120 Commits (cd00a87db732687d0d6a9ffdc1eb9f6f5ebc49b6)

Author	SHA1	Message	Date
Erick Friis	3a2eb6e12b	infra: add print rule to ruff (#16221) ... Added noqa for existing prints. Can slowly remove / will prevent more being intro'd	8 months ago
Eugene Yurtsev	780e84ae79	community[minor]: SQLDatabase Add fetch mode `cursor`, query parameters, query by selectable, expose execution options, and documentation (#17191) ... - **Description:** Improve `SQLDatabase` adapter component to promote code re-use, see [suggestion](https://github.com/langchain-ai/langchain/pull/16246#pullrequestreview-1846590962). - **Needed by:** GH-16246 - **Addressed to:** @baskaryan, @cbornet ## Details - Add `cursor` fetch mode - Accept SQL query parameters - Accept both `str` and SQLAlchemy selectables as query expression - Expose `execution_options` - Documentation page (notebook) about `SQLDatabase` [^1] See [About SQLDatabase](https://github.com/langchain-ai/langchain/blob/c1c7b763/docs/docs/integrations/tools/sql_database.ipynb). [^1]: Apparently there hasn't been any yet? --------- Co-authored-by: Andreas Motl <andreas.motl@crate.io>	8 months ago
Leonid Ganeline	563f325034	experimental[patch]: fixed import in `experimental` (#17078)	8 months ago
Giulio Zani	9f0b63dba0	experimental[patch]: Fixes issue #17060 (#17062) ... As described in issue #17060, in the case in which text has only one sentence the following function fails. Checking for that and adding a return case fixed the issue. ```python def split_text(self, text: str) -> List[str]: """Split text into multiple components.""" # Splitting the essay on '.', '?', and '!' single_sentences_list = re.split(r"(?<=[.?!])\s+", text) sentences = [ {"sentence": x, "index": i} for i, x in enumerate(single_sentences_list) ] sentences = combine_sentences(sentences) embeddings = self.embeddings.embed_documents( [x["combined_sentence"] for x in sentences] ) for i, sentence in enumerate(sentences): sentence["combined_sentence_embedding"] = embeddings[i] distances, sentences = calculate_cosine_distances(sentences) start_index = 0 # Create a list to hold the grouped sentences chunks = [] breakpoint_percentile_threshold = 95 breakpoint_distance_threshold = np.percentile( distances, breakpoint_percentile_threshold ) # If you want more chunks, lower the percentile cutoff indices_above_thresh = [ i for i, x in enumerate(distances) if x > breakpoint_distance_threshold ] # The indices of those breakpoints on your list # Iterate through the breakpoints to slice the sentences for index in indices_above_thresh: # The end index is the current breakpoint end_index = index # Slice the sentence_dicts from the current start index to the end index group = sentences[start_index : end_index + 1] combined_text = " ".join([d["sentence"] for d in group]) chunks.append(combined_text) # Update the start index for the next group start_index = index + 1 # The last group, if any sentences remain if start_index < len(sentences): combined_text = " ".join([d["sentence"] for d in sentences[start_index:]]) chunks.append(combined_text) return chunks ``` Co-authored-by: Giulio Zani <salamanderxing@Giulios-MBP.homenet.telecomitalia.it>	8 months ago
Bagatur	7d03d8f586	docs: fix docstring examples (#16889)	8 months ago
Bagatur	b0347f3e2b	docs: add csv use case (#16756)	8 months ago
Massimiliano Pronesti	1bc8d9a943	experimental[patch]: missing resolution strategy in anonymization (#16653) ... - **Description:** Presidio-based anonymizers are not working because `_remove_conflicts_and_get_text_manipulation_data` was being called without a conflict resolution strategy. This PR fixes this issue. In addition, it removes some mutable default arguments (antipattern). To reproduce the issue, just run the very first cell of this [notebook](https://python.langchain.com/docs/guides/privacy/2/) from langchain's documentation. <!