langchain

Commit Graph

Author	SHA1	Message	Date
Bagatur	93d0ad97fe	anthropic[patch]: test image input (#23155 )	3 months ago
Leonid Ganeline	3dfd055411	anthropic: docstrings (#23145 ) Added missed docstrings. Format docstrings to the consistent format (used in the API Reference)	3 months ago
Bagatur	90559fde70	openai[patch], standard-tests[patch]: don't pass in falsey stop vals (#23153 ) adds an image input test to standard-tests as well	3 months ago
Bagatur	093ae04d58	core[patch]: Pin pydantic in py3.12.4 (#23130 )	3 months ago
Bagatur	d96f67b06f	standard-tests[patch]: Update chat model standard tests (#22378 ) - Refactor standard test classes to make them easier to configure - Update openai to support stop_sequences init param - Update groq to support stop_sequences init param - Update fireworks to support max_retries init param - Update ChatModel.bind_tools to type tool_choice - Update groq to handle tool_choice="any". this may be controversial --------- Co-authored-by: Chester Curme <chester.curme@gmail.com>	3 months ago
ccurme	722c8f50ea	openai[patch]: add stream_usage parameter (#22854 ) Here we add `stream_usage` to ChatOpenAI as: 1. a boolean attribute 2. a kwarg to _stream and _astream. Question: should the `stream_usage` attribute be `bool`, or `bool \| None`? Currently I've kept it `bool` and defaulted to False. It was implemented on [ChatAnthropic](`e832bbb486/libs/partners/anthropic/langchain_anthropic/chat_models.py (L535)`) as a bool. However, to maintain support for users who access the behavior via OpenAI's `stream_options` param, this ends up being possible: ```python llm = ChatOpenAI(model_kwargs={"stream_options": {"include_usage": True}}) assert not llm.stream_usage ``` (and this model will stream token usage). Some options for this: - it's ok - make the `stream_usage` attribute bool or None - make an \_\_init\_\_ for ChatOpenAI, set a `._stream_usage` attribute and read `.stream_usage` from a property Open to other ideas as well.	3 months ago
Hakan Özdemir	c437b1aab7	[Partner]: Add metadata to stream response (#22716 ) Adds `response_metadata` to stream responses from OpenAI. This is returned with `invoke` normally, but wasn't implemented for `stream`. --------- Co-authored-by: Chester Curme <chester.curme@gmail.com>	3 months ago
Jacob Lee	181a61982f	anthropic[minor]: Adds streaming tool call support for Anthropic (#22687 ) Preserves string content chunks for non tool call requests for convenience. One thing - Anthropic events look like this: ``` RawContentBlockStartEvent(content_block=TextBlock(text='', type='text'), index=0, type='content_block_start') RawContentBlockDeltaEvent(delta=TextDelta(text='<thinking>\nThe', type='text_delta'), index=0, type='content_block_delta') RawContentBlockDeltaEvent(delta=TextDelta(text=' provide', type='text_delta'), index=0, type='content_block_delta') ... RawContentBlockStartEvent(content_block=ToolUseBlock(id='toolu_01GJ6x2ddcMG3psDNNe4eDqb', input={}, name='get_weather', type='tool_use'), index=1, type='content_block_start') RawContentBlockDeltaEvent(delta=InputJsonDelta(partial_json='', type='input_json_delta'), index=1, type='content_block_delta') ``` Note that `delta` has a `type` field. With this implementation, I'm dropping it because `merge_list` behavior will concatenate strings. We currently have `index` as a special field when merging lists, would it be worth adding `type` too? If so, what do we set as a context block chunk? `text` vs. `text_delta`/`tool_use` vs `input_json_delta`? CC @ccurme @efriis @baskaryan	3 months ago
ccurme	f40b2c6f9d	fireworks[patch]: add usage_metadata to (a)invoke and (a)stream (#22906 )	3 months ago
