117 Commits (c816d036998ad4a1970c9d90698516e1fbf6812b)

Author	SHA1	Message	Date
maang-h	1055b9a309	community[minor]: Implement ZhipuAIEmbeddings interface (#22821) ... - **Description:** Implement ZhipuAIEmbeddings interface, include: - The `embed_query` method - The `embed_documents` method refer to [ZhipuAI Embedding-2](https://open.bigmodel.cn/dev/api#text_embedding) --------- Co-authored-by: Eugene Yurtsev <eugene@langchain.dev>	3 months ago
Eugene Yurtsev	265e650e64	community[patch]: Update root_validators embeddings: llamacpp, jina, dashscope, mosaicml, huggingface_hub, Toolkits: Connery, ChatModels: PAI_EAS, (#22828) ... This PR updates root validators for: * Embeddings: llamacpp, jina, dashscope, mosaicml, huggingface_hub * Toolkits: Connery * ChatModels: PAI_EAS Following this issue: https://github.com/langchain-ai/langchain/issues/22819	3 months ago
JonZeolla	32ba8cfab0	community[minor]: implement huggingface show_progress consistently (#22682) ... - **Description:** This implements `show_progress` more consistently (i.e. it is also added to the `HuggingFaceBgeEmbeddings` object). - **Issue:** This implements `show_progress` more consistently in the embeddings huggingface classes. Previously this could have been set via `encode_kwargs`. - **Dependencies:** None - **Twitter handle:** @jonzeolla	3 months ago
Mathis Joffre	ea43f40daf	community[minor]: Add support for OVHcloud AI Endpoints Embedding (#22667) ... **Description:** Add support for [OVHcloud AI Endpoints](https://endpoints.ai.cloud.ovh.net/) Embedding models. Inspired by: https://gist.github.com/gmasse/e1f99339e161f4830df6be5d0095349a Signed-off-by: Joffref <mariusjoffre@gmail.com>	3 months ago
maang-h	89128b7a49	community[patch]: add detailed paragraph and example for BaichuanTextEmbeddings (#22031) ... - **Description:** add detailed paragraph and example for BaichuanTextEmbeddings - **Issue:** the issue #21983	4 months ago
Erick Friis	58192d617f	community: fix huggingface deprecations (#22522)	4 months ago
Bagatur	17c127531a	community[patch]: deprecate all HF classes (#22444)	4 months ago
Ethan Yang	52da6a160d	community[patch]: Update OpenVINO embedding and reranker to support static input shape (#22171) ... It can help to deploy embedding models on NPU device	4 months ago
Harichandan Roy	1f751343e2	community[patch]: update embeddings/oracleai.py (#22240) ... Thank you for contributing to LangChain! - [ ] **PR title**: "package: description" - Where "package" is whichever of langchain, community, core, experimental, etc. is being modified. Use "docs: ..." for purely docs changes, "templates: ..." for template changes, "infra: ..." for CI changes. - Example: "community: add foobar LLM" "community/embeddings: update oracleai.py" - [ ] **PR message**: ***Delete this entire checklist*** and replace with - **Description:** a description of the change - **Issue:** the issue # it fixes, if applicable - **Dependencies:** any dependencies required for this change - **Twitter handle:** if your PR gets announced, and you'd like a mention, we'll gladly shout you out! Adding oracle VECTOR_ARRAY_T support. - [ ] **Add tests and docs**: If you're adding a new integration, please include 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. It lives in `docs/docs/integrations` directory. Tests are not impacted. - [ ] **Lint and test**: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. See contribution guidelines for more: https://python.langchain.com/docs/contributing/ Done. Additional guidelines: - Make sure optional dependencies are imported within a function. - Please do not add dependencies to pyproject.toml files (even optional ones) unless they are required for unit tests. - Most PRs should not touch more than one package. - Changes should be backwards compatible. - If you are adding something to community, do not re-import it in langchain. If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.	4 months ago
