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harrison/alpaca
nc/poe-handler-chat-model
nc/poe-handler
harrison/mrkl-parser
harrison/agent-experiments
harrison/replicate
harrison/chat-chain
harrison/update-wandb
harrison/debug
harrison/qasper
harrison/dbpedia
harrison/changes
jeremy/guardrails
nc/guardrails-error-handling
harrison/guardrails
harrison/use-output-parsers
John-Church-guard
agent_evaluation
harrison/kor-chain
harrison/inference-api
ankush/callback-refactor
harrison/eval
harrison/audio
ankush/prompt-abstractions
harrison/memory-chat
harrison/indexes
ankush/partial-prompt-apply
harrison/sagemaker
harrison/datetime
harrison/openapiagent
harrison/paged-pdf
harrison/pswsl
ankush/example-runner
harrison/guards
scad/api-chain
harrison/prompt-bugs
harrison/sql-agent
harrison/pinecone-try-except
harrison/callback-updates
harrison/map-rerank
harrison/combine-docs-parse
harrison/azure-rfc
harrison/sequential_chain_from_prompts
harrison/agent-refactor
harrison/agent_intermediate_steps
harrison/agent_multi_inputs
harrison/promot-mrkl
harrison/fix_logging_api
harrison/use_output_parser
harrison/track_intermediate_steps
harrison/sql_error
harrison/logging_to_file
harrison/output_parser
harrison/flexible_model_args
harrison/agent-improvements
harrison/router_docs
harrison/docs
samantha/add_llm_to_example
harrison/reorg_smart_chains
mako-templates
harrison/save_metadatas
harrison/router
harrison/custom_pipeline
harrison/chain_pipeline
harrison/prompts_docs
harrison/attempt_citing_in_prompt
harrison/load_prompt
harrison/prompts_take_2
harrison/ape
harrison/prompt_examples
harrison/add_dependencies
langchain-ai21==0.1.4
langchain-ai21==0.1.5
langchain-ai21==0.1.6
langchain-ai21==0.1.7
langchain-airbyte==0.1.1
langchain-anthropic==0.1.12
langchain-anthropic==0.1.13
langchain-anthropic==0.1.14rc1
langchain-anthropic==0.1.14rc2
langchain-anthropic==0.1.15
langchain-anthropic==0.1.16
langchain-anthropic==0.1.17
langchain-anthropic==0.1.18
langchain-anthropic==0.1.19
langchain-anthropic==0.1.20
langchain-anthropic==0.1.21
langchain-anthropic==0.1.22
langchain-anthropic==0.1.23
langchain-anthropic==0.2.0
langchain-anthropic==0.2.0.dev0
langchain-anthropic==0.2.0.dev1
langchain-anthropic==0.2.1
langchain-anthropic==0.2.2
langchain-anthropic==0.2.3
langchain-azure-dynamic-sessions==0.1.0
langchain-azure-dynamic-sessions==0.1.0rc0
langchain-azure-dynamic-sessions==0.2.0
langchain-box==0.1.0
langchain-box==0.2.0
langchain-box==0.2.1
langchain-chroma==0.1.1
langchain-chroma==0.1.2
langchain-chroma==0.1.4
langchain-cli==0.0.22
langchain-cli==0.0.23
langchain-cli==0.0.24
langchain-cli==0.0.25
langchain-cli==0.0.26
langchain-cli==0.0.27
langchain-cli==0.0.28
langchain-cli==0.0.29
langchain-cli==0.0.30
langchain-cli==0.0.31
langchain-community==0.0.35
langchain-community==0.0.36
langchain-community==0.0.37
langchain-community==0.0.38
langchain-community==0.2.0
langchain-community==0.2.0rc1
langchain-community==0.2.1
langchain-community==0.2.10
langchain-community==0.2.11
langchain-community==0.2.12
langchain-community==0.2.13
langchain-community==0.2.14
langchain-community==0.2.15
langchain-community==0.2.16
langchain-community==0.2.17
langchain-community==0.2.2
langchain-community==0.2.3
langchain-community==0.2.4
langchain-community==0.2.5
langchain-community==0.2.6
langchain-community==0.2.7
langchain-community==0.2.9
langchain-community==0.3.0
langchain-community==0.3.0.dev1
langchain-community==0.3.0.dev2
langchain-community==0.3.1
langchain-core==0.1.47
langchain-core==0.1.48
langchain-core==0.1.50
langchain-core==0.1.51
langchain-core==0.1.52
langchain-core==0.2.0
langchain-core==0.2.0rc1
langchain-core==0.2.1
langchain-core==0.2.10
langchain-core==0.2.11
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langchain-core==0.2.27
langchain-core==0.2.28
langchain-core==0.2.29
langchain-core==0.2.29rc1
langchain-core==0.2.2rc1
langchain-core==0.2.3
langchain-core==0.2.30
langchain-core==0.2.31
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langchain-core==0.2.37
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langchain-core==0.2.5
langchain-core==0.2.6
langchain-core==0.2.7
langchain-core==0.2.8
langchain-core==0.2.9
langchain-core==0.3.0
langchain-core==0.3.0.dev1
langchain-core==0.3.0.dev2
langchain-core==0.3.0.dev3
langchain-core==0.3.0.dev4
langchain-core==0.3.0.dev5
langchain-core==0.3.1
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langchain-core==0.3.3
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langchain-core==0.3.5
langchain-core==0.3.6
langchain-core==0.3.7
langchain-core==0.3.8
langchain-core==0.3.9
langchain-couchbase==0.0.1
langchain-couchbase==0.1.0
langchain-couchbase==0.1.1
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langchain-experimental==0.3.0.dev1
langchain-experimental==0.3.1
langchain-fireworks==0.1.3
