mirror of
https://github.com/crewAIInc/crewAI.git
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Adding support to force a tool return to be the final answer. (#867)
* Adding support to force a tool return to be the final answer. This will at the end of the execution return the tool output. It will return the output of the latest tool with the flag * Update src/crewai/agent.py Co-authored-by: Gui Vieira <guilherme_vieira@me.com> * Update tests/agent_test.py Co-authored-by: Gui Vieira <guilherme_vieira@me.com> --------- Co-authored-by: Gui Vieira <guilherme_vieira@me.com>
This commit is contained in:
João Moura
525
poetry.lock
generated
525
poetry.lock
generated
@@ -343,17 +343,17 @@ lxml = ["lxml"]
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[[package]]
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name = "boto3"
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version = "1.34.137"
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version = "1.34.139"
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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 = "boto3-1.34.137-py3-none-any.whl", hash = "sha256:7cb697d67fd138ceebc6f789919ae370c092a50c6b0ccc4ef483027935502eab"},
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{file = "boto3-1.34.137.tar.gz", hash = "sha256:0b21b84db4619b3711a6f643d465a5a25e81231ee43615c55a20ff6b89c6cc3c"},
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{file = "boto3-1.34.139-py3-none-any.whl", hash = "sha256:98b2a12bcb30e679fa9f60fc74145a39db5ec2ca7b7c763f42896e3bd9b3a38d"},
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{file = "boto3-1.34.139.tar.gz", hash = "sha256:32b99f0d76ec81fdca287ace2c9744a2eb8b92cb62bf4d26d52a4f516b63a6bf"},
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]
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[package.dependencies]
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botocore = ">=1.34.137,<1.35.0"
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botocore = ">=1.34.139,<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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@@ -362,13 +362,13 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
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[[package]]
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name = "botocore"
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version = "1.34.137"
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version = "1.34.139"
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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-1.34.137-py3-none-any.whl", hash = "sha256:a980fa4adec4bfa23fff70a3512622e9412c69c791898a52cafc2458b0be6040"},
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{file = "botocore-1.34.137.tar.gz", hash = "sha256:e29c8e9bfda0b20a1997792968e85868bfce42fefad9730f633a81adcff3f2ef"},
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{file = "botocore-1.34.139-py3-none-any.whl", hash = "sha256:dd1e085d4caa2a4c1b7d83e3bc51416111c8238a35d498e9d3b04f3b63b086ba"},
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{file = "botocore-1.34.139.tar.gz", hash = "sha256:df023d8cf8999d574214dad4645cb90f9d2ccd1494f6ee2b57b1ab7522f6be77"},
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]
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[package.dependencies]
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@@ -458,13 +458,13 @@ test = ["flake8", "isort", "pytest"]
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[[package]]
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name = "certifi"
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version = "2024.6.2"
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version = "2024.7.4"
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description = "Python package for providing Mozilla's CA Bundle."