maang-h	13140dc4ff	community[patch]: Update the default api_url and reqeust_body of sparkllm embedding (#22136) ... - **Description:** When I was running the SparkLLMTextEmbeddings, app_id, api_key and api_secret are all correct, but it cannot run normally using the current URL. ```python # example from langchain_community.embeddings import SparkLLMTextEmbeddings embedding= SparkLLMTextEmbeddings( spark_app_id="my-app-id", spark_api_key="my-api-key", spark_api_secret="my-api-secret" ) embedding= "hello" print(spark.embed_query(text1)) ```  So I updated the url and request body parameters according to [Embedding_api](https://www.xfyun.cn/doc/spark/Embedding_api.html), now it is runnable.	4 months ago
Yuwen Hu	ba0dca46d7	community[minor]: Add IPEX-LLM BGE embedding support on both Intel CPU and GPU (#22226) ... **Description:** [IPEX-LLM](https://github.com/intel-analytics/ipex-llm) is a PyTorch library for running LLM on Intel CPU and GPU (e.g., local PC with iGPU, discrete GPU such as Arc, Flex and Max) with very low latency. This PR adds ipex-llm integrations to langchain for BGE embedding support on both Intel CPU and GPU. **Dependencies:** `ipex-llm`, `sentence-transformers` **Contribution maintainer**: @Oscilloscope98 **tests and docs**: - langchain/docs/docs/integrations/text_embedding/ipex_llm.ipynb - langchain/docs/docs/integrations/text_embedding/ipex_llm_gpu.ipynb - langchain/libs/community/tests/integration_tests/embeddings/test_ipex_llm.py --------- Co-authored-by: Shengsheng Huang <shannie.huang@gmail.com>	4 months ago
Joan Fontanals	a7ae16f912	add `embed_image` API to JinaEmbedding (#22416) ... - **Description:** Add `embed_image` to JinaEmbedding to embed images - **Twitter handle:** https://x.com/JinaAI_	4 months ago
Bagatur	50186da0a1	infra: rm unused # noqa violations (#22049) ... Updating #21137	4 months ago
acho98	45ed5f3f51	community[minor]: Add Clova Embeddings for LangChain Community (#21890) ... - [ ] **PR title**: "Add Naver ClovaX embedding to LangChain community" - HyperClovaX is a large language model developed by [Naver](https://clova-x.naver.com/welcome). It's a powerful and purpose-trained LLM. - You can visit the embedding service provided by [ClovaX](https://www.ncloud.com/product/aiService/clovaStudio) - You may get CLOVA_EMB_API_KEY, CLOVA_EMB_APIGW_API_KEY, CLOVA_EMB_APP_ID From https://www.ncloud.com/product/aiService/clovaStudio --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	4 months ago
Matthew Hoffman	4f2e3bd7fd	community[patch]: fix public interface for embeddings module (#21650) ... ## Description The existing public interface for `langchain_community.emeddings` is broken. In this file, `__all__` is statically defined, but is subsequently overwritten with a dynamic expression, which type checkers like pyright do not support. pyright actually gives the following diagnostic on the line I am requesting we remove: [reportUnsupportedDunderAll](https://github.com/microsoft/pyright/blob/main/docs/configuration.md#reportUnsupportedDunderAll): ``` Operation on "__all__" is not supported, so exported symbol list may be incorrect ``` Currently, I get the following errors when attempting to use publicablly exported classes in `langchain_community.emeddings`: ```python import langchain_community.embeddings langchain_community.embeddings.HuggingFaceEmbeddings(...) # error: "HuggingFaceEmbeddings" is not exported from module "langchain_community.embeddings" (reportPrivateImportUsage) ``` This is solved easily by removing the dynamic expression.	4 months ago
Sevin F. Varoglu	1bc0ea5496	community[patch]: update OctoAIEmbeddings to subclass OpenAIEmbeddings (#21805)	4 months ago
Jens	b0b302ec6b	community[patch]: fixed aleph alpha default emedding request (#21826) ... - **Description:** In the aleph alpha client the paramater `normalize` is *not* optional. Setting this to `None` gives an error. - **Dependencies:** None Co-authored-by: Jens Lücke <jens.luecke@tngtech.com> Co-authored-by: Jens <jens.luecke@hu-berlin.de> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	4 months ago
