Add Upstash Vector Store support (#2004)
* docs(migration): add UPSTASH_VECTOR_REST_URL and UPSTASH_VECTOR_REST_TOKEN to the list of default environment variables pyproject.toml: add upstash-vector package as a dependency with version 0.4.0 src/backend/base/langflow/components/vectorsearch/UpstashSearch.py: create UpstashSearchComponent for implementing a Vector Store using Upstash src/backend/base/langflow/components/vectorstores/Upstash.py: create UpstashVectorStoreComponent for implementing a Vector Store using Upstash src/backend/base/langflow/services/settings/constants.py: add UPSTASH_VECTOR_REST_URL and UPSTASH_VECTOR_REST_TOKEN to the list of variables to get from the environment * ✨ (UpstashSearch.py): Add support for 'number_of_results' and 'text_key' parameters in UpstashSearchComponent to enhance search functionality ♻️ (Upstash.py): Refactor UpstashVectorStoreComponent to include 'text_key' parameter for consistency and improved functionality * ♻️ (Upstash.py): refactor UpstashVectorStoreComponent to improve code readability and maintainability by restructuring the instantiation of UpstashVectorStore instances based on conditions and adding support for adding documents directly to the instance. * feat: Update langchain-core, langchainhub, langsmith, and requests dependencies to latest versions
This commit is contained in:
Gabriel Luiz Freitas Almeida
GitHub
parent
39f86a409a
commit
4c113d5ac0
7 changed files with 239 additions and 52 deletions
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@ -105,6 +105,8 @@ The default list at the moment is:
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- PINECONE_API_KEY
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- SEARCHAPI_API_KEY
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- SERPAPI_API_KEY
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- UPSTASH_VECTOR_REST_URL
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- UPSTASH_VECTOR_REST_TOKEN
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- VECTARA_CUSTOMER_ID
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- VECTARA_CORPUS_ID
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- VECTARA_API_KEY
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94
poetry.lock
generated
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poetry.lock
generated
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@ -167,20 +167,20 @@ files = [
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[[package]]
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name = "anthropic"
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version = "0.26.1"
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version = "0.27.0"
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description = "The official Python library for the anthropic API"
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optional = false
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python-versions = ">=3.7"
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files = [
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{file = "anthropic-0.26.1-py3-none-any.whl", hash = "sha256:2812b9b250b551ed8a1f0a7e6ae3f005654098994f45ebca5b5808bd154c9628"},
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{file = "anthropic-0.26.1.tar.gz", hash = "sha256:26680ff781a6f678a30a1dccd0743631e602b23a47719439ffdef5335fa167d8"},
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{file = "anthropic-0.27.0-py3-none-any.whl", hash = "sha256:c6e73035e910b3ff3f52853b15b42c5e99bf649ce0b510bd491a2c4befeda694"},
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{file = "anthropic-0.27.0.tar.gz", hash = "sha256:9a86671376d376c4e75981a5dc2dc9c81f8e277b38e9240b3c0a7f574b4cc2a6"},
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]
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[package.dependencies]
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anyio = ">=3.5.0,<5"
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distro = ">=1.7.0,<2"
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httpx = ">=0.23.0,<1"
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jiter = ">=0.1.0,<1"
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jiter = ">=0.4.0,<1"
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pydantic = ">=1.9.0,<3"
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sniffio = "*"
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tokenizers = ">=0.13.0"
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@ -472,17 +472,17 @@ files = [
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[[package]]
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name = "boto3"
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version = "1.34.114"
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version = "1.34.115"
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description = "The AWS SDK for Python"
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optional = false
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python-versions = ">=3.8"
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files = [
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{file = "boto3-1.34.114-py3-none-any.whl", hash = "sha256:4460958d2b0c53bd2195b23ed5d45db2350e514486fe8caeb38b285b30742280"},
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{file = "boto3-1.34.114.tar.gz", hash = "sha256:eeb11bca9b19d12baf93436fb8a16b8b824f1f7e8b9bcc722607e862c46b1b08"},
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{file = "boto3-1.34.115-py3-none-any.whl", hash = "sha256:0a580de3d25364da5db26ecc7dde9438ee1be1e529a7c04cc96972b6e2258378"},
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{file = "boto3-1.34.115.tar.gz", hash = "sha256:67f5a6d6e6eff9c15711c265173b53eb4ad8d05b756b76ef33ac792cea7958f6"},
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]
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[package.dependencies]
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botocore = ">=1.34.114,<1.35.0"
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botocore = ">=1.34.115,<1.35.0"
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jmespath = ">=0.7.1,<2.0.0"
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s3transfer = ">=0.10.0,<0.11.0"
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@ -491,13 +491,13 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
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[[package]]
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name = "botocore"
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version = "1.34.114"
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version = "1.34.115"
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description = "Low-level, data-driven core of boto 3."
