mirror of
https://github.com/hwchase17/langchain.git
synced 2025-07-09 14:35:50 +00:00
parent
4c97a10bd0
commit
f91ce4eddf
6
libs/langserve/poetry.lock
generated
6
libs/langserve/poetry.lock
generated
@ -1626,7 +1626,7 @@ test = ["hatch", "ipykernel", "openapi-core (>=0.18.0,<0.19.0)", "openapi-spec-v
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[[package]]
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name = "langchain"
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version = "0.0.304"
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version = "0.0.305"
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description = "Building applications with LLMs through composability"
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optional = false
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python-versions = ">=3.8.1,<4.0"
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@ -1655,7 +1655,7 @@ clarifai = ["clarifai (>=9.1.0)"]
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cohere = ["cohere (>=4,<5)"]
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docarray = ["docarray[hnswlib] (>=0.32.0,<0.33.0)"]
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embeddings = ["sentence-transformers (>=2,<3)"]
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extended-testing = ["amazon-textract-caller (<2)", "anthropic (>=0.3.11,<0.4.0)", "arxiv (>=1.4,<2.0)", "assemblyai (>=0.17.0,<0.18.0)", "atlassian-python-api (>=3.36.0,<4.0.0)", "beautifulsoup4 (>=4,<5)", "bibtexparser (>=1.4.0,<2.0.0)", "cassio (>=0.1.0,<0.2.0)", "chardet (>=5.1.0,<6.0.0)", "dashvector (>=1.0.1,<2.0.0)", "esprima (>=4.0.1,<5.0.0)", "faiss-cpu (>=1,<2)", "feedparser (>=6.0.10,<7.0.0)", "geopandas (>=0.13.1,<0.14.0)", "gitpython (>=3.1.32,<4.0.0)", "gql (>=3.4.1,<4.0.0)", "html2text (>=2020.1.16,<2021.0.0)", "jinja2 (>=3,<4)", "jq (>=1.4.1,<2.0.0)", "lxml (>=4.9.2,<5.0.0)", "markdownify (>=0.11.6,<0.12.0)", "mwparserfromhell (>=0.6.4,<0.7.0)", "mwxml (>=0.3.3,<0.4.0)", "newspaper3k (>=0.2.8,<0.3.0)", "openai (>=0,<1)", "openai (>=0,<1)", "openapi-schema-pydantic (>=1.2,<2.0)", "pandas (>=2.0.1,<3.0.0)", "pdfminer-six (>=20221105,<20221106)", "pgvector (>=0.1.6,<0.2.0)", "psychicapi (>=0.8.0,<0.9.0)", "py-trello (>=0.19.0,<0.20.0)", "pymupdf (>=1.22.3,<2.0.0)", "pypdf (>=3.4.0,<4.0.0)", "pypdfium2 (>=4.10.0,<5.0.0)", "pyspark (>=3.4.0,<4.0.0)", "rank-bm25 (>=0.2.2,<0.3.0)", "rapidfuzz (>=3.1.1,<4.0.0)", "requests-toolbelt (>=1.0.0,<2.0.0)", "scikit-learn (>=1.2.2,<2.0.0)", "sqlite-vss (>=0.1.2,<0.2.0)", "streamlit (>=1.18.0,<2.0.0)", "sympy (>=1.12,<2.0)", "telethon (>=1.28.5,<2.0.0)", "timescale-vector (>=0.0.1,<0.0.2)", "tqdm (>=4.48.0)", "xata (>=1.0.0a7,<2.0.0)", "xmltodict (>=0.13.0,<0.14.0)"]
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extended-testing = ["amazon-textract-caller (<2)", "anthropic (>=0.3.11,<0.4.0)", "arxiv (>=1.4,<2.0)", "assemblyai (>=0.17.0,<0.18.0)", "atlassian-python-api (>=3.36.0,<4.0.0)", "beautifulsoup4 (>=4,<5)", "bibtexparser (>=1.4.0,<2.0.0)", "cassio (>=0.1.0,<0.2.0)", "chardet (>=5.1.0,<6.0.0)", "dashvector (>=1.0.1,<2.0.0)", "esprima (>=4.0.1,<5.0.0)", "faiss-cpu (>=1,<2)", "feedparser (>=6.0.10,<7.0.0)", "geopandas (>=0.13.1,<0.14.0)", "gitpython (>=3.1.32,<4.0.0)", "gql (>=3.4.1,<4.0.0)", "html2text (>=2020.1.16,<2021.0.0)", "jinja2 (>=3,<4)", "jq (>=1.4.1,<2.0.0)", "lxml (>=4.9.2,<5.0.0)", "markdownify (>=0.11.6,<0.12.0)", "motor (>=3.3.1,<4.0.0)", "mwparserfromhell (>=0.6.4,<0.7.0)", "mwxml (>=0.3.3,<0.4.0)", "newspaper3k (>=0.2.8,<0.3.0)", "openai (>=0,<1)", "openai (>=0,<1)", "openapi-schema-pydantic (>=1.2,<2.0)", "pandas (>=2.0.1,<3.0.0)", "pdfminer-six (>=20221105,<20221106)", "pgvector (>=0.1.6,<0.2.0)", "psychicapi (>=0.8.0,<0.9.0)", "py-trello (>=0.19.0,<0.20.0)", "pymupdf (>=1.22.3,<2.0.0)", "pypdf (>=3.4.0,<4.0.0)", "pypdfium2 (>=4.10.0,<5.0.0)", "pyspark (>=3.4.0,<4.0.0)", "rank-bm25 (>=0.2.2,<0.3.0)", "rapidfuzz (>=3.1.1,<4.0.0)", "requests-toolbelt (>=1.0.0,<2.0.0)", "scikit-learn (>=1.2.2,<2.0.0)", "sqlite-vss (>=0.1.2,<0.2.0)", "streamlit (>=1.18.0,<2.0.0)", "sympy (>=1.12,<2.0)", "telethon (>=1.28.5,<2.0.0)", "timescale-vector (>=0.0.1,<0.0.2)", "tqdm (>=4.48.0)", "xata (>=1.0.0a7,<2.0.0)", "xmltodict (>=0.13.0,<0.14.0)"]
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javascript = ["esprima (>=4.0.1,<5.0.0)"]
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llms = ["clarifai (>=9.1.0)", "cohere (>=4,<5)", "huggingface_hub (>=0,<1)", "manifest-ml (>=0.0.1,<0.0.2)", "nlpcloud (>=1,<2)", "openai (>=0,<1)", "openlm (>=0.0.5,<0.0.6)", "torch (>=1,<3)", "transformers (>=4,<5)"]
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openai = ["openai (>=0,<1)", "tiktoken (>=0.3.2,<0.6.0)"]
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@ -1666,7 +1666,7 @@ text-helpers = ["chardet (>=5.1.0,<6.0.0)"]
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type = "git"
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url = "https://github.com/langchain-ai/langchain"
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reference = "HEAD"
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resolved_reference = "4ad0f3de2b1c423d2900d925e26c0097b8741e90"
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resolved_reference = "8b4cb4eb60e3935eea895aa955d68ca0afce788c"
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subdirectory = "libs/langchain"
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[[package]]
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@ -4,6 +4,7 @@ from typing import Any
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import pytest
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from langchain.schema.messages import (
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HumanMessage,
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HumanMessageChunk,
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SystemMessage,
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)
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@ -32,6 +33,7 @@ from langserve.serialization import simple_dumps, simple_loads
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"additional_kwargs": {},
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"type": "human",
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"example": False,
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"is_chunk": False,
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}
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]
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},
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@ -44,6 +46,7 @@ from langserve.serialization import simple_dumps, simple_loads
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"content": "Hello",
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"example": False,
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"type": "human",
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"is_chunk": False,
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},
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),
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# Test with a list containing mixed elements
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@ -55,50 +58,60 @@ from langserve.serialization import simple_dumps, simple_loads
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"content": "Hello",
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"example": False,