Liuww	332ffed393	community[patch]: Adopting the lighter-weight xinference_client (#21900) ... While integrating the xinference_embedding, we observed that the downloaded dependency package is quite substantial in size. With a focus on resource optimization and efficiency, if the project requirements are limited to its vector processing capabilities, we recommend migrating to the xinference_client package. This package is more streamlined, significantly reducing the storage space requirements of the project and maintaining a feature focus, making it particularly suitable for scenarios that demand lightweight integration. Such an approach not only boosts deployment efficiency but also enhances the application's maintainability, rendering it an optimal choice for our current context. --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	4 months ago
maang-h	9f8d18c028	community[patch]: Fix unintended newline in print statement in exception for BaichuanTextEmbeddings (#21820) ... - **Code:** langchain_community/embeddings/baichuan.py:82 - **Description:** When I make an error using 'baichuan embeddings', the printed error message is wrapped (there is actually no need to wrap) ```python # example from langchain_community.embeddings import BaichuanTextEmbeddings # error key BAICHUAN_API_KEY = "sk-xxxxxxxxxxxxx" embeddings = BaichuanTextEmbeddings(baichuan_api_key=BAICHUAN_API_KEY) text_1 = "今天天气不错" query_result = embeddings.embed_query(text_1) ``` 	4 months ago
Oguz Vuruskaner	5b35f077f9	[community][fix](DeepInfraEmbeddings): Implement chunking for large batches (#21189) ... **Description:** This PR introduces chunking logic to the `DeepInfraEmbeddings` class to handle large batch sizes without exceeding maximum batch size of the backend. This enhancement ensures that embedding generation processes large batches by breaking them down into smaller, manageable chunks, each conforming to the maximum batch size limit. **Issue:** Fixes #21189 **Dependencies:** No new dependencies introduced.	5 months ago
Alex JW	d3ce6aad2e	community: Instantiate GPT4AllEmbeddings with parameters (#21238) ... ### GPT4AllEmbeddings parameters --- **Description:** As of right now the **Embed4All** class inside _GPT4AllEmbeddings_ is instantiated as it's default which leaves no room to customize the chosen model and it's behavior. Thus: - GPT4AllEmbeddings can now be instantiated with custom parameters like a different model that shall be used. --------- Co-authored-by: AlexJauchWalser <alexander.jauch-walser@knime.com>	5 months ago
Miroslav	04e2611fea	Added additional headers for HuggingFaceInferenceAPIEmbeddings endpoint. (#21282) ... Thank you for contributing to LangChain! - [ ] **HuggingFaceInferenceAPIEmbeddings**: "Additional Headers" - Where: langchain, community, embeddings. huggingface.py. - Community: add additional headers when needed by custom HuggingFace TEI embedding endpoints. HuggingFaceInferenceAPIEmbeddings" - [ ] **PR message**: ***Delete this entire checklist*** and replace with - **Description:** Adding the `additional_headers` to be passed to requests library if needed - **Dependencies:** none - [ ] **Add tests and docs**: If you're adding a new integration, please include 1. Tested with locally available TEI endpoints with and without `additional_headers` 2. Example Usage ```python embeddings=HuggingFaceInferenceAPIEmbeddings( api_key=MY_CUSTOM_API_KEY, api_url=MY_CUSTOM_TEI_URL, additional_headers={ "Content-Type": "application/json" } ) ``` Additional guidelines: - Make sure optional dependencies are imported within a function. - Please do not add dependencies to pyproject.toml files (even optional ones) unless they are required for unit tests. - Most PRs should not touch more than one package. - Changes should be backwards compatible. - If you are adding something to community, do not re-import it in langchain. If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, hwchase17. --------- Co-authored-by: Massimiliano Pronesti <massimiliano.pronesti@gmail.com> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	5 months ago
Jorge Piedrahita Ortiz	e65652c3e8	community: add SambaNova embeddings integration (#21227) ... - **Description:** SambaNova hosted embeddings integration	5 months ago
