delayedkarma/langchain-issues · Datasets at Hugging Face

https://api.github.com/repos/langchain-ai/langchain/issues/12807

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1,975,107,403

PR_kwDOIPDwls5eeqLV

12,807

Disable trace_on_chain_group auto-tracing

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2023-11-02T22:00:47

2023-11-03T17:05:10

2023-11-03T17:05:09

COLLABORATOR

null

Previously we treated trace_on_chain_group as a command to always start tracing. This is unintuitive (makes the function do 2 things), and makes it harder to toggle tracing

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1,975,099,341

PR_kwDOIPDwls5eeoXk

12,806

add import tests to all modules

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2023-11-02T21:54:53

2023-11-02T22:32:56

2023-11-02T22:32:55

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1,975,074,103

PR_kwDOIPDwls5eeiu8

12,805

Add template for rag-singlestoredb

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2023-11-02T21:35:59

2023-11-03T00:51:01

2023-11-03T00:51:00

CONTRIBUTOR

null

This change adds a new template for simple RAG using the SingleStoreDB vectorstore. Twitter: @alexjpeng

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PR_kwDOIPDwls5eehyl

12,804

fix imports

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2023-11-02T22:32:32

2023-11-02T22:32:31

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1,975,037,118

I_kwDOIPDwls51uKy-

12,803

PLEASE make all subsequent versions of Langchain backwards compatible!!!

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2023-11-02T21:07:39

2023-11-02T21:36:25

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NONE

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### Feature request Example of what NOT to do: https://github.com/langchain-ai/langchain/issues/12507 Langchain, PLEASE stop doing this. PLEASE make all your updates backwards compatible. As it is, if you keep making changes like moving modules around, existing scripts break with every new update of Langchain. ### Motivation It is so frustrating to have to try and guess which version of Langchain will actually work with my code. ### Your contribution Just stop moving modules around. You cause way more harm than good when you do that, because tutorials for Langchain have to be rewritten and new versions of Langchain are not compatible with Langchain code written just a few months ago.

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1,975,014,585

PR_kwDOIPDwls5eeVoC

12,801

__getattr__ should rase AttributeError not ImportError on missing attributes

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2023-11-02T20:50:16

2023-11-02T21:08:55

2023-11-02T21:08:54

CONTRIBUTOR

null

[The python spec](https://docs.python.org/3/reference/datamodel.html#object.__getattr__) requires that `__getattr__` throw `AttributeError` for missing attributes but there are several places throwing `ImportError` in the current code base. This causes a specific problem with `hasattr` since it calls `__getattr__` then looks only for `AttributeError` exceptions. At present, calling `hasattr` on any of these modules will raise an unexpected exception that most code will not handle as `hasattr` throwing exceptions is not expected. In our case this is triggered by an exception tracker (Airbrake) that attempts to collect the version of all installed modules with code that looks like: `if hasattr(mod, "__version__"):`. With `HEAD` this is causing our exception tracker to fail on all exceptions. I only changed instances of unknown attributes raising `ImportError` and left instances of known attributes raising `ImportError`. It feels a little weird but doesn't seem to break anything.

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12,800

Add input types to cypher templates

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12,798

Automatically add configurable key to config_schema if config_specs i…

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2023-11-02T19:03:35

2023-11-02T21:46:16

2023-11-02T21:46:15

COLLABORATOR

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…s present

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Add KDBAI vector store

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2023-11-02T18:54:24

2024-01-16T14:51:40

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Addition of KDBAI vector store (https://kdb.ai). Dependencies: `kdbai_client` v0.1.2 Python package. Sample notebook: `docs/docs/integrations/vectorstores/kdbai.ipynb` Tag maintainer: @bu2kx Twitter handle: @kxsystems

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CLI 0.0.13, Configurable Template Demo

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2023-11-02T18:36:24

2023-11-02T18:42:59

2023-11-02T18:42:58

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Add template for self-query-qdrant

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2023-11-02T18:34:21

2023-11-03T20:37:30

CONTRIBUTOR

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This PR adds a self-querying template using Qdrant as a vector store. The template uses an artificial dataset and was implemented in a way that simplifies passing different components and choosing LLM and embedding providers.

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Neo4j Advanced RAG template

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2023-11-02T18:00:34

2023-11-03T20:22:56

CONTRIBUTOR

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Todo: - [x] Docs

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Add support for Cohere embed V3

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2023-11-02T17:15:12

2023-11-07T14:22:53

2023-11-06T20:07:31

NONE

null

### Feature request The new cohere V3 embed endpoints have a new required parameter - input_type. Langchain currently doesn't support this parameter https://txt.cohere.com/introducing-embed-v3/ ### Motivation Being able to use the newest multilingual embedding capabilities is something users who are developing an international product would find very important ### Your contribution Documentation!

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Add mask API key to Petals LLM

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2023-11-02T16:23:02

2023-11-03T14:05:36

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- **Description:** Add masking of API Key for `Petals` LLM when printed. - Added unit tests to validate API key handling and representation in the `Petals` class. - **Issue:** https://github.com/langchain-ai/langchain/issues/12165 - **Dependencies:** None - **Tag maintainer:** @eyurtsev ```py # output of `__repr__()` method # llm = Petals(model_name="bigscience/bloom-petals") # llm Petals(client=DistributedBloomForCausalLM( (transformer): DistributedBloomModel( (word_embeddings): Embedding(250880, 14336) (word_embeddings_layernorm): LayerNorm((14336,), eps=1e-05, elementwise_affine=True) (h): RemoteSequential(modules=bigscience/bloom-petals.0..bigscience/bloom-petals.69) (ln_f): LayerNorm((14336,), eps=1e-05, elementwise_affine=True) ) (lm_head): LMHead() ), tokenizer=BloomTokenizerFast(name_or_path='bigscience/bloom-petals', vocab_size=250680, model_max_length=1000000000000000019884624838656, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '<s>', 'eos_token': '</s>', 'unk_token': '<unk>', 'pad_token': '<pad>'}, clean_up_tokenization_spaces=False), added_tokens_decoder={ 0: AddedToken("<unk>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), 1: AddedToken("<s>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), 2: AddedToken("</s>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), 3: AddedToken("<pad>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), }, huggingface_api_key=SecretStr('**********')) ```

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Update llamacpp.ipynb

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2023-11-02T16:20:55

2023-11-02T19:52:12

CONTRIBUTOR

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HuggingFace -> Hugging Face

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Issue: Amazon Bedrock Cohere Command LLM - Malformed input request: 2 schema violations found

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2023-11-02T16:06:47

2023-11-02T16:21:34

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### System Info Sample Snippet: ``` from langchain.chains.question_answering import load_qa_chain chain = load_qa_chain(llm, chain_type = "stuff") query = "decentralized identity" docs = docsearch.similarity_search(query) text = chain({"input_documents": docs, "question": query, "verbose": True}) ``` Error: ``` ValueError: Error raised by bedrock service: An error occurred (ValidationException) when calling the InvokeModel operation: Malformed input request: 2 schema violations found, please reformat your input and try again. ``` ### Who can help? _No response_ ### Information - [ ] The official example notebooks/scripts - [ ] My own modified scripts ### Related Components - [X] LLMs/Chat Models - [X] Embedding Models - [ ] Prompts / Prompt Templates / Prompt Selectors - [ ] Output Parsers - [ ] Document Loaders - [ ] Vector Stores / Retrievers - [ ] Memory - [ ] Agents / Agent Executors - [ ] Tools / Toolkits - [X] Chains - [ ] Callbacks/Tracing - [ ] Async ### Reproduction ``` from langchain.llms.bedrock import Bedrock from langchain.embeddings import BedrockEmbeddings modelId = 'cohere.command-text-v14' bedrock_runtime = boto3.client(service_name='bedrock-runtime', region_name='us-east-1') llm = Bedrock(model_id=modelId, client=bedrock_runtime ) docs = read_and_split_docs(data_directory) bedrock_embeddings = BedrockEmbeddings(model_id="amazon.titan-embed-text-v1", client=bedrock_runtime) docsearch = Pinecone.from_texts( [t.page_content for t in docs], bedrock_embeddings, index_name=index_name ) from langchain.chains.question_answering import load_qa_chain chain = load_qa_chain(llm, chain_type = "stuff") query = "Human: decentralized identity. Assistant:" docs = docsearch.similarity_search(query) text = chain({"input_documents": docs, "question": query, "verbose": True}) ``` ### Expected behavior return some response

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BookendAI Embeddings

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2023-11-02T16:02:19

2023-11-20T17:55:24

CONTRIBUTOR

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- **Description:** https://bookend.ai/ langchain embeddings integration - **Dependencies:** n/a (just using `requests`) - **Tag maintainer:** stvhu-bookend - **Twitter handle:** https://twitter.com/bookendai

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12,788

GGML_ASSERT when using LlamaCppEmbeddings using langchain with quantized Llama 7B chat model

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2023-11-02T15:23:06

2023-11-03T04:00:11

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when i used vocab_only=True for tokenize and add documents to opensearch vectors store, facing the following issue. could you please help me to fix, GGML_ASSERT: C:\Users\pip-install-vabntc\project\llama-cpp-python\vendor\llama.cpp\llama.cpp:4032: !!kv_self.ctx

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CLI 0.0.12

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example of reusing the same prompt with different inputs

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2023-11-02T15:20:36

2023-11-22T10:13:44

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1,974,482,582

PR_kwDOIPDwls5echWT

12,785

Fix AddableDict raising exception when used with non-addable values

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2023-11-02T15:16:47

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PR_kwDOIPDwls5ecgP4

12,784

Fix on_llm_new_token(chunk=) for some chat models

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2023-11-02T15:14:15

2023-11-02T16:33:45

2023-11-02T16:33:44

COLLABORATOR

null

It was passing in message instead of generation

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PR_kwDOIPDwls5ecNGG

12,783

Implement stream() and astream() for agents

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2023-11-02T14:32:31

2023-11-28T08:11:38

2023-11-28T08:11:37

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``` ---- chunk 1 {'actions': [AgentActionMessageLog(tool='Search', tool_input="Leo DiCaprio's current girlfriend", log="\nInvoking: `Search` with `Leo DiCaprio's current girlfriend`\n\n\n", message_log=[AIMessageChunk(content='', additional_kwargs={'function_call': {'name': 'Search', 'arguments': '{\n "__arg1": "Leo DiCaprio\'s current girlfriend"\n}'}})])], 'messages': [AIMessageChunk(content='', additional_kwargs={'function_call': {'name': 'Search', 'arguments': '{\n "__arg1": "Leo DiCaprio\'s current girlfriend"\n}'}})]} ---- chunk 2 {'messages': [FunctionMessage(content="According to Us, the 48-year-old actor is now “exclusively” dating Italian model Vittoria Ceretti. A source told Us that DiCaprio is “completely smitten” with Ceretti, and their relationship is “going so well that Leo's actually being exclusive.”", name='Search')], 'steps': [AgentStep(action=AgentActionMessageLog(tool='Search', tool_input="Leo DiCaprio's current girlfriend", log="\nInvoking: `Search` with `Leo DiCaprio's current girlfriend`\n\n\n", message_log=[AIMessageChunk(content='', additional_kwargs={'function_call': {'name': 'Search', 'arguments': '{\n "__arg1": "Leo DiCaprio\'s current girlfriend"\n}'}})]), observation="According to Us, the 48-year-old actor is now “exclusively” dating Italian model Vittoria Ceretti. A source told Us that DiCaprio is “completely smitten” with Ceretti, and their relationship is “going so well that Leo's actually being exclusive.”")]} ---- chunk 3 {'actions': [AgentActionMessageLog(tool='Search', tool_input='Vittoria Ceretti age', log='\nInvoking: `Search` with `Vittoria Ceretti age`\n\n\n', message_log=[AIMessageChunk(content='', additional_kwargs={'function_call': {'name': 'Search', 'arguments': '{\n "__arg1": "Vittoria Ceretti age"\n}'}})])], 'messages': [AIMessageChunk(content='', additional_kwargs={'function_call': {'name': 'Search', 'arguments': '{\n "__arg1": "Vittoria Ceretti age"\n}'}})]} ---- chunk 4 {'messages': [FunctionMessage(content='25 years', name='Search')], 'steps': [AgentStep(action=AgentActionMessageLog(tool='Search', tool_input='Vittoria Ceretti age', log='\nInvoking: `Search` with `Vittoria Ceretti age`\n\n\n', message_log=[AIMessageChunk(content='', additional_kwargs={'function_call': {'name': 'Search', 'arguments': '{\n "__arg1": "Vittoria Ceretti age"\n}'}})]), observation='25 years')]} ---- chunk 5 {'actions': [AgentActionMessageLog(tool='Calculator', tool_input='25^0.43', log='\nInvoking: `Calculator` with `25^0.43`\n\n\n', message_log=[AIMessageChunk(content='', additional_kwargs={'function_call': {'name': 'Calculator', 'arguments': '{\n "__arg1": "25^0.43"\n}'}})])], 'messages': [AIMessageChunk(content='', additional_kwargs={'function_call': {'name': 'Calculator', 'arguments': '{\n "__arg1": "25^0.43"\n}'}})]} ---- chunk 6 {'messages': [FunctionMessage(content='Answer: 3.991298452658078', name='Calculator')], 'steps': [AgentStep(action=AgentActionMessageLog(tool='Calculator', tool_input='25^0.43', log='\nInvoking: `Calculator` with `25^0.43`\n\n\n', message_log=[AIMessageChunk(content='', additional_kwargs={'function_call': {'name': 'Calculator', 'arguments': '{\n "__arg1": "25^0.43"\n}'}})]), observation='Answer: 3.991298452658078')]} ---- chunk 7 {'messages': [AIMessage(content="Leonardo DiCaprio's current girlfriend is the Italian model Vittoria Ceretti, who is 25 years old. Her age raised to the 0.43 power is approximately 3.99.")], 'output': "Leonardo DiCaprio's current girlfriend is the Italian model " 'Vittoria Ceretti, who is 25 years old. Her age raised to the 0.43 ' 'power is approximately 3.99.'} ---- final {'actions': [AgentActionMessageLog(tool='Search', tool_input="Leo DiCaprio's current girlfriend", log="\nInvoking: `Search` with `Leo DiCaprio's current girlfriend`\n\n\n", message_log=[AIMessageChunk(content='', additional_kwargs={'function_call': {'name': 'Search', 'arguments': '{\n "__arg1": "Leo DiCaprio\'s current girlfriend"\n}'}})]), AgentActionMessageLog(tool='Search', tool_input='Vittoria Ceretti age', log='\nInvoking: `Search` with `Vittoria Ceretti age`\n\n\n', message_log=[AIMessageChunk(content='', additional_kwargs={'function_call': {'name': 'Search', 'arguments': '{\n "__arg1": "Vittoria Ceretti age"\n}'}})]), AgentActionMessageLog(tool='Calculator', tool_input='25^0.43', log='\nInvoking: `Calculator` with `25^0.43`\n\n\n', message_log=[AIMessageChunk(content='', additional_kwargs={'function_call': {'name': 'Calculator', 'arguments': '{\n "__arg1": "25^0.43"\n}'}})])], 'messages': [AIMessageChunk(content='', additional_kwargs={'function_call': {'name': 'Search', 'arguments': '{\n "__arg1": "Leo DiCaprio\'s current girlfriend"\n}'}}), FunctionMessage(content="According to Us, the 48-year-old actor is now “exclusively” dating Italian model Vittoria Ceretti. A source told Us that DiCaprio is “completely smitten” with Ceretti, and their relationship is “going so well that Leo's actually being exclusive.”", name='Search'), AIMessageChunk(content='', additional_kwargs={'function_call': {'name': 'Search', 'arguments': '{\n "__arg1": "Vittoria Ceretti age"\n}'}}), FunctionMessage(content='25 years', name='Search'), AIMessageChunk(content='', additional_kwargs={'function_call': {'name': 'Calculator', 'arguments': '{\n "__arg1": "25^0.43"\n}'}}), FunctionMessage(content='Answer: 3.991298452658078', name='Calculator'), AIMessage(content="Leonardo DiCaprio's current girlfriend is the Italian model Vittoria Ceretti, who is 25 years old. Her age raised to the 0.43 power is approximately 3.99.")], 'output': "Leonardo DiCaprio's current girlfriend is the Italian model " 'Vittoria Ceretti, who is 25 years old. Her age raised to the 0.43 ' 'power is approximately 3.99.', 'steps': [AgentStep(action=AgentActionMessageLog(tool='Search', tool_input="Leo DiCaprio's current girlfriend", log="\nInvoking: `Search` with `Leo DiCaprio's current girlfriend`\n\n\n", message_log=[AIMessageChunk(content='', additional_kwargs={'function_call': {'name': 'Search', 'arguments': '{\n "__arg1": "Leo DiCaprio\'s current girlfriend"\n}'}})]), observation="According to Us, the 48-year-old actor is now “exclusively” dating Italian model Vittoria Ceretti. A source told Us that DiCaprio is “completely smitten” with Ceretti, and their relationship is “going so well that Leo's actually being exclusive.”"), AgentStep(action=AgentActionMessageLog(tool='Search', tool_input='Vittoria Ceretti age', log='\nInvoking: `Search` with `Vittoria Ceretti age`\n\n\n', message_log=[AIMessageChunk(content='', additional_kwargs={'function_call': {'name': 'Search', 'arguments': '{\n "__arg1": "Vittoria Ceretti age"\n}'}})]), observation='25 years'), AgentStep(action=AgentActionMessageLog(tool='Calculator', tool_input='25^0.43', log='\nInvoking: `Calculator` with `25^0.43`\n\n\n', message_log=[AIMessageChunk(content='', additional_kwargs={'function_call': {'name': 'Calculator', 'arguments': '{\n "__arg1": "25^0.43"\n}'}})]), observation='Answer: 3.991298452658078')]} ```

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Update langchain to langchain-cli in README.md

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null

2

2023-11-02T14:11:02

2023-11-03T20:23:30

NONE

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When I tried this quick start, I had to substitute all the `langchain` command for `langchain-cli` commands. This PR updates the README to reflect that.