ccurme	73c76b9628	anthropic[patch]: always add tool_result type to ToolMessage content (#22721 ) Anthropic tool results can contain image data, which are typically represented with content blocks having `"type": "image"`. Currently, these content blocks are passed as-is as human/user messages to Anthropic, which raises BadRequestError as it expects a tool_result block to follow a tool_use. Here we update ChatAnthropic to nest the content blocks inside a tool_result content block. Example: ```python import base64 import httpx from langchain_anthropic import ChatAnthropic from langchain_core.messages import AIMessage, HumanMessage, ToolMessage from langchain_core.pydantic_v1 import BaseModel, Field # Fetch image image_url = "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg" image_data = base64.b64encode(httpx.get(image_url).content).decode("utf-8") class FetchImage(BaseModel): should_fetch: bool = Field(..., description="Whether an image is requested.") llm = ChatAnthropic(model="claude-3-sonnet-20240229").bind_tools([FetchImage]) messages = [ HumanMessage(content="Could you summon a beautiful image please?"), AIMessage( content=[ { "type": "tool_use", "id": "toolu_01Rn6Qvj5m7955x9m9Pfxbcx", "name": "FetchImage", "input": {"should_fetch": True}, }, ], tool_calls=[ { "name": "FetchImage", "args": {"should_fetch": True}, "id": "toolu_01Rn6Qvj5m7955x9m9Pfxbcx", }, ], ), ToolMessage( name="FetchImage", content=[ { "type": "image", "source": { "type": "base64", "media_type": "image/jpeg", "data": image_data, }, }, ], tool_call_id="toolu_01Rn6Qvj5m7955x9m9Pfxbcx", ), ] llm.invoke(messages) ``` Trace: https://smith.langchain.com/public/d27e4fc1-a96d-41e1-9f52-54f5004122db/r	3 months ago
Lucas Tucker	7114aed78f	docs: Standardize ChatGroq (#22751 ) Updated ChatGroq doc string as per issue https://github.com/langchain-ai/langchain/issues/22296:"langchain_groq: updated docstring for ChatGroq in langchain_groq to match that of the description (in the appendix) provided in issue https://github.com/langchain-ai/langchain/issues/22296. " Issue: This PR is in response to issue https://github.com/langchain-ai/langchain/issues/22296, and more specifically the ChatGroq model. In particular, this PR updates the docstring for langchain/libs/partners/groq/langchain_groq/chat_model.py by adding the following sections: Instantiate, Invoke, Stream, Async, Tool calling, Structured Output, and Response metadata. I used the template from the Anthropic implementation and referenced the Appendix of the original issue post. I also noted that: `usage_metadata `returns none for all ChatGroq models I tested; there is no mention of image input in the ChatGroq documentation; unlike that of ChatHuggingFace, `.stream(messages)` for ChatGroq returned blocks of output. --------- Co-authored-by: lucast2021 <lucast2021@headroyce.org> Co-authored-by: Bagatur <baskaryan@gmail.com>	3 months ago
Anush	e002c855bd	qdrant[patch]: Use collection_exists API instead of exceptions (#22764 ) ## Description Currently, the Qdrant integration relies on exceptions raised by [`get_collection` ](https://qdrant.tech/documentation/concepts/collections/#collection-info) to check if a collection exists. Using [`collection_exists`](https://qdrant.tech/documentation/concepts/collections/#check-collection-existence) is recommended to avoid missing any unhandled exceptions. This PR addresses this. ## Testing All integration and unit tests pass. No user-facing changes.	3 months ago
ccurme	42257b120f	partners: fix numpy dep (#22858 ) Following https://github.com/langchain-ai/langchain/pull/22813, which added python 3.12 to CI, here we update numpy accordingly in partner packages.	3 months ago