Rashmi Pawar	a2fdabdad2	mark NemoEmbeddings as deprecated (#21239) ... The NemoEmbeddings is deprecated, instead use langchain-nvidia-ai-endpoints NVIDIAEmbeddings interface. cc: @mattf --------- Co-authored-by: Daniel Glogowski <167348611+dglogo@users.noreply.github.com> Co-authored-by: andyjessen <62343929+andyjessen@users.noreply.github.com> Co-authored-by: Chris Germann <88305668+TAAGECH9@users.noreply.github.com> Co-authored-by: gere <gere@kapo.zh.ch> Co-authored-by: Chester Curme <chester.curme@gmail.com>	5 months ago
Rohan Aggarwal	8021d2a2ab	community[minor]: Oraclevs integration (#21123) ... Thank you for contributing to LangChain! - Oracle AI Vector Search Oracle AI Vector Search is designed for Artificial Intelligence (AI) workloads that allows you to query data based on semantics, rather than keywords. One of the biggest benefit of Oracle AI Vector Search is that semantic search on unstructured data can be combined with relational search on business data in one single system. This is not only powerful but also significantly more effective because you don't need to add a specialized vector database, eliminating the pain of data fragmentation between multiple systems. - Oracle AI Vector Search is designed for Artificial Intelligence (AI) workloads that allows you to query data based on semantics, rather than keywords. One of the biggest benefit of Oracle AI Vector Search is that semantic search on unstructured data can be combined with relational search on business data in one single system. This is not only powerful but also significantly more effective because you don't need to add a specialized vector database, eliminating the pain of data fragmentation between multiple systems. This Pull Requests Adds the following functionalities Oracle AI Vector Search : Vector Store Oracle AI Vector Search : Document Loader Oracle AI Vector Search : Document Splitter Oracle AI Vector Search : Summary Oracle AI Vector Search : Oracle Embeddings - We have added unit tests and have our own local unit test suite which verifies all the code is correct. We have made sure to add guides for each of the components and one end to end guide that shows how the entire thing runs. - We have made sure that make format and make lint run clean. Additional guidelines: - Make sure optional dependencies are imported within a function. - Please do not add dependencies to pyproject.toml files (even optional ones) unless they are required for unit tests. - Most PRs should not touch more than one package. - Changes should be backwards compatible. - If you are adding something to community, do not re-import it in langchain. If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, hwchase17. --------- Co-authored-by: skmishraoracle <shailendra.mishra@oracle.com> Co-authored-by: hroyofc <harichandan.roy@oracle.com> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	5 months ago
ccurme	6da3d92b42	(all): update removal in deprecation warnings from 0.2 to 0.3 (#21265) ... We are pushing out the removal of these to 0.3. `find . -type f -name "*.py" -exec sed -i '' 's/removal="0\.2/removal="0.3/g' {} +`	5 months ago
Charlie Marsh	8f38b7a725	multiple: Remove unnecessary Ruff suppression comments (#21050) ... ## Summary I ran `ruff check --extend-select RUF100 -n` to identify `# noqa` comments that weren't having any effect in Ruff, and then `ruff check --extend-select RUF100 -n --fix` on select files to remove all of the unnecessary `# noqa: F401` violations. It's possible that these were needed at some point in the past, but they're not necessary in Ruff v0.1.15 (used by LangChain) or in the latest release. Co-authored-by: Erick Friis <erick@langchain.dev>	5 months ago
Leonid Ganeline	85094cbb3a	docs: community docstring updates (#21040) ... Added missed docstrings. Updated docstrings to consistent format.	5 months ago