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12,781

In Runnable.stream_log build up final_output from adding output chunks

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2023-11-02T14:00:29

2023-11-28T21:50:43

2023-11-28T21:50:42

COLLABORATOR

null

Add arg to omit streamed_output list, in cases where final_output is enough this saves bandwidth

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1,974,212,272

I_kwDOIPDwls51rBaw

12,780

UnboundLocalError in langchain.retrievers.google_vertex_ai_search

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2023-11-02T13:07:25

2023-11-03T19:46:23

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### System Info Version 0.0.328, macOS, Python 3.11.5 In [_convert_website_search_response() ](https://github.com/langchain-ai/langchain/blob/master/libs/langchain/langchain/retrievers/google_vertex_ai_search.py#L120-L154) of [langchain.retrievers.google_vertex_ai_search](https://github.com/langchain-ai/langchain/blob/master/libs/langchain/langchain/retrievers/google_vertex_ai_search.py), if no documents are found it will try and print: ``` print( f"No {chunk_type} could be found.\n" "Make sure that your data store is using Advanced Website Indexing.\n" "https://cloud.google.com/generative-ai-app-builder/docs/about-advanced-features#advanced-website-indexing" # noqa: E501 ) ``` However, the `chunk_type` variable is defined only if documents have been found, and is therefore unbound, leading to exception and crash. ### Who can help? _No response_ ### Information - [ ] The official example notebooks/scripts - [ ] My own modified scripts ### Related Components - [ ] LLMs/Chat Models - [ ] Embedding Models - [ ] Prompts / Prompt Templates / Prompt Selectors - [ ] Output Parsers - [ ] Document Loaders - [ ] Vector Stores / Retrievers - [ ] Memory - [ ] Agents / Agent Executors - [ ] Tools / Toolkits - [ ] Chains - [ ] Callbacks/Tracing - [ ] Async ### Reproduction Any query that will fail to produce documents at all. ### Expected behavior The variable should be bound so that the exception is avoided.

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PR_kwDOIPDwls5ebkRb

12,779

Docs: 'memory' -> 'history' typo.

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2023-11-02T13:04:49

2023-11-02T20:09:39

CONTRIBUTOR

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The 'MessagesPlaceholder' expects 'history' but 'RunnablePassthrough' is assigning 'memory'.

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bump 329

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COLLABORATOR

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PR_kwDOIPDwls5ebeIh

12,777

Fix broken links to use cases

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2023-11-02T12:48:18

2023-11-02T20:20:55

CONTRIBUTOR

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This PR replaces broken links to end to end usecases ([/docs/use_cases](https://python.langchain.com/docs/use_cases)) with a non-broken version ([/docs/use_cases/qa_structured/sql](https://python.langchain.com/docs/use_cases/qa_structured/sql)), consistently with the "Use cases" navigation button at the top of the page.

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12,776

WebResearchRetriever enhancement with Memory and Reingestion of Documents

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2023-11-02T12:35:11

2023-11-02T12:37:37

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### Feature request WebResearchRetriever is a really great way to build a RAG based solution on public data. The challenge with using it in production is two things: 1. WebResearchRetriever contains a field called url_database and its an in memory python list, it would be good to provide some sort of alternative (maybe a memory based backend). 2. Documents on the web get updated, so some sort of staleness after the google search to reload and reingest the document again would be very great. (i.e expire the url from the database after some time delta, check if the url is already in the vectorstore, purge the docs, then regingest the site). Suggestion: add the following fields to WebResearchRetriever: 1. url_seen_ttl: TimeDelta 2. url_database_backend: MemoryBackend (some memory object in langchain that supports ttl or the ability to save a last lived field 3. purge_already_existing_documents: bool I think the above should be optional to avoid adding more latency for purging documents to avoid performance regressions. Vectorstore abstraction doesnt also provide a simple way to filter by metadata unsure what to do there. ### Motivation I am trying to make a WebResearchRetriever on public technical documentation and it gets updated every sprint release cycle, thus having something that is long living in a vectordb does not meet the requirements. Those two specific asks will help me use the out of the box functionality in langchain rather than overriding the baseretriever an making my own custom websearchretriever with memory. ### Your contribution I can help with a PR if it makes sense to have in langchain, otherwise I will take this as not something the community wants which is fair, I have a good sense of how to implement it for my own use case.

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Core dump with Hugginface Embedding on aarch64 (M1 macbook)

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### System Info linux: 6.5.0-asahi-15-1-edge-ARCH python=3.11.5 langchain=0.0.327 sentence-transformers=2.2.2 ### Who can help? _No response_ ### Information - [ ] The official example notebooks/scripts - [X] My own modified scripts ### Related Components - [ ] LLMs/Chat Models - [X] Embedding Models - [ ] Prompts / Prompt Templates / Prompt Selectors - [ ] Output Parsers - [ ] Document Loaders - [ ] Vector Stores / Retrievers - [ ] Memory - [ ] Agents / Agent Executors - [ ] Tools / Toolkits - [ ] Chains - [ ] Callbacks/Tracing - [ ] Async ### Reproduction The followig code simply causes the script to crash with a core dump: `zsh: segmentation fault (core dumped) python3 bge.py`. Note that I have no trouble downloading the model when this script runs for the first time. Also, this works as expected on my x86 machines. ``` from langchain.embeddings import HuggingFaceBgeEmbeddings def embed(query): model_name = "BAAI/bge-base-en-v1.5" encode_kwargs = {'normalize_embeddings': True} # set True to compute cosine similarity bge_model = HuggingFaceBgeEmbeddings( model_name=model_name, model_kwargs={'device': 'cpu'}, encode_kwargs=encode_kwargs ) vector = bge_model.embed_query(query) print(vector) def main(): embed("Hello there.") if __name__ == "__main__": main() ``` ### Expected behavior This script should simply print a list of floating point numbers, i.e., the result of the embedding.

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12,774

Fixed a typo in templates/docs/CONTRIBUTING.md (delimeters =>delimiters)

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- **Description:** Just fixed a minor typo in templates/docs/CONTRIBUTING.md. - **Issue:** No linked issues. Very small contribution!

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Add option to set request parameters for MathpixPDFLoader

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### Feature request **Status Quo** Currently, the [MathpixPDFLoader](https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/pdf.html#MathpixPDFLoader) sets its data property as follows: ``` @property def data(self) -> dict: options = {"conversion_formats": {self.processed_file_format: True}} return {"options_json": json.dumps(options)} ``` However, there are a variety of additional useful parameters that can be defined in the MathPix API calls: https://docs.mathpix.com/#request-parameters-6 For instance, this includes `enable_tables_fallback`, `numbers_default_to_math`, `enable_spell_check` etc. It would be great if these parameters could be specified as keyword arguments directly in the MathpixPDFLoader. ### Motivation For instance, tables do not always get parsed properly in PDFs and therefore in some cases it can make sense to set enable_tables_fallback=True. ### Your contribution TBD

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Issue: Schema error when ingesting documents

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### Issue you'd like to raise. The error {'error': [{'message': "'id' is a reserved property name, no such prop with name 'id' found in class 'LangChain_14ee2519c3154dcb9ea3f47a8967d0e8' in the schema. Check your schema files for which properties in this class are available"}]} loader = ConfluenceLoader( url="URL", username="USERNAME", api_key="API_KEY") documents = loader.load(space_key="SPACE_KEY", include_attachments=True, limit=150) text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=0) documents = text_splitter.split_documents(documents) db = Weaviate.from_documents(documents, embeddings, client=client, by_text=False) chatbot = RetrievalQA.from_chain_type( llm=llm, chain_type="stuff", retriever=db.as_retriever(search_type="similarity",search_kwargs={"k": 1}), ) prompt = PromptTemplate(template=template, input_variables=["query"]) import sys while True: message=input("prompt: ") if message=='exit': print('Exiting') sys.exit() if message=='': continue response = chatbot.run(prompt.format(query=message)) ### Suggestion: _No response_

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YoutubeLoader throws 'module not found' error

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### System Info Running langchain in Nextjs app ``` "langchain": "^0.0.175", "next": "^13.5.2", "react": "18.2.0", ``` ### Who can help? @eyurtsev ### Information - [X] The official example notebooks/scripts - [ ] My own modified scripts ### Related Components - [ ] LLMs/Chat Models - [ ] Embedding Models - [ ] Prompts / Prompt Templates / Prompt Selectors - [ ] Output Parsers - [X] Document Loaders - [ ] Vector Stores / Retrievers - [ ] Memory - [ ] Agents / Agent Executors - [ ] Tools / Toolkits - [ ] Chains - [ ] Callbacks/Tracing - [ ] Async ### Reproduction I'm using the YoutubeLoader as described in the docs. The YoutubeLoader is part of a route handler in my NextJs application. ``` // in youtube service export async function getYoutubeTranscript(youtubeUrl: string) { const loader = YoutubeLoader.createFromUrl(youtubeUrl, { language: 'en', addVideoInfo: true, }) const docs = await loader.load() return docs .map((doc) => doc.pageContent) .join(' ') .replaceAll('\n', ' ') } ``` ``` // in route handler const transcript = await getYoutubeTranscript(link) ``` When using the route, I get an error because of a missing dependency - on my machine the route still works though. ![image](https://github.com/langchain-ai/langchain/assets/113305699/0890279e-f741-408a-9cb1-7e6cbc49c878) Manually installing canvas via `npm i canvas` fixes the issue, but when I deploy to vercel, the function exceeds the maximum size limit of 50 MB compressed, because the canvas package is 45 MB compressed... Not manually installing the dependency causes the route on Vercel to always return a 405 because of the missing dependency: ![image](https://github.com/langchain-ai/langchain/assets/113305699/bf1b95bf-4f99-4ceb-8e6f-740f14346cd3) I realize that this is not caused by the YoutubeLoader itself, but still hoping for any pointers or ideas how to fix this. ### Expected behavior YoutubeLoader works without throwing a 'module not found' error

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Use data from all Google search results in SerpApi.com wrapper

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CONTRIBUTOR

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- **Description:** Use all Google search results data in SerpApi.com wrapper instead of the first one only - **Tag maintainer:** @hwchase17 _P.S. `libs/langchain/tests/integration_tests/utilities/test_serpapi.py` are not executed during the `make test`._

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support LIKE comparator (full text match) in Qdrant

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**Description:** Support [Qdrant full text match filtering](https://qdrant.tech/documentation/concepts/filtering/#full-text-match) by adding Comparator.LIKE to QdrantTranslator.

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Add LCEL-compatible `SerpApiRun` and `SerpApiResults` tools

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CONTRIBUTOR

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- **Description:** Add LCEL-compatible `SerpApiRun` and `SerpApiResults` tools - **Tag maintainer:** @baskaryan - **Twitter handle:** [@ilyazub_](https://twitter.com/ilyazub_) Example usage: ```python # docs/docs/expression_language/cookbook/tools.ipynb search = SerpApiRun() template = """turn the following user input into a search query for a search engine: {input}""" prompt = ChatPromptTemplate.from_template(template) model = ChatOpenAI() chain = prompt | model | StrOutputParser() | search chain.invoke({"input": "Which club is Cristiano Ronaldo playing right now?"}) ```

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12,767

Issue: When using FAISS vector store, how can I get the size of vector store

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2023-11-04T23:17:18

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### Issue you'd like to raise. When using FAISS vector store, how can I get the size of vector store? For example, I used FAISS.load_local(path, embeddings) to load a vector store, how to get the size of the loaded vector store? Which should be the total number of documents in it. ### Suggestion: _No response_

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12,766

ConversationEntityMemory + SQLiteEntityStore doesn't store chat_history to the database at all

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### System Info Langchain == 0.0.327 sqlite3 Here's how the setup is done Entity memory ``` memory = ConversationEntityMemory( llm=llm, input_key='question', entity_store=store, chat_history_key='chat_history', return_messages=True ) ``` Entity store ``` store = SQLiteEntityStore( session_id=f'session_{name}', db_file=os.path.abspath('storage/db/chat_history.sqlite3'), table_name='chat_history' ) ``` It doesn't store any chat history to the sqlite database. Ofcourse a table for each conversation id is getting created and it does store only one row i.e. the summary of the conversation. But nothing else getting stored. I am using ```RetrievalQA``` as well as ```ConversationalRetrievalChain``` and it doesn't work with either of them ``` chain = RetrievalQA.from_chain_type( llm=llm, retriever=vectordb, // chroma db is used and works properly chain_type_kwargs={ "prompt": QUERY_PROMPT, "memory": memory, "verbose": False }, # memory=memory, // doesnt work here verbose=False ) ``` or ``` chain = ConversationalRetrievalChain.from_llm( retriever=vectordb, llm=llm, memory=memory ) ``` LLM is as provided ``` llm = ChatOpenAI(...) ``` ### Who can help? _No response_ ### Information - [ ] The official example notebooks/scripts - [ ] My own modified scripts ### Related Components - [X] LLMs/Chat Models - [ ] Embedding Models - [ ] Prompts / Prompt Templates / Prompt Selectors - [ ] Output Parsers - [ ] Document Loaders - [ ] Vector Stores / Retrievers - [X] Memory - [ ] Agents / Agent Executors - [ ] Tools / Toolkits - [X] Chains - [ ] Callbacks/Tracing - [ ] Async ### Reproduction As I have checked the chat_history.py script, found out that the particular method is not implemented till now File path ``` .venv/lib/python3.11/site-packages/langchain/schema/chat_history.py ``` Method details (line 56-63) ``` @abstractmethod def add_message(self, message: BaseMessage) -> None: """Add a Message object to the store. Args: message: A BaseMessage object to store. """ raise NotImplementedError() ``` I think this method is responsible for storing the chat history to the persistent database ### Expected behavior The code should save the chat_history (prompt + response) to the sqlite database after each prompt.