ccurme	b626c3ca23	groq[patch]: add usage_metadata to (a)invoke and (a)stream (#22834 )	3 months ago
ccurme	936aedd10c	mistral[patch]: add usage_metadata to (a)invoke and (a)stream (#22781 )	3 months ago
Lucas Tucker	cb79e80b0b	docs: standardize ChatHuggingFace (#22693 ) Updated ChatHuggingFace doc string as per issue #22296: "langchain_huggingface: updated docstring for ChatHuggingFace in langchain_huggingface to match that of the description (in the appendix) provided in issue #22296. " Issue: This PR is in response to issue #22296, and more specifically ChatHuggingFace model. In particular, this PR updates the docstring for langchain/libs/partners/hugging_face/langchain_huggingface/chat_models/huggingface.py by adding the following sections: Instantiate, Invoke, Stream, Async, Tool calling, and Response metadata. I used the template from the Anthropic implementation and referenced the Appendix of the original issue post. I also noted that: langchain_community hugging face llms do not work with langchain_huggingface's ChatHuggingFace model (at least for me); the .stream(messages) functionality of ChatHuggingFace only returned a block of response. --------- Co-authored-by: lucast2021 <lucast2021@headroyce.org> Co-authored-by: Bagatur <baskaryan@gmail.com>	3 months ago
ccurme	f9fdca6cc2	openai: add `parallel_tool_calls` to api ref (#22746 ) ![Screenshot 2024-06-10 at 1 41 24 PM](https://github.com/langchain-ai/langchain/assets/26529506/2626bf9c-41c6-4431-b2e1-f59de1e4e468)	3 months ago
Nithish Raghunandanan	f2f0e0e13d	couchbase: Add the initial version of Couchbase partner package (#22087 ) Co-authored-by: Nithish Raghunandanan <nithishr@users.noreply.github.com> Co-authored-by: Erick Friis <erick@langchain.dev>	3 months ago
ccurme	f32d57f6f0	anthropic: refactor streaming to use events api; add streaming usage metadata (#22628 ) - Refactor streaming to use raw events; - Add `stream_usage` class attribute and kwarg to stream methods that, if True, will include separate chunks in the stream containing usage metadata. There are two ways to implement streaming with anthropic's python sdk. They have slight differences in how they surface usage metadata. 1. [Use helper functions](https://github.com/anthropics/anthropic-sdk-python?tab=readme-ov-file#streaming-helpers). This is what we are doing now. ```python count = 1 with client.messages.stream(params) as stream: for text in stream.text_stream: snapshot = stream.current_message_snapshot print(f"{count}: {snapshot.usage} -- {text}") count = count + 1 final_snapshot = stream.get_final_message() print(f"{count}: {final_snapshot.usage}") ``` ``` 1: Usage(input_tokens=8, output_tokens=1) -- Hello 2: Usage(input_tokens=8, output_tokens=1) -- ! 3: Usage(input_tokens=8, output_tokens=1) -- How 4: Usage(input_tokens=8, output_tokens=1) -- can 5: Usage(input_tokens=8, output_tokens=1) -- I 6: Usage(input_tokens=8, output_tokens=1) -- assist 7: Usage(input_tokens=8, output_tokens=1) -- you 8: Usage(input_tokens=8, output_tokens=1) -- today 9: Usage(input_tokens=8, output_tokens=1) -- ? 10: Usage(input_tokens=8, output_tokens=12) ``` To do this correctly, we need to emit a new chunk at the end of the stream containing the usage metadata. 