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optional = false
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python-versions = ">=3.8"
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files = [
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{file = "botocore-1.34.114-py3-none-any.whl", hash = "sha256:606d1e55984d45e41a812badee292755f4db0233eed9cca63ea3bb8f5755507f"},
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{file = "botocore-1.34.114.tar.gz", hash = "sha256:5705f74fda009656a218ffaf4afd81228359160f2ab806ab8222d07e9da3a73b"},
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{file = "botocore-1.34.115-py3-none-any.whl", hash = "sha256:15b8ad1ee0e9cd57884fb0bcaf3a9551d2552e44a02c2ffb55ec583eebdb888e"},
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{file = "botocore-1.34.115.tar.gz", hash = "sha256:a5d5e28b9c847b17a1ecb7660b46b83d9512b125f671e03e93d14bf6f0b274c2"},
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]
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[package.dependencies]
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@ -4075,17 +4075,17 @@ langchain-core = ">=0.1.43,<0.3"
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[[package]]
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name = "langchain-astradb"
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version = "0.3.2"
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version = "0.3.3"
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description = "An integration package connecting Astra DB and LangChain"
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optional = false
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python-versions = "<4.0,>=3.8.1"
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files = [
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{file = "langchain_astradb-0.3.2-py3-none-any.whl", hash = "sha256:15afc5c0105e863e8f57bf8686490c00be47ed05e47d3263ad1577f2031c0dd5"},
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{file = "langchain_astradb-0.3.2.tar.gz", hash = "sha256:4316f2c59402779a347a811e1b5470a0570348cb89baac17472d860b63188122"},
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{file = "langchain_astradb-0.3.3-py3-none-any.whl", hash = "sha256:39deef1253947ef1bfaf3c27881ecdf07621d96c2cf37814aed9e506a9bee217"},
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{file = "langchain_astradb-0.3.3.tar.gz", hash = "sha256:f9a996ec4bef134896195430adeb7f264389c368a03d2ea91356837e8ddde091"},
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]
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[package.dependencies]
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astrapy = ">=1,<2"
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astrapy = ">=1.2,<2.0"
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langchain-core = ">=0.1.31,<0.3"
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numpy = ">=1,<2"
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@ -4150,13 +4150,13 @@ extended-testing = ["aiosqlite (>=0.19.0,<0.20.0)", "aleph-alpha-client (>=2.15.