Leonid Ganeline	dc7c06bc07	community[minor]: import fix (#20995) ... Issue: When the third-party package is not installed, whenever we need to `pip install <package>` the ImportError is raised. But sometimes, the `ValueError` or `ModuleNotFoundError` is raised. It is bad for consistency. Change: replaced the `ValueError` or `ModuleNotFoundError` with `ImportError` when we raise an error with the `pip install <package>` message. Note: Ideally, we replace all `try: import... except... raise ... `with helper functions like `import_aim` or just use the existing [langchain_core.utils.utils.guard_import](https://api.python.langchain.com/en/latest/utils/langchain_core.utils.utils.guard_import.html#langchain_core.utils.utils.guard_import) But it would be much bigger refactoring. @baskaryan Please, advice on this.	5 months ago
davidefantiniIntel	f386f71bb3	community: fix tqdm import (#20263) ... Description: Fix tqdm import in QuantizedBiEncoderEmbeddings	5 months ago
Dmitry Tyumentsev	f111efeb6e	community[patch]: YandexGPT API add ability to disable request logging (#20670) ... Closes (#20622) Added the ability to [disable logging of requests to YandexGPT](https://yandex.cloud/en/docs/foundation-models/operations/yandexgpt/disable-logging).	5 months ago
Ethan Yang	2d6d796040	community: Add save_model function for openvino reranker and embedding (#19896)	5 months ago
Erick Friis	f09bd0b75b	upstage: init package (#20574) ... Co-authored-by: Sean Cho <sean@upstage.ai> Co-authored-by: JuHyung-Son <sonju0427@gmail.com>	5 months ago
pjb157	479be3cc91	community[minor]: Unify Titan Takeoff Integrations and Adding Embedding Support (#18775) ... **Community: Unify Titan Takeoff Integrations and Adding Embedding Support** **Description:** Titan Takeoff no longer reflects this either of the integrations in the community folder. The two integrations (TitanTakeoffPro and TitanTakeoff) where causing confusion with clients, so have moved code into one place and created an alias for backwards compatibility. Added Takeoff Client python package to do the bulk of the work with the requests, this is because this package is actively updated with new versions of Takeoff. So this integration will be far more robust and will not degrade as badly over time. **Issue:** Fixes bugs in the old Titan integrations and unified the code with added unit test converge to avoid future problems. **Dependencies:** Added optional dependency takeoff-client, all imports still work without dependency including the Titan Takeoff classes but just will fail on initialisation if not pip installed takeoff-client **Twitter** @MeryemArik9 Thanks all :) --------- Co-authored-by: Bagatur <baskaryan@gmail.com> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	5 months ago
Egor Krasheninnikov	c8391d4ff1	community[patch]: Fix YandexGPT embeddings (#19720) ... Fix of YandexGPT embeddings. The current version uses a single `model_name` for queries and documents, essentially making the `embed_documents` and `embed_query` methods the same. Yandex has a different endpoint (`model_uri`) for encoding documents, see [this](https://yandex.cloud/en/docs/yandexgpt/concepts/embeddings). The bug may impact retrievers built with `YandexGPTEmbeddings` (for instance FAISS database as retriever) since they use both `embed_documents` and `embed_query`. A simple snippet to test the behaviour: ```python from langchain_community.embeddings.yandex import YandexGPTEmbeddings embeddings = YandexGPTEmbeddings() q_emb = embeddings.embed_query('hello world') doc_emb = embeddings.embed_documents(['hello world', 'hello world']) q_emb == doc_emb[0] ``` The response is `True` with the current version and `False` with the changes I made. Twitter: @egor_krash --------- Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	5 months ago
Leonid Ganeline	7cf2d2759d	community[patch]: docstrings update (#20301) ... Added missed docstrings. Format docstings to the consistent form.	5 months ago
Leonid Ganeline	4cb5f4c353	community[patch]: import flattening fix (#20110) ... This PR should make it easier for linters to do type checking and for IDEs to jump to definition of code. See #20050 as a template for this PR. - As a byproduct: Added 3 missed `test_imports`. - Added missed `SolarChat` in to __init___.py Added it into test_import ut. - Added `# type: ignore` to fix linting. It is not clear, why linting errors appear after ^ changes. --------- Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>	5 months ago
