Commit Graph

2151 Commits (52714cedd4b93e3b114607a2488d5c51c7e73380)
 

Author SHA1 Message Date
Tommaso De Lorenzo 52714cedd4
fixing total cost finetuned model giving zero (#5144)
# OpanAI finetuned model giving zero tokens cost

Very simple fix to the previously committed solution to allowing
finetuned Openai models.

Improves #5127 

---------

Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago
Harrison Chase 94cf391ef1
standardize json parsing (#5168)
Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago
Davis Chase 2b2176a3c1
tfidf retriever (#5114)
Co-authored-by: vempaliakhil96 <vempaliakhil96@gmail.com>
1 year ago
Shukri b00c77dc62
Improve weaviate vectorstore docs (#5201)
# Improve weaviate vectorstore docs
1 year ago
Tomaz Bratanic fd866d1801
Update Cypher QA prompt (#5173)
# Improve Cypher QA prompt

The current QA prompt is optimized for networkX answer generation, which
returns all the possible triples.
However, Cypher search is a bit more focused and doesn't necessary
return all the context information.
Due to that reason, the model sometimes refuses to generate an answer
even though the information is provided:

![Screenshot from 2023-05-24
08-36-23](https://github.com/hwchase17/langchain/assets/19948365/351cf9c1-2567-447c-91fd-284ae3fa1ccf)


To fix this issue, I have updated the prompt. Interestingly, I tried
many variations with less instructions and they didn't work properly.
However, the current fix works nicely.
![Screenshot from 2023-05-24
08-37-25](https://github.com/hwchase17/langchain/assets/19948365/fc830603-e6ec-4a23-8a86-eaf572996014)
1 year ago
Zach Schillaci aa14e223ee
Reuse `length_func` in `MapReduceDocumentsChain` (#5181)
# Reuse `length_func` in `MapReduceDocumentsChain`

Pretty straightforward refactor in `MapReduceDocumentsChain`. Reusing
the local variable `length_func`, instead of the longer alternative
`self.combine_document_chain.prompt_length`.

@hwchase17
1 year ago
Harrison Chase 11c26ebb55
Harrison/modelscope (#5156)
Co-authored-by: thomas-yanxin <yx20001210@163.com>
Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago
Davis Chase 2d5588c5f0
bump 179 (#5200) 1 year ago
Saba Sturua 47e4ee4370
adjust docarray docstrings (#5185)
Follow up of https://github.com/hwchase17/langchain/pull/5015

Thanks for catching this! 

Just a small PR to adjust couple of strings to these changes

Signed-off-by: jupyterjazz <saba.sturua@jina.ai>
1 year ago
Jeff Vestal cf19a2a59f
example usage (#5182)
Adding example usage for elasticsearch knn embeddings
[per](https://github.com/hwchase17/langchain/pull/3401#issuecomment-1548518389)


https://github.com/hwchase17/langchain/blob/master/langchain/embeddings/elasticsearch.py
1 year ago
Ikko Eltociear Ashimine fff21a0b35
Update rellm_experimental.ipynb (#5189)
# Your PR Title (What it does)

HuggingFace -> Hugging Face
1 year ago
Nolan Tremelling faa26650c9
Beam (#4996)
# Beam

Calls the Beam API wrapper to deploy and make subsequent calls to an
instance of the gpt2 LLM in a cloud deployment. Requires installation of
the Beam library and registration of Beam Client ID and Client Secret.
Additional calls can then be made through the instance of the large
language model in your code or by calling the Beam API.

---------

Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago
Ofer Mendelevitch c81fb88035
Vectara (#5069)
# Vectara Integration

This PR provides integration with Vectara. Implemented here are:
* langchain/vectorstore/vectara.py
* tests/integration_tests/vectorstores/test_vectara.py
* langchain/retrievers/vectara_retriever.py
And two IPYNB notebooks to do more testing:
* docs/modules/chains/index_examples/vectara_text_generation.ipynb
* docs/modules/indexes/vectorstores/examples/vectara.ipynb

---------

Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago
Jason Bosco 9c4b43b494
Add Typesense vector store (#1674)
Closes #931.

---------

Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago
Leonid Ganeline 33929489b9
docs: added missed `document_loaders` examples (#5150)
# DOCS added missed document_loader examples

Added missed examples: `JSON`, `Open Document Format (ODT)`,
`Wikipedia`, `tomarkdown`.
Updated them to a consistent format.