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12,765

create_sql_agent checks schema of a table with partiton field always goes wrong

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### Issue you'd like to raise. In create_Sql_agent, when the agent is querying a table schema with partition field, it nevers adds parition and the program goes wrong, how to let the agent add partition field everytime it queries a table schema? Many thanks. ### Suggestion: _No response_

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zep: Update Zep docs and messaging

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CONTRIBUTOR

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Update Zep documentation with messaging, more details. @baskaryan, @eyurtsev

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Issue: getting not implemented error when using async chromium loader

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2024-01-16T00:44:22

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### Issue you'd like to raise. I tried to use webscraping by using langchain and used the async chromium loader as per the lanchain documentation but I was getting error asyncio.run() error so I made some chnages that i found on web but its still not working . below is the code: import asyncio import playwright from langchain.document_loaders import AsyncChromiumLoader from langchain.document_transformers import BeautifulSoupTransformer import nest_asyncio nest_asyncio.apply() async def main(): # Create an instance of AsyncChromiumLoader with a list of URLs urls = ["https://www.hdfcbank.com/personal/borrow/popular-loans/personal-loan/eligibility"] # Replace with your desired URLs loader = AsyncChromiumLoader(urls) # Load the URLs html = await loader.load() # Print the HTML content for url, content in html.items(): print(f"URL: {url}\nHTML Content: {content}\n") if __name__ == "__main__": asyncio.run(main()) ### Suggestion: _No response_

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zep/rag conversation zep template

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2

2023-11-02T04:07:12

2023-11-03T21:17:04

2023-11-03T20:34:44

CONTRIBUTOR

null

LangServe template for a RAG Conversation App using Zep. @baskaryan, @eyurtsev

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DPP retriever

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2023-11-02T03:08:49

2023-11-14T02:50:46

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### Feature request DPP (Determinantal Point Process) retriever for retrieve examples. ### Motivation DPPRetriever can obtain diverse examples. Therefore, I think DDP is needed in langchain. ### Your contribution NO

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Implement TTL for RedisSemanticCache

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2023-11-02T02:35:54

2023-11-07T16:04:23

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CONTRIBUTOR

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- **Description:** Allows a TTL to be set for the keys created by RedisSemanticCache - **Issue**: #3213 - **Dependencies:** N/A - **Tag maintainer:** @baskaryan

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Issue: Why did the agent provide the action and action input, but instead of executing it, it directly finished the chain

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2023-11-02T02:24:40

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### Issue you'd like to raise. I provide the agent a get_date function as a tool，but when I ask the agent what is today's date， the agent provide the action and action input, but instead of executing it, it directly finished the chain。 ![image](https://github.com/langchain-ai/langchain/assets/149214596/737293ae-ef41-4c66-aef2-fe1267217c37) ![image](https://github.com/langchain-ai/langchain/assets/149214596/e1644d5e-9e52-4322-904a-b332f81d32c8) ![image](https://github.com/langchain-ai/langchain/assets/149214596/eaadad2c-0bc9-43ef-8b5e-d5a12626a3ea) ### Suggestion: _No response_

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12,758

Issue: analytic chatbot that's based on Langchain (with agents and tools) and Streamlit is too slow

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2024-01-01T00:53:36

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### Issue you'd like to raise. I created an analytic chatbot using Langchain (with tools and agents) for the backend and Streamlit for the frontend. It works, but for some users' questions, it takes too much time to output anything. If I look at the output of intermediate steps, I can see that the chatbot tries to print out all relevant rows in the output. For example, below, the chatbot found 40 relevant comments and printed them out in one of its intermediate steps one by one (it takes up to one minute). [![enter image description here][1]][1] Code for chatbot: ``` def load_data(path): return pd.read_csv(path) if st.sidebar.button('Use Data'): # If button is clicked, load the EDW.csv file st.session_state["df"] = load_data('./data/EDW.csv') uploaded_file = st.sidebar.file_uploader("Choose a CSV file", type="csv") if "df" in st.session_state: msgs = StreamlitChatMessageHistory() memory = ConversationBufferWindowMemory(chat_memory=msgs, return_messages=True, k=5, memory_key="chat_history", output_key="output") if len(msgs.messages) == 0 or st.sidebar.button("Reset chat history"): msgs.clear() msgs.add_ai_message("How can I help you?") st.session_state.steps = {} avatars = {"human": "user", "ai": "assistant"} # Display a chat input widget if prompt := st.chat_input(placeholder=""): st.chat_message("user").write(prompt) llm = AzureChatOpenAI( deployment_name = "gpt-4", model_name = "gpt-4", openai_api_key = os.environ["OPENAI_API_KEY"], openai_api_version = os.environ["OPENAI_API_VERSION"], openai_api_base = os.environ["OPENAI_API_BASE"], temperature = 0, streaming=True ) max_number_of_rows = 40 agent_analytics_node = create_pandas_dataframe_agent( llm, st.session_state["df"], verbose=False, agent_type=AgentType.OPENAI_FUNCTIONS, reduce_k_below_max_tokens=True, # to not exceed token limit max_execution_time = 20, early_stopping_method="generate", # will generate a final answer after the max_execution_time has been surpassed # max_iterations=2, # to cap an agent at taking a certain number of steps ) tool_analytics_node = Tool( return_intermediate_steps=False, name='Analytics Node', func=agent_analytics_node.run, description=f''' This tool is useful when you need to answer questions about data stored in a pandas dataframe, referred to as 'df'. 'df' comprises the following columns: {st.session_state["df"].columns.to_list()}. Here is a sample of the data: {st.session_state["df"].head(5)}. When working with df, ensure not to output more than {max_number_of_rows} rows at once, either in intermediate steps or in the final answer. This is because df could contain too many rows, which could potentially overload memory, for example instead of `df[df['survey_comment'].str.contains('wet', na=False, case=False)]['survey_comment'].tolist()` use `df[df['survey_comment'].str.contains('wet', na=False, case=False)]['survey_comment'].head({max_number_of_rows}).tolist()`. ''' ) tools = [tool_analytics_node] chat_agent = ConversationalChatAgent.from_llm_and_tools(llm=llm, tools=tools, return_intermediate_steps=False) executor = AgentExecutor.from_agent_and_tools( agent=chat_agent, tools=tools, memory=memory, return_intermediate_steps=False, handle_parsing_errors=True, verbose=False, ) with st.chat_message("assistant"): st_cb = StreamlitCallbackHandler(st.container(), expand_new_thoughts=False) response = executor(prompt, callbacks=[st_cb]) st.write(response["output"]) ``` [1]: https://i.stack.imgur.com/xyaVZl.png ### Suggestion: My questions are: 1) Is there any way to speed up this process? 2) How can I disable the intermediate output of the chatbot? (I already put `return_intermediate_steps=False`, `verbose=False`, and `expand_new_thoughts=False`, but the chatbot still shows intermediate steps.)

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feat: add a rag template for momento vector index

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CONTRIBUTOR

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# Description Add a RAG template showcasing Momento Vector Index as a vector store. Includes a project directory and README. # **Twitter handle** Tag the company @momentohq for a mention and @mlonml for the contribution.

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12,756

Fixes to the docs for timescale vector template

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2023-11-02T00:21:05

2023-11-02T01:48:23

CONTRIBUTOR

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**Description:** Changes to timescale vector template docs and index description.

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12,755

new course on `DeepLearning.ai`

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2023-11-02T00:19:01

2023-11-10T22:22:54

2023-11-10T21:55:28

COLLABORATOR

null

Added a new course on [DeepLearning.ai](https://learn.deeplearning.ai/functions-tools-agents-langchain) Added the LangChain `Wikipedia` link. Probably, it can be placed in the "More" menu.

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12,754

Open Clip multimodal embeddings

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12,753

Added ability to use tuned model with ChatVertexAI

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2023-11-01T23:40:23

2023-11-17T03:08:28

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- **Description:** Was not able to use a tuned model when using "ChatVertexAI" added that based on how it was done in non chat VertexAI class. - **Issue:** N/A - **Dependencies:** N/A - **Tag maintainer:** @baskaryan - **Twitter handle:** @arian_jahiri

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Langchain Agent Duplicates Response Separated by "\n" with Finetuned LLM

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### System Info Running with `langchain==0.0.327` on Fedora Linux and Windows. Finetuning with `gpt-3.5-turbo-16k-0613`. Language: `Python 3.10.11` ### Who can help? @hwchase17 @agola11 ### Information - [ ] The official example notebooks/scripts - [X] My own modified scripts ### Related Components - [X] LLMs/Chat Models - [ ] Embedding Models - [ ] Prompts / Prompt Templates / Prompt Selectors - [X] Output Parsers - [ ] Document Loaders - [ ] Vector Stores / Retrievers - [ ] Memory - [X] Agents / Agent Executors - [ ] Tools / Toolkits - [x] Chains - [ ] Callbacks/Tracing - [ ] Async ### Reproduction Hello, I have created a simple langchain agent with a Tool and with an LLM. However, the LLM passed into the agent actually points to my **finetuned** GPT instance. We notice that the output responses contain an accurate response, but repeated and separated by a newline. I have [fine-tuned on the sample prompts](https://platform.openai.com/docs/guides/fine-tuning/preparing-your-dataset) from the official OpenAI documentation on making a sarcastic chatbot. Here is the JSONL file I used for fine tuning: https://pastebin.com/BDV0Tjyk. Here is my agent code: ``` llm = ChatOpenAI(temperature=0, model=<OUR_MODEL_ID>, streaming=False) tools = [ Tool.from_function( func=add_asdf, name="add_asdf", description="useful when someone asks to add asdf to a string.", ), ] agent_kwargs = { "system_message": SystemMessage( content="Marv is a factual chatbot that is also sarcastic." ), } agent = initialize_agent( tools, llm, agent=AgentType.OPENAI_FUNCTIONS, agent_kwargs=agent_kwargs, max_execution_time=90, early_stopping_method="generate", handle_parsing_errors=True, tags=[], ) result = agent.run("Where's the sahara desert located?") print(result) ``` Now this does seem to work correctly and use the fine tuned instance (as we can see the responses are definitely sarcastic), but we notice that in its response, the agent seems to be combining **the same response twice, but separated by a newline.** Output: ``` In North Africa. But who's keeping track of giant deserts anyway? In North Africa. But who's keeping track of giant deserts anyway? ``` Looking at the generations from the debug: ``` "generations": [ [ { "text": "In North Africa. But who's keeping track of giant deserts anyway?\nIn North Africa. But who's keeping track of giant deserts anyway?", "generation_info": { "finish_reason": "stop" }, "type": "ChatGeneration", "message": { "lc": 1, "type": "constructor", "id": [ "langchain", "schema", "messages", "AIMessage" ], "kwargs": { "content": "In North Africa. But who's keeping track of giant deserts anyway?\nIn North Africa. But who's keeping track of giant deserts anyway?", "additional_kwargs": {} } } } ] ] ``` Some important details: - We notice that we only execute the LLM _one_ time (i.e. there are no duplicate runs of the llm in the chain). - Our fine tuned instance works perfectly in the OpenAI playground, and with the OpenAI python library. **Hence, this seems to be a langchain-specific issue and nothing to do with our training data or fine tuning.** - The issue does not occur 100% of the time. Occasionally, only one response is returned. I am happy to provide more information on debug logs or anything about the fine-tuned model for replication. We'd love any information or nuances about using a fine-tuned instance with a Langchain agent, or guidance on what could be going wrong. Thanks! ### Expected behavior Only one response should be generated: ``` In North Africa. But who's keeping track of giant deserts anyway? ``` The response contains a copy of the response separated by a newline: ``` { "output": "In North Africa. But who's keeping track of giant deserts anyway?\nIn North Africa. But who's keeping track of giant deserts anyway?" } ```

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12,751

Fixes 'Nonetype' not iterable for ObsidianLoader

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2023-11-01T22:48:56

2023-11-01T23:07:11

2023-11-01T23:07:10

COLLABORATOR

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Implements #12726 from @Di3mex