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langchain-fireworks==0.1.7
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langchain-fireworks==0.2.0.dev0
langchain-fireworks==0.2.0.dev1
langchain-fireworks==0.2.0.dev2
langchain-fireworks==0.2.1
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langchain-groq==0.2.0.dev1
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langchain-huggingface==0.0.3
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langchain-huggingface==0.1.0.dev1
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langchain-ibm==0.1.6
langchain-ibm==0.1.7
langchain-ibm==0.1.8
langchain-ibm==0.1.9
langchain-milvus==0.1.0
langchain-milvus==0.1.1
langchain-milvus==0.1.2
langchain-milvus==0.1.3
langchain-milvus==0.1.4
langchain-milvus==0.1.5
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langchain-mistralai==0.1.11
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langchain-mistralai==0.1.13
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langchain-mistralai==0.1.7
langchain-mistralai==0.1.8
langchain-mistralai==0.1.9
langchain-mistralai==0.2.0
langchain-mistralai==0.2.0.dev1
langchain-mongodb==0.1.4
langchain-mongodb==0.1.5
langchain-mongodb==0.1.6
langchain-mongodb==0.1.7
langchain-mongodb==0.1.8
langchain-mongodb==0.1.9
langchain-mongodb==0.2.0
langchain-mongodb==0.2.0.dev1
langchain-nomic==0.1.0
langchain-nomic==0.1.1
langchain-nomic==0.1.2
langchain-nomic==0.1.3
langchain-ollama==0.1.0
langchain-ollama==0.1.1
langchain-ollama==0.1.2
langchain-ollama==0.1.3
langchain-ollama==0.2.0
langchain-ollama==0.2.0.dev1
langchain-openai==0.1.10
langchain-openai==0.1.11
langchain-openai==0.1.12
langchain-openai==0.1.13
langchain-openai==0.1.14
langchain-openai==0.1.15
langchain-openai==0.1.16
langchain-openai==0.1.17
langchain-openai==0.1.19
langchain-openai==0.1.20
langchain-openai==0.1.21
langchain-openai==0.1.21rc1
langchain-openai==0.1.21rc2
langchain-openai==0.1.22
langchain-openai==0.1.23
langchain-openai==0.1.24
langchain-openai==0.1.25
langchain-openai==0.1.5
langchain-openai==0.1.6
langchain-openai==0.1.7
langchain-openai==0.1.8
langchain-openai==0.1.8rc1
langchain-openai==0.1.9
langchain-openai==0.2.0
langchain-openai==0.2.0.dev0
langchain-openai==0.2.0.dev1
langchain-openai==0.2.0.dev2
langchain-openai==0.2.1
langchain-openai==0.2.2
langchain-pinecone==0.1.1
langchain-pinecone==0.1.2
langchain-pinecone==0.1.3
langchain-pinecone==0.2.0
langchain-pinecone==0.2.0.dev1
langchain-prompty==0.0.1
langchain-prompty==0.0.2
langchain-prompty==0.0.3
langchain-prompty==0.1.0
langchain-qdrant==0.0.1
langchain-qdrant==0.1.0
langchain-qdrant==0.1.1
langchain-qdrant==0.1.2
langchain-qdrant==0.1.3
langchain-qdrant==0.1.4
langchain-qdrant==0.2.0.dev1
langchain-robocorp==0.0.10
langchain-robocorp==0.0.10.post1
langchain-robocorp==0.0.6
langchain-robocorp==0.0.7
langchain-robocorp==0.0.8
langchain-robocorp==0.0.9
langchain-robocorp==0.0.9.post1
langchain-text-splitters==0.0.2
langchain-text-splitters==0.2.0
langchain-text-splitters==0.2.1
langchain-text-splitters==0.2.2
langchain-text-splitters==0.2.4
langchain-text-splitters==0.3.0
langchain-text-splitters==0.3.0.dev0
langchain-text-splitters==0.3.0.dev1
langchain-together==0.1.1
langchain-together==0.1.2
langchain-together==0.1.3
langchain-together==0.1.4
langchain-together==0.1.5
langchain-unstructured==0.1.0
langchain-unstructured==0.1.1
langchain-unstructured==0.1.2
langchain-unstructured==0.1.4
langchain-unstructured==0.1.5
langchain-upstage==0.1.4
langchain-upstage==0.1.5
langchain-voyageai==0.1.1
langchain-voyageai==0.1.2
langchain==0.1.17
langchain==0.1.19
langchain==0.1.20
langchain==0.2.0
langchain==0.2.0rc1
langchain==0.2.0rc2
langchain==0.2.1
langchain==0.2.10
langchain==0.2.11
langchain==0.2.12
langchain==0.2.13
langchain==0.2.14
langchain==0.2.15
langchain==0.2.16
langchain==0.2.2
langchain==0.2.3
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langchain==0.2.6
langchain==0.2.7
langchain==0.2.8
langchain==0.2.9
langchain==0.3.0
langchain==0.3.0.dev1
langchain==0.3.0.dev2
langchain==0.3.1
langchain==0.3.2
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${ noResults }
9937 Commits (3d54784e6df13d45a798f5b97cde34a7f97efc3b)
Author | SHA1 | Message | Date |
---|---|---|---|
bilk0h |
3d54784e6d
|
text-splitters: Fix/recursive json splitter data persistence issue (#21529)
Thank you for contributing to LangChain! **Description:** Noticed an issue with when I was calling `RecursiveJsonSplitter().split_json()` multiple times that I was getting weird results. I found an issue where `chunks` list in the `_json_split` method. If chunks is not provided when _json_split (which is the case when split_json calls _json_split) then the same list is used for subsequent calls to `_json_split`. You can see this in the test case i also added to this commit. Output should be: ``` [{'a': 1, 'b': 2}] [{'c': 3, 'd': 4}] ``` Instead you get: ``` [{'a': 1, 'b': 2}] [{'a': 1, 'b': 2, 'c': 3, 'd': 4}] ``` --------- Co-authored-by: Nuno Campos <nuno@langchain.dev> Co-authored-by: isaac hershenson <ihershenson@hmc.edu> Co-authored-by: Isaac Francisco <78627776+isahers1@users.noreply.github.com> |