## Who can review?

@hwchase17 
@dev2049
1 year ago
Daniel Quinteros c111134a55
Clarification of the reference to the "get_text_legth" function in ge… (#5154)
# Clarification of the reference to the "get_text_legth" function in
getting_started.md

Reference to the function "get_text_legth" in the documentation did not
make sense. Comment added for clarification.

@hwchase17
1 year ago
Daniel Quinteros de4ef24f75
Docs: updated getting_started.md (#5151)
# Docs: updated getting_started.md

Just accommodating some unnecessary spaces in the example of "pass few
shot examples to a prompt template".

@vowelparrot
1 year ago
mbchang b1b7f3541c
fix: fix current_time=Now bug for aadd_documents in TimeWeightedRetriever (#5155)
# Same as PR #5045, but for async

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Fixes #4825 

I had forgotten to update the asynchronous counterpart `aadd_documents`
with the bug fix from PR #5045, so this PR also fixes `aadd_documents`
too.

## Who can review?

Community members can review the PR once tests pass. Tag
maintainers/contributors who might be interested:
@dev2049

<!-- For a quicker response, figure out the right person to tag with @

        @hwchase17 - project lead

        Tracing / Callbacks
        - @agola11

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        - @agola11

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        - @eyurtsev

        Models
        - @hwchase17
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        Agents / Tools / Toolkits
        - @vowelparrot
        
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        - @dev2049
        
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1 year ago
Jeremiah Lowin 925dd3e59e
Add async versions of predict() and predict_messages() (#4867)
# Add async versions of predict() and predict_messages()

#4615 introduced a unifying interface for "base" and "chat" LLM models
via the new `predict()` and `predict_messages()` methods that allow both
types of models to operate on string and message-based inputs,
respectively.

This PR adds async versions of the same (`apredict()` and
`apredict_messages()`) that are identical except for their use of
`agenerate()` in place of `generate()`, which means they repurpose all
existing work on the async backend.


## Who can review?

Community members can review the PR once tests pass. Tag
maintainers/contributors who might be interested:
        @hwchase17 (follows his work on #4615)
        @agola11 (async)

---------

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
1 year ago
Junlin Zhou 9242998db1
Empty check before pop (#4929)
# Check whether 'other' is empty before popping

This PR could fix a potential 'popping empty set' error.

Co-authored-by: Junlin Zhou <jlzhou@zjuici.com>
1 year ago
Daniel King de6e6c764e
Add MosaicML inference endpoints (#4607)
# Add MosaicML inference endpoints
This PR adds support in langchain for MosaicML inference endpoints. We
both serve a select few open source models, and allow customers to
deploy their own models using our inference service. Docs are here
(https://docs.mosaicml.com/en/latest/inference.html), and sign up form
is here (https://forms.mosaicml.com/demo?utm_source=langchain). I'm not
intimately familiar with the details of langchain, or the contribution
process, so please let me know if there is anything that needs fixing or
this is the wrong way to submit a new integration, thanks!

I'm also not sure what the procedure is for integration tests. I have
tested locally with my api key.

## Who can review?
@hwchase17

---------

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
1 year ago
Adheeban Manoharan 68f0d45485
Adding Weather Loader (#5056)
Co-authored-by: Tyler Hutcherson <tyler.hutcherson@redis.com>
Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago
Jeff Vestal 0b542a9706
Add ElasticsearchEmbeddings class for generating embeddings using Elasticsearch models (#3401)
This PR introduces a new module, `elasticsearch_embeddings.py`, which
provides a wrapper around Elasticsearch embedding models. The new
ElasticsearchEmbeddings class allows users to generate embeddings for
documents and query texts using a [model deployed in an Elasticsearch
cluster](https://www.elastic.co/guide/en/machine-learning/current/ml-nlp-model-ref.html#ml-nlp-model-ref-text-embedding).

### Main features:

1. The ElasticsearchEmbeddings class initializes with an Elasticsearch
connection object and a model_id, providing an interface to interact
with the Elasticsearch ML client through
[infer_trained_model](https://elasticsearch-py.readthedocs.io/en/v8.7.0/api.html?highlight=trained%20model%20infer#elasticsearch.client.MlClient.infer_trained_model)
.
2. The `embed_documents()` method generates embeddings for a list of
documents, and the `embed_query()` method generates an embedding for a
single query text.
3. The class supports custom input text field names in case the deployed
model expects a different field name than the default `text_field`.
4. The implementation is compatible with any model deployed in
Elasticsearch that generates embeddings as output.