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[[package]]
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name = "langchain-core"
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version = "0.2.1"
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version = "0.2.2"
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description = "Building applications with LLMs through composability"
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optional = false
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python-versions = "<4.0,>=3.8.1"
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files = [
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{file = "langchain_core-0.2.1-py3-none-any.whl", hash = "sha256:3521e1e573988c47399fca9739270c5d34f8ecec147253ad829eb9ff288f76d5"},
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{file = "langchain_core-0.2.1.tar.gz", hash = "sha256:49383126168d934559a543ce812c485048d9e6ac9b6798fbf3d4a72b6bba5b0c"},
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{file = "langchain_core-0.2.2-py3-none-any.whl", hash = "sha256:4b3b55a5f214acbcf8d6d8e322da3a9d6248d6b6f45ac1b86ab0494fd3716128"},
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{file = "langchain_core-0.2.2.tar.gz", hash = "sha256:6884a87f7ac8e0d43e4d83c5f9efa95236c7bd535e22a0a51db19156875b4cd6"},
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]
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[package.dependencies]
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@ -4259,18 +4259,18 @@ tokenizers = ">=0.15.1,<1"
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[[package]]
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name = "langchain-openai"
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version = "0.1.7"
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version = "0.1.8"
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description = "An integration package connecting OpenAI and LangChain"
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optional = false
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python-versions = "<4.0,>=3.8.1"
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files = [
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{file = "langchain_openai-0.1.7-py3-none-any.whl", hash = "sha256:39c3cb22bb739900ae8294d4d9939a6138c0ca7ad11198e57038eb14c08d04ec"},
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{file = "langchain_openai-0.1.7.tar.gz", hash = "sha256:fd7e1c33ba8e2cab4b2154f3a2fd4a0d9cc6518b41cf49bb87255f9f732a4896"},
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{file = "langchain_openai-0.1.8-py3-none-any.whl", hash = "sha256:8125c84223e9f43b05defbca64eedbcf362fd78a680de6c25e64f973b34a8063"},
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{file = "langchain_openai-0.1.8.tar.gz", hash = "sha256:a11fcce15def7917c44232abda6baaa63dfc79fe44be1531eea650d39a44cd95"},
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]
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[package.dependencies]
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langchain-core = ">=0.1.46,<0.3"
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openai = ">=1.24.0,<2.0.0"
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langchain-core = ">=0.2.2,<0.3"
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openai = ">=1.26.0,<2.0.0"
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tiktoken = ">=0.7,<1"
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[[package]]
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@ -4380,13 +4380,13 @@ url = "src/backend/base"
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[[package]]
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name = "langfuse"
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version = "2.33.0"
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version = "2.33.1"
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description = "A client library for accessing langfuse"
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optional = false
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python-versions = "<4.0,>=3.8.1"
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files = [
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{file = "langfuse-2.33.0-py3-none-any.whl", hash = "sha256:362e3078c5a891df0b7ba3c9ce82f046d1f0274eab3d55337e443fff526f18ad"},
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{file = "langfuse-2.33.0.tar.gz", hash = "sha256:3ca2ef8539a8f28cb80135f4b46b80d5585ce183f8e2035f318be296d09d7d88"},
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{file = "langfuse-2.33.1-py3-none-any.whl", hash = "sha256:61ff3ff4b9c9c195028c981cba892106fdf90028e3950209a15f0ae06a378a36"},
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{file = "langfuse-2.33.1.tar.gz", hash = "sha256:444a870e8b13ad37df710931389ecd3bad9997e550edf3c3178b5a0bd7ada013"},
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]
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[package.dependencies]
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@ -4404,13 +4404,13 @@ openai = ["openai (>=0.27.8)"]
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[[package]]
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name = "langsmith"
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version = "0.1.63"
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version = "0.1.65"
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description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
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optional = false
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python-versions = "<4.0,>=3.8.1"
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files = [
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{file = "langsmith-0.1.63-py3-none-any.whl", hash = "sha256:7810afdf5e3f3b472fc581a29371fb96cd843dde2149e048d1b9610325159d1e"},
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{file = "langsmith-0.1.63.tar.gz", hash = "sha256:a609405b52f6f54df442a142cbf19ab38662d54e532f96028b4c546434d4afdf"},
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{file = "langsmith-0.1.65-py3-none-any.whl", hash = "sha256:ab4487029240e69cca30da1065f1e9138e5a7ca2bbe8c697f0bd7d5839f71cf7"},
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{file = "langsmith-0.1.65.tar.gz", hash = "sha256:d3c2eb2391478bd79989f02652cf66e29a7959d677614b6993a47cef43f7f43b"},
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]
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[package.dependencies]
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[[package]]
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name = "litellm"
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version = "1.39.2"
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version = "1.39.4"
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description = "Library to easily interface with LLM API providers"
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optional = false
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python-versions = "!=2.7.*,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,!=3.7.*,>=3.8"