4 months ago |
Yuki Watanabe |
9ab7a6df39
|
docs: Overhaul Databricks components documentation (#22884)
**Description:** Documentation at [integrations/llms/databricks](https://python.langchain.com/v0.2/docs/integrations/llms/databricks/) is not up-to-date and includes examples about chat model and embeddings, which should be located in the different corresponding subdirectories. This PR split the page into correct scope and overhaul the contents. **Note**: This PR might be hard to review on the diffs view, please use the following preview links for the changed pages. - `ChatDatabricks`: https://langchain-git-fork-b-step62-chat-databricks-doc-langchain.vercel.app/v0.2/docs/integrations/chat/databricks/ - `Databricks`: https://langchain-git-fork-b-step62-chat-databricks-doc-langchain.vercel.app/v0.2/docs/integrations/llms/databricks/ - `DatabricksEmbeddings`: https://langchain-git-fork-b-step62-chat-databricks-doc-langchain.vercel.app/v0.2/docs/integrations/text_embedding/databricks/ - [x] **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/ --------- Signed-off-by: B-Step62 <yuki.watanabe@databricks.com> |
4 months ago |
鹿鹿鹿鲨 |
6b46b5e9ce
|
community: add **request_kwargs and expect TimeError AsyncHtmlLoader (#23068)
- **Description:** add `**request_kwargs` and expect `TimeError` in `_fetch` function for AsyncHtmlLoader. This allows you to fill in the kwargs parameter when using the `load()` method of the `AsyncHtmlLoader` class. Co-authored-by: Yucolu <yucolu@tencent.com> |
4 months ago |
Leonid Ganeline |
109a70fc64
|
ibm: docstrings (#23149)
Added missed docstrings. Format docstrings to the consistent format (used in the API Reference) |
4 months ago |
Ryan Elston |
86ee4f0daa
|
text-splitters: Introduce Experimental Markdown Syntax Splitter (#22257)
#### Description This MR defines a `ExperimentalMarkdownSyntaxTextSplitter` class. The main goal is to replicate the functionality of the original `MarkdownHeaderTextSplitter` which extracts the header stack as metadata but with one critical difference: it keeps the whitespace of the original text intact. This draft reimplements the `MarkdownHeaderTextSplitter` with a very different algorithmic approach. Instead of marking up each line of the text individually and aggregating them back together into chunks, this method builds each chunk sequentially and applies the metadata to each chunk. This makes the implementation simpler. However, since it's designed to keep white space intact its not a full drop in replacement for the original. Since it is a radical implementation change to the original code and I would like to get feedback to see if this is a worthwhile replacement, should be it's own class, or is not a good idea at all. Note: I implemented the `return_each_line` parameter but I don't think it's a necessary feature. I'd prefer to remove it. This implementation also adds the following additional features: - Splits out code blocks and includes the language in the `"Code"` metadata key - Splits text on the horizontal rule `---` as well - The `headers_to_split_on` parameter is now optional - with sensible defaults that can be overridden. #### Issue Keeping the whitespace keeps the paragraphs structure and the formatting of the code blocks intact which allows the caller much more flexibility in how they want to further split the individuals sections of the resulting documents. This addresses the issues brought up by the community in the following issues: - https://github.com/langchain-ai/langchain/issues/20823 - https://github.com/langchain-ai/langchain/issues/19436 - https://github.com/langchain-ai/langchain/issues/22256 #### Dependencies N/A #### Twitter handle @RyanElston --------- Co-authored-by: isaac hershenson <ihershenson@hmc.edu> |
4 months ago |
Bagatur |
93d0ad97fe
|
anthropic[patch]: test image input (#23155) | 4 months ago |
Leonid Ganeline |
3dfd055411
|
anthropic: docstrings (#23145)
Added missed docstrings. Format docstrings to the consistent format (used in the API Reference) |
4 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 |
4 months ago |
Bagatur |
e8a8286012
|
core[patch]: runnablewithchathistory from core.runnables (#23136) | 4 months ago |
Jacob Lee |
2ae718796e
|
docs[patch]: Fix typo in feedback (#23146) | 4 months ago |
Jacob Lee |
74749c909d
|
docs[patch]: Adds feedback input after thumbs up/down (#23141)
CC @baskaryan |
4 months ago |
Bagatur |
cf38981bb7
|
docs: use trim_messages in chatbot how to (#23139) | 4 months ago |
Vadym Barda |
b483bf5095
|
core[minor]: handle boolean data in draw_mermaid (#23135)