### Benefits:

1. Simplifies the process of generating embeddings using Elasticsearch
models.
2. Provides a clean and intuitive interface to interact with the
Elasticsearch ML client.
3. Allows users to easily integrate Elasticsearch-generated embeddings.

Related issue https://github.com/hwchase17/langchain/issues/3400

---------

Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago
Theodore Rolle 754b5133e9
Improve PlanningOutputParser whitespace handling (#5143)
Some LLM's will produce numbered lists with leading whitespace, i.e. in
response to "What is the sum of 2 and 3?":
```
Plan:
  1. Add 2 and 3.
  2. Given the above steps taken, please respond to the users original question.
```
This commit updates the PlanningOutputParser regex to ignore leading
whitespace before the step number, enabling it to correctly parse this
format.
1 year ago
Tommaso De Lorenzo 5002f3ae35
solving #2887 (#5127)
# Allowing openAI fine-tuned models
Very simple fix that checks whether a openAI `model_name` is a
fine-tuned model when loading `context_size` and when computing call's
cost in the `openai_callback`.

Fixes #2887 
---------

Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago
Myeongseop Kim 7a75bb2121
docs: fix minor typo + add wikipedia package installation part in human_input_llm.ipynb (#5118)
# Fix typo + add wikipedia package installation part in
human_input_llm.ipynb
This PR
1. Fixes typo ("the the human input LLM"), 
2. Addes wikipedia package installation part (in accordance with
`WikipediaQueryRun`
[documentation](https://python.langchain.com/en/latest/modules/agents/tools/examples/wikipedia.html))

in `human_input_llm.ipynb`
(`docs/modules/models/llms/examples/human_input_llm.ipynb`)
1 year ago
Davis Chase 753f4cfc26
bump 178 (#5130) 1 year ago
Ayan Bandyopadhyay 5c87dbf5a8
Add link to Psychic from document loaders documentation page (#5115)
# Add link to Psychic from document loaders documentation page

In my previous PR I forgot to update `document_loaders.rst` to link to
`psychic.ipynb` to make it discoverable from the main documentation.
1 year ago
Tian Wei d7f807b71f
Add AzureCognitiveServicesToolkit to call Azure Cognitive Services API (#5012)
# Add AzureCognitiveServicesToolkit to call Azure Cognitive Services
API: achieve some multimodal capabilities

This PR adds a toolkit named AzureCognitiveServicesToolkit which bundles
the following tools:
- AzureCogsImageAnalysisTool: calls Azure Cognitive Services image
analysis API to extract caption, objects, tags, and text from images.
- AzureCogsFormRecognizerTool: calls Azure Cognitive Services form
recognizer API to extract text, tables, and key-value pairs from
documents.
- AzureCogsSpeech2TextTool: calls Azure Cognitive Services speech to
text API to transcribe speech to text.
- AzureCogsText2SpeechTool: calls Azure Cognitive Services text to
speech API to synthesize text to speech.

This toolkit can be used to process image, document, and audio inputs.
---------

Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago
Jamie Broomall d4fd589638
WhyLabs callback (#4906)
# Add a WhyLabs callback handler

* Adds a simple WhyLabsCallbackHandler
* Add required dependencies as optional
* protect against missing modules with imports
* Add docs/ecosystem basic example

based on initial prototype from @andrewelizondo

> this integration gathers privacy preserving telemetry on text with
whylogs and sends stastical profiles to WhyLabs platform to monitoring
these metrics over time. For more information on what WhyLabs is see:
https://whylabs.ai

After you run the notebook (if you have env variables set for the API
Keys, org_id and dataset_id) you get something like this in WhyLabs:
![Screenshot
(443)](https://github.com/hwchase17/langchain/assets/88007022/6bdb3e1c-4243-4ae8-b974-23a8bb12edac)

Co-authored-by: Andre Elizondo <andre@whylabs.ai>
Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago
Eugene Yurtsev d56313acba
Improve effeciency of TextSplitter.split_documents, iterate once (#5111)
# Improve TextSplitter.split_documents, collect page_content and
metadata in one iteration

## Who can review?

Community members can review the PR once tests pass. Tag
maintainers/contributors who might be interested:

@eyurtsev In the case where documents is a generator that can only be
iterated once making this change is a huge help. Otherwise a silent
issue happens where metadata is empty for all documents when documents
is a generator. So we expand the argument from `List[Document]` to
`Union[Iterable[Document], Sequence[Document]]`

---------

Co-authored-by: Steven Tartakovsky <tartakovsky.developer@gmail.com>
1 year ago
Jettro Coenradie b950022894
Fixes issue #5072 - adds additional support to Weaviate (#5085)
Implementation is similar to search_distance and where_filter

# adds 'additional' support to Weaviate queries

Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago
Zander Chase 87bba2e8d3
Pass Dataset Name by Name not Position (#5108)
Pass dataset name by name
1 year ago
Matt Rickard de6a401a22
Add OpenLM LLM multi-provider (#4993)
OpenLM is a zero-dependency OpenAI-compatible LLM provider that can call
different inference endpoints directly via HTTP. It implements the
OpenAI Completion class so that it can be used as a drop-in replacement
for the OpenAI API. This changeset utilizes BaseOpenAI for minimal added
code.

---------

Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago
Gergely Imreh 69de33e024
Add Mastodon toots loader (#5036)
# Add Mastodon toots loader.

Loader works either with public toots, or Mastodon app credentials. Toot
text and user info is loaded.

I've also added integration test for this new loader as it works with
public data, and a notebook with example output run now.

---------

Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago
mbchang e173e032bc
fix: assign current_time to datetime.now() if current_time is None (#5045)
# Assign `current_time` to `datetime.now()` if it `current_time is None`
in `time_weighted_retriever`

Fixes #4825 

As implemented, `add_documents` in `TimeWeightedVectorStoreRetriever`
assigns `doc.metadata["last_accessed_at"]` and
`doc.metadata["created_at"]` to `datetime.datetime.now()` if
`current_time` is not in `kwargs`.
```python
    def add_documents(self, documents: List[Document], **kwargs: Any) -> List[str]:
        """Add documents to vectorstore."""
        current_time = kwargs.get("current_time", datetime.datetime.now())
        # Avoid mutating input documents
        dup_docs = [deepcopy(d) for d in documents]
        for i, doc in enumerate(dup_docs):
            if "last_accessed_at" not in doc.metadata:
                doc.metadata["last_accessed_at"] = current_time
            if "created_at" not in doc.metadata:
                doc.metadata["created_at"] = current_time
            doc.metadata["buffer_idx"] = len(self.memory_stream) + i
        self.memory_stream.extend(dup_docs)
        return self.vectorstore.add_documents(dup_docs, **kwargs)
``` 
However, from the way `add_documents` is being called from
`GenerativeAgentMemory`, `current_time` is set as a `kwarg`, but it is
given a value of `None`:
```python
    def add_memory(
        self, memory_content: str, now: Optional[datetime] = None
    ) -> List[str]:
        """Add an observation or memory to the agent's memory."""
        importance_score = self._score_memory_importance(memory_content)
        self.aggregate_importance += importance_score
        document = Document(
            page_content=memory_content, metadata={"importance": importance_score}
        )
        result = self.memory_retriever.add_documents([document], current_time=now)
```
The default of `now` was set in #4658 to be None. The proposed fix is
the following:
```python
    def add_documents(self, documents: List[Document], **kwargs: Any) -> List[str]:
        """Add documents to vectorstore."""
        current_time = kwargs.get("current_time", datetime.datetime.now())
        # `current_time` may exist in kwargs, but may still have the value of None.
        if current_time is None:
            current_time = datetime.datetime.now()
```
Alternatively, we could just set the default of `now` to be
`datetime.datetime.now()` everywhere instead. Thoughts @hwchase17? If we
still want to keep the default to be `None`, then this PR should fix the
above issue. If we want to set the default to be
`datetime.datetime.now()` instead, I can update this PR with that
alternative fix. EDIT: seems like from #5018 it looks like we would
prefer to keep the default to be `None`, in which case this PR should
fix the error.
1 year ago
Leonid Ganeline c28cc0f1ac
changed ValueError to ImportError (#5103)
# changed ValueError to ImportError

Code cleaning.
Fixed inconsistencies in ImportError handling. Sometimes it raises
ImportError and sometime ValueError.
I've changed all cases to the `raise ImportError`
Also:
- added installation instruction in the error message, where it missed;
- fixed several installation instructions in the error message;
- fixed several error handling in regards to the ImportError
1 year ago
venetisgr 5e47c648ed
Update serpapi.py (#4947)
Added link option in  _process_response

<!--
In _process_respons "snippet" provided non working links for the case
that "links" had the correct answer. Thus added an elif statement before
snippet
-->

<!-- Remove if not applicable -->

Fixes # (issue)
In _process_response link provided correct answers while the snippet
reply provided non working links

@vowelparrot 
## Before submitting

<!-- If you're adding a new integration, include an integration test and
an example notebook showing its use! -->

## Who can review?

Community members can review the PR once tests pass. Tag
maintainers/contributors who might be interested:

<!-- For a quicker response, figure out the right person to tag with @

        @hwchase17 - project lead

        Tracing / Callbacks
        - @agola11

        Async
        - @agola11

        DataLoaders
        - @eyurtsev

        Models
        - @hwchase17
        - @agola11

        Agents / Tools / Toolkits
        - @vowelparrot
        
        VectorStores / Retrievers / Memory
        - @dev2049
        
 -->

---------

Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago
Ankit Arya 5b2b436fab
Fixed import error for AutoGPT e.g. from langchain.experimental.auton… (#5101)
`from langchain.experimental.autonomous_agents.autogpt.agent import
AutoGPT` results in an import error as AutoGPT is not defined in the
__init__.py file

https://python.langchain.com/en/latest/use_cases/autonomous_agents/marathon_times.html

An Alternate, way would be to be directly update the import statement to
be `from langchain.experimental import AutoGPT`

Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago
Ankush Gola 467ca6f025
update langchainplus client and docker file to reflect port changes (#5005)
# Currently, only the dev images are updated
1 year ago
Shawn91 9e649462ce
fix: add_texts method of Weaviate vector store creats wrong embeddings (#4933)
# fix a bug in the add_texts method of Weaviate vector store that creats
wrong embeddings

The following is the original code in the `add_texts` method of the
Weaviate vector store, from line 131 to 153, which contains a bug. The
code here includes some extra explanations in the form of comments and
some omissions.

```python
            for i, doc in enumerate(texts):

                # some code omitted

                if self._embedding is not None:
                    # variable texts is a list of string and doc here is just a string. 
                    # list(doc) actually breaks up the string into characters.
                    # so, embeddings[0] is just the embedding of the first character
                    embeddings = self._embedding.embed_documents(list(doc))
                    batch.add_data_object(
                        data_object=data_properties,
                        class_name=self._index_name,
                        uuid=_id,
                        vector=embeddings[0],
                    )
```

To fix this bug, I pulled the embedding operation out of the for loop
and embed all texts at once.

Co-authored-by: Shawn91 <zyx199199@qq.com>
Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago
Eduard van Valkenburg 1cb04f2b26
PowerBI major refinement in working of tool and tweaks in the rest (#5090)
# PowerBI major refinement in working of tool and tweaks in the rest

I've gained some experience with more complex sets and the earlier
implementation had too many tries by the agent to create DAX, so
refactored the code to run the LLM to create dax based on a question and
then immediately run the same against the dataset, with retries and a
prompt that includes the error for the retry. This works much better!

Also did some other refactoring of the inner workings, making things
clearer, more concise and faster.
1 year ago
hwaking e57ebf3922
add get_top_k_cosine_similarity method to get max top k score and index (#5059)
# Row-wise cosine similarity between two equal-width matrices and return
the max top_k score and index, the score all greater than
threshold_score.

Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago
Donger 039f8f1abb
Add the usage of SSL certificates for Elasticsearch and user password authentication (#5058)
Enhance the code to support SSL authentication for Elasticsearch when
using the VectorStore module, as previous versions did not provide this
capability.
@dev2049

---------

Co-authored-by: caidong <zhucaidong1992@gmail.com>
Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago
Andreas Liebschner 44dc959584
Improve pinecone hybrid search retriever adding metadata support (#5098)
# Improve pinecone hybrid search retriever adding metadata support

I simply remove the hardwiring of metadata to the existing
implementation allowing one to pass `metadatas` attribute to the
constructors and in `get_relevant_documents`. I also add one missing pip
install to the accompanying notebook (I am not adding dependencies, they
were pre-existing).

First contribution, just hoping to help, feel free to critique :) 
my twitter username is `@andreliebschner`

While looking at hybrid search I noticed #3043 and #1743. I think the
former can be closed as following the example right now (even prior to
my improvements) works just fine, the latter I think can be also closed
safely, maybe pointing out the relevant classes and example. Should I
reply those issues mentioning someone?

@dev2049, @hwchase17

---------

Co-authored-by: Andreas Liebschner <a.liebschner@shopfully.com>
1 year ago
Deepak S V 5cd12102be
Improving Resilience of MRKL Agent (#5014)
This is a highly optimized update to the pull request
https://github.com/hwchase17/langchain/pull/3269

Summary:
1) Added ability to MRKL agent to self solve the ValueError(f"Could not
parse LLM output: `{llm_output}`") error, whenever llm (especially
gpt-3.5-turbo) does not follow the format of MRKL Agent, while returning
"Action:" & "Action Input:".
2) The way I am solving this error is by responding back to the llm with
the messages "Invalid Format: Missing 'Action:' after 'Thought:'" &
"Invalid Format: Missing 'Action Input:' after 'Action:'" whenever
Action: and Action Input: are not present in the llm output
respectively.

For a detailed explanation, look at the previous pull request.

New Updates:
1) Since @hwchase17 , requested in the previous PR to communicate the
self correction (error) message, using the OutputParserException, I have
added new ability to the OutputParserException class to store the
observation & previous llm_output in order to communicate it to the next
Agent's prompt. This is done, without breaking/modifying any of the
functionality OutputParserException previously performs (i.e.
OutputParserException can be used in the same way as before, without
passing any observation & previous llm_output too).

---------

Co-authored-by: Deepak S V <svdeepak99@users.noreply.github.com>
1 year ago
Michael Landis 6eacd88ae7
fix: revert docarray explicit transitive dependencies and use extras instead (#5015)
tldr: The docarray [integration
PR](https://github.com/hwchase17/langchain/pull/4483) introduced a
pinned dependency to protobuf. This is a docarray dependency, not a
langchain dependency. Since this is handled by the docarray
dependencies, it is unnecessary here.

Further, as a pinned dependency, this quickly leads to incompatibilities
with application code that consumes the library. Much less with a
heavily used library like protobuf.

Detail: as we see in the [docarray

integration](https://github.com/hwchase17/langchain/pull/4483/files#diff-50c86b7ed8ac2cf95bd48334961bf0530cdc77b5a56f852c5c61b89d735fd711R81-R83),
the transitive dependencies of docarray were also listed as langchain
dependencies. This is unnecessary as the docarray project has an
appropriate
[extras](a01a05542d/pyproject.toml (L70)).
The docarray project also does not require this _pinned_ version of
protobuf, rather [a minimum
version](a01a05542d/pyproject.toml (L41)).
So this pinned version was likely in error.

To fix this, this PR reverts the explicit hnswlib and protobuf
dependencies and adds the hnswlib extras install for docarray (which
installs hnswlib and protobuf, as originally intended). Because version
`0.32.0`
of the docarray hnswlib extras added protobuf, we bump the docarray
dependency from `^0.31.0` to `^0.32.0`.

# revert docarray explicit transitive dependencies and use extras
instead

## Who can review?

@dev2049 -- reviewed the original PR
@eyurtsev -- bumped the pinned protobuf dependency a few days ago

---------

Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago
Davis Chase fcd88bccb3
Bump 177 (#5095) 1 year ago
Harrison Chase 10ba201d05
Harrison/neo4j (#5078)
Co-authored-by: Tomaz Bratanic <bratanic.tomaz@gmail.com>
Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago
Deepak S V 49ca02711e
Improved query, print & exception handling in REPL Tool (#4997)
Update to pull request https://github.com/hwchase17/langchain/pull/3215

Summary:
1) Improved the sanitization of query (using regex), by removing python
command (since gpt-3.5-turbo sometimes assumes python console as a
terminal, and runs python command first which causes error). Also
sometimes 1 line python codes contain single backticks.
2) Added 7 new test cases.

For more details, view the previous pull request.

---------

Co-authored-by: Deepak S V <svdeepak99@users.noreply.github.com>
1 year ago