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files = [
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{file = "litellm-1.39.2-py3-none-any.whl", hash = "sha256:843cb9a4d45c89ba6da95529815ec83ee7e4b7fe07aa0ed633102f600fddd9ad"},
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{file = "litellm-1.39.2.tar.gz", hash = "sha256:96c4f3d522ccf32817357b1e9f5f63fa36a4a884f336314e1f6d66c0576d689e"},
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{file = "litellm-1.39.4-py3-none-any.whl", hash = "sha256:3edd2b153153e8902770ada641b93bcdeaba8d23cb579e599919331b52741040"},
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{file = "litellm-1.39.4.tar.gz", hash = "sha256:f7ec8ef44257235de10c8e0d326fff0083b48de4bc71531d78d8c6778af9d401"},
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]
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[package.dependencies]
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[[package]]
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name = "openai"
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version = "1.30.4"
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version = "1.30.5"
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description = "The official Python library for the openai API"
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optional = false
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python-versions = ">=3.7.1"
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files = [
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{file = "openai-1.30.4-py3-none-any.whl", hash = "sha256:fb2635efd270efaf9fac2e07558d7948373b940637d3ae3ab624c1a983d4f03f"},
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{file = "openai-1.30.4.tar.gz", hash = "sha256:f3488d9a1c4e0d332b019377d27d7cb4b3d6103fd5d0a416c7ceac780d1d9b88"},
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{file = "openai-1.30.5-py3-none-any.whl", hash = "sha256:2ad95e926de0d2e09cde632a9204b0a6dca4a03c2cdcc84329b01f355784355a"},
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{file = "openai-1.30.5.tar.gz", hash = "sha256:5366562eb2c5917e6116ae0391b7ae6e3acd62b0ae3f565ada32b35d8fcfa106"},
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]
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[package.dependencies]
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[[package]]
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name = "sympy"
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version = "1.12"
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version = "1.12.1"
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description = "Computer algebra system (CAS) in Python"
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optional = false
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python-versions = ">=3.8"
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files = [
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{file = "sympy-1.12-py3-none-any.whl", hash = "sha256:c3588cd4295d0c0f603d0f2ae780587e64e2efeedb3521e46b9bb1d08d184fa5"},
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{file = "sympy-1.12.tar.gz", hash = "sha256:ebf595c8dac3e0fdc4152c51878b498396ec7f30e7a914d6071e674d49420fb8"},
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{file = "sympy-1.12.1-py3-none-any.whl", hash = "sha256:9b2cbc7f1a640289430e13d2a56f02f867a1da0190f2f99d8968c2f74da0e515"},
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{file = "sympy-1.12.1.tar.gz", hash = "sha256:2877b03f998cd8c08f07cd0de5b767119cd3ef40d09f41c30d722f6686b0fb88"},
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]
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[package.dependencies]
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mpmath = ">=0.19"
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mpmath = ">=1.1.0,<1.4.0"
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[[package]]
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name = "tbb"
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pyperclip = "*"
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six = "*"
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[[package]]
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name = "upstash-vector"
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version = "0.4.0"
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description = "Serverless Vector SDK from Upstash"
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optional = false
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python-versions = "<4.0,>=3.8"
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files = [
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{file = "upstash_vector-0.4.0-py3-none-any.whl", hash = "sha256:1ba11d8fc7d036bf93fde741b862c9e04ad962397dc600d1dc7546b63a84da82"},
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{file = "upstash_vector-0.4.0.tar.gz", hash = "sha256:a8ae11b2d3989c2615f1f06c66af39da763af7f7239b625fede621bf2fbb997d"},
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]
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[package.dependencies]
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httpx = ">=0.24.0,<0.28"
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[[package]]
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name = "uritemplate"
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version = "4.1.1"
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[metadata]
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lock-version = "2.0"
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python-versions = ">=3.10,<3.13"
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content-hash = "36778b105f6f6e5efd0c1d37651d7b97defb0bc0db74b868a41e38de22251924"
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content-hash = "476c95dc8c6adb597a0cd2783eab65c02e0398fc144aa74d56a4cb36032f496f"
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youtube-transcript-api = "^0.6.2"
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markdown = "^3.6"
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langchain-chroma = "^0.1.1"
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upstash-vector = "^0.4.0"
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[tool.poetry.group.dev.dependencies]
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from typing import List, Optional
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from langchain_core.embeddings import Embeddings
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from langflow.components.vectorstores.base.model import LCVectorStoreComponent
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from langflow.components.vectorstores.Upstash import UpstashVectorStoreComponent
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from langflow.field_typing import Text
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from langflow.schema import Record
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class UpstashSearchComponent(UpstashVectorStoreComponent, LCVectorStoreComponent):
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"""
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A custom component for implementing a Vector Store using Upstash.