-- Thank you for contributing to LangChain! Please title your PR "<package>: <description>", where <package> is whichever of langchain, community, core, experimental, etc. is being modified. Replace this entire comment with: - **Description:** a description of the change, - **Issue:** the issue # it fixes if applicable, - **Dependencies:** any dependencies required for this change, - **Twitter handle:** we announce bigger features on Twitter. If your PR gets announced, and you'd like a mention, we'll gladly shout you out! Please make sure your PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` from the root of the package you've modified to check this locally. See contribution guidelines for more information on how to write/run tests, lint, etc: https://python.langchain.com/docs/contributing/ 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. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. -->	8 months ago
Bagatur	bccb07f93e	core[patch]: simple prompt pretty printing (#15968)	8 months ago
Harrison Chase	20abe24819	experimental[minor]: Add semantic chunker (#15799)	9 months ago
Bagatur	baeac236b6	langchain[patch], experimental[patch]: update utilities imports (#15438)	9 months ago
Bagatur	1678d6ca17	langchain[patch], experimental[patch], docs: update tools imports (#15433)	9 months ago
Bagatur	fa5d49f2c1	docs, experimental[patch], langchain[patch], community[patch]: update storage imports (#15429) ... ran ```bash g grep -l "langchain.vectorstores" | xargs -L 1 sed -i '' "s/langchain\.vectorstores/langchain_community.vectorstores/g" g grep -l "langchain.document_loaders" | xargs -L 1 sed -i '' "s/langchain\.document_loaders/langchain_community.document_loaders/g" g grep -l "langchain.chat_loaders" | xargs -L 1 sed -i '' "s/langchain\.chat_loaders/langchain_community.chat_loaders/g" g grep -l "langchain.document_transformers" | xargs -L 1 sed -i '' "s/langchain\.document_transformers/langchain_community.document_transformers/g" g grep -l "langchain\.graphs" | xargs -L 1 sed -i '' "s/langchain\.graphs/langchain_community.graphs/g" g grep -l "langchain\.memory\.chat_message_histories" | xargs -L 1 sed -i '' "s/langchain\.memory\.chat_message_histories/langchain_community.chat_message_histories/g" gco master libs/langchain/tests/unit_tests/*/test_imports.py gco master libs/langchain/tests/unit_tests/**/test_public_api.py ```	9 months ago
Bagatur	480626dc99	docs, community[patch], experimental[patch], langchain[patch], cli[pa… (#15412) ... …tch]: import models from community ran ```bash git grep -l 'from langchain\.chat_models' | xargs -L 1 sed -i '' "s/from\ langchain\.chat_models/from\ langchain_community.chat_models/g" git grep -l 'from langchain\.llms' | xargs -L 1 sed -i '' "s/from\ langchain\.llms/from\ langchain_community.llms/g" git grep -l 'from langchain\.embeddings' | xargs -L 1 sed -i '' "s/from\ langchain\.embeddings/from\ langchain_community.embeddings/g" git checkout master libs/langchain/tests/unit_tests/llms git checkout master libs/langchain/tests/unit_tests/chat_models git checkout master libs/langchain/tests/unit_tests/embeddings/test_imports.py make format cd libs/langchain; make format cd ../experimental; make format cd ../core; make format ```	9 months ago
Bagatur	8e0d5813c2	langchain[patch], experimental[patch]: replace langchain.schema imports (#15410) ... Import from core instead. Ran: ```bash git grep -l 'from langchain.schema\.output_parser' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.output_parser/from\ langchain_core.output_parsers/g" git grep -l 'from langchain.schema\.messages' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.messages/from\ langchain_core.messages/g" git grep -l 'from langchain.schema\.document' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.document/from\ langchain_core.documents/g" git grep -l 'from langchain.schema\.runnable' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.runnable/from\ langchain_core.runnables/g" git grep -l 'from langchain.schema\.vectorstore' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.vectorstore/from\ langchain_core.vectorstores/g" git grep -l 'from langchain.schema\.language_model' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.language_model/from\ langchain_core.language_models/g" git grep -l 'from langchain.schema\.embeddings' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.embeddings/from\ langchain_core.embeddings/g" git grep -l 'from langchain.schema\.storage' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.storage/from\ langchain_core.stores/g" git checkout master libs/langchain/tests/unit_tests/schema/ make format cd libs/experimental make format cd ../langchain make format ```	9 months ago