Ethan Yang	48f84e253e	community[minor]: Add OpenVINO rerank model support (#19791) ... @eaidova @AlexKoff88 Could you help to review, thanks --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	6 months ago
shahrin014	f51e6a35ba	community[patch]: OllamaEmbeddings - Pass headers to post request (#16880) ... ## Feature - Set additional headers in constructor - Headers will be sent in post request This feature is useful if deploying Ollama on a cloud service such as hugging face, which requires authentication tokens to be passed in the request header. ## Tests - Test if header is passed - Test if header is not passed Similar to https://github.com/langchain-ai/langchain/pull/15881 --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	6 months ago
高璟琦	ec7a59c96c	community[minor]: Add solar embedding (#19761) ... Solar is a large language model developed by [Upstage](https://upstage.ai/). It's a powerful and purpose-trained LLM. You can visit the embedding service provided by Solar within this pr. You may get **SOLAR_API_KEY** from https://console.upstage.ai/services/embedding You can refer to more details about accepted llm integration at https://python.langchain.com/docs/integrations/llms/solar.	6 months ago
Ethan Yang	7164015135	community[minor]: Add Openvino embedding support (#19632) ... This PR is used to support both HF and BGE embeddings with openvino --------- Co-authored-by: Alexander Kozlov <alexander.kozlov@intel.com>	6 months ago
T Cramer	540ebf35a9	community[patch]: Add explicit error message to Bedrock error output. (#17328) ... - **Description:** Propagate Bedrock errors into Langchain explicitly. Use-case: unset region error is hidden behind 'Could not load credentials...' message - **Issue:** [17654](https://github.com/langchain-ai/langchain/issues/17654) - **Dependencies:** None --------- Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	6 months ago
kYLe	124ab79c23	community[minor]: Add Anyscale embedding support (#17605) ... **Description:** Add embedding model support for Anyscale Endpoint **Dependencies:** openai --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	6 months ago
Lance Martin	12843f292f	community[patch]: llama cpp embeddings reset default n_batch (#17594) ... When testing Nomic embeddings -- ``` from langchain_community.embeddings import LlamaCppEmbeddings embd_model_path = "/Users/rlm/Desktop/Code/llama.cpp/models/nomic-embd/nomic-embed-text-v1.Q4_K_S.gguf" embd_lc = LlamaCppEmbeddings(model_path=embd_model_path) embedding_lc = embd_lc.embed_query(query) ``` We were seeing this error for strings > a certain size -- ``` File ~/miniforge3/envs/llama2/lib/python3.9/site-packages/llama_cpp/llama.py:827, in Llama.embed(self, input, normalize, truncate, return_count) 824 s_sizes = [] 826 # add to batch --> 827 self._batch.add_sequence(tokens, len(s_sizes), False) 828 t_batch += n_tokens 829 s_sizes.append(n_tokens) File ~/miniforge3/envs/llama2/lib/python3.9/site-packages/llama_cpp/_internals.py:542, in _LlamaBatch.add_sequence(self, batch, seq_id, logits_all) 540 self.batch.token[j] = batch[i] 541 self.batch.pos[j] = i --> 542 self.batch.seq_id[j][0] = seq_id 543 self.batch.n_seq_id[j] = 1 544 self.batch.logits[j] = logits_all ValueError: NULL pointer access ``` The default `n_batch` of llama-cpp-python's Llama is `512` but we were explicitly setting it to `8`. These need to be set to equal for embedding models. * The embedding.cpp example has an assertion to make sure these are always equal. * Apparently this is not being done properly in llama-cpp-python. With `n_batch` set to 8, if more than 8 tokens are passed the batch runs out of space and it crashes. This also explains why the CPU compute buffer size was small: raw client with default `n_batch=512` ``` llama_new_context_with_model: CPU input buffer size = 3.51 MiB llama_new_context_with_model: CPU compute buffer size = 21.00 MiB ``` langchain with `n_batch=8` ``` llama_new_context_with_model: CPU input buffer size = 0.04 MiB llama_new_context_with_model: CPU compute buffer size = 0.33 MiB ``` We can work around this by passing `n_batch=512`, but this will not be obvious to some users: ``` embedding = LlamaCppEmbeddings(model_path=embd_model_path, n_batch=512) ``` From discussion w/ @cebtenzzre. Related: https://github.com/abetlen/llama-cpp-python/issues/1189 Co-authored-by: Bagatur <baskaryan@gmail.com>	6 months ago