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"type": "human",
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"is_chunk": False,
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},
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{
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"additional_kwargs": {},
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"content": "Hi",
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"type": "system",
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"is_chunk": False,
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},
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{"additional_kwargs": {}, "content": "Hi", "type": "system"},
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42,
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"world",
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],
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),
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# # Attention: This test is not correct right now
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# # Test with full and chunk messages
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# (
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# [HumanMessage(content="Hello"), HumanMessageChunk(content="Hi")],
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# [
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# {
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# "additional_kwargs": {},
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# "content": "Hello",
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# "example": False,
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# "type": "human",
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# },
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# {
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# "additional_kwargs": {},
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# "content": "Hi",
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# "example": False,
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# "type": "human",
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# },
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# ],
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# ),
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# # Attention: This test is not correct right now
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# # Test with full and chunk messages
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# (
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# [HumanMessageChunk(content="Hello"), HumanMessage(content="Hi")],
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# [
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# {
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# "additional_kwargs": {},
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# "content": "Hello",
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# "example": False,
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# "type": "human",
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# },
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# {
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# "additional_kwargs": {},
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# "content": "Hi",
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# "example": False,
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# "type": "human",
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# },
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# ],
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# ),
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# Attention: This test is not correct right now
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# Test with full and chunk messages
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(
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[HumanMessage(content="Hello"), HumanMessageChunk(content="Hi")],
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[
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{
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"additional_kwargs": {},
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"content": "Hello",
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"example": False,
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"type": "human",
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"is_chunk": False,
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},
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{
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"additional_kwargs": {},
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"content": "Hi",
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"example": False,
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"type": "human",
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"is_chunk": True,
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},
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],
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),
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# Attention: This test is not correct right now
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# Test with full and chunk messages
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(
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[HumanMessageChunk(content="Hello"), HumanMessage(content="Hi")],
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[
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{
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"additional_kwargs": {},
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"content": "Hello",
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"example": False,
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"type": "human",
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"is_chunk": True,
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},
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{
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"additional_kwargs": {},
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"content": "Hi",
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"example": False,
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"type": "human",
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"is_chunk": False,
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},
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],
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),
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# Test with a dictionary containing mixed elements
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(
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{
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@ -112,6 +125,7 @@ from langserve.serialization import simple_dumps, simple_loads
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"content": "Greetings",
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"example": False,
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"type": "human",
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"is_chunk": False,
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},
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"numbers": [1, 2, 3],
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"boom": "Hello, world!",
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