Nuno Campos	eb5e250188	Propagate context vars in all classes/methods ... - Any direct usage of ThreadPoolExecutor or asyncio.run_in_executor needs manual handling of context vars	9 months ago
Leonid Ganeline	b2fd41331e	docs: docstrings `langchain_community` update (#14889) ... Addded missed docstrings. Fixed inconsistency in docstrings. **Note** CC @efriis There were PR errors on `langchain_experimental/prompt_injection_identifier/hugging_face_identifier.py` But, I didn't touch this file in this PR! Can it be some cache problems? I fixed this error.	9 months ago
Oleksandr Yaremchuk	d82a3828f2	Improve prompt injection detection (#14842) ... - **Description:** This is addition to [my previous PR](https://github.com/langchain-ai/langchain/pull/13930) with improvements to flexibility allowing different models and notebook to use ONNX runtime for faster speed. Since the last PR, [our model](https://huggingface.co/laiyer/deberta-v3-base-prompt-injection) got more than 660k downloads, and with the [public benchmark](https://huggingface.co/spaces/laiyer/prompt-injection-benchmark) showed much fewer false-positives than the previous one from deepset. Additionally, on the ONNX runtime, it can be running 3x faster on the CPU, which might be handy for builders using Langchain. **Issue:** N/A - **Dependencies:** N/A - **Tag maintainer:** N/A - **Twitter handle:** `@laiyer_ai`	9 months ago
Bagatur	ed58eeb9c5	community[major], core[patch], langchain[patch], experimental[patch]: Create langchain-community (#14463) ... Moved the following modules to new package langchain-community in a backwards compatible fashion: ``` mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community ``` Moved the following to core ``` mv langchain/langchain/utils/json_schema.py core/langchain_core/utils mv langchain/langchain/utils/html.py core/langchain_core/utils mv langchain/langchain/utils/strings.py core/langchain_core/utils cat langchain/langchain/utils/env.py >> core/langchain_core/utils/env.py rm langchain/langchain/utils/env.py ``` See .scripts/community_split/script_integrations.sh for all changes	10 months ago
Anish Nag	6da0cfea0e	experimental[patch]: SmartLLMChain Output Key Customization (#14466) ... **Description** The `SmartLLMChain` was was fixed to output key "resolution". Unfortunately, this prevents the ability to use multiple `SmartLLMChain` in a `SequentialChain` because of colliding output keys. This change simply gives the option the customize the output key to allow for sequential chaining. The default behavior is the same as the current behavior. Now, it's possible to do the following: ``` from langchain.chat_models import ChatOpenAI from langchain.prompts import PromptTemplate from langchain_experimental.smart_llm import SmartLLMChain from langchain.chains import SequentialChain joke_prompt = PromptTemplate( input_variables=["content"], template="Tell me a joke about {content}.", ) review_prompt = PromptTemplate( input_variables=["scale", "joke"], template="Rate the following joke from 1 to {scale}: {joke}" ) llm = ChatOpenAI(temperature=0.9, model_name="gpt-4-32k") joke_chain = SmartLLMChain(llm=llm, prompt=joke_prompt, output_key="joke") review_chain = SmartLLMChain(llm=llm, prompt=review_prompt, output_key="review") chain = SequentialChain( chains=[joke_chain, review_chain], input_variables=["content", "scale"], output_variables=["review"], verbose=True ) response = chain.run({"content": "chickens", "scale": "10"}) print(response) ``` --------- Co-authored-by: Erick Friis <erick@langchain.dev>	10 months ago