This change should address graph rendering issues for edges with boolean data Example from langgraph: ```python from typing import Annotated, TypedDict from langchain_core.messages import AnyMessage from langgraph.graph import END, START, StateGraph from langgraph.graph.message import add_messages class State(TypedDict): messages: Annotated[list[AnyMessage], add_messages] def branch(state: State) -> bool: return 1 + 1 == 3 graph_builder = StateGraph(State) graph_builder.add_node("foo", lambda state: {"messages": [("ai", "foo")]}) graph_builder.add_node("bar", lambda state: {"messages": [("ai", "bar")]}) graph_builder.add_conditional_edges( START, branch, path_map={True: "foo", False: "bar"}, then=END, ) app = graph_builder.compile() print(app.get_graph().draw_mermaid()) ``` Previous behavior: ```python AttributeError: 'bool' object has no attribute 'split' ``` Current behavior: ```python %%{init: {'flowchart': {'curve': 'linear'}}}%% graph TD; __start__[__start__]:::startclass; __end__[__end__]:::endclass; foo([foo]):::otherclass; bar([bar]):::otherclass; __start__ -. ('a',) .-> foo; foo --> __end__; __start__ -. ('b',) .-> bar; bar --> __end__; classDef startclass fill:#ffdfba; classDef endclass fill:#baffc9; classDef otherclass fill:#fad7de; ``` |
4 months ago |
Bagatur |
093ae04d58
|
core[patch]: Pin pydantic in py3.12.4 (#23130) | 4 months ago |
hmasdev |
ff0c06b1e5
|
langchain[patch]: fix `OutputType` of OutputParsers and fix legacy API in OutputParsers (#19792)
# Description This pull request aims to address specific issues related to the ambiguity and error-proneness of the output types of certain output parsers, as well as the absence of unit tests for some parsers. These issues could potentially lead to runtime errors or unexpected behaviors due to type mismatches when used, causing confusion for developers and users. Through clarifying output types, this PR seeks to improve the stability and reliability. Therefore, this pull request - fixes the `OutputType` of OutputParsers to be the expected type; - e.g. `OutputType` property of `EnumOutputParser` raises `TypeError`. This PR introduce a logic to extract `OutputType` from its attribute. - and fixes the legacy API in OutputParsers like `LLMChain.run` to the modern API like `LLMChain.invoke`; - Note: For `OutputFixingParser`, `RetryOutputParser` and `RetryWithErrorOutputParser`, this PR introduces `legacy` attribute with False as default value in order to keep the backward compatibility - and adds the tests for the `OutputFixingParser` and `RetryOutputParser`. The following table shows my expected output and the actual output of the `OutputType` of OutputParsers. I have used this table to fix `OutputType` of OutputParsers. | Class Name of OutputParser | My Expected `OutputType` (after this PR)| Actual `OutputType` [evidence](#evidence) (before this PR)| Fix Required | |---------|--------------|---------|--------| | BooleanOutputParser | `<class 'bool'>` | `<class 'bool'>` | NO | | CombiningOutputParser | `typing.Dict[str, Any]` | `TypeError` is raised | YES | | DatetimeOutputParser | `<class 'datetime.datetime'>` | `<class 'datetime.datetime'>` | NO | | EnumOutputParser(enum=MyEnum) | `MyEnum` | `TypeError` is raised | YES | | OutputFixingParser | The same type as `self.parser.OutputType` | `~T` | YES | | CommaSeparatedListOutputParser | `typing.List[str]` | `typing.List[str]` | NO | | MarkdownListOutputParser | `typing.List[str]` | `typing.List[str]` | NO | | NumberedListOutputParser | `typing.List[str]` | `typing.List[str]` | NO | | JsonOutputKeyToolsParser | `typing.Any` | `typing.Any` | NO | | JsonOutputToolsParser | `typing.Any` | `typing.Any` | NO | | PydanticToolsParser | `typing.Any` | `typing.Any` | NO | | PandasDataFrameOutputParser | `typing.Dict[str, Any]` | `TypeError` is raised | YES | | PydanticOutputParser(pydantic_object=MyModel) | `<class '__main__.MyModel'>` | `<class '__main__.MyModel'>` | NO | | RegexParser | `typing.Dict[str, str]` | `TypeError` is raised | YES | | RegexDictParser | `typing.Dict[str, str]` | `TypeError` is raised | YES | | RetryOutputParser | The same type as `self.parser.OutputType` | `~T` | YES | | RetryWithErrorOutputParser | The same type as `self.parser.OutputType` | `~T` | YES | | StructuredOutputParser | `typing.Dict[str, Any]` | `TypeError` is raised | YES | | YamlOutputParser(pydantic_object=MyModel) | `MyModel` | `~T` | YES | NOTE: In "Fix Required", "YES" means that it is required to fix in this PR while "NO" means that it is not required. # Issue No issues for this PR. # Twitter handle - [hmdev3](https://twitter.com/hmdev3) # Questions: 1. Is it required to create tests for legacy APIs `LLMChain.run` in the following scripts? - libs/langchain/tests/unit_tests/output_parsers/test_fix.py; - libs/langchain/tests/unit_tests/output_parsers/test_retry.py. 2. Is there a more appropriate expected output type than I expect in the above table? - e.g. the `OutputType` of `CombiningOutputParser` should be SOMETHING... # Actual outputs (before this PR) <div id='evidence'></div> <details><summary>Actual outputs</summary> ## Requirements - Python==3.9.13 - langchain==0.1.13 ```python Python 3.9.13 (tags/v3.9.13:6de2ca5, May 17 2022, 16:36:42) [MSC v.1929 64 bit (AMD64)] on win32 Type "help", "copyright", "credits" or "license" for more information. >>> import langchain >>> langchain.