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12,749

Bump got, @docusaurus/core and @docusaurus/preset-classic in /docs

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2023-11-01T21:47:38

2023-11-07T23:53:54

2023-11-07T23:53:43

CONTRIBUTOR

null

Bumps [got](https://github.com/sindresorhus/got) to 12.6.1 and updates ancestor dependencies [got](https://github.com/sindresorhus/got), [@docusaurus/core](https://github.com/facebook/docusaurus/tree/HEAD/packages/docusaurus) and [@docusaurus/preset-classic](https://github.com/facebook/docusaurus/tree/HEAD/packages/docusaurus-preset-classic). These dependencies need to be updated together. Updates `got` from 9.6.0 to 12.6.1 <details> <summary>Release notes</summary> <p><em>Sourced from <a href="https://github.com/sindresorhus/got/releases">got's releases</a>.</em></p> <blockquote> <h2>v12.6.1</h2> <ul> <li>Fix <code>get-stream</code> import statement (<a href="https://redirect.github.com/sindresorhus/got/issues/2266">#2266</a>) 67d5039</li> </ul> <p><a href="https://github.com/sindresorhus/got/compare/v12.6.0...v12.6.1">https://github.com/sindresorhus/got/compare/v12.6.0...v12.6.1</a></p> <h2>v12.6.0</h2> <ul> <li>Update dependencies 88c88fb 979272e</li> <li>Loosen URL validation strictness (<a href="https://redirect.github.com/sindresorhus/got/issues/2200">#2200</a>) 0ca0b7f</li> </ul> <p><a href="https://github.com/sindresorhus/got/compare/v12.5.3...v12.6.0">https://github.com/sindresorhus/got/compare/v12.5.3...v12.6.0</a></p> <h2>v12.5.3</h2> <ul> <li>Fix abort event listeners not always being cleaned up (<a href="https://redirect.github.com/sindresorhus/got/issues/2162">#2162</a>) 3cc40b5</li> </ul> <p><a href="https://github.com/sindresorhus/got/compare/v12.5.2...v12.5.3">https://github.com/sindresorhus/got/compare/v12.5.2...v12.5.3</a></p> <h2>v12.5.2</h2> <ul> <li>Improve TypeScript 4.9 compatibility (<a href="https://redirect.github.com/sindresorhus/got/issues/2163">#2163</a>) 39f83b6</li> </ul> <p><a href="https://github.com/sindresorhus/got/compare/v12.5.1...v12.5.2">https://github.com/sindresorhus/got/compare/v12.5.1...v12.5.2</a></p> <h2>v12.5.1</h2> <ul> <li>Fix compatibility with TypeScript and ESM 3b3ea67</li> <li>Fix request body not being properly cached (<a href="https://redirect.github.com/sindresorhus/got/issues/2150">#2150</a>) 3e9d3af</li> </ul> <p><a href="https://github.com/sindresorhus/got/compare/v12.5.0...v12.5.1">https://github.com/sindresorhus/got/compare/v12.5.0...v12.5.1</a></p> <h2>v12.5.0</h2> <ul> <li>Disable method rewriting on 307 and 308 status codes (<a href="https://redirect.github.com/sindresorhus/got/issues/2145">#2145</a>) e049e94</li> <li>Upgrade dependencies 8630815 f0ac0b3 4c3762a</li> </ul> <p><a href="https://github.com/sindresorhus/got/compare/v12.4.1...v12.5.0">https://github.com/sindresorhus/got/compare/v12.4.1...v12.5.0</a></p> <h2>v12.4.1</h2> <h3>Fixes</h3> <ul> <li>Fix <code>options.context</code> being not extensible b671480715dbbff908e9a385f5e714570c663cd7</li> <li>Don't emit <code>uploadProgress</code> after promise cancelation 693de217b030816f574d6e4cb505ee2e77b21c29</li> </ul> <p><a href="https://github.com/sindresorhus/got/compare/v12.4.0...v12.4.1">https://github.com/sindresorhus/got/compare/v12.4.0...v12.4.1</a></p> <h2>v12.4.0</h2> <h3>Improvements</h3> <ul> <li>Support FormData without known length (<a href="https://redirect.github.com/sindresorhus/got/issues/2120">#2120</a>) 850773c</li> </ul> <h3>Fixes</h3> <ul> <li>Don&<a href="https://redirect.github.com/sindresorhus/got/issues/39">#39</a>;t call <code>beforeError</code> hooks with <code>HTTPError</code> if the <code>throwHttpErrors</code> option is <code>false</code> (<a href="https://redirect.github.com/sindresorhus/got/issues/2104">#2104</a>) 3927348</li> </ul>  </blockquote> <p>... (truncated)</p> </details> <details> <summary>Commits</summary> <ul> <li><a href="https://github.com/sindresorhus/got/commit/c405f5407863ef8faca3af397204d6f192a56320"><code>c405f54</code></a> 12.6.1</li> <li><a href="https://github.com/sindresorhus/got/commit/67d5039ff5a5518489529f9706199234e9b64ad6"><code>67d5039</code></a> Fix <code>get-stream</code> import statement (<a href="https://redirect.github.com/sindresorhus/got/issues/2266">#2266</a>)</li> <li><a href="https://github.com/sindresorhus/got/commit/469a45554ff29ca13050a2714eabaaec9f7160f7"><code>469a455</code></a> Meta tweaks</li> <li><a href="https://github.com/sindresorhus/got/commit/8f77e8d07d8684cde95d351feafaa308b466dff4"><code>8f77e8d</code></a> Fix readme "axios bugs" urls (<a href="https://redirect.github.com/sindresorhus/got/issues/2253">#2253</a>)</li> <li><a href="https://github.com/sindresorhus/got/commit/af928f6d3974d7106718d37acc6bd1d33d2cec70"><code>af928f6</code></a> Fix type error on build (<a href="https://redirect.github.com/sindresorhus/got/issues/2251">#2251</a>)</li> <li><a href="https://github.com/sindresorhus/got/commit/702ed352ac5d8527deaf4a5821d0274afc56e9d8"><code>702ed35</code></a> Meta tweaks</li> <li><a href="https://github.com/sindresorhus/got/commit/e4460f771b7acff845a2ca6f6de3f7693faa406d"><code>e4460f7</code></a> Add failing tests for <a href="https://redirect.github.com/sindresorhus/got/issues/2170">#2170</a> (<a href="https://redirect.github.com/sindresorhus/got/issues/2171">#2171</a>)</li> <li><a href="https://github.com/sindresorhus/got/commit/13a68d36e0f6aed98cf39269e597489da5480c00"><code>13a68d3</code></a> 12.6.0</li> <li><a href="https://github.com/sindresorhus/got/commit/88c88fbc469683dad33d418681cb7017d0e9fcbf"><code>88c88fb</code></a> Update dependencies</li> <li><a href="https://github.com/sindresorhus/got/commit/0ca0b7f7134f41b45a51370154041cc97c28ca60"><code>0ca0b7f</code></a> Do not enforce newest URI rules on URLs (<a href="https://redirect.github.com/sindresorhus/got/issues/2200">#2200</a>)</li> <li>Additional commits viewable in <a href="https://github.com/sindresorhus/got/compare/v9.6.0...v12.6.1">compare view</a></li> </ul> </details> <br /> Updates `@docusaurus/core` from 2.4.0 to 3.0.0 <details> <summary>Release notes</summary> <p><em>Sourced from <a href="https://github.com/facebook/docusaurus/releases"><code>@docusaurus/core</code>'s releases</a>.</em></p> <blockquote> <h2>3.0.0 (2023-10-31)</h2> <ul> <li>GitHub PR: <a href="https://redirect.github.com/facebook/docusaurus/pull/9478">facebook/docusaurus#9478</a></li> <li>GitHub release notes: <a href="https://github.com/facebook/docusaurus/releases/tag/v3.0.0">https://github.com/facebook/docusaurus/releases/tag/v3.0.0</a></li> <li>GitHub release discussion: <a href="https://github.com/facebook/docusaurus/discussions/9481">https://github.com/facebook/docusaurus/discussions/9481</a></li> <li>Upgrade guide: <a href="https://docusaurus.io/docs/migration/v3">docusaurus.io/docs/migration/v3</a></li> </ul> <h4>:boom: Breaking Change</h4> <ul> <li><code>create-docusaurus</code>, <code>docusaurus-mdx-loader</code>, <code>docusaurus-plugin-content-blog</code>, <code>docusaurus-remark-plugin-npm2yarn</code>, <code>docusaurus-theme-classic</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9451">#9451</a> feat(mdx-loader): upgrade to MDX v3 (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-plugin-content-docs</code>, <code>docusaurus-plugin-ideal-image</code>, <code>docusaurus-types</code>, <code>docusaurus-utils</code>, <code>docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9317">#9317</a> feat(core): support TypeScript + ESM configuration (<a href="https://github.com/harryzcy"><code>@harryzcy</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-theme-classic</code>, <code>docusaurus-theme-common</code>, <code>docusaurus-theme-live-codeblock</code>, <code>docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9316">#9316</a> chore: upgrade syntax highlighting dependencies, <code>prism-react-renderer</code> to v2, <code>react-live</code> to v4 (<a href="https://github.com/harryzcy"><code>@harryzcy</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-cssnano-preset</code>, <code>docusaurus-logger</code>, <code>docusaurus-mdx-loader</code>, <code>docusaurus-migrate</code>, <code>docusaurus-plugin-client-redirects</code>, <code>docusaurus-plugin-content-blog</code>, <code>docusaurus-plugin-content-docs</code>, <code>docusaurus-plugin-content-pages</code>, <code>docusaurus-plugin-debug</code>, <code>docusaurus-plugin-google-analytics</code>, <code>docusaurus-plugin-google-gtag</code>, <code>docusaurus-plugin-google-tag-manager</code>, <code>docusaurus-plugin-ideal-image</code>, <code>docusaurus-plugin-pwa</code>, <code>docusaurus-plugin-sitemap</code>, <code>docusaurus-preset-classic</code>, <code>docusaurus-remark-plugin-npm2yarn</code>, <code>docusaurus-theme-classic</code>, <code>docusaurus-theme-common</code>, <code>docusaurus-theme-live-codeblock</code>, <code>docusaurus-theme-mermaid</code>, <code>docusaurus-theme-search-algolia</code>, <code>docusaurus-theme-translations</code>, <code>docusaurus-utils-common</code>, <code>docusaurus-utils-validation</code>, <code>docusaurus-utils</code>, <code>docusaurus</code>, <code>eslint-plugin</code>, <code>lqip-loader</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9348">#9348</a> chore: update node engine version 18 (<a href="https://github.com/OzakIOne"><code>@OzakIOne</code></a>)</li> </ul> </li> <li><code>docusaurus-plugin-content-docs</code>, <code>docusaurus-theme-classic</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9310">#9310</a> chore(plugin-docs): remove legacy versioned prefix on doc ids and sidebar names in versioned sidebars (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>docusaurus-theme-classic</code>, <code>docusaurus-theme-translations</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9308">#9308</a> fix(theme): make warning a first-class admonition, and deprecate caution admonition (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>docusaurus-theme-common</code>, <code>docusaurus-theme-live-codeblock</code>, <code>docusaurus-theme-mermaid</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9305">#9305</a> feat(theme-mermaid): upgrade Mermaid to v10.4 - handle async rendering (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-plugin-content-docs</code>, <code>docusaurus-plugin-debug</code>, <code>docusaurus-plugin-google-analytics</code>, <code>docusaurus-plugin-google-gtag</code>, <code>docusaurus-plugin-google-tag-manager</code>, <code>docusaurus-plugin-ideal-image</code>, <code>docusaurus-plugin-pwa</code>, <code>docusaurus-theme-classic</code>, <code>docusaurus-theme-common</code>, <code>docusaurus-theme-live-codeblock</code>, <code>docusaurus-theme-mermaid</code>, <code>docusaurus-theme-search-algolia</code>, <code>docusaurus-tsconfig</code>, <code>docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9258">#9258</a> feat: Docusaurus v3 upgrades and require TypeScript 5 (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>docusaurus-plugin-content-blog</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9189">#9189</a> feat(blog-plugin): limit option for blog feedOptions (<a href="https://github.com/johnnyreilly"><code>@johnnyreilly</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-tsconfig</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9050">#9050</a> feat: create official TypeScript base config <code>@docusaurus/tsconfig</code> (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-mdx-loader</code>, <code>docusaurus-module-type-aliases</code>, <code>docusaurus-plugin-client-redirects</code>, <code>docusaurus-plugin-content-blog</code>, <code>docusaurus-plugin-content-docs</code>, <code>docusaurus-plugin-content-pages</code>, <code>docusaurus-plugin-debug</code>, <code>docusaurus-plugin-google-analytics</code>, <code>docusaurus-plugin-google-gtag</code>, <code>docusaurus-plugin-google-tag-manager</code>, <code>docusaurus-plugin-ideal-image</code>, <code>docusaurus-plugin-pwa</code>, <code>docusaurus-plugin-sitemap</code>, <code>docusaurus-preset-classic</code>, <code>docusaurus-theme-classic</code>, <code>docusaurus-theme-common</code>, <code>docusaurus-theme-live-codeblock</code>, <code>docusaurus-theme-mermaid</code>, <code>docusaurus-theme-search-algolia</code>, <code>docusaurus-types</code>, <code>docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/8961">#8961</a> feat: React 18 + automatic JSX runtime + build --dev (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9026">#9026</a> chore: remove facebook template (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-mdx-loader</code>, <code>docusaurus-migrate</code>, <code>docusaurus-plugin-content-blog</code>, <code>docusaurus-remark-plugin-npm2yarn</code>, <code>docusaurus-theme-classic</code>, <code>docusaurus-theme-common</code>, <code>docusaurus-theme-mermaid</code>, <code>docusaurus-types</code>, <code>docusaurus-utils-validation</code>, <code>docusaurus-utils</code>, <code>docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/8288">#8288</a> feat: upgrade to MDX v2 (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>docusaurus-plugin-content-docs</code>, <code>docusaurus-theme-classic</code>, <code>docusaurus-theme-common</code>, <code>docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/7966">#7966</a> fix(plugin-docs,theme): refactor docs plugin routes and component tree (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> </ul> <h4>:rocket: New Feature</h4> <ul> <li><code>create-docusaurus</code>, <code>docusaurus-mdx-loader</code>, <code>docusaurus-plugin-content-blog</code>, <code>docusaurus-remark-plugin-npm2yarn</code>, <code>docusaurus-theme-classic</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9451">#9451</a> feat(mdx-loader): upgrade to MDX v3 (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>docusaurus-mdx-loader</code>, <code>docusaurus-utils</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9394">#9394</a> feat(mdx-loader): Remark plugin to report unused MDX / Markdown directives (<a href="https://github.com/OzakIOne"><code>@OzakIOne</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-plugin-content-docs</code>, <code>docusaurus-plugin-ideal-image</code>, <code>docusaurus-types</code>, <code>docusaurus-utils</code>, <code>docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9317">#9317</a> feat(core): support TypeScript + ESM configuration (<a href="https://github.com/harryzcy"><code>@harryzcy</code></a>)</li> </ul> </li> <li><code>docusaurus-theme-common</code>, <code>docusaurus-theme-live-codeblock</code>, <code>docusaurus-theme-mermaid</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9305">#9305</a> feat(theme-mermaid): upgrade Mermaid to v10.4 - handle async rendering (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9241">#9241</a> feat: support bun package manager in <code>create-docusaurus</code> (<a href="https://github.com/colinhacks"><code>@colinhacks</code></a>)</li> </ul> </li> </ul>  </blockquote> <p>... (truncated)</p> </details> <details> <summary>Changelog</summary> <p><em>Sourced from <a href="https://github.com/facebook/docusaurus/blob/main/CHANGELOG.md"><code>@docusaurus/core</code>'s changelog</a>.</em></p> <blockquote> <h2>3.0.0 (2023-10-31)</h2> <h4>:boom: Breaking Change</h4> <ul> <li><code>create-docusaurus</code>, <code>docusaurus-mdx-loader</code>, <code>docusaurus-plugin-content-blog</code>, <code>docusaurus-remark-plugin-npm2yarn</code>, <code>docusaurus-theme-classic</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9451">#9451</a> feat(mdx-loader): upgrade to MDX v3 (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-plugin-content-docs</code>, <code>docusaurus-plugin-ideal-image</code>, <code>docusaurus-types</code>, <code>docusaurus-utils</code>, <code>docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9317">#9317</a> feat(core): support TypeScript + ESM configuration (<a href="https://github.com/harryzcy"><code>@harryzcy</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-theme-classic</code>, <code>docusaurus-theme-common</code>, <code>docusaurus-theme-live-codeblock</code>, <code>docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9316">#9316</a> chore: upgrade syntax highlighting dependencies, <code>prism-react-renderer</code> to v2, <code>react-live</code> to v4 (<a href="https://github.com/harryzcy"><code>@harryzcy</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-cssnano-preset</code>, <code>docusaurus-logger</code>, <code>docusaurus-mdx-loader</code>, <code>docusaurus-migrate</code>, <code>docusaurus-plugin-client-redirects</code>, <code>docusaurus-plugin-content-blog</code>, <code>docusaurus-plugin-content-docs</code>, <code>docusaurus-plugin-content-pages</code>, <code>docusaurus-plugin-debug</code>, <code>docusaurus-plugin-google-analytics</code>, <code>docusaurus-plugin-google-gtag</code>, <code>docusaurus-plugin-google-tag-manager</code>, <code>docusaurus-plugin-ideal-image</code>, <code>docusaurus-plugin-pwa</code>, <code>docusaurus-plugin-sitemap</code>, <code>docusaurus-preset-classic</code>, <code>docusaurus-remark-plugin-npm2yarn</code>, <code>docusaurus-theme-classic</code>, <code>docusaurus-theme-common</code>, <code>docusaurus-theme-live-codeblock</code>, <code>docusaurus-theme-mermaid</code>, <code>docusaurus-theme-search-algolia</code>, <code>docusaurus-theme-translations</code>, <code>docusaurus-utils-common</code>, <code>docusaurus-utils-validation</code>, <code>docusaurus-utils</code>, <code>docusaurus</code>, <code>eslint-plugin</code>, <code>lqip-loader</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9348">#9348</a> chore: update node engine version 18 (<a href="https://github.com/OzakIOne"><code>@OzakIOne</code></a>)</li> </ul> </li> <li><code>docusaurus-plugin-content-docs</code>, <code>docusaurus-theme-classic</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9310">#9310</a> chore(plugin-docs): remove legacy versioned prefix on doc ids and sidebar names in versioned sidebars (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>docusaurus-theme-classic</code>, <code>docusaurus-theme-translations</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9308">#9308</a> fix(theme): make warning a first-class admonition, and deprecate caution admonition (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>docusaurus-theme-common</code>, <code>docusaurus-theme-live-codeblock</code>, <code>docusaurus-theme-mermaid</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9305">#9305</a> feat(theme-mermaid): upgrade Mermaid to v10.4 - handle async rendering (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-plugin-content-docs</code>, <code>docusaurus-plugin-debug</code>, <code>docusaurus-plugin-google-analytics</code>, <code>docusaurus-plugin-google-gtag</code>, <code>docusaurus-plugin-google-tag-manager</code>, <code>docusaurus-plugin-ideal-image</code>, <code>docusaurus-plugin-pwa</code>, <code>docusaurus-theme-classic</code>, <code>docusaurus-theme-common</code>, <code>docusaurus-theme-live-codeblock</code>, <code>docusaurus-theme-mermaid</code>, <code>docusaurus-theme-search-algolia</code>, <code>docusaurus-tsconfig</code>, <code>docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9258">#9258</a> feat: Docusaurus v3 upgrades and require TypeScript 5 (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>docusaurus-plugin-content-blog</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9189">#9189</a> feat(blog-plugin): limit option for blog feedOptions (<a href="https://github.com/johnnyreilly"><code>@johnnyreilly</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-tsconfig</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9050">#9050</a> feat: create official TypeScript base config <code>@docusaurus/tsconfig</code> (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-mdx-loader</code>, <code>docusaurus-module-type-aliases</code>, <code>docusaurus-plugin-client-redirects</code>, <code>docusaurus-plugin-content-blog</code>, <code>docusaurus-plugin-content-docs</code>, <code>docusaurus-plugin-content-pages</code>, <code>docusaurus-plugin-debug</code>, <code>docusaurus-plugin-google-analytics</code>, <code>docusaurus-plugin-google-gtag</code>, <code>docusaurus-plugin-google-tag-manager</code>, <code>docusaurus-plugin-ideal-image</code>, <code>docusaurus-plugin-pwa</code>, <code>docusaurus-plugin-sitemap</code>, <code>docusaurus-preset-classic</code>, <code>docusaurus-theme-classic</code>, <code>docusaurus-theme-common</code>, <code>docusaurus-theme-live-codeblock</code>, <code>docusaurus-theme-mermaid</code>, <code>docusaurus-theme-search-algolia</code>, <code>docusaurus-types</code>, <code>docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/8961">#8961</a> feat: React 18 + automatic JSX runtime + build --dev (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9026">#9026</a> chore: remove facebook template (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-mdx-loader</code>, <code>docusaurus-migrate</code>, <code>docusaurus-plugin-content-blog</code>, <code>docusaurus-remark-plugin-npm2yarn</code>, <code>docusaurus-theme-classic</code>, <code>docusaurus-theme-common</code>, <code>docusaurus-theme-mermaid</code>, <code>docusaurus-types</code>, <code>docusaurus-utils-validation</code>, <code>docusaurus-utils</code>, <code>docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/8288">#8288</a> feat: upgrade to MDX v2 (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>docusaurus-plugin-content-docs</code>, <code>docusaurus-theme-classic</code>, <code>docusaurus-theme-common</code>, <code>docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/7966">#7966</a> fix(plugin-docs,theme): refactor docs plugin routes and component tree (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> </ul> <h4>:rocket: New Feature</h4> <ul> <li><code>create-docusaurus</code>, <code>docusaurus-mdx-loader</code>, <code>docusaurus-plugin-content-blog</code>, <code>docusaurus-remark-plugin-npm2yarn</code>, <code>docusaurus-theme-classic</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9451">#9451</a> feat(mdx-loader): upgrade to MDX v3 (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>docusaurus-mdx-loader</code>, <code>docusaurus-utils</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9394">#9394</a> feat(mdx-loader): Remark plugin to report unused MDX / Markdown directives (<a href="https://github.com/OzakIOne"><code>@OzakIOne</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-plugin-content-docs</code>, <code>docusaurus-plugin-ideal-image</code>, <code>docusaurus-types</code>, <code>docusaurus-utils</code>, <code>docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9317">#9317</a> feat(core): support TypeScript + ESM configuration (<a href="https://github.com/harryzcy"><code>@harryzcy</code></a>)</li> </ul> </li> <li><code>docusaurus-theme-common</code>, <code>docusaurus-theme-live-codeblock</code>, <code>docusaurus-theme-mermaid</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9305">#9305</a> feat(theme-mermaid): upgrade Mermaid to v10.4 - handle async rendering (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9241">#9241</a> feat: support bun package manager in <code>create-docusaurus</code> (<a href="https://github.com/colinhacks"><code>@colinhacks</code></a>)</li> </ul> </li> <li><code>docusaurus-plugin-content-blog</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9189">#9189</a> feat(blog-plugin): limit option for blog feedOptions (<a href="https://github.com/johnnyreilly"><code>@johnnyreilly</code></a>)</li> </ul> </li> <li><code>docusaurus-theme-classic</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9152">#9152</a> feat(theme): add support for meta og locale and alternates (<a href="https://github.com/FlorinaPacurar"><code>@FlorinaPacurar</code></a>)</li> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9028">#9028</a> feat(theme): add ability to inject data attributes from query-string - possibility to create an iframe/embed variant of a page (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> </ul>  </blockquote> <p>... (truncated)</p> </details> <details> <summary>Commits</summary> <ul> <li><a href="https://github.com/facebook/docusaurus/commit/ca8b4638c47119d38838656c4a11ee3a5e7ba6f2"><code>ca8b463</code></a> v3.0.0</li> <li><a href="https://github.com/facebook/docusaurus/commit/495c7936b605e6b8881f000d23a8463a9d6d850c"><code>495c793</code></a> chore: v3.0.0-rc.1 release (<a href="https://github.com/facebook/docusaurus/tree/HEAD/packages/docusaurus/issues/9453">#9453</a>)</li> <li><a href="https://github.com/facebook/docusaurus/commit/7ee2f75ce1e645f75ae42b9f2f7f76cfc45b1743"><code>7ee2f75</code></a> chore: v3.0.0-rc.0 release (<a href="https://github.com/facebook/docusaurus/tree/HEAD/packages/docusaurus/issues/9418">#9418</a>)</li> <li><a href="https://github.com/facebook/docusaurus/commit/45f1a669b5ab29a04365f20e88e37e085c0fb4de"><code>45f1a66</code></a> feat(core): support TypeScript + ESM configuration (<a href="https://github.com/facebook/docusaurus/tree/HEAD/packages/docusaurus/issues/9317">#9317</a>)</li> <li><a href="https://github.com/facebook/docusaurus/commit/643a7fe5a325dacfd1d809a1f40a9688e9634fa7"><code>643a7fe</code></a> fix(core): log missing errorInfo in React 18 onRecoverableError callback (<a href="https://github.com/facebook/docusaurus/tree/HEAD/packages/docusaurus/issues/9387">#9387</a>)</li> <li><a href="https://github.com/facebook/docusaurus/commit/1319996083a2becf38967a99f6db290c1d5c99cb"><code>1319996</code></a> feat(core): throw error when official docusaurus dependencies use different v...