Erick Friis	b3f226e8f8	core[patch], langchain[patch], experimental[patch]: import CI (#14414)	10 months ago
Bagatur	b2280fd874	core[patch], langchain[patch]: fix required deps (#14373)	10 months ago
kavinraj A S	ab6b41937a	Fixed a typo in smart_llm prompt (#13052) ... <!-- Thank you for contributing to LangChain! Replace this entire comment with: - **Description:** a description of the change, - **Issue:** the issue # it fixes (if applicable), - **Dependencies:** any dependencies required for this change, - **Tag maintainer:** for a quicker response, tag the relevant maintainer (see below), - **Twitter handle:** we announce bigger features on Twitter. If your PR gets announced, and you'd like a mention, we'll gladly shout you out! Please make sure your PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` to check this locally. See contribution guidelines for more information on how to write/run tests, lint, etc: https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md If you're adding a new integration, please include: 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. It lives in `docs/extras` directory. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. -->	10 months ago
Lance Martin	66848871fc	Multi-modal RAG template (#14186) ... * OpenCLIP embeddings * GPT-4V --------- Co-authored-by: Erick Friis <erick@langchain.dev>	10 months ago
Eun Hye Kim	f758c8adc4	Fix #11737 issue (extra_tools option of create_pandas_dataframe_agent is not working) (#13203) ... - **Description:** Fix #11737 issue (extra_tools option of create_pandas_dataframe_agent is not working), - **Issue:** #11737 , - **Dependencies:** no, - **Tag maintainer:** @baskaryan, @eyurtsev, @hwchase17 I needed this method at work, so I modified it myself and used it. There is a similar issue(#11737) and PR(#13018) of @PyroGenesis, so I combined my code at the original PR. You may be busy, but it would be great help for me if you checked. Thank you. - **Twitter handle:** @lunara_x If you need an .ipynb example about this, please tag me. I will share what I am working on after removing any work-related content. --------- Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	10 months ago
Abdul	82102c99b3	langchain[patch]: Running SQLDatabaseChain adds prefix "SQLQuery:\n" (#14058) ... - **Issue:** https://github.com/langchain-ai/langchain/issues/12077 --------- Co-authored-by: Abdul Kader Maliyakkal <maliyakk@amazon.com>	10 months ago
James Braza	24385a00de	core[minor], langchain[patch], experimental[patch]: Added missing `py.typed` to `langchain_core` (#14143) ... See PR title. From what I can see, `poetry` will auto-include this. Please let me know if I am missing something here. --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	10 months ago
Lance Martin	cbe4753e1a	Update Open CLIP embd (#14155) ... Prior default model required a large amt of RAM and often crashed Jupyter ntbk kernel.	10 months ago
Jacob Lee	3328507f11	langchain[patch], experimental[minor]: Adds OllamaFunctions wrapper (#13330) ... CC @baskaryan @hwchase17 @jmorganca Having a bit of trouble importing `langchain_experimental` from a notebook, will figure it out tomorrow ~Ah and also is blocked by #13226~ --------- Co-authored-by: Lance Martin <lance@langchain.dev> Co-authored-by: Bagatur <baskaryan@gmail.com>	10 months ago
Leonid Ganeline	bf5787f58b	experimental[patch]: fixed namespace bug (#13585) ... It was : `from langchain.schema.prompts import BasePromptTemplate` but because of the breaking change in the ns, it is now `from langchain.schema.prompt_template import BasePromptTemplate` This bug prevents building the API Reference for the langchain_experimental	10 months ago