2. [Handle raw events](https://github.com/anthropics/anthropic-sdk-python?tab=readme-ov-file#streaming-responses) ```python stream = client.messages.create(params, stream=True) count = 1 for event in stream: print(f"{count}: {event}") count = count + 1 ``` ``` 1: RawMessageStartEvent(message=Message(id='msg_01Vdyov2kADZTXqSKkfNJXcS', content=[], model='claude-3-haiku-20240307', role='assistant', stop_reason=None, stop_sequence=None, type='message', usage=Usage(input_tokens=8, output_tokens=1)), type='message_start') 2: RawContentBlockStartEvent(content_block=TextBlock(text='', type='text'), index=0, type='content_block_start') 3: RawContentBlockDeltaEvent(delta=TextDelta(text='Hello', type='text_delta'), index=0, type='content_block_delta') 4: RawContentBlockDeltaEvent(delta=TextDelta(text='!', type='text_delta'), index=0, type='content_block_delta') 5: RawContentBlockDeltaEvent(delta=TextDelta(text=' How', type='text_delta'), index=0, type='content_block_delta') 6: RawContentBlockDeltaEvent(delta=TextDelta(text=' can', type='text_delta'), index=0, type='content_block_delta') 7: RawContentBlockDeltaEvent(delta=TextDelta(text=' I', type='text_delta'), index=0, type='content_block_delta') 8: RawContentBlockDeltaEvent(delta=TextDelta(text=' assist', type='text_delta'), index=0, type='content_block_delta') 9: RawContentBlockDeltaEvent(delta=TextDelta(text=' you', type='text_delta'), index=0, type='content_block_delta') 10: RawContentBlockDeltaEvent(delta=TextDelta(text=' today', type='text_delta'), index=0, type='content_block_delta') 11: RawContentBlockDeltaEvent(delta=TextDelta(text='?', type='text_delta'), index=0, type='content_block_delta') 12: RawContentBlockStopEvent(index=0, type='content_block_stop') 13: RawMessageDeltaEvent(delta=Delta(stop_reason='end_turn', stop_sequence=None), type='message_delta', usage=MessageDeltaUsage(output_tokens=12)) 14: RawMessageStopEvent(type='message_stop') ``` Here we implement the second option, in part because it should make things easier when implementing streaming tool calls in the near future. This would add two new chunks to the stream-- one at the beginning and one at the end-- with blank content and containing usage metadata. We add kwargs to the stream methods and a class attribute allowing for this behavior to be toggled. I enabled it by default. If we merge this we can add the same kwargs / attribute to OpenAI. Usage: ```python from langchain_anthropic import ChatAnthropic model = ChatAnthropic( model="claude-3-haiku-20240307", temperature=0 ) full = None for chunk in model.stream("hi"): full = chunk if full is None else full + chunk print(chunk) print(f"\nFull: {full}") ``` ``` content='' id='run-8a20843f-25c7-4025-ad72-9add395899e3' usage_metadata={'input_tokens': 8, 'output_tokens': 0, 'total_tokens': 8} content='Hello' id='run-8a20843f-25c7-4025-ad72-9add395899e3' content='!' id='run-8a20843f-25c7-4025-ad72-9add395899e3' content=' How' id='run-8a20843f-25c7-4025-ad72-9add395899e3' content=' can' id='run-8a20843f-25c7-4025-ad72-9add395899e3' content=' I' id='run-8a20843f-25c7-4025-ad72-9add395899e3' content=' assist' id='run-8a20843f-25c7-4025-ad72-9add395899e3' content=' you' id='run-8a20843f-25c7-4025-ad72-9add395899e3' content=' today' id='run-8a20843f-25c7-4025-ad72-9add395899e3' content='?' id='run-8a20843f-25c7-4025-ad72-9add395899e3' content='' id='run-8a20843f-25c7-4025-ad72-9add395899e3' usage_metadata={'input_tokens': 0, 'output_tokens': 12, 'total_tokens': 12} Full: content='Hello! How can I assist you today?' id='run-8a20843f-25c7-4025-ad72-9add395899e3' usage_metadata={'input_tokens': 8, 'output_tokens': 12, 'total_tokens': 20} ```	3 months ago
seyf97	2904c50cd5	openai[patch]: correct grammar in exception message in embeddings/base.py (#22629 ) Correct the grammar error for missing transformers package ValueError	3 months ago
Anush	80560419b0	qdrant[patch]: Make path optional in from_existing_collection() (#21875 ) ## Description The `path` param is used to specify the local persistence directory, which isn't required if using Qdrant server. This is a breaking but necessary change.	3 months ago