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"""
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display_name: str = "Upstash Search"
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description: str = "Search an Upstash Vector Store for similar documents."
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def build_config(self):
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"""
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Builds the configuration for the component.
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Returns:
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- dict: A dictionary containing the configuration options for the component.
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"""
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return {
|
||||
"search_type": {
|
||||
"display_name": "Search Type",
|
||||
"options": ["Similarity", "MMR"],
|
||||
},
|
||||
"input_value": {"display_name": "Input"},
|
||||
"inputs": {"display_name": "Input", "input_types": ["Document", "Record"]},
|
||||
"embedding": {
|
||||
"display_name": "Embedding",
|
||||
"input_types": ["Embeddings"],
|
||||
"info": "To use Upstash's embeddings, don't provide an embedding.",
|
||||
},
|
||||
"index_url": {
|
||||
"display_name": "Index URL",
|
||||
"info": "The URL of the Upstash index.",
|
||||
},
|
||||
"index_token": {
|
||||
"display_name": "Index Token",
|
||||
"info": "The token for the Upstash index.",
|
||||
},
|
||||
"number_of_results": {
|
||||
"display_name": "Number of Results",
|
||||
"info": "Number of results to return.",
|
||||
"advanced": True,
|
||||
},
|
||||
"text_key": {
|
||||
"display_name": "Text Key",
|
||||
"info": "The key in the record to use as text.",
|
||||
"advanced": True,
|
||||
},
|
||||
}
|
||||
|
||||
def build( # type: ignore[override]
|
||||
self,
|
||||
input_value: Text,
|
||||
search_type: str,
|
||||
text_key: str = "text",
|
||||
index_url: Optional[str] = None,
|
||||
index_token: Optional[str] = None,
|
||||
embedding: Optional[Embeddings] = None,
|
||||
number_of_results: int = 4,
|
||||
) -> List[Record]:
|
||||
vector_store = super().build(
|
||||
embedding=embedding,
|
||||
text_key=text_key,
|
||||
index_url=index_url,
|
||||
index_token=index_token,
|
||||
)
|
||||
if not vector_store:
|
||||
raise ValueError("Failed to load the Upstash Vector Store.")
|
||||
|
||||
return self.search_with_vector_store(
|
||||
input_value=input_value, search_type=search_type, vector_store=vector_store, k=number_of_results
|
||||
)
|
||||
89
src/backend/base/langflow/components/vectorstores/Upstash.py
Normal file
89
src/backend/base/langflow/components/vectorstores/Upstash.py
Normal file
|
|
@ -0,0 +1,89 @@
|
|||
from typing import List, Optional, Union
|
||||
|
||||
from langchain_community.vectorstores.upstash import UpstashVectorStore
|
||||
from langchain_core.embeddings import Embeddings
|
||||
from langchain_core.retrievers import BaseRetriever
|
||||
from langchain_core.vectorstores import VectorStore
|
||||
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.schema.schema import Record
|
||||
|
||||
|
||||
class UpstashVectorStoreComponent(CustomComponent):
|
||||
"""
|
||||
A custom component for implementing a Vector Store using Upstash.