</li> <li><a href="https://github.com/facebook/docusaurus/commit/dceaae41d7f3fc148a2d2240a3c89e0e9c22aa4c"><code>dceaae4</code></a> chore: upgrade syntax highlighting dependencies, <code>prism-react-renderer</code> to v2...</li> <li><a href="https://github.com/facebook/docusaurus/commit/bde9cfd84d99ea1ca8fc59bf51f9d4001d6527f2"><code>bde9cfd</code></a> chore: update node engine version 18 (<a href="https://github.com/facebook/docusaurus/tree/HEAD/packages/docusaurus/issues/9348">#9348</a>)</li> <li><a href="https://github.com/facebook/docusaurus/commit/52d79c4e0cf8876903aa079cf8cbcd46f265505a"><code>52d79c4</code></a> chore: v3.0.0-beta.0 release (<a href="https://github.com/facebook/docusaurus/tree/HEAD/packages/docusaurus/issues/9311">#9311</a>)</li> <li><a href="https://github.com/facebook/docusaurus/commit/6e8e276e406e24c46bf34385dd47ebd2e44bc152"><code>6e8e276</code></a> fix(cli): disable vertical borders of the update notification (<a href="https://github.com/facebook/docusaurus/tree/HEAD/packages/docusaurus/issues/9309">#9309</a>)</li> <li>Additional commits viewable in <a href="https://github.com/facebook/docusaurus/commits/v3.0.0/packages/docusaurus">compare view</a></li> </ul> </details> <br /> Updates `@docusaurus/preset-classic` from 2.4.0 to 3.0.0 <details> <summary>Release notes</summary> <p><em>Sourced from <a href="https://github.com/facebook/docusaurus/releases"><code>@docusaurus/preset-classic</code>'s releases</a>.</em></p> <blockquote> <h2>3.0.0 (2023-10-31)</h2> <ul> <li>GitHub PR: <a href="https://redirect.github.com/facebook/docusaurus/pull/9478">facebook/docusaurus#9478</a></li> <li>GitHub release notes: <a href="https://github.com/facebook/docusaurus/releases/tag/v3.0.0">https://github.com/facebook/docusaurus/releases/tag/v3.0.0</a></li> <li>GitHub release discussion: <a href="https://github.com/facebook/docusaurus/discussions/9481">https://github.com/facebook/docusaurus/discussions/9481</a></li> <li>Upgrade guide: <a href="https://docusaurus.io/docs/migration/v3">docusaurus.io/docs/migration/v3</a></li> </ul> <h4>:boom: Breaking Change</h4> <ul> <li><code>create-docusaurus</code>, <code>docusaurus-mdx-loader</code>, <code>docusaurus-plugin-content-blog</code>, <code>docusaurus-remark-plugin-npm2yarn</code>, <code>docusaurus-theme-classic</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9451">#9451</a> feat(mdx-loader): upgrade to MDX v3 (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-plugin-content-docs</code>, <code>docusaurus-plugin-ideal-image</code>, <code>docusaurus-types</code>, <code>docusaurus-utils</code>, <code>docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9317">#9317</a> feat(core): support TypeScript + ESM configuration (<a href="https://github.com/harryzcy"><code>@harryzcy</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-theme-classic</code>, <code>docusaurus-theme-common</code>, <code>docusaurus-theme-live-codeblock</code>, <code>docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9316">#9316</a> chore: upgrade syntax highlighting dependencies, <code>prism-react-renderer</code> to v2, <code>react-live</code> to v4 (<a href="https://github.com/harryzcy"><code>@harryzcy</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-cssnano-preset</code>, <code>docusaurus-logger</code>, <code>docusaurus-mdx-loader</code>, <code>docusaurus-migrate</code>, <code>docusaurus-plugin-client-redirects</code>, <code>docusaurus-plugin-content-blog</code>, <code>docusaurus-plugin-content-docs</code>, <code>docusaurus-plugin-content-pages</code>, <code>docusaurus-plugin-debug</code>, <code>docusaurus-plugin-google-analytics</code>, <code>docusaurus-plugin-google-gtag</code>, <code>docusaurus-plugin-google-tag-manager</code>, <code>docusaurus-plugin-ideal-image</code>, <code>docusaurus-plugin-pwa</code>, <code>docusaurus-plugin-sitemap</code>, <code>docusaurus-preset-classic</code>, <code>docusaurus-remark-plugin-npm2yarn</code>, <code>docusaurus-theme-classic</code>, <code>docusaurus-theme-common</code>, <code>docusaurus-theme-live-codeblock</code>, <code>docusaurus-theme-mermaid</code>, <code>docusaurus-theme-search-algolia</code>, <code>docusaurus-theme-translations</code>, <code>docusaurus-utils-common</code>, <code>docusaurus-utils-validation</code>, <code>docusaurus-utils</code>, <code>docusaurus</code>, <code>eslint-plugin</code>, <code>lqip-loader</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9348">#9348</a> chore: update node engine version 18 (<a href="https://github.com/OzakIOne"><code>@OzakIOne</code></a>)</li> </ul> </li> <li><code>docusaurus-plugin-content-docs</code>, <code>docusaurus-theme-classic</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9310">#9310</a> chore(plugin-docs): remove legacy versioned prefix on doc ids and sidebar names in versioned sidebars (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>docusaurus-theme-classic</code>, <code>docusaurus-theme-translations</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9308">#9308</a> fix(theme): make warning a first-class admonition, and deprecate caution admonition (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>docusaurus-theme-common</code>, <code>docusaurus-theme-live-codeblock</code>, <code>docusaurus-theme-mermaid</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9305">#9305</a> feat(theme-mermaid): upgrade Mermaid to v10.4 - handle async rendering (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-plugin-content-docs</code>, <code>docusaurus-plugin-debug</code>, <code>docusaurus-plugin-google-analytics</code>, <code>docusaurus-plugin-google-gtag</code>, <code>docusaurus-plugin-google-tag-manager</code>, <code>docusaurus-plugin-ideal-image</code>, <code>docusaurus-plugin-pwa</code>, <code>docusaurus-theme-classic</code>, <code>docusaurus-theme-common</code>, <code>docusaurus-theme-live-codeblock</code>, <code>docusaurus-theme-mermaid</code>, <code>docusaurus-theme-search-algolia</code>, <code>docusaurus-tsconfig</code>, <code>docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9258">#9258</a> feat: Docusaurus v3 upgrades and require TypeScript 5 (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>docusaurus-plugin-content-blog</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9189">#9189</a> feat(blog-plugin): limit option for blog feedOptions (<a href="https://github.com/johnnyreilly"><code>@johnnyreilly</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-tsconfig</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9050">#9050</a> feat: create official TypeScript base config <code>@docusaurus/tsconfig</code> (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-mdx-loader</code>, <code>docusaurus-module-type-aliases</code>, <code>docusaurus-plugin-client-redirects</code>, <code>docusaurus-plugin-content-blog</code>, <code>docusaurus-plugin-content-docs</code>, <code>docusaurus-plugin-content-pages</code>, <code>docusaurus-plugin-debug</code>, <code>docusaurus-plugin-google-analytics</code>, <code>docusaurus-plugin-google-gtag</code>, <code>docusaurus-plugin-google-tag-manager</code>, <code>docusaurus-plugin-ideal-image</code>, <code>docusaurus-plugin-pwa</code>, <code>docusaurus-plugin-sitemap</code>, <code>docusaurus-preset-classic</code>, <code>docusaurus-theme-classic</code>, <code>docusaurus-theme-common</code>, <code>docusaurus-theme-live-codeblock</code>, <code>docusaurus-theme-mermaid</code>, <code>docusaurus-theme-search-algolia</code>, <code>docusaurus-types</code>, <code>docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/8961">#8961</a> feat: React 18 + automatic JSX runtime + build --dev (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9026">#9026</a> chore: remove facebook template (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-mdx-loader</code>, <code>docusaurus-migrate</code>, <code>docusaurus-plugin-content-blog</code>, <code>docusaurus-remark-plugin-npm2yarn</code>, <code>docusaurus-theme-classic</code>, <code>docusaurus-theme-common</code>, <code>docusaurus-theme-mermaid</code>, <code>docusaurus-types</code>, <code>docusaurus-utils-validation</code>, <code>docusaurus-utils</code>, <code>docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/8288">#8288</a> feat: upgrade to MDX v2 (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>docusaurus-plugin-content-docs</code>, <code>docusaurus-theme-classic</code>, <code>docusaurus-theme-common</code>, <code>docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/7966">#7966</a> fix(plugin-docs,theme): refactor docs plugin routes and component tree (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> </ul> <h4>:rocket: New Feature</h4> <ul> <li><code>create-docusaurus</code>, <code>docusaurus-mdx-loader</code>, <code>docusaurus-plugin-content-blog</code>, <code>docusaurus-remark-plugin-npm2yarn</code>, <code>docusaurus-theme-classic</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9451">#9451</a> feat(mdx-loader): upgrade to MDX v3 (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>docusaurus-mdx-loader</code>, <code>docusaurus-utils</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9394">#9394</a> feat(mdx-loader): Remark plugin to report unused MDX / Markdown directives (<a href="https://github.com/OzakIOne"><code>@OzakIOne</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-plugin-content-docs</code>, <code>docusaurus-plugin-ideal-image</code>, <code>docusaurus-types</code>, <code>docusaurus-utils</code>, <code>docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9317">#9317</a> feat(core): support TypeScript + ESM configuration (<a href="https://github.com/harryzcy"><code>@harryzcy</code></a>)</li> </ul> </li> <li><code>docusaurus-theme-common</code>, <code>docusaurus-theme-live-codeblock</code>, <code>docusaurus-theme-mermaid</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9305">#9305</a> feat(theme-mermaid): upgrade Mermaid to v10.4 - handle async rendering (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9241">#9241</a> feat: support bun package manager in <code>create-docusaurus</code> (<a href="https://github.com/colinhacks"><code>@colinhacks</code></a>)</li> </ul> </li> </ul>  </blockquote> <p>... (truncated)</p> </details> <details> <summary>Changelog</summary> <p><em>Sourced from <a href="https://github.com/facebook/docusaurus/blob/main/CHANGELOG.md"><code>@docusaurus/preset-classic</code>'s changelog</a>.</em></p> <blockquote> <h2>3.0.0 (2023-10-31)</h2> <h4>:boom: Breaking Change</h4> <ul> <li><code>create-docusaurus</code>, <code>docusaurus-mdx-loader</code>, <code>docusaurus-plugin-content-blog</code>, <code>docusaurus-remark-plugin-npm2yarn</code>, <code>docusaurus-theme-classic</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9451">#9451</a> feat(mdx-loader): upgrade to MDX v3 (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-plugin-content-docs</code>, <code>docusaurus-plugin-ideal-image</code>, <code>docusaurus-types</code>, <code>docusaurus-utils</code>, <code>docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9317">#9317</a> feat(core): support TypeScript + ESM configuration (<a href="https://github.com/harryzcy"><code>@harryzcy</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-theme-classic</code>, <code>docusaurus-theme-common</code>, <code>docusaurus-theme-live-codeblock</code>, <code>docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9316">#9316</a> chore: upgrade syntax highlighting dependencies, <code>prism-react-renderer</code> to v2, <code>react-live</code> to v4 (<a href="https://github.com/harryzcy"><code>@harryzcy</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-cssnano-preset</code>, <code>docusaurus-logger</code>, <code>docusaurus-mdx-loader</code>, <code>docusaurus-migrate</code>, <code>docusaurus-plugin-client-redirects</code>, <code>docusaurus-plugin-content-blog</code>, <code>docusaurus-plugin-content-docs</code>, <code>docusaurus-plugin-content-pages</code>, <code>docusaurus-plugin-debug</code>, <code>docusaurus-plugin-google-analytics</code>, <code>docusaurus-plugin-google-gtag</code>, <code>docusaurus-plugin-google-tag-manager</code>, <code>docusaurus-plugin-ideal-image</code>, <code>docusaurus-plugin-pwa</code>, <code>docusaurus-plugin-sitemap</code>, <code>docusaurus-preset-classic</code>, <code>docusaurus-remark-plugin-npm2yarn</code>, <code>docusaurus-theme-classic</code>, <code>docusaurus-theme-common</code>, <code>docusaurus-theme-live-codeblock</code>, <code>docusaurus-theme-mermaid</code>, <code>docusaurus-theme-search-algolia</code>, <code>docusaurus-theme-translations</code>, <code>docusaurus-utils-common</code>, <code>docusaurus-utils-validation</code>, <code>docusaurus-utils</code>, <code>docusaurus</code>, <code>eslint-plugin</code>, <code>lqip-loader</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9348">#9348</a> chore: update node engine version 18 (<a href="https://github.com/OzakIOne"><code>@OzakIOne</code></a>)</li> </ul> </li> <li><code>docusaurus-plugin-content-docs</code>, <code>docusaurus-theme-classic</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9310">#9310</a> chore(plugin-docs): remove legacy versioned prefix on doc ids and sidebar names in versioned sidebars (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>docusaurus-theme-classic</code>, <code>docusaurus-theme-translations</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9308">#9308</a> fix(theme): make warning a first-class admonition, and deprecate caution admonition (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>docusaurus-theme-common</code>, <code>docusaurus-theme-live-codeblock</code>, <code>docusaurus-theme-mermaid</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9305">#9305</a> feat(theme-mermaid): upgrade Mermaid to v10.4 - handle async rendering (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-plugin-content-docs</code>, <code>docusaurus-plugin-debug</code>, <code>docusaurus-plugin-google-analytics</code>, <code>docusaurus-plugin-google-gtag</code>, <code>docusaurus-plugin-google-tag-manager</code>, <code>docusaurus-plugin-ideal-image</code>, <code>docusaurus-plugin-pwa</code>, <code>docusaurus-theme-classic</code>, <code>docusaurus-theme-common</code>, <code>docusaurus-theme-live-codeblock</code>, <code>docusaurus-theme-mermaid</code>, <code>docusaurus-theme-search-algolia</code>, <code>docusaurus-tsconfig</code>, <code>docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9258">#9258</a> feat: Docusaurus v3 upgrades and require TypeScript 5 (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>docusaurus-plugin-content-blog</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9189">#9189</a> feat(blog-plugin): limit option for blog feedOptions (<a href="https://github.com/johnnyreilly"><code>@johnnyreilly</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-tsconfig</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9050">#9050</a> feat: create official TypeScript base config <code>@docusaurus/tsconfig</code> (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-mdx-loader</code>, <code>docusaurus-module-type-aliases</code>, <code>docusaurus-plugin-client-redirects</code>, <code>docusaurus-plugin-content-blog</code>, <code>docusaurus-plugin-content-docs</code>, <code>docusaurus-plugin-content-pages</code>, <code>docusaurus-plugin-debug</code>, <code>docusaurus-plugin-google-analytics</code>, <code>docusaurus-plugin-google-gtag</code>, <code>docusaurus-plugin-google-tag-manager</code>, <code>docusaurus-plugin-ideal-image</code>, <code>docusaurus-plugin-pwa</code>, <code>docusaurus-plugin-sitemap</code>, <code>docusaurus-preset-classic</code>, <code>docusaurus-theme-classic</code>, <code>docusaurus-theme-common</code>, <code>docusaurus-theme-live-codeblock</code>, <code>docusaurus-theme-mermaid</code>, <code>docusaurus-theme-search-algolia</code>, <code>docusaurus-types</code>, <code>docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/8961">#8961</a> feat: React 18 + automatic JSX runtime + build --dev (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9026">#9026</a> chore: remove facebook template (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-mdx-loader</code>, <code>docusaurus-migrate</code>, <code>docusaurus-plugin-content-blog</code>, <code>docusaurus-remark-plugin-npm2yarn</code>, <code>docusaurus-theme-classic</code>, <code>docusaurus-theme-common</code>, <code>docusaurus-theme-mermaid</code>, <code>docusaurus-types</code>, <code>docusaurus-utils-validation</code>, <code>docusaurus-utils</code>, <code>docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/8288">#8288</a> feat: upgrade to MDX v2 (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>docusaurus-plugin-content-docs</code>, <code>docusaurus-theme-classic</code>, <code>docusaurus-theme-common</code>, <code>docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/7966">#7966</a> fix(plugin-docs,theme): refactor docs plugin routes and component tree (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> </ul> <h4>:rocket: New Feature</h4> <ul> <li><code>create-docusaurus</code>, <code>docusaurus-mdx-loader</code>, <code>docusaurus-plugin-content-blog</code>, <code>docusaurus-remark-plugin-npm2yarn</code>, <code>docusaurus-theme-classic</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9451">#9451</a> feat(mdx-loader): upgrade to MDX v3 (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>docusaurus-mdx-loader</code>, <code>docusaurus-utils</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9394">#9394</a> feat(mdx-loader): Remark plugin to report unused MDX / Markdown directives (<a href="https://github.com/OzakIOne"><code>@OzakIOne</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code>, <code>docusaurus-plugin-content-docs</code>, <code>docusaurus-plugin-ideal-image</code>, <code>docusaurus-types</code>, <code>docusaurus-utils</code>, <code>docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9317">#9317</a> feat(core): support TypeScript + ESM configuration (<a href="https://github.com/harryzcy"><code>@harryzcy</code></a>)</li> </ul> </li> <li><code>docusaurus-theme-common</code>, <code>docusaurus-theme-live-codeblock</code>, <code>docusaurus-theme-mermaid</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9305">#9305</a> feat(theme-mermaid): upgrade Mermaid to v10.4 - handle async rendering (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> <li><code>create-docusaurus</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9241">#9241</a> feat: support bun package manager in <code>create-docusaurus</code> (<a href="https://github.com/colinhacks"><code>@colinhacks</code></a>)</li> </ul> </li> <li><code>docusaurus-plugin-content-blog</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9189">#9189</a> feat(blog-plugin): limit option for blog feedOptions (<a href="https://github.com/johnnyreilly"><code>@johnnyreilly</code></a>)</li> </ul> </li> <li><code>docusaurus-theme-classic</code> <ul> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9152">#9152</a> feat(theme): add support for meta og locale and alternates (<a href="https://github.com/FlorinaPacurar"><code>@FlorinaPacurar</code></a>)</li> <li><a href="https://redirect.github.com/facebook/docusaurus/pull/9028">#9028</a> feat(theme): add ability to inject data attributes from query-string - possibility to create an iframe/embed variant of a page (<a href="https://github.com/slorber"><code>@slorber</code></a>)</li> </ul> </li> </ul>  </blockquote> <p>... (truncated)</p> </details> <details> <summary>Commits</summary> <ul> <li><a href="https://github.com/facebook/docusaurus/commit/ca8b4638c47119d38838656c4a11ee3a5e7ba6f2"><code>ca8b463</code></a> v3.0.0</li> <li><a href="https://github.com/facebook/docusaurus/commit/495c7936b605e6b8881f000d23a8463a9d6d850c"><code>495c793</code></a> chore: v3.0.0-rc.1 release (<a href="https://github.com/facebook/docusaurus/tree/HEAD/packages/docusaurus-preset-classic/issues/9453">#9453</a>)</li> <li><a href="https://github.com/facebook/docusaurus/commit/7ee2f75ce1e645f75ae42b9f2f7f76cfc45b1743"><code>7ee2f75</code></a> chore: v3.0.0-rc.0 release (<a href="https://github.com/facebook/docusaurus/tree/HEAD/packages/docusaurus-preset-classic/issues/9418">#9418</a>)</li> <li><a href="https://github.com/facebook/docusaurus/commit/bde9cfd84d99ea1ca8fc59bf51f9d4001d6527f2"><code>bde9cfd</code></a> chore: update node engine version 18 (<a href="https://github.com/facebook/docusaurus/tree/HEAD/packages/docusaurus-preset-classic/issues/9348">#9348</a>)</li> <li><a href="https://github.com/facebook/docusaurus/commit/52d79c4e0cf8876903aa079cf8cbcd46f265505a"><code>52d79c4</code></a> chore: v3.0.0-beta.0 release (<a href="https://github.com/facebook/docusaurus/tree/HEAD/packages/docusaurus-preset-classic/issues/9311">#9311</a>)</li> <li><a href="https://github.com/facebook/docusaurus/commit/7d033cc8c08e0c8fd57baff7390540def6eb6046"><code>7d033cc</code></a> chore: v3.0.0-alpha.0 release (<a href="https://github.com/facebook/docusaurus/tree/HEAD/packages/docusaurus-preset-classic/issues/9072">#9072</a>)</li> <li><a href="https://github.com/facebook/docusaurus/commit/187e5aa218e764b06dcbbb50f22ced72159a8532"><code>187e5aa</code></a> feat: React 18 + automatic JSX runtime + build --dev (<a href="https://github.com/facebook/docusaurus/tree/HEAD/packages/docusaurus-preset-classic/issues/8961">#8961</a>)</li> <li><a href="https://github.com/facebook/docusaurus/commit/0425917a50aae78cebd3ec9501ff85411b3bd13e"><code>0425917</code></a> fix(preset-classic): install the right plugin for googleTagManager (<a href="https://github.com/facebook/docusaurus/tree/HEAD/packages/docusaurus-preset-classic/issues/8597">#8597</a>)</li> <li><a href="https://github.com/facebook/docusaurus/commit/428af8af5ebb8dbcd619a12f5da524143130331c"><code>428af8a</code></a> feat(plugin-google-tag-manager): add new google-tag-manager plugin + deprecat...</li> <li><a href="https://github.com/facebook/docusaurus/commit/c4f808aba8fd5d9e3c8bd9d9c02d0f9a7cb26d2c"><code>c4f808a</code></a> fix(preset-classic): broken link in "unrecognized keys" error message (<a href="https://github.com/facebook/docusaurus/tree/HEAD/packages/docusaurus-preset-classic/issues/8029">#8029</a>)</li> <li>Additional commits viewable in <a href="https://github.com/facebook/docusaurus/commits/v3.0.0/packages/docusaurus-preset-classic">compare view</a></li> </ul> </details> <br /> Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting `@dependabot rebase`. [//]: # (dependabot-automerge-start) [//]: # (dependabot-automerge-end) --- <details> <summary>Dependabot commands and options</summary> <br /> You can trigger Dependabot actions by commenting on this PR: - `@dependabot rebase` will rebase this PR - `@dependabot recreate` will recreate this PR, overwriting any edits that have been made to it - `@dependabot merge` will merge this PR after your CI passes on it - `@dependabot squash and merge` will squash and merge this PR after your CI passes on it - `@dependabot cancel merge` will cancel a previously requested merge and block automerging - `@dependabot reopen` will reopen this PR if it is closed - `@dependabot close` will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually - `@dependabot show <dependency name> ignore conditions` will show all of the ignore conditions of the specified dependency - `@dependabot ignore this major version` will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself) - `@dependabot ignore this minor version` will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself) - `@dependabot ignore this dependency` will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself) You can disable automated security fix PRs for this repo from the [Security Alerts page](https://github.com/langchain-ai/langchain/network/alerts). </details>