ccurme	b57aa89f34	multiple: implement ls_params (#22621 ) implement ls_params for ai21, fireworks, groq.	3 months ago
ccurme	c1ef731503	anthropic: update attribute name and alias (#22625 ) update name to `stop_sequences` and alias to `stop` (instead of the other way around), since `stop_sequences` is the name used by anthropic.	3 months ago
ccurme	3999761201	multiple: add `stop` attribute (#22573 )	3 months ago
ccurme	e08879147b	Revert "anthropic: stream token usage" (#22624 ) Reverts langchain-ai/langchain#20180	3 months ago
Bagatur	0d495f3f63	anthropic: stream token usage (#20180 ) open to other ideas <img width="1181" alt="Screenshot 2024-04-08 at 5 34 08 PM" src="https://github.com/langchain-ai/langchain/assets/22008038/03eb11c4-5eb5-43e3-9109-a13f76098fa4"> --------- Co-authored-by: Chester Curme <chester.curme@gmail.com>	3 months ago
Satyam Kumar	17b486a37b	openai, azure: update model_name in ChatResult to use name from API response (#22569 ) The response.get("model", self.model_name) checks if the model key exists in the response dictionary. If it does, it uses that value; otherwise, it uses self.model_name. 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" - [ ] 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! - [ ] 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. - [ ] 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/ 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. --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	3 months ago
ccurme	1925bde32e	together: bump langchain-core (#22616 ) langchain-together depends on langchain-openai ^0.1.8 langchain-openai 0.1.8 has langchain-core >= 0.2.2 Here we bump langchain-core to 0.2.2, just to pass minimum dependency version tests.	3 months ago
ccurme	35f4aa927b	together[patch]: Release 0.1.3 (#22615 )	3 months ago
Ethan Yang	29064848f9	[Community]add option to delete the prompt from HF output (#22225 ) This will help to solve pattern mismatching issue when parsing the output in Agent. https://github.com/langchain-ai/langchain/issues/21912	3 months ago
Bagatur	b2daba37c7	nomic[patch]: Release 0.1.2 (#22561 )	3 months ago
Zach Nussbaum	14f3014cce	embeddings: nomic embed vision (#22482 ) Thank you for contributing to LangChain! Description: Adds Langchain support for Nomic Embed Vision Twitter handle: nomic_ai,zach_nussbaum - [x] 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. - [ ] 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/ 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. --------- Co-authored-by: Lance Martin <122662504+rlancemartin@users.noreply.github.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	3 months ago
Erick Friis	4050d6ea2b	huggingface: remove text-generation dep (#22543 )	3 months ago
Erick Friis	a6fc74f379	ai21: fix core version (#22544 )	3 months ago
Asaf Joseph Gardin	75cba742e5	ai21: fix ai21 unittests (#22526 ) Co-authored-by: Asaf Gardin <asafg@ai21.com> Co-authored-by: Erick Friis <erick@langchain.dev>	3 months ago
Bagatur	cb183a9bf1	docs: update anthropic chat model (#22483 ) Related to #22296 And update anthropic to accept base_url	4 months ago
Erick Friis	d700ce8545	robocorp: typo (#22509 )	4 months ago
Erick Friis	39fd44579a	robocorp: release 0.0.9.post1 (#22507 )	4 months ago
Erick Friis	339e3b7f55	ai21: release 0.1.6 (#22508 )	4 months ago
ccurme	3c53cea760	together, upstage: bump minimum langchain-openai version (#22505 )	4 months ago
Bagatur	efcb04f84b	mongodb[patch]: Release 0.1.6 (#22501 )	4 months ago
Bagatur	222b1ba112	groq[patch]: Release 0.1.5 (#22500 )	4 months ago