|
||||
"""
|
||||
|
||||
display_name: str = "Upstash"
|
||||
description: str = "Create and Utilize an Upstash Vector Store"
|
||||
|
||||
def build_config(self):
|
||||
"""
|
||||
Builds the configuration for the component.
|
||||
|
||||
Returns:
|
||||
- dict: A dictionary containing the configuration options for the component.
|
||||
"""
|
||||
return {
|
||||
"inputs": {"display_name": "Input", "input_types": ["Document", "Record"]},
|
||||
"embedding": {
|
||||
"display_name": "Embedding",
|
||||
"input_types": ["Embeddings"],
|
||||
"info": "To use Upstash's embeddings, don't provide an embedding.",
|
||||
},
|
||||
"index_url": {
|
||||
"display_name": "Index URL",
|
||||
"info": "The URL of the Upstash index.",
|
||||
},
|
||||
"index_token": {
|
||||
"display_name": "Index Token",
|
||||
"info": "The token for the Upstash index.",
|
||||
},
|
||||
"text_key": {
|
||||
"display_name": "Text Key",
|
||||
"info": "The key in the record to use as text.",
|
||||
"advanced": True,
|
||||
},
|
||||
}
|
||||
|
||||
def build(
|
||||
self,
|
||||
inputs: Optional[List[Record]] = None,
|
||||
text_key: str = "text",
|
||||
index_url: Optional[str] = None,
|
||||
index_token: Optional[str] = None,
|
||||
embedding: Optional[Embeddings] = None,
|
||||
) -> Union[VectorStore, BaseRetriever]:
|
||||
documents = []
|
||||
for _input in inputs or []:
|
||||
if isinstance(_input, Record):
|
||||
documents.append(_input.to_lc_document())
|
||||
else:
|
||||
documents.append(_input)
|
||||
|
||||
use_upstash_embedding = embedding is None
|
||||
if not documents:
|
||||
upstash_vs = UpstashVectorStore(
|
||||
embedding=embedding or use_upstash_embedding,
|
||||
text_key=text_key,
|
||||
index_url=index_url,
|
||||
index_token=index_token,
|
||||
)
|
||||
else:
|
||||
if use_upstash_embedding:
|
||||
upstash_vs = UpstashVectorStore(
|
||||
embedding=use_upstash_embedding,
|
||||
text_key=text_key,
|
||||
index_url=index_url,
|
||||
index_token=index_token,
|
||||
)
|
||||
upstash_vs.add_documents(documents)
|
||||
elif embedding:
|
||||
upstash_vs = UpstashVectorStore.from_documents(
|
||||
documents=documents, # type: ignore
|
||||
embedding=embedding,
|
||||
text_key=text_key,
|
||||
index_url=index_url,
|
||||
index_token=index_token,
|
||||
)
|
||||
return upstash_vs
|
||||
|
|
@ -17,6 +17,8 @@ VARIABLES_TO_GET_FROM_ENVIRONMENT = [
|
|||
"PINECONE_API_KEY",
|
||||
"SEARCHAPI_API_KEY",
|
||||
"SERPAPI_API_KEY",
|
||||
"UPSTASH_VECTOR_REST_URL",
|
||||
"UPSTASH_VECTOR_REST_TOKEN",
|
||||
"VECTARA_CUSTOMER_ID",
|
||||
"VECTARA_CORPUS_ID",
|
||||
"VECTARA_API_KEY",
|
||||
|
|
|
|||
24
src/backend/base/poetry.lock
generated
24
src/backend/base/poetry.lock
generated
|
|
@ -1224,13 +1224,13 @@ extended-testing = ["aiosqlite (>=0.19.0,<0.20.0)", "aleph-alpha-client (>=2.15.