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optional = false
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python-versions = ">=3.6"
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files = [
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{file = "certifi-2024.6.2-py3-none-any.whl", hash = "sha256:ddc6c8ce995e6987e7faf5e3f1b02b302836a0e5d98ece18392cb1a36c72ad56"},
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{file = "certifi-2024.6.2.tar.gz", hash = "sha256:3cd43f1c6fa7dedc5899d69d3ad0398fd018ad1a17fba83ddaf78aa46c747516"},
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{file = "certifi-2024.7.4-py3-none-any.whl", hash = "sha256:c198e21b1289c2ab85ee4e67bb4b4ef3ead0892059901a8d5b622f24a1101e90"},
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{file = "certifi-2024.7.4.tar.gz", hash = "sha256:5a1e7645bc0ec61a09e26c36f6106dd4cf40c6db3a1fb6352b0244e7fb057c7b"},
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]
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[[package]]
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@@ -840,13 +840,13 @@ files = [
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[[package]]
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name = "crewai-tools"
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version = "0.4.6"
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version = "0.4.7"
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description = "Set of tools for the crewAI framework"
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optional = false
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python-versions = "<=3.13,>=3.10"
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files = [
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{file = "crewai_tools-0.4.6-py3-none-any.whl", hash = "sha256:bfce205766da58a83233f82ed1f31f931656eb1f9c40b38f947cbf03afdf6e0d"},
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{file = "crewai_tools-0.4.6.tar.gz", hash = "sha256:f4b1ae8b5cf7c4b53da40223eb9734129b5fb71e7a77b676909129512307bd32"},
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{file = "crewai_tools-0.4.7-py3-none-any.whl", hash = "sha256:3ff04b2da07d2c48e72f898511295b4a10038dd3e4fe859baa93fec1fb8baf8e"},
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{file = "crewai_tools-0.4.7.tar.gz", hash = "sha256:4502a5e0ab94a7dae6638d000768f80049918909ca5338cdebc280351b3ce003"},
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]
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[package.dependencies]
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@@ -854,9 +854,9 @@ beautifulsoup4 = ">=4.12.3,<5.0.0"
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chromadb = ">=0.4.22,<0.5.0"
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docker = ">=7.1.0,<8.0.0"
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docx2txt = ">=0.8,<0.9"
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embedchain = ">=0.1.113,<0.2.0"
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embedchain = ">=0.1.114,<0.2.0"
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lancedb = ">=0.5.4,<0.6.0"
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langchain = ">=0.1.4,<0.2.0"
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langchain = ">0.2,<=0.3"
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openai = ">=1.12.0,<2.0.0"
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pydantic = ">=2.6.1,<3.0.0"
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pyright = ">=1.1.350,<2.0.0"
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@@ -884,21 +884,6 @@ webencodings = "*"
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doc = ["sphinx", "sphinx_rtd_theme"]
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test = ["flake8", "isort", "pytest"]
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[[package]]
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name = "dataclasses-json"
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version = "0.6.7"
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description = "Easily serialize dataclasses to and from JSON."
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optional = false
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python-versions = "<4.0,>=3.7"
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files = [
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{file = "dataclasses_json-0.6.7-py3-none-any.whl", hash = "sha256:0dbf33f26c8d5305befd61b39d2b3414e8a407bedc2834dea9b8d642666fb40a"},
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{file = "dataclasses_json-0.6.7.tar.gz", hash = "sha256:b6b3e528266ea45b9535223bc53ca645f5208833c29229e847b3f26a1cc55fc0"},
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]
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[package.dependencies]
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marshmallow = ">=3.18.0,<4.0.0"
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typing-inspect = ">=0.4.0,<1"
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[[package]]
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name = "decorator"
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version = "5.1.1"
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@@ -1054,13 +1039,13 @@ idna = ">=2.0.0"
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[[package]]
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name = "embedchain"
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version = "0.1.113"
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version = "0.1.114"
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description = "Simplest open source retrieval (RAG) framework"
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optional = false