Johannes Foulds	fc40bd4cdb	AnthropicFunctions function_call compatibility (#13901) ... - **Description:** Updates to `AnthropicFunctions` to be compatible with the OpenAI `function_call` functionality. - **Issue:** The functionality to indicate `auto`, `none` and a forced function_call was not completely implemented in the existing code. - **Dependencies:** None - **Tag maintainer:** @baskaryan , and any of the other maintainers if needed. - **Twitter handle:** None I have specifically tested this functionality via AWS Bedrock with the Claude-2 and Claude-Instant models.	10 months ago
Oleksandr Yaremchuk	c0277d06e8	experimental[patch] Update prompt injection model (#13930) ... - **Description:** Existing model used for Prompt Injection is quite outdated but we fine-tuned and open-source a new model based on the same model deberta-v3-base from Microsoft - [laiyer/deberta-v3-base-prompt-injection](https://huggingface.co/laiyer/deberta-v3-base-prompt-injection). It supports more up-to-date injections and less prone to false-positives. - **Dependencies:** No - **Tag maintainer:** - - **Twitter handle:** @alex_yaremchuk --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	10 months ago
Bob Lin	e6ebde9688	experimental[patch]: Add experimental.agent imports (#13839) ... - **Description:** The experimental package needs to be compatible with the usage of importing agents For example, if i use `from langchain.agents import create_pandas_dataframe_agent`, running the program will prompt the following information: ``` Traceback (most recent call last): File "/Users/dongwm/test/main.py", line 1, in <module> from langchain.agents import create_pandas_dataframe_agent File "/Users/dongwm/test/venv/lib/python3.11/site-packages/langchain/agents/__init__.py", line 87, in __getattr__ raise ImportError( ImportError: create_pandas_dataframe_agent has been moved to langchain experimental. See https://github.com/langchain-ai/langchain/discussions/11680 for more information. Please update your import statement from: `langchain.agents.create_pandas_dataframe_agent` to `langchain_experimental.agents.create_pandas_dataframe_agent`. ``` But when I changed to `from langchain_experimental.agents import create_pandas_dataframe_agent`, it was actually wrong: ```python Traceback (most recent call last): File "/Users/dongwm/test/main.py", line 2, in <module> from langchain_experimental.agents import create_pandas_dataframe_agent ImportError: cannot import name 'create_pandas_dataframe_agent' from 'langchain_experimental.agents' (/Users/dongwm/test/venv/lib/python3.11/site-packages/langchain_experimental/agents/__init__.py) ``` I should use `from langchain_experimental.agents.agent_toolkits import create_pandas_dataframe_agent`. In order to solve the problem and make it compatible, I added additional import code to the langchain_experimental package. Now it can be like this Used `from langchain_experimental.agents import create_pandas_dataframe_agent` - **Twitter handle:** [lin_bob57617](https://twitter.com/lin_bob57617)	10 months ago
Bagatur	c61e30632e	BUG: more core fixes (#13665) ... Fix some circular deps: - move PromptValue into top level module bc both PromptTemplates and OutputParsers import - move tracer context vars to `tracers.context` and import them in functions in `callbacks.manager` - add core import tests	10 months ago
Martin Krasser	79ed66f870	EXPERIMENTAL Generic LLM wrapper to support chat model interface with configurable chat prompt format (#8295) ... ## Update 2023-09-08 This PR now supports further models in addition to Lllama-2 chat models. See [this comment](#issuecomment-1668988543) for further details. The title of this PR has been updated accordingly. ## Original PR description This PR adds a generic `Llama2Chat` model, a wrapper for LLMs able to serve Llama-2 chat models (like `LlamaCPP`, `HuggingFaceTextGenInference`, ...). It implements `BaseChatModel`, converts a list of chat messages into the [required Llama-2 chat prompt format](https://huggingface.co/blog/llama2#how-to-prompt-llama-2) and forwards the formatted prompt as `str` to the wrapped `LLM`. Usage example: ```python # uses a locally hosted Llama2 chat model llm = HuggingFaceTextGenInference( inference_server_url="http://127.0.0.1:8080/", max_new_tokens=512, top_k=50, temperature=0.1, repetition_penalty=1.03, ) # Wrap llm to support Llama2 chat prompt format. # Resulting model is a chat model model = Llama2Chat(llm=llm) messages = [ SystemMessage(content="You are a helpful assistant."), MessagesPlaceholder(variable_name="chat_history"), HumanMessagePromptTemplate.from_template("{text}"), ] prompt = ChatPromptTemplate.from_messages(messages) memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True) chain = LLMChain(llm=model, prompt=prompt, memory=memory) # use chat model in a conversation # ... ``` Also part of this PR are tests and a demo notebook. - Tag maintainer: @hwchase17 - Twitter handle: `@mrt1nz` --------- Co-authored-by: Erick Friis <erick@langchain.dev>	10 months ago
Bagatur	1c67db4c18	Move OAI assistants to langchain and add callbacks (#13236)	10 months ago
Lance Martin	d2e50b3108	Add Chroma multimodal cookbook (#12952) ... Pending: * https://github.com/chroma-core/chroma/pull/1294 * https://github.com/chroma-core/chroma/pull/1293 --------- Co-authored-by: Erick Friis <erick@langchain.dev> Co-authored-by: Bagatur <baskaryan@gmail.com>	11 months ago
Bagatur	8b2a82b5ce	Bagatur/docs smith context (#13139)	11 months ago
Bagatur	55aeff6777	oai assistant multiple actions (#13068)	11 months ago
Bagatur	57e19989f6	Bagatur/oai assistant (#13010)	11 months ago
Noam Gat	14e8c74736	LM Format Enforcer Integration + Sample Notebook (#12625) ... ## Description This PR adds support for [lm-format-enforcer](https://github.com/noamgat/lm-format-enforcer) to LangChain.  The library is similar to jsonformer / RELLM which are supported in Langchain, but has several advantages such as - Batching and Beam search support - More complete JSON Schema support - LLM has control over whitespace, improving quality - Better runtime performance due to only calling the LLM's generate() function once per generate() call. The integration is loosely based on the jsonformer integration in terms of project structure. ## Dependencies No compile-time dependency was added, but if `lm-format-enforcer` is not installed, a runtime error will occur if it is trying to be used. ## Tests Due to the integration modifying the internal parameters of the underlying huggingface transformer LLM, it is not possible to test without building a real LM, which requires internet access. So, similar to the jsonformer and RELLM integrations, the testing is via the notebook. ## Twitter Handle [@noamgat](https://twitter.com/noamgat) Looking forward to hearing feedback! --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	11 months ago
Predrag Gruevski	f94e24dfd7	Install and use `ruff format` instead of black for code formatting. (#12585) ... Best to review one commit at a time, since two of the commits are 100% autogenerated changes from running `ruff format`: - Install and use `ruff format` instead of black for code formatting. - Output of `ruff format .` in the `langchain` package. - Use `ruff format` in experimental package. - Format changes in experimental package by `ruff format`. - Manual formatting fixes to make `ruff .` pass.	11 months ago
Harrison Chase	0ca539eb85	Clean up deprecated agents and update __init__ in experimental (#12231) ... Update init paths in experimental	11 months ago
Shorthills AI	25c98dbba9	Fixed some grammatical and Exception types issues (#12015) ... Fixed some grammatical issues and Exception types. @baskaryan , @eyurtsev --------- Co-authored-by: Sanskar Tanwar <142409040+SanskarTanwarShorthillsAI@users.noreply.github.com> Co-authored-by: UpneetShorthillsAI <144228282+UpneetShorthillsAI@users.noreply.github.com> Co-authored-by: HarshGuptaShorthillsAI <144897987+HarshGuptaShorthillsAI@users.noreply.github.com> Co-authored-by: AdityaKalraShorthillsAI <143726711+AdityaKalraShorthillsAI@users.noreply.github.com> Co-authored-by: SakshiShorthillsAI <144228183+SakshiShorthillsAI@users.noreply.github.com>	11 months ago
Nikhil Jha	dff24285ea	Comprehend Moderation 0.2 (#11730) ... This PR replaces the previous `Intent` check with the new `Prompt Safety` check. The logic and steps to enable chain moderation via the Amazon Comprehend service, allowing you to detect and redact PII, Toxic, and Prompt Safety information in the LLM prompt or answer remains unchanged. This implementation updates the code and configuration types with respect to `Prompt Safety`. ### Usage sample ```python from langchain_experimental.comprehend_moderation import (BaseModerationConfig, ModerationPromptSafetyConfig, ModerationPiiConfig, ModerationToxicityConfig ) pii_config = ModerationPiiConfig( labels=["SSN"], redact=True, mask_character="X" ) toxicity_config = ModerationToxicityConfig( threshold=0.5 ) prompt_safety_config = ModerationPromptSafetyConfig( threshold=0.5 ) moderation_config = BaseModerationConfig( filters=[pii_config, toxicity_config, prompt_safety_config] ) comp_moderation_with_config = AmazonComprehendModerationChain( moderation_config=moderation_config, #specify the configuration client=comprehend_client, #optionally pass the Boto3 Client verbose=True ) template = """Question: {question} Answer:""" prompt = PromptTemplate(template=template, input_variables=["question"]) responses = [ "Final Answer: A credit card number looks like 1289-2321-1123-2387. A fake SSN number looks like 323-22-9980. John Doe's phone number is (999)253-9876.", "Final Answer: This is a really shitty way of constructing a birdhouse. This is fucking insane to think that any birds would actually create their motherfucking nests here." ] llm = FakeListLLM(responses=responses) llm_chain = LLMChain(prompt=prompt, llm=llm) chain = ( prompt | comp_moderation_with_config | {llm_chain.input_keys[0]: lambda x: x['output'] } | llm_chain | { "input": lambda x: x['text'] } | comp_moderation_with_config ) try: response = chain.invoke({"question": "A sample SSN number looks like this 123-456-7890. Can you give me some more samples?"}) except Exception as e: print(str(e)) else: print(response['output']) ``` ### Output ```python > Entering new AmazonComprehendModerationChain chain... Running AmazonComprehendModerationChain... Running pii Validation... Running toxicity Validation... Running prompt safety Validation... > Finished chain. > Entering new AmazonComprehendModerationChain chain... Running AmazonComprehendModerationChain... Running pii Validation... Running toxicity Validation... Running prompt safety Validation... > Finished chain. Final Answer: A credit card number looks like 1289-2321-1123-2387. A fake SSN number looks like XXXXXXXXXXXX John Doe's phone number is (999)253-9876. ``` --------- Co-authored-by: Jha <nikjha@amazon.com> Co-authored-by: Anjan Biswas <anjanavb@amazon.com> Co-authored-by: Anjan Biswas <84933469+anjanvb@users.noreply.github.com>	11 months ago
Erick Friis	95ae40ff90	Fix Anthropic Functions ainvoke (#12215) ... Removes custom `NotImplementedError` in experimental anthropic functions, allowing it to fallback on default `ainvoke` implementation.	11 months ago
Harrison Chase	ee69116761	move csv agent to langchain experimental (#12113)	11 months ago
Harrison Chase	03bf6ef473	add missing init files (#12114)	11 months ago
Bagatur	85302a9ec1	Add CI check that integration tests compile (#12090)	11 months ago
Predrag Gruevski	392df7b2e3	Type hints on varargs and kwargs that take anything should be `Any`. (#11950) ... Type hinting `*args` as `List[Any]` means that each positional argument should be a list. Type hinting `**kwargs` as `Dict[str, Any]` means that each keyword argument should be a dict of strings. This is almost never what we actually wanted, and doesn't seem to be what we want in any of the cases I'm replacing here.	11 months ago
Predrag Gruevski	dcd0392423	Upgrade to newer black (23.10) and ruff (first 0.1.x!) versions. (#11944) ... Minor lint dependency version upgrade to pick up latest functionality. Ruff's new v0.1 version comes with lots of nice features, like fix-safety guarantees and a preview mode for not-yet-stable features: https://astral.sh/blog/ruff-v0.1.0	11 months ago