|
|||
|
||||
[[package]]
|
||||
name = "langchain-core"
|
||||
version = "0.2.1"
|
||||
version = "0.2.2"
|
||||
description = "Building applications with LLMs through composability"
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.8.1"
|
||||
files = [
|
||||
{file = "langchain_core-0.2.1-py3-none-any.whl", hash = "sha256:3521e1e573988c47399fca9739270c5d34f8ecec147253ad829eb9ff288f76d5"},
|
||||
{file = "langchain_core-0.2.1.tar.gz", hash = "sha256:49383126168d934559a543ce812c485048d9e6ac9b6798fbf3d4a72b6bba5b0c"},
|
||||
{file = "langchain_core-0.2.2-py3-none-any.whl", hash = "sha256:4b3b55a5f214acbcf8d6d8e322da3a9d6248d6b6f45ac1b86ab0494fd3716128"},
|
||||
{file = "langchain_core-0.2.2.tar.gz", hash = "sha256:6884a87f7ac8e0d43e4d83c5f9efa95236c7bd535e22a0a51db19156875b4cd6"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -1281,13 +1281,13 @@ extended-testing = ["beautifulsoup4 (>=4.12.3,<5.0.0)", "lxml (>=4.9.3,<6.0)"]
|
|||
|
||||
[[package]]
|
||||
name = "langchainhub"
|
||||
version = "0.1.16"
|
||||
version = "0.1.17"
|
||||
description = "The LangChain Hub API client"
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.8.1"
|
||||
files = [
|
||||
{file = "langchainhub-0.1.16-py3-none-any.whl", hash = "sha256:a4379a1879cc6b441b8d02cc65e28a54f160fba61c9d1d4b0eddc3a276dff99a"},
|
||||
{file = "langchainhub-0.1.16.tar.gz", hash = "sha256:9f11e68fddb575e70ef4b28800eedbd9eeb180ba508def04f7153ea5b246b6fc"},
|
||||
{file = "langchainhub-0.1.17-py3-none-any.whl", hash = "sha256:4c609b3948252c71670f0d98f73413b515cfd2f6701a7b40ce959203e6133e04"},
|
||||
{file = "langchainhub-0.1.17.tar.gz", hash = "sha256:af7df0cb1cebc7a6e0864e8632ae48ecad39ed96568f699c78657b9d04e50b46"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -1296,13 +1296,13 @@ types-requests = ">=2.31.0.2,<3.0.0.0"
|
|||
|
||||
[[package]]
|
||||
name = "langsmith"
|
||||
version = "0.1.63"
|
||||
version = "0.1.65"
|
||||
description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.8.1"
|
||||
files = [
|
||||
{file = "langsmith-0.1.63-py3-none-any.whl", hash = "sha256:7810afdf5e3f3b472fc581a29371fb96cd843dde2149e048d1b9610325159d1e"},
|
||||
{file = "langsmith-0.1.63.tar.gz", hash = "sha256:a609405b52f6f54df442a142cbf19ab38662d54e532f96028b4c546434d4afdf"},
|
||||
{file = "langsmith-0.1.65-py3-none-any.whl", hash = "sha256:ab4487029240e69cca30da1065f1e9138e5a7ca2bbe8c697f0bd7d5839f71cf7"},
|
||||
{file = "langsmith-0.1.65.tar.gz", hash = "sha256:d3c2eb2391478bd79989f02652cf66e29a7959d677614b6993a47cef43f7f43b"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -2466,13 +2466,13 @@ files = [
|
|||
|
||||
[[package]]
|
||||
name = "requests"
|
||||
version = "2.32.2"
|
||||
version = "2.32.3"
|
||||
description = "Python HTTP for Humans."
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "requests-2.32.2-py3-none-any.whl", hash = "sha256:fc06670dd0ed212426dfeb94fc1b983d917c4f9847c863f313c9dfaaffb7c23c"},
|
||||
{file = "requests-2.32.2.tar.gz", hash = "sha256:dd951ff5ecf3e3b3aa26b40703ba77495dab41da839ae72ef3c8e5d8e2433289"},
|
||||
{file = "requests-2.32.3-py3-none-any.whl", hash = "sha256:70761cfe03c773ceb22aa2f671b4757976145175cdfca038c02654d061d6dcc6"},
|
||||
{file = "requests-2.32.3.tar.gz", hash = "sha256:55365417734eb18255590a9ff9eb97e9e1da868d4ccd6402399eaf68af20a760"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue