accessed.
The original notebook has the `faiss` title which is duplicated in
the`faiss.jpynb`. As a result, we have two `faiss` items in the
vectorstore ToC. And the first item breaks the searching order (it is
placed between `A...` items).
- I updated title to `Asynchronous Faiss`.
**Description/Issue:**
When OpenAI calls a function with no args, the args are `""` rather than
`"{}"`. Then `json.loads("")` blows up. This PR handles it correctly.
**Dependencies:** None
- Fixed titles for two notebooks. They were inconsistent with other
titles and clogged ToC.
- Added `Upstash` description and link
- Moved the authentication text up in the `Elasticsearch` nb, right
after package installation. It was on the end of the page which was a
wrong place.
This PR brings a few minor improvements to the docs, namely class/method
docstrings and the demo notebook.
- A note on how to control concurrency levels to tune performance in
bulk inserts, both in the class docstring and the demo notebook;
- Slightly increased concurrency defaults after careful experimentation
(still on the conservative side even for clients running on
less-than-typical network/hardware specs)
- renamed the DB token variable to the standardized
`ASTRA_DB_APPLICATION_TOKEN` name (used elsewhere, e.g. in the Astra DB
docs)
- added a note and a reference (add_text docstring, demo notebook) on
allowed metadata field names.
Thank you!