__version__ '0.1.13' >>> from langchain import output_parsers ``` ### `BooleanOutputParser` ```python >>> output_parsers.BooleanOutputParser().OutputType <class 'bool'> ``` ### `CombiningOutputParser` ```python >>> output_parsers.CombiningOutputParser(parsers=[output_parsers.DatetimeOutputParser(), output_parsers.CommaSeparatedListOutputParser()]).OutputType Traceback (most recent call last): File "<stdin>", line 1, in <module> File "D:\workspace\venv\lib\site-packages\langchain_core\output_parsers\base.py", line 160, in OutputType raise TypeError( TypeError: Runnable CombiningOutputParser doesn't have an inferable OutputType. Override the OutputType property to specify the output type. ``` ### `DatetimeOutputParser` ```python >>> output_parsers.DatetimeOutputParser().OutputType <class 'datetime.datetime'> ``` ### `EnumOutputParser` ```python >>> from enum import Enum >>> class MyEnum(Enum): ... a = 'a' ... b = 'b' ... >>> output_parsers.EnumOutputParser(enum=MyEnum).OutputType Traceback (most recent call last): File "<stdin>", line 1, in <module> File "D:\workspace\venv\lib\site-packages\langchain_core\output_parsers\base.py", line 160, in OutputType raise TypeError( TypeError: Runnable EnumOutputParser doesn't have an inferable OutputType. Override the OutputType property to specify the output type. ``` ### `OutputFixingParser` ```python >>> output_parsers.OutputFixingParser(parser=output_parsers.DatetimeOutputParser()).OutputType ~T ``` ### `CommaSeparatedListOutputParser` ```python >>> output_parsers.CommaSeparatedListOutputParser().OutputType typing.List[str] ``` ### `MarkdownListOutputParser` ```python >>> output_parsers.MarkdownListOutputParser().OutputType typing.List[str] ``` ### `NumberedListOutputParser` ```python >>> output_parsers.NumberedListOutputParser().OutputType typing.List[str] ``` ### `JsonOutputKeyToolsParser` ```python >>> output_parsers.JsonOutputKeyToolsParser(key_name='tool').OutputType typing.Any ``` ### `JsonOutputToolsParser` ```python >>> output_parsers.JsonOutputToolsParser().OutputType typing.Any ``` ### `PydanticToolsParser` ```python >>> from langchain.pydantic_v1 import BaseModel >>> class MyModel(BaseModel): ... a: int ... >>> output_parsers.PydanticToolsParser(tools=[MyModel, MyModel]).OutputType typing.Any ``` ### `PandasDataFrameOutputParser` ```python >>> output_parsers.PandasDataFrameOutputParser().OutputType Traceback (most recent call last): File "<stdin>", line 1, in <module> File "D:\workspace\venv\lib\site-packages\langchain_core\output_parsers\base.py", line 160, in OutputType raise TypeError( TypeError: Runnable PandasDataFrameOutputParser doesn't have an inferable OutputType. Override the OutputType property to specify the output type. ``` ### `PydanticOutputParser` ```python >>> output_parsers.PydanticOutputParser(pydantic_object=MyModel).OutputType <class '__main__.MyModel'> ``` ### `RegexParser` ```python >>> output_parsers.RegexParser(regex='$', output_keys=['a']).OutputType Traceback (most recent call last): File "<stdin>", line 1, in <module> File "D:\workspace\venv\lib\site-packages\langchain_core\output_parsers\base.py", line 160, in OutputType raise TypeError( TypeError: Runnable RegexParser doesn't have an inferable OutputType. Override the OutputType property to specify the output type. ``` ### `RegexDictParser` ```python >>> output_parsers.RegexDictParser(output_key_to_format={'a':'a'}).OutputType Traceback (most recent call last): File "<stdin>", line 1, in <module> File "D:\workspace\venv\lib\site-packages\langchain_core\output_parsers\base.py", line 160, in OutputType raise TypeError( TypeError: Runnable RegexDictParser doesn't have an inferable OutputType. Override the OutputType property to specify the output type. ``` ### `RetryOutputParser` ```python >>> output_parsers.RetryOutputParser(parser=output_parsers.DatetimeOutputParser()).OutputType ~T ``` ### `RetryWithErrorOutputParser` ```python >>> output_parsers.RetryWithErrorOutputParser(parser=output_parsers.DatetimeOutputParser()).OutputType ~T ``` ### `StructuredOutputParser` ```python >>> from langchain.output_parsers.structured import ResponseSchema >>> response_schemas = [ResponseSchema(name="foo",description="a list of strings",type="List[string]"),ResponseSchema(name="bar",description="a string",type="string"), ] >>> output_parsers.StructuredOutputParser.from_response_schemas(response_schemas).OutputType Traceback (most recent call last): File "<stdin>", line 1, in <module> File "D:\workspace\venv\lib\site-packages\langchain_core\output_parsers\base.py", line 160, in OutputType raise TypeError( TypeError: Runnable StructuredOutputParser doesn't have an inferable OutputType. Override the OutputType property to specify the output type. ``` ### `YamlOutputParser` ```python >>> output_parsers.YamlOutputParser(pydantic_object=MyModel).OutputType ~T ``` <div> --------- Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com> |
4 months ago |