Bagatur	f021be510e	milvus[patch]: Release 0.1.1 (#22499 )	4 months ago
Bagatur	64d68c17cd	upstage[patch]: Release 0.1.6 (#22498 )	4 months ago
Bagatur	8e86080def	mistralai[patch]: Release 0.1.8 (#22494 )	4 months ago
Bagatur	e850de2422	huggingface[patch]: release 0.0.2 (#22493 )	4 months ago
Joydeep Banik Roy	3796672c67	community, milvus, pinecone, qdrant, mongo: Broadcast operation failure while using simsimd beyond v3.7.7 (#22271 ) - [ ] Packages affected: - community: fix `cosine_similarity` to support simsimd beyond 3.7.7 - partners/milvus: fix `cosine_similarity` to support simsimd beyond 3.7.7 - partners/mongodb: fix `cosine_similarity` to support simsimd beyond 3.7.7 - partners/pinecone: fix `cosine_similarity` to support simsimd beyond 3.7.7 - partners/qdrant: fix `cosine_similarity` to support simsimd beyond 3.7.7 - [ ] Broadcast operation failure while using simsimd beyond v3.7.7: - Description: I was using simsimd 4.3.1 and the unsupported operand type issue popped up. When I checked out the repo and ran the tests, they failed as well (have attached a screenshot for that). Looks like it is a variant of https://github.com/langchain-ai/langchain/issues/18022 . Prior to 3.7.7, simd.cdist returned an ndarray but now it returns simsimd.DistancesTensor which is ineligible for a broadcast operation with numpy. With this change, it also remove the need to explicitly cast `Z` to numpy array - Issue: #19905 - Dependencies: No - Twitter handle: https://x.com/GetzJoydeep <img width="1622" alt="Screenshot 2024-05-29 at 2 50 00 PM" src="https://github.com/langchain-ai/langchain/assets/31132555/fb27b383-a9ae-4a6f-b355-6d503b72db56"> - [ ] Considerations: 1. I started with community but since similar changes were there in Milvus, MongoDB, Pinecone, and QDrant so I modified their files as well. If touching multiple packages in one PR is not the norm, then I can remove them from this PR and raise separate ones 2. I have run and verified that the tests work. Since, only MongoDB had tests, I ran theirs and verified it works as well. Screenshots attached : <img width="1573" alt="Screenshot 2024-05-29 at 2 52 13 PM" src="https://github.com/langchain-ai/langchain/assets/31132555/ce87d1ea-19b6-4900-9384-61fbc1a30de9"> <img width="1614" alt="Screenshot 2024-05-29 at 3 33 51 PM" src="https://github.com/langchain-ai/langchain/assets/31132555/6ce1d679-db4c-4291-8453-01028ab2dca5"> I have added a test for simsimd. I feel it may not go well with the CI/CD setup as installing simsimd is not a dependency requirement. I have just imported simsimd to ensure simsimd cosine similarity is invoked. However, its not a good approach. Suggestions are welcome and I can make the required changes on the PR. Please provide guidance on the same as I am new to the community. --------- Co-authored-by: Bagatur <baskaryan@gmail.com> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	4 months ago
Michal Gregor	98b2e7b195	huggingface[patch]: Support for HuggingFacePipeline in ChatHuggingFace. (#22194 ) - Description: Added support for using HuggingFacePipeline in ChatHuggingFace (previously it was only usable with API endpoints, probably by oversight). - Issue: #19997 - Dependencies: none - Twitter handle: none --------- Co-authored-by: Bagatur <baskaryan@gmail.com> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	4 months ago
Miroslav	cbd5720011	huggingface[patch]: Skip Login to HuggingFaceHub when token is not set (#22365 )	4 months ago
Bagatur	678a19a5f7	infra: bump anthropic mypy 1 (#22373 )	4 months ago

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535 Commits (93d0ad97fed9b01ffc7cf79497e9d82e0a1e5f2d)