hulitaitai	dc2c9dd4d7	Update text2vec.py (#19657) ... Add that URL of the embedding tool "text2vec". Fix minor mistakes in the doc-string.	6 months ago
yuwenzho	3a7d2cf443	community[minor]: Add ITREX optimized Embeddings (#18474) ... Introduction [Intel® Extension for Transformers](https://github.com/intel/intel-extension-for-transformers) is an innovative toolkit designed to accelerate GenAI/LLM everywhere with the optimal performance of Transformer-based models on various Intel platforms Description adding ITREX runtime embeddings using intel-extension-for-transformers. added mdx documentation and example notebooks added embedding import testing. --------- Signed-off-by: yuwenzho <yuwen.zhou@intel.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	6 months ago
Tom Aarsen	e0a1278d2b	docs: HFEmbeddings: Add more information to model_kwargs/encode_kwargs (#19594) ... - **Description:** Be more explicit with the `model_kwargs` and `encode_kwargs` for `HuggingFaceEmbeddings`. - **Issue:** - - **Dependencies:** - I received some reports by my users that they didn't realise that you could change the default `batch_size` with `HuggingFaceEmbeddings`, which may be attributed to how the `model_kwargs` and `encode_kwargs` don't give much information about what you can specify. I've added some parameter names & links to the Sentence Transformers documentation to help clear it up. Let me know if you'd rather have Markdown/Sphinx-style hyperlinks rather than a "bare URL". - Tom Aarsen	6 months ago
hulitaitai	d7c14cb6f9	community[minor]: Add embeddings integration for text2vec (#19267) ... Create a Class which allows to use the "text2vec" open source embedding model. It should install the model by running 'pip install -U text2vec'. Example to call the model through LangChain: from langchain_community.embeddings.text2vec import Text2vecEmbeddings embedding = Text2vecEmbeddings() bookend.embed_documents([ "This is a CoSENT(Cosine Sentence) model.", "It maps sentences to a 768 dimensional dense vector space.", ]) bookend.embed_query( "It can be used for text matching or semantic search." ) --------- Co-authored-by: Bagatur <baskaryan@gmail.com> Co-authored-by: Eugene Yurtsev <eugene@langchain.dev> Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>	6 months ago
Anindyadeep	b2a11ce686	community[minor]: Prem AI langchain integration (#19113) ... ### Prem SDK integration in LangChain This PR adds the integration with [PremAI's](https://www.premai.io/) prem-sdk with langchain. User can now access to deployed models (llms/embeddings) and use it with langchain's ecosystem. This PR adds the following: ### This PR adds the following: - [x] Add chat support - [X] Adding embedding support - [X] writing integration tests - [X] writing tests for chat - [X] writing tests for embedding - [X] writing unit tests - [X] writing tests for chat - [X] writing tests for embedding - [X] Adding documentation - [X] writing documentation for chat - [X] writing documentation for embedding - [X] run `make test` - [X] run `make lint`, `make lint_diff` - [X] Final checks (spell check, lint, format and overall testing) --------- Co-authored-by: Anindyadeep Sannigrahi <anindyadeepsannigrahi@Anindyadeeps-MacBook-Pro.local> Co-authored-by: Bagatur <baskaryan@gmail.com> Co-authored-by: Erick Friis <erick@langchain.dev> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	6 months ago
Dmitry Tyumentsev	08b769d539	community[patch]: YandexGPT Use recent yandexcloud sdk version (#19341) ... Fixed inability to work with [yandexcloud SDK](https://pypi.org/project/yandexcloud/) version higher 0.265.0	6 months ago