Artem Mukhin |
e271f75bee
|
docs: Fix URL formatting in deprecation warnings (#23075)
**Description** Updated the URLs in deprecation warning messages. The URLs were previously written as raw strings and are now formatted to be clickable HTML links. Example of a broken link in the current API Reference: https://api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.extraction.create_extraction_chain_pydantic.html <img width="942" alt="Screenshot 2024-06-18 at 13 21 07" src="https://github.com/langchain-ai/langchain/assets/4854600/a1b1863c-cd03-4af2-a9bc-70375407fb00"> |
4 months ago |
Gabriel Petracca |
c6660df58e
|
community[minor]: Implement Doctran async execution (#22372)
**Description** The DoctranTextTranslator has an async transform function that was not implemented because [the doctran library](https://github.com/psychic-api/doctran) uses a sync version of the `execute` method. - I implemented the `DoctranTextTranslator.atransform_documents()` method using `asyncio.to_thread` to run the function in a separate thread. - I updated the example in the Notebook with the new async version. - The performance improvements can be appreciated when a big document is divided into multiple chunks. Relates to: - Issue #14645: https://github.com/langchain-ai/langchain/issues/14645 - Issue #14437: https://github.com/langchain-ai/langchain/issues/14437 - https://github.com/langchain-ai/langchain/pull/15264 --------- Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com> |
4 months ago |
Eugene Yurtsev |
aa6415aa7d
|
core[minor]: Support multiple keys in get_from_dict_or_env (#23086)
Support passing multiple keys for ge_from_dict_or_env |
4 months ago |
nold |
226802f0c4
|
community: add args_schema to SearxSearch (#22954)
This change adds args_schema (pydantic BaseModel) to SearxSearchRun for correct schema formatting on LLM function calls Issue: currently using SearxSearchRun with OpenAI function calling returns the following error "TypeError: SearxSearchRun._run() got an unexpected keyword argument '__arg1' ". This happens because the schema sent to the LLM is "input: '{"__arg1":"foobar"}'" while the method should be called with the "query" parameter. --------- Co-authored-by: Harrison Chase <hw.chase.17@gmail.com> |
4 months ago |
Bagatur |
01783d67fc
|
core[patch]: Release 0.2.9 (#23091) | 4 months ago |
Finlay Macklon |
616d06d7fe
|
community: glob multiple patterns when using DirectoryLoader (#22852)
- **Description:** Updated *community.langchain_community.document_loaders.directory.py* to enable the use of multiple glob patterns in the `DirectoryLoader` class. Now, the glob parameter is of type `list[str] | str` and still defaults to the same value as before. I updated the docstring of the class to reflect this, and added a unit test to *community.tests.unit_tests.document_loaders.test_directory.py* named `test_directory_loader_glob_multiple`. This test also shows an example of how to use the new functionality. - ~~Issue:~~**Discussion Thread:** https://github.com/langchain-ai/langchain/discussions/18559 - **Dependencies:** None - **Twitter handle:** N/a - [x] **Add tests and docs** - Added test (described above) - Updated class docstring - [x] **Lint and test** --------- Co-authored-by: isaac hershenson <ihershenson@hmc.edu> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com> Co-authored-by: Isaac Francisco <78627776+isahers1@users.noreply.github.com> |
4 months ago |
Eugene Yurtsev |
5564d9e404
|
core[patch]: Document BaseStore (#23082)
Add doc-string to BaseStore |
4 months ago |
Takuya Igei |
9f791b6ad5
|
core[patch],community[patch],langchain[patch]: `tenacity` dependency to version `>=8.1.0,<8.4.0` (#22973)
Fix https://github.com/langchain-ai/langchain/issues/22972. - [x] **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" - [x] **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! - [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. - [x] **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. |
4 months ago |
Raghav Dixit |
74c4cbb859
|
LanceDB example minor change (#23069)
Removed package version `0.6.13` in the example. |
4 months ago |
Bagatur |
ddfbca38df
|
docs: add trim_messages to chatbot (#23061) | 4 months ago |
Lance Martin |
931b41b30f
|
Update Fireworks link (#23058) | 4 months ago |
Leonid Ganeline |
6a66d8e2ca
|
docs: `AWS` platform page update (#23063)
Added a reference to the `GlueCatalogLoader` new document loader. |
4 months ago |
Raviraj |
858ce264ef
|
SemanticChunker : Feature Addition ("Semantic Splitting with gradient") (#22895)
```SemanticChunker``` currently provide three methods to split the texts semantically: - percentile - standard_deviation - interquartile I propose new method ```gradient```. In this method, the gradient of distance is used to split chunks along with the percentile method (technically) . This method is useful when chunks are highly correlated with each other or specific to a domain e.g. legal or medical. The idea is to apply anomaly detection on gradient array so that the distribution become wider and easy to identify boundaries in highly semantic data. I have tested this merge on a set of 10 domain specific documents (mostly legal). Details : - **Issue:** Improvement - **Dependencies:** NA - **Twitter handle:** [x.com/prajapat_ravi](https://x.com/prajapat_ravi) @hwchase17 --------- Co-authored-by: Raviraj Prajapat <raviraj.prajapat@sirionlabs.com> Co-authored-by: isaac hershenson <ihershenson@hmc.edu> |
4 months ago |
Raghav Dixit |
55705c0f5e
|
LanceDB integration update (#22869)
Added : - [x] relevance search (w/wo scores) - [x] maximal marginal search - [x] image ingestion - [x] filtering support - [x] hybrid search w reranking make test, lint_diff and format checked. |
4 months ago |
Chang Liu |
62c8a67f56
|
community: add KafkaChatMessageHistory (#22216)
Add chat history store based on Kafka. Files added: `libs/community/langchain_community/chat_message_histories/kafka.py` `docs/docs/integrations/memory/kafka_chat_message_history.ipynb` New issue to be created for future improvement: 1. Async method implementation. 2. Message retrieval based on timestamp. 3. Support for other configs when connecting to cloud hosted Kafka (e.g. add `api_key` field) 4. Improve unit testing & integration testing. |
4 months ago |
shimajiroxyz |
3e835a1aa1
|
langchain: add id_key option to EnsembleRetriever for metadata-based document merging (#22950)
**Description:** - What I changed - By specifying the `id_key` during the initialization of `EnsembleRetriever`, it is now possible to determine which documents to merge scores for based on the value corresponding to the `id_key` element in the metadata, instead of `page_content`. Below is an example of how to use the modified `EnsembleRetriever`: ```python retriever = EnsembleRetriever(retrievers=[ret1, ret2], id_key="id") # The Document returned by each retriever must keep the "id" key in its metadata. ``` - Additionally, I added a script to easily test the behavior of the `invoke` method of the modified `EnsembleRetriever`. - Why I changed - There are cases where you may want to calculate scores by treating Documents with different `page_content` as the same when using `EnsembleRetriever`. For example, when you want to ensemble the search results of the same document described in two different languages. - The previous `EnsembleRetriever` used `page_content` as the basis for score aggregation, making the above usage difficult. Therefore, the score is now calculated based on the specified key value in the Document's metadata. **Twitter handle:** @shimajiroxyz |
4 months ago |
mackong |
39f6c4169d
|
langchain[patch]: add tool messages formatter for tool calling agent (#22849)
- **Description:** add tool_messages_formatter for tool calling agent, make tool messages can be formatted in different ways for your LLM. - **Issue:** N/A - **Dependencies:** N/A |
4 months ago |
Lucas Tucker |
e25a5966b5
|
docs: Standardize DocumentLoader docstrings (#22932)
**Standardizing DocumentLoader docstrings (of which there are many)** This PR addresses issue #22866 and adds docstrings according to the issue's specified format (in the appendix) for files csv_loader.py and json_loader.py in langchain_community.document_loaders. In particular, the following sections have been added to both CSVLoader and JSONLoader: Setup, Instantiate, Load, Async load, and Lazy load. It may be worth adding a 'Metadata' section to the JSONLoader docstring to clarify how we want to extract the JSON metadata (using the `metadata_func` argument). The files I used to walkthrough the various sections were `example_2.json` from [HERE](https://support.oneskyapp.com/hc/en-us/articles/208047697-JSON-sample-files) and `hw_200.csv` from [HERE](https://people.sc.fsu.edu/~jburkardt/data/csv/csv.html). --------- Co-authored-by: lucast2021 <lucast2021@headroyce.org> Co-authored-by: isaac hershenson <ihershenson@hmc.edu> |
4 months ago |
Leonid Ganeline |
a56ff199a7
|
docs: embeddings classes (#22927)
Added a table with all Embedding classes. |
4 months ago |
Mohammad Mohtashim |