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APIChain add restrictions to domains (CVE-2023-32786)

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2023-11-01T21:37:28

2023-11-01T22:50:36

2023-11-01T22:50:35

COLLABORATOR

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* Restrict the chain to specific domains by default * This is a breaking change, but it will fail loudly upon object instantiation -- so there should be no silent errors for users * Resolves CVE-2023-32786

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Demo Server, Fix Timescale

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2023-11-01T21:30:05

2023-11-01T22:29:35

2023-11-01T22:29:34

COLLABORATOR

null

- improve demo server - missing deps

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1,973,112,630

I_kwDOIPDwls51m082

12,745

[Extraction template] Query decomposition + routing

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2023-11-01T21:05:55

2023-11-01T21:18:55

null

COLLABORATOR

null

### Feature request Template that show routing across N datastores ### Motivation Reasoning about [where to fetch information (https://python.langchain.com/docs/expression_language/how_to/routing) from a natural language query is important for retrieval across data sources. ### Your contribution Add template

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1,973,104,857

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12,744

[Fine tuning template] Fine-tune LLM

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2023-11-01T21:00:11

2023-11-01T21:02:19

null

COLLABORATOR

null

### Feature request Add template to simplify fine-tuning ### Motivation [LLM fine-tuning](https://blog.langchain.dev/using-langsmith-to-support-fine-tuning-of-open-source-llms/) can improve task-specific performance ### Your contribution Add template

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1,973,100,842

I_kwDOIPDwls51myEq

12,743

[Fine tuning template] Fine-tune embedding model

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2023-11-01T20:57:07

2023-11-01T21:27:08

null

COLLABORATOR

null

### Feature request Set up template to simplify fine-tuning of embedding models. ### Motivation [Fine-tuning](https://blog.langchain.dev/using-langsmith-to-support-fine-tuning-of-open-source-llms/) of embedding models can improve RAG. ### Your contribution Add template

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1,973,096,837

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12,742

[Evaluation template] Runs evaluation against LangSmith (public) dataset

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2023-11-01T20:53:55

2023-11-01T20:56:03

null

COLLABORATOR

null

### Feature request Given a runnable (e.g., RAG pipeline) automatically run eval against a given (public) dataset ### Motivation Made evaluation simple by abstracting w/ a template and passing in only a runnable. (Template can be called as RemoteRunnable.) Benchmark your runnable on an existing public LangSmith dataset. Will differ depending on the use-case / dataset of choice. ### Your contribution Add template

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1,973,076,333

I_kwDOIPDwls51msFt

12,741

[Data generation template] Synthetic QA pairs from input document

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2023-11-01T20:40:08

2023-11-01T20:50:22

null

COLLABORATOR

null

### Feature request Synthetic dataset generation and extraction (to JSON or similar) ### Motivation Datasets (for eval or fine-tuning) are challenging to generate. Some prompts have used LLMs to [generate](https://smith.langchain.com/hub/homanp/question-answer-pair?ref=blog.langchain.dev&organizationId=1fa8b1f4-fcb9-4072-9aa9-983e35ad61b8) them. ### Your contribution Add template

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1,973,071,476

I_kwDOIPDwls51mq50

12,740

[Summarization template] Audio

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1

2023-11-01T20:36:18

2024-01-09T07:55:36

null

COLLABORATOR

null

### Feature request Summarization on audio content (podcasts, YT videos, lectures) would be useful. ### Motivation Prior work by [AssemblyAI](https://github.com/AssemblyAI/youtube-tutorials/blob/main/podcast-summary-app/podcasts.py) has focused on this. ### Your contribution Add template

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1,973,068,176

I_kwDOIPDwls51mqGQ

12,739

[Extraction template] NER

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2023-11-01T20:33:54

2024-01-12T02:27:37

null

COLLABORATOR

null

### Feature request Name Entity Recognition is the process of identifying and classifying named entities (like people, organizations, dates, and locations) in text. ### Motivation NER is useful in various areas: 1. Information Retrieval: Helps in improving the efficiency of search engines. For example, if someone searches for "Apple," understanding whether they mean the fruit or the tech company can be crucial. 2. Content Recommendation: For news or media agencies, knowing what entities are mentioned in articles can help in recommending related content to users. 3. Data Mining: For extracting structured information from unstructured datasets. 4. Question Answering: Helps chatbots and virtual assistants understand and respond to user queries more accurately. 5. Knowledge Graph Construction: Crucial for building structured databases of information extracted from text. ### Your contribution Add template

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1,973,055,694

I_kwDOIPDwls51mnDO

12,738

[Agent template] Local / oss agent

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2023-11-01T20:24:36

2023-11-01T20:26:47

null

COLLABORATOR

null

### Feature request Use oss LLM w/ agent (e.g., [Zephyr](https://huggingface.co/HuggingFaceH4/zephyr-7b-alpha)) ### Motivation See notes [here](https://blog.llamaindex.ai/dumber-llm-agents-need-more-constraints-and-better-tools-17a524c59e12), [here](https://betterprogramming.pub/exploring-react-agent-for-better-prompting-in-rag-pipeline-b231aae0ca7c), [here](https://www.pinecone.io/learn/series/langchain/langchain-agents/) on use-cases that admit well to oss LLM agents. ### Your contribution Add template

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1,973,045,358

I_kwDOIPDwls51mkhu

12,737

[Query construction template] Semantic + SQL with pgvector

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2023-11-01T20:16:56

2023-11-01T20:19:05

null

COLLABORATOR

null

### Feature request SQL + semantic searching w/ pgvector ### Motivation Follow the format of [this cookbook](https://github.com/langchain-ai/langchain/pull/12365/files) to enable unified SQL + semantic search (on a column with embeddings). ### Your contribution Template

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1,973,043,278

PR_kwDOIPDwls5eXqxT

12,736

template updates

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1

2023-11-01T20:15:28

2023-11-01T20:53:27

COLLABORATOR

null

- langchain license - add timescale vector dep to that template

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1,973,027,411

I_kwDOIPDwls51mgJT

12,735

[Extraction template] Tables from unstructured text

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open

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null

0

2023-11-01T20:04:17

2023-11-01T20:06:25

null

COLLABORATOR

null

### Feature request Extraction a structured (e.g., csv, pandas DF, etc) table from unstructured text ### Motivation LLMs can infer table structure from text input. A template that performs this and output a dataq (e.g., csv, pandas DF, etc) object would be useful. ### Your contribution Add template

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1,973,023,622

I_kwDOIPDwls51mfOG

12,734

[Tagging template] Support ticket classification

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2

2023-11-01T20:01:25

2023-12-07T20:24:09

null

COLLABORATOR

null

### Feature request Tagging using (local LLM or API) for categorizing support tickets ### Motivation Support ticket classification ### Your contribution Add template

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1,973,010,897

PR_kwDOIPDwls5eXjtx

12,733

Use jinja2 sandboxing by default

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1

2023-11-01T19:51:55

2023-11-01T21:54:02

COLLABORATOR

null

* This is an opt-in feature, so users should be aware of risks if using jinja2. * Regardless we'll add sandboxing by default to jinja2 templates -- this sandboxing is a best effort basis. * Best strategy is still to make sure that jinja2 templates are only loaded from trusted sources.

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1,973,001,832

I_kwDOIPDwls51mZ5o

12,732

[RAG template] Multi-modal

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null

1

2023-11-01T19:47:42

2023-11-02T16:22:24

null

COLLABORATOR

null

### Feature request Template that features multi-modal RAG ### Motivation * [Unstructured for document processing](https://github.com/langchain-ai/langchain/blob/master/cookbook/Semi_structured_and_multi_modal_RAG.ipynb) * Multimodal embeddings * Showcase vectorstore(s) that support img+text * Multi-modal LLM for answer synthesis ### Your contribution Multi-modal RAG

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PR_kwDOIPDwls5eXeFX

12,731

enable the device_map parameter in huggingface pipeline

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2023-11-01T19:40:22

2023-12-22T05:43:28

2023-11-02T21:29:07

CONTRIBUTOR

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### Enabling `device_map` in HuggingFacePipeline For multi-gpu settings with large models, the [accelerate](https://huggingface.co/docs/accelerate/usage_guides/big_modeling#using--accelerate) library provides the `device_map` parameter to automatically distribute the model across GPUs / disk. The [Transformers pipeline](https://github.com/huggingface/transformers/blob/3520e37e86913715959ff14fef76340010c8de57/src/transformers/pipelines/__init__.py#L543) enables users to specify `device` (or) `device_map`, and handles cases (with warnings) when both are specified. However, Langchain's HuggingFacePipeline only supports specifying `device` when calling transformers which limits large models and multi-gpu use-cases. Additionally, the [default value](https://github.com/praveenv/langchain/blob/8bd3ce59cd4ef80db5eb52922bb31588596939e1/libs/langchain/langchain/llms/huggingface_pipeline.py#L72) of `device` is initialized to `-1` , which is incompatible with the transformers pipeline when `device_map` is specified. This PR addresses the addition of `device_map` as a parameter , and solves the incompatibility of `device = -1` when `device_map` is also specified. An additional test has been added for this feature. Additionally, some existing tests no longer work since 1. `max_new_tokens` has to be specified under `pipeline_kwargs` and not `model_kwargs` 2. The GPT2 tokenizer raises a `ValueError: Pipeline with tokenizer without pad_token cannot do batching`, since the `tokenizer.pad_token` is `None` ([related issue](https://github.com/huggingface/transformers/issues/19853) on the transformers repo). This PR handles fixing these tests as well.

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I_kwDOIPDwls51mQBh

12,730

Adding memory with customprompt and Custom agent is resulting in error

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2023-11-01T19:22:39

2023-11-01T19:31:59

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NONE

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I have made a Custom Prompt template using: ``` `class CustomPromptTemplate(BaseChatPromptTemplate): # The template to use template: str # The list of tools available tools: List[Tool] def format_messages(self, **kwargs) -> str: # Get the intermediate steps (AgentAction, Observation tuples) # Format them in a particular way intermediate_steps = kwargs.pop("intermediate_steps") thoughts = "" for action, observation in intermediate_steps: thoughts += action.log thoughts += f"\nObservation: {observation}\nThought: " # Set the agent_scratchpad variable to that value kwargs["agent_scratchpad"] = thoughts # Create a tools variable from the list of tools provided kwargs["tools"] = "\n".join([f"{tool.name}: {tool.description}" for tool in self.tools]) # Create a list of tool names for the tools provided kwargs["tool_names"] = ", ".join([tool.name for tool in self.tools]) kwargs["df_head"]=df.head() formatted = self.template.format(**kwargs) return [HumanMessage(content=formatted)]` ``` Calling this: ``` prompt = CustomPromptTemplate( template=template, tools=tools, input_variables=["input","intermediate_steps","df_head","history"] ) ``` I have also created custom agent: ``` llm_chain = LLMChain(llm=llm, prompt=prompt) tool_names = [tool.name for tool in tools] agent = LLMSingleActionAgent( llm_chain=llm_chain, output_parser=output_parser, stop=["\nObservation:"], allowed_tools=tool_names ) ``` Executing agent: ``` from langchain.memory import ConversationBufferWindowMemory memory=ConversationBufferWindowMemory(memory_key='chat_history', return_messages=True, output_key='answer',k=2) agent_executor_new = AgentExecutor.from_agent_and_tools(agent=agent, tools=tools, verbose=True,memory=memory) ``` Running this with (**As per documentation**): ``` agent_executor_new.run({'input':"Generate top 3 insights on sales in Q4 and compare it against other quarters?"}) ``` Results in this error: ``` `File ~/anaconda3/lib/python3.10/site-packages/langchain/chains/base.py:443, in Chain.prep_inputs(self, inputs) 441 external_context = self.memory.load_memory_variables(inputs) 442 inputs = dict(inputs, **external_context) --> 443 self._validate_inputs(inputs) 444 return inputs File ~/anaconda3/lib/python3.10/site-packages/langchain/chains/base.py:195, in Chain._validate_inputs(self, inputs) 193 missing_keys = set(self.input_keys).difference(inputs) 194 if missing_keys: --> 195 raise ValueError(f"Missing some input keys: {missing_keys}") ValueError: Missing some input keys: {'df_head', 'history'}` ``` When I supply the missing input values: ``` agent_executor_new.run({'input':"Generate top 3 insights on sales in Q4 and compare it against other quarters?",'df_head':df.head(),'history':memory})` ``` It results in this error: ``` File ~/anaconda3/lib/python3.10/site-packages/langchain/memory/chat_memory.py:35, in BaseChatMemory.save_context(self, inputs, outputs) > 33 def save_context(self, inputs: Dict[str, Any], outputs: Dict[str, str]) -> None: > 34 """Save context from this conversation to buffer.""" > ---> 35 input_str, output_str = self._get_input_output(inputs, outputs) > 36 self.chat_memory.add_user_message(input_str) > 37 self.chat_memory.add_ai_message(output_str) > > File ~/anaconda3/lib/python3.10/site-packages/langchain/memory/chat_memory.py:22, in BaseChatMemory._get_input_output(self, inputs, outputs) > 18 def _get_input_output( > 19 self, inputs: Dict[str, Any], outputs: Dict[str, str] > 20 ) -> Tuple[str, str]: > 21 if self.input_key is None: > ---> 22 prompt_input_key = get_prompt_input_key(inputs, self.memory_variables) > 23 else: > 24 prompt_input_key = self.input_key > > File ~/anaconda3/lib/python3.10/site-packages/langchain/memory/utils.py:19, in get_prompt_input_key(inputs, memory_variables) > 17 prompt_input_keys = list(set(inputs).difference(memory_variables + ["stop"])) > 18 if len(prompt_input_keys) != 1: > ---> 19 raise ValueError(f"One input key expected got {prompt_input_keys}") > 20 return prompt_input_keys[0] > ValueError: One input key expected got ['df_head', 'history', 'input']` ``` Please help!!

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Update template index w/ Timescale

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Error after adding memory to custom agent and prompt template

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I have made a Custom Prompt template using:

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Fixes 'Nonetype' not iterable for ObsidianLoader

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2023-11-01T18:51:57

2023-11-01T22:46:59

2023-11-01T22:44:20

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When the frontmatter of an Obsidian note contains a tags key which has an empty value an error is raised as a 'Nonetype' is being iterated. This leads to the Loader failing. ``` markdown --- date: 2023-10-17 13:59 modification_date: 2023-10-17 13:59 tags: --- ```

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Add support for vectorstores that return cosine similarity (and not d…

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2023-11-01T18:33:08

2023-11-02T22:36:48

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CONTRIBUTOR

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Issue: https://github.com/langchain-ai/langchain/issues/12707 Pinecone's default distance strategy on index creation is cosine similarity and not cosine distance. While, we can have a custom _cosine_similarity_relevance_score_fn for Pinecone, I think other vectorstores may also return cosine similarity (and/or distance),i.e. we should expose this to the user so that we can choose the appropriate relevance function

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Add model config to invocation params

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2023-11-01T18:25:37

2023-11-03T02:19:29

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COLLABORATOR

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Also add a default invocation params property for the base LLM. Our inheritance here is .... messy, I don't think this breaks the other implementations at this time. Also if you think the config oughtn't go in invocation params, open to alternatives

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correcting a bug in VertexAIModelGarden class

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2023-11-01T17:29:40

2023-11-27T14:14:14

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**Description:** The PR is fixing the following: - As it stands the VertexAIModelGarden class is not working as the arguments in the code for Generation method is wrong. Corrected for both generate and agenerate - The location is hardcoded as us-central1. Removed this as the models in Model garden can be deployed in other locations - Added documentation to tuned_model_name to give an example of it should look like. **Tag maintainer:** @baskaryan **Dependencies:** No dependency required for this change

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bump 328, exp 37

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Issue: How to implement validation on number of arguments in tools?

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2023-11-01T18:51:55

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### Issue you'd like to raise. I am using the STRUCTURED_CHAT_ZERO_SHOT_REACT_DESCRIPTION agent and I am trying to implement tools that take varying number of arguments (e.g. tool1 takes a single argument and tool2 takes 3 arguments). I am using arg_schema to define the arguments and their types. I am wondering how can I return a message to the agent in case the input arguments do not satisfy the arg_schema without erroring out the service. My objective with this is that the agent will try again after modifying the "Thought". How do I do that? ### Suggestion: _No response_

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Issue: Agent doesn't actually utilize custom tool

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### Issue you'd like to raise. Agent calls get_date_time custom tool but does not actually use it. The following was its output Action: Amadeus\_flight\_offers\_search, { "originLocationCode": "LA", "destinationLocationCode": "NYC", "departureDate": "$(get\_date\_time)", "returnDate": "$(get\_date\_time)", "adults": 1, "children": 0, "max": 1, "nonStop": false, "maxPrice": 0, "currencyCode": "USD", "travelClass": "ECONOMY" } Observation: The flight offers search has been completed. Please review the results for your desired flight. ``` # Create Amadeus toolkit toolkit = AmadeusToolkit() tools = toolkit.get_tools() # Set up the LLMChain, passing in memory template = """You are an AI chatbot having a conversation with a human. {history} Human: {human_input} AI: """ prompt = PromptTemplate(input_variables=["history", "human_input"], template=template) llm = ChatOllama(model="mistral:7b-instruct", verbose=True, callback_manager = CallbackManager([StreamingStdOutCallbackHandler()])) # Define custom tool datetime_tool = Tool( name="get_date_time", func=lambda x: datetime.now().isoformat(), # '%Y-%m-%dT%H:%M:%S' description="Use the system's default time zone to return the current date and time", ) # Add the new tool to tool list tools.append(datetime_tool) system_message = SystemMessage(content=""" You are a helpful, respectful and honest travel agent. ... """) agent = initialize_agent( tools=tools, llm=llm, verbose=True, early_stopping_method="generate", memory=memory, agent_kwargs={"system_message": system_message, "extra_prompt_messages": [MessagesPlaceholder(variable_name="memory")]}, agent=AgentType.STRUCTURED_CHAT_ZERO_SHOT_REACT_DESCRIPTION, ) ``` ### Suggestion: _No response_

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feat: implement support for different type of containers for AWS Sagemaker LLM Streaming

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2023-11-01T15:29:34

2023-11-02T22:45:05

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PR adds the ability to have multiple types of content handling on streams, instead of the current hardcoded solution for LMI containers (https://aws.amazon.com/blogs/machine-learning/elevating-the-generative-ai-experience-introducing-streaming-support-in-amazon-sagemaker-hosting/) It iterates upon #10535 , where I've added the `_stream` implementation as well as added some Jupyter examples on how to implement.

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feat: Supprt pgvecto.rs as a VectorStore

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2023-11-01T15:19:36

2023-11-03T00:23:28

2023-11-03T00:16:04

CONTRIBUTOR

null

Supprt [pgvecto.rs](https://github.com/tensorchord/pgvecto.rs) as a new VectorStore type. This introduces a new dependency [pgvecto_rs](https://pypi.org/project/pgvecto_rs/) and upgrade SQLAlchemy to ^2. Relate to https://github.com/tensorchord/pgvecto.rs/issues/11

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12,717

fix: Added State Preservation to Vertex AI Search MultiTurn Retriever

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2023-11-01T15:19:32

2023-12-12T01:37:08

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CONTRIBUTOR

null

- Fixes Issue where Vertex AI Search MultiTurn Retriever doesn't maintain conversation state. @baskaryan, @eyurtsev, @hwchase17

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dash not underscore

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2023-11-01T15:00:30

2023-11-01T16:48:38

2023-11-01T16:48:37

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template names are auto-populating with the wrong convention (with underscores)

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12,715

Update google_vertex_ai_palm.ipynb

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2023-11-01T14:55:27

2023-11-01T23:05:45

CONTRIBUTOR

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Fixed a typo

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OpenAIEmbeddings fails to connect

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2023-11-01T14:36:00

2023-11-08T21:27:57

NONE

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### System Info Ubuntu 22.04 python = "3.11" langchain = "0.0.320" openai = "0.28.1" ### Who can help? https://github.com/hwchase17 https://github.com/agola11 ### Information - [X] The official example notebooks/scripts - [ ] My own modified scripts ### Related Components - [ ] LLMs/Chat Models - [X] Embedding Models - [ ] Prompts / Prompt Templates / Prompt Selectors - [ ] Output Parsers - [ ] Document Loaders - [ ] Vector Stores / Retrievers - [ ] Memory - [ ] Agents / Agent Executors - [ ] Tools / Toolkits - [ ] Chains - [ ] Callbacks/Tracing - [ ] Async ### Reproduction Surprisingly, this very basic call: ``` def testing_langchain_interface(self): openai_key = os.getenv('OPENAI_API_KEY') text = "This is the text to be embedded" result = OpenAIEmbeddings(openai_api_key=openai_key).embed_documents([text]) ``` Results in this error: ``` [2023-11-01 10:10:02] [WARNING] TESTING - Retrying (Retry(total=1, connect=None, read=None, redirect=None, status=None)) after connection broken by 'ProxyError('Cannot connect to proxy.', OSError('Tunnel connection failed: 400 Bad Request'))': /v1/embeddings [2023-11-01 10:10:02] [WARNING] TESTING - Retrying (Retry(total=0, connect=None, read=None, redirect=None, status=None)) after connection broken by 'ProxyError('Cannot connect to proxy.', OSError('Tunnel connection failed: 400 Bad Request'))': /v1/embeddings [2023-11-01 10:10:02] [WARNING] TESTING - Retrying langchain.embeddings.openai.embed_with_retry.<locals>._embed_with_retry in 4.0 seconds as it raised APIConnectionError: Error communicating with OpenAI: HTTPSConnectionPool(host='api.openai.com', port=443): Max retries exceeded with url: /v1/embeddings (Caused by ProxyError('Cannot connect to proxy.', OSError('Tunnel connection failed: 400 Bad Request'))). ``` Kwargs values at call site in _embed_with_retry: ``` {'input': [[2028, 374, 279, 1495, 311, 387, 23711]], 'model': 'text-embedding-ada-002', 'request_timeout': None, 'headers': None, 'api_key': '***', , 'organization': '', 'api_base': '', 'api_type': 'openai', 'api_version': ''} ``` While this code: ``` def testing_openai_interface(self): openai.api_key = os.getenv('OPENAI_API_KEY') model = "text-embedding-ada-002" text = "This is the text to be embedded" result = openai.Embedding.create(input=text, model=model, api_type='openai') ``` executes correctly and connects to the OpenAI API. ### Expected behavior OpenAIEmbeddings should connect without error to OpenAI api.

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12,713

Correct number of elements in config list in `batch()` and `abatch()` of `BaseLLM`

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2023-11-03T00:28:48

CONTRIBUTOR

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- **Description:** Correct number of elements in config list in `batch()` and `abatch()` of `BaseLLM` in case `max_concurrency` is not None. - **Issue:** #12643 - **Twitter handle:** @akionux

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12,712

OpenAIEmbeddings timeout parameter doesn't work

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2023-11-01T13:51:58

2023-11-01T14:03:07

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NONE

null

### System Info langchain==0.0.327, MacOS, Python 3.11.6 ### Who can help? @netseye ### Information - [ ] The official example notebooks/scripts - [X] My own modified scripts ### Related Components - [ ] LLMs/Chat Models - [X] Embedding Models - [ ] Prompts / Prompt Templates / Prompt Selectors - [ ] Output Parsers - [ ] Document Loaders - [ ] Vector Stores / Retrievers - [ ] Memory - [ ] Agents / Agent Executors - [ ] Tools / Toolkits - [ ] Chains - [ ] Callbacks/Tracing - [ ] Async ### Reproduction I'm trying to use OpenAIEmbeddings with Chroma ``` embedding_function = OpenAIEmbeddings( openai_api_type="azure", deployment="text-embedding-ada-002", model="text-embedding-ada-002", openai_api_base="https://something.openai.azure.com/", openai_api_key=os.getenv("AZURE_OPENAI_KEY"), ) vector_store = Chroma.from_documents( docs, embedding_function, persist_directory=os.getenv("CHROMA_DB") ) ``` and I'm getting `Retrying langchain.embeddings.openai.embed_with_retry.<locals>._embed_with_retry in 10.0 seconds as it raised RateLimitError: Requests to the Embeddings_Create Operation under Azure OpenAI API version 2022-12-01 have exceeded call rate limit of your current OpenAI S0 pricing tier. Please retry after 20 seconds. Please go here: https://aka.ms/oai/quotaincrease if you would like to further increase the default rate limit..` I tried to set request_timeout to different values, but it seems to be ignored, because behaviour doesn't change, I still see this requests to OpenAI endpoint with the same frequency. ### Expected behavior I would expect having this timeout invocated when there is an Exception from OpenAI is caught.

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12,711

Weaviate - Fix schema existence check

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2023-11-01T13:08:32

2023-11-01T15:22:15

CONTRIBUTOR

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This will allow you create the schema beforehand. The check was failing and preventing importing into existing classes.

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12,710

Milvus wrapper doesn't support http URI

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### System Info ``` langchain==0.0.315 pymilvus==2.3.0 Python 3.11.5 ``` ### Who can help? @hwchase17 @agola11 ### Information - [ ] The official example notebooks/scripts - [X] My own modified scripts ### Related Components - [ ] LLMs/Chat Models - [ ] Embedding Models - [ ] Prompts / Prompt Templates / Prompt Selectors - [ ] Output Parsers - [ ] Document Loaders - [x] Vector Stores / Retrievers - [ ] Memory - [ ] Agents / Agent Executors - [ ] Tools / Toolkits - [ ] Chains - [ ] Callbacks/Tracing - [ ] Async ### Reproduction Minimal code to reproduce: ```python from langchain.embeddings.base import Embeddings from langchain.vectorstores import Milvus class DummyEmbeddings(Embeddings): def embed_documents(): return [[]] def embed_query(self): return [] if __name__ == "__main__": Milvus( embedding_function=DummyEmbeddings(), collection_name="foo", connection_args={ "uri": "http://localhost:19530", "user": "", "password": "", "secure": False, }, ) ``` Running the code results in an exception coming from the [milvus adapter](https://github.com/langchain-ai/langchain/blob/5ae51a8a85d1a37ea98afeaf639a72ac74a50523/libs/langchain/langchain/vectorstores/milvus.py#L191) ```sh > python -m milvus_reproduce Traceback (most recent call last): File "<frozen runpy>", line 198, in _run_module_as_main File "<frozen runpy>", line 88, in _run_code File "milvus_reproduce.py", line 14, in <module> Milvus( File ".venv/lib/python3.11/site-packages/langchain/vectorstores/milvus.py", line 155, in __init__ self.alias = self._create_connection_alias(connection_args) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".venv/lib/python3.11/site-packages/langchain/vectorstores/milvus.py", line 191, in _create_connection_alias given_address = uri.split("https://")[1] ~~~~~~~~~~~~~~~~~~~~~^^^ IndexError: list index out of range ``` ### Expected behavior The milvus adapter must allow for http uris. The exception happens because the adapter assumes the uri always starts with `https://`. Instead one should parse url and get the netloc: ```python from urllib import parse given_address = parse.urlparse(uri).netloc ``` Similar to what `pymilvus` bindings [do](https://github.com/milvus-io/pymilvus/blob/master/pymilvus/orm/connections.py#L338).

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12,709

Exception “I now know the final answer” thrown when using “create_pandas_df_agent”

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2023-11-01T12:23:00

2023-11-06T12:38:50

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### System Info I encountered an issue while using the create_pandas_df_agent function in LangChain to process data. When I asked a question about the data, an exception was thrown with the message “I now know the final answer”. This phenomenon is not inevitable model is "gpt-3.5-turbo" ### Who can help? _No response_ ### Information - [X] The official example notebooks/scripts - [ ] My own modified scripts ### Related Components - [X] LLMs/Chat Models - [ ] Embedding Models - [ ] Prompts / Prompt Templates / Prompt Selectors - [X] Output Parsers - [ ] Document Loaders - [ ] Vector Stores / Retrievers - [ ] Memory - [X] Agents / Agent Executors - [ ] Tools / Toolkits - [ ] Chains - [ ] Callbacks/Tracing - [ ] Async ### Reproduction `self.llm = AzureChatOpenAI( openai_api_base=self.api_base, openai_api_version=self.api_version, deployment_name=self.deployment_name, openai_api_key=self.api_token, openai_api_type="azure", max_tokens = self.max_tokens, model_name = self.model_name, ) self._dfagent = create_pandas_df_agent(self._llm.llm,df,verbose=True) # tempt is a user problem result = Result() try: res = self._dfagent.run(tempt) result.content = res result.status = 'success' except Exception as exception: result.error = ( "Unfortunately, I was not able to answer your question, " "because of the following error:\n" f"\n{exception}\n" ) result.status = 'error' return result` ### Expected behavior I hope it returns the results normally

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12,707

similarity_score_threshold not working as expected with ConversationalRetrievalChain

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2023-11-01T11:26:58

2023-11-01T18:08:05

null

NONE

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### System Info LangChain version: langchain==0.0.327 Python version: Python 3.11.4 System: Windows 11 x64 ### Who can help? @hwchase17 @agola11 ### Information - [ ] The official example notebooks/scripts - [ ] My own modified scripts ### Related Components - [ ] LLMs/Chat Models - [ ] Embedding Models - [ ] Prompts / Prompt Templates / Prompt Selectors - [ ] Output Parsers - [ ] Document Loaders - [ ] Vector Stores / Retrievers - [ ] Memory - [ ] Agents / Agent Executors - [ ] Tools / Toolkits - [X] Chains - [ ] Callbacks/Tracing - [ ] Async ### Reproduction Here is my retriever- ```py retriever = vectorstore.as_retriever( search_type="similarity_score_threshold", search_kwargs={ "score_threshold": 0.8, "k": 5, "filter": {"source": {"$in": self.config.get("author")}}, } ) ``` and chain- ```py chain = ConversationalRetrievalChain.from_llm( llm=chat_model, retriever=retriever, memory=memory, chain_type="stuff", combine_docs_chain_kwargs={"prompt": prompt}, get_chat_history=lambda h: h, condense_question_llm=ChatOpenAI(temperature=0.04), verbose=True, ) ``` In retriever, `similarity_score_threshold` is not working as expected. For now, I am using `0.8` as `score_threshold` for retriever. I am not getting any Documents in return. However, this piece of code is giving me the expected Documents. Note that I am not specifying any score during similarity search. I am checking the score of each Document manually with 0.8 as a threshold. ```py vectorstore.similarity_search_with_score( query=query, k=5, filter={"source": {"$in": self.config.get("author")}}, namespace="my_namespace", ) ``` ### Expected behavior The below piece of codes should return the same Documents from Pinecone. ```py retriever = vectorstore.as_retriever( search_type="similarity_score_threshold", search_kwargs={ "score_threshold": 0.8, "k": 5, "filter": {"source": {"$in": self.config.get("author")}}, } ) ``` ```py vectorstore.similarity_search_with_score( query=query, k=5, filter={"source": {"$in": self.config.get("author")}}, namespace="my_namespace", ) ```

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12,706

Issue: How can I utilize different histories for different users

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### Issue you'd like to raise. I am using the ConversationBufferWindowMemory class and I would like to have different memories for different users. So that each user has its individual memory. memory = ConversationBufferWindowMemory(k=3, memory_key="chat_history", return_messages=True) qa = ConversationalRetrievalChain.from_llm(llm_model, vector_store.as_retriever(search_kwargs={'k': 2}), memory=memory, ### Suggestion: _No response_

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12,705

CerebriumAI model_api_request deprecation

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2023-11-01T10:57:49

2023-11-01T11:10:03

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CONTRIBUTOR

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### System Info Langchain 0.0.327 Python 3.10 ### Who can help? @hwchase17 or @eyurtsev are contributors of CerebriumAI based on Github history. ### Information - [X] The official example notebooks/scripts - [ ] My own modified scripts ### Related Components - [X] LLMs/Chat Models - [ ] Embedding Models - [ ] Prompts / Prompt Templates / Prompt Selectors - [ ] Output Parsers - [ ] Document Loaders - [ ] Vector Stores / Retrievers - [ ] Memory - [ ] Agents / Agent Executors - [ ] Tools / Toolkits - [ ] Chains - [ ] Callbacks/Tracing - [ ] Async ### Reproduction Reference: https://docs.cerebrium.ai/cerebrium/cortex/examples/langchain As a result it always returns ```Could not import cerebrium python package. Please install it with `pip install cerebrium`.``` as part of the following code ``` from cerebrium import model_api_request except ImportError: raise ValueError( "Could not import cerebrium python package. " "Please install it with `pip install cerebrium`." ) ``` ### Expected behavior Returns value from the Cerebrium AI instance.

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Cerebrium model_api_request deprecation

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2023-11-01T10:49:31

2023-12-04T17:26:33

2023-12-04T17:26:32

CONTRIBUTOR

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- **Description:** As part of my conversation with Cerebrium team, `model_api_request` will be no longer available in cerebrium lib so it needs to be replaced. - **Issue:** #12705 12705, - **Dependencies:** Cerebrium team (agreed) - **Tag maintainer:** @eyurtsev - **Twitter handle:** No official Twitter account sorry :D

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Fixed vertexai streaming with codey model

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2023-11-01T10:39:36

2023-11-01T10:39:48

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When using `codey` models in vertexai there is no candidate_count parameter in default_params and it is not required in kwargs too. Need to use full syntax dict.pop(key, default).

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community: Integrate Xinference Chat

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2023-11-01T10:31:41

2023-12-28T03:55:37

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- [Xorbits Inference(Xinference)](https://github.com/xorbitsai/inference) is a powerful and versatile library designed to serve language, speech recognition, and multimodal models. Xinference supports a variety of GGML-compatible models including chatglm, whisper, and vicuna, and utilizes heterogeneous hardware and a distributed architecture for seamless cross-device and cross-server model deployment. - This PR integrates Xinference chat into LangChain. - Dependencies: To install the depenedencies for this integration, run `pip install "xinference[all]"` - Example Usage: To start a local instance of Xinference, run `xinference`. To deploy Xinference in a distributed cluster, first start an Xinference supervisor using `xinference-supervisor`: `xinference-supervisor -H "${supervisor_host}"` Then, start the Xinference workers using `xinference-worker` on each server you want to run them on. `xinference-worker -e "http://${supervisor_host}:9997"` To use Xinference with LangChain, you also need to launch a model. You can use command line interface (CLI) to do so. Fo example: `xinference launch -n vicuna-v1.3 -f ggmlv3 -q q4_0`. This launches a model named vicuna-v1.3 with `model_format="ggmlv3"` and `quantization="q4_0"`. A model UID is returned for you to use. Now you can use Xinference with LangChain: ```python from langchain.chat_models import ChatXinference from langchain.schema import AIMessage, HumanMessage, SystemMessage chat = ChatXinference( server_url=server_url, # Xinference server url model_uid=model_uid, # Xinference model uid generate_config={ "max_tokens": 5, "temperature": 0, }, ) messages = [ SystemMessage( content="You are a helpful assistant that translates English to Italian." ), HumanMessage( content="Translate the following sentence from English to Italian: " "I love programming." ), ] chat(messages) ``` ``` AIMessage(content=' Io amo programmare.') ``` Xinference is still under rapid development. Feel free to [join our Slack community](https://xorbitsio.slack.com/join/shared_invite/zt-1z3zsm9ep-87yI9YZ_B79HLB2ccTq4WA) to get the latest updates! Request for review: @hwchase17, @baskaryan Twitter handle: https://twitter.com/Xorbitsio

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