60ba02f5db
|
[Community]: Fixed DDG DuckDuckGoSearchResults Docstring (#22968)
- **Description:** A very small fix in the Docstring of `DuckDuckGoSearchResults` identified in the following issue. - **Issue:** #22961 --------- Co-authored-by: Harrison Chase <hw.chase.17@gmail.com> |
4 months ago |
Eun Hye Kim |
70761af8cf
|
community: Fix #22975 (Add SSL Verification Option to Requests Class in langchain_community) (#22977)
- **PR title**: "community: Fix #22975 (Add SSL Verification Option to Requests Class in langchain_community)" - **PR message**: - **Description:** - Added an optional verify parameter to the Requests class with a default value of True. - Modified the get, post, patch, put, and delete methods to include the verify parameter. - Updated the _arequest async context manager to include the verify parameter. - Added the verify parameter to the GenericRequestsWrapper class and passed it to the Requests class. - **Issue:** This PR fixes issue #22975. - **Dependencies:** No additional dependencies are required for this change. - **Twitter handle:** @lunara_x You can check this change with below code. ```python from langchain_openai.chat_models import ChatOpenAI from langchain.requests import RequestsWrapper from langchain_community.agent_toolkits.openapi import planner from langchain_community.agent_toolkits.openapi.spec import reduce_openapi_spec with open("swagger.yaml") as f: data = yaml.load(f, Loader=yaml.FullLoader) swagger_api_spec = reduce_openapi_spec(data) llm = ChatOpenAI(model='gpt-4o') swagger_requests_wrapper = RequestsWrapper(verify=False) # modified point superset_agent = planner.create_openapi_agent(swagger_api_spec, swagger_requests_wrapper, llm, allow_dangerous_requests=True, handle_parsing_errors=True) superset_agent.run( "Tell me the number and types of charts and dashboards available." ) ``` --------- Co-authored-by: Harrison Chase <hw.chase.17@gmail.com> |
4 months ago |
Mohammad Mohtashim |
bf839676c7
|
[Community]: FIxed the DocumentDBVectorSearch `_similarity_search_without_score` (#22970)
- **Description:** The PR #22777 introduced a bug in `_similarity_search_without_score` which was raising the `OperationFailure` error. The mistake was syntax error for MongoDB pipeline which has been corrected now. - **Issue:** #22770 |
4 months ago |
Nuno Campos |
f01f12ce1e
|
Include "no escape" and "inverted section" mustache vars in Prompt.input_variables and Prompt.input_schema (#22981) | 4 months ago |
Bella Be |
7a0b36501f
|
docs: Update how to docs for pydantic compatibility (#22983)
Add missing imports in docs from langchain_core.tools BaseTool --------- Co-authored-by: Eugene Yurtsev <eugene@langchain.dev> |
4 months ago |
Jacob Lee |
3b7b276f6f
|
docs[patch]: Adds evaluation sections (#23050)
Also want to add an index/rollup page to LangSmith docs to enable linking to a how-to category as a group (e.g. https://docs.smith.langchain.com/how_to_guides/evaluation/) CC @agola11 @hinthornw |
4 months ago |
Jacob Lee |
6605ae22f6
|
docs[patch]: Update docs links (#23013) | 4 months ago |
Bagatur |
c2b2e3266c
|
core[minor]: message transformer utils (#22752) | 4 months ago |
Qingchuan Hao |
c5e0acf6f0
|
docs: add bing search integration to agent (#22929)
- [x] **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/ |
4 months ago |
Anders Swanson |
aacc6198b9
|
community: OCI GenAI embedding batch size (#22986)
Thank you for contributing to LangChain! - [x] **PR title**: "community: OCI GenAI embedding batch size" - [x] **PR message**: - **Issue:** #22985 - [ ] **Add tests and docs**: N/A - [x] **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. --------- Signed-off-by: Anders Swanson <anders.swanson@oracle.com> Co-authored-by: Chester Curme <chester.curme@gmail.com> |
4 months ago |
Bagatur |
8235bae48e
|
core[patch]: Release 0.2.8 (#23012) | 4 months ago |
Bagatur |
5ee6e22983
|
infra: test all dependents on any change (#22994) | 4 months ago |
Nuno Campos |
bd4b68cd54
|
core: run_in_executor: Wrap StopIteration in RuntimeError (#22997)
- StopIteration can't be set on an asyncio.Future it raises a TypeError and leaves the Future pending forever so we need to convert it to a RuntimeError |
4 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> |
4 months ago |
Bob Lin |
14f0cdad58
|
docs: Add some 3rd party tutorials (#22931)
Langchain is very popular among developers in China, but there are still no good Chinese books or documents, so I want to add my own Chinese resources on langchain topics, hoping to give Chinese readers a better experience using langchain. This is not a translation of the official langchain documentation, but my understanding. --------- Co-authored-by: ccurme <chester.curme@gmail.com> |
4 months ago |
Jacob Lee |
893299c3c9
|
docs[patch]: Reorder streaming guide, add tags (#22993)
CC @hinthornw |
4 months ago |