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python-versions = "<=3.13,>=3.9"
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files = [
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{file = "embedchain-0.1.113-py3-none-any.whl", hash = "sha256:f37b029d8f8509a5db99d1579168ab2ba7d5841c280289f6a2ae702601caf96f"},
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{file = "embedchain-0.1.113.tar.gz", hash = "sha256:5477012d37912a0e89758263b1a8db4699b7d0dedd7f18ccc89f3381d6b9173d"},
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{file = "embedchain-0.1.114-py3-none-any.whl", hash = "sha256:ce1b16196bcf53c679cacead0551a5466c33a9080a82be63f973e4437b0823ca"},
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{file = "embedchain-0.1.114.tar.gz", hash = "sha256:fa5c4a29dd3c6b1137c772e1bc3e2d7ca489c58f46f4c7f7de133b3b9fc56e72"},
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]
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[package.dependencies]
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@@ -1070,7 +1055,7 @@ chromadb = ">=0.4.24,<0.5.0"
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clarifai = ">=10.0.1,<11.0.0"
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google-cloud-aiplatform = ">=1.26.1,<2.0.0"
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gptcache = ">=0.1.43,<0.2.0"
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langchain = ">=0.1.4,<0.2.0"
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langchain = ">0.2,<=0.3"
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langchain-cohere = ">=0.1.4,<0.2.0"
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langchain-openai = ">=0.1.7,<0.2.0"
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openai = ">=1.1.1"
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@@ -1098,7 +1083,7 @@ huggingface-hub = ["huggingface_hub (>=0.17.3,<0.18.0)"]
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lancedb = ["lancedb (>=0.6.2,<0.7.0)"]
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llama2 = ["replicate (>=0.15.4,<0.16.0)"]
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milvus = ["pymilvus (==2.4.3)"]
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mistralai = ["langchain-mistralai (>=0.0.3,<0.0.4)"]
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mistralai = ["langchain-mistralai (>=0.1.9,<0.2.0)"]
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modal = ["modal (>=0.56.4329,<0.57.0)"]
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mysql = ["mysql-connector-python (>=8.1.0,<9.0.0)"]
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opensearch = ["opensearch-py (==2.3.1)"]
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@@ -1109,7 +1094,7 @@ qdrant = ["qdrant-client (>=1.6.3,<2.0.0)"]
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rss-feed = ["feedparser (>=6.0.10,<7.0.0)", "listparser (>=0.19,<0.20)", "newspaper3k (>=0.2.8,<0.3.0)"]
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slack = ["flask (>=2.3.3,<3.0.0)", "slack-sdk (==3.21.3)"]
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together = ["together (>=0.2.8,<0.3.0)"]
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vertexai = ["langchain-google-vertexai (>=0.0.5,<0.0.6)"]
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vertexai = ["langchain-google-vertexai (>=1.0.6,<2.0.0)"]
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weaviate = ["weaviate-client (>=3.24.1,<4.0.0)"]
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whatsapp = ["flask (>=2.3.3,<3.0.0)", "twilio (>=8.5.0,<9.0.0)"]
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youtube = ["youtube-transcript-api (>=0.6.1,<0.7.0)", "yt_dlp (>=2023.11.14,<2024.0.0)"]
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@@ -1443,13 +1428,13 @@ requests = ["requests (>=2.20.0,<3.0.0.dev0)"]
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[[package]]
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name = "google-cloud-aiplatform"
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version = "1.57.0"
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version = "1.58.0"
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description = "Vertex AI API client library"
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optional = false
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python-versions = ">=3.8"
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files = [
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{file = "google-cloud-aiplatform-1.57.0.tar.gz", hash = "sha256:113905f100cb0a9ad744a2445a7675f92f28600233ba499614aa704d11a809b7"},
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{file = "google_cloud_aiplatform-1.57.0-py2.py3-none-any.whl", hash = "sha256:ca5391a56e0cc8f4ed39a2beb7be02f51936ff04fd5304775a72a86c345d0e47"},
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{file = "google-cloud-aiplatform-1.58.0.tar.gz", hash = "sha256:7a05aceac4a6c7eaa26e684e9f202b829cc7e57f82bffe7281684275a553fcad"},
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{file = "google_cloud_aiplatform-1.58.0-py2.py3-none-any.whl", hash = "sha256:21f1320860f4916183ec939fdf2ff3fc1d7fdde97fe5795974257ab21f9458ec"},
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]
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[package.dependencies]
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@@ -1470,7 +1455,7 @@ autologging = ["mlflow (>=1.27.0,<=2.1.1)"]
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cloud-profiler = ["tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (>=2.4.0,<3.0.0dev)", "werkzeug (>=2.0.0,<2.1.0dev)"]
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datasets = ["pyarrow (>=10.0.1)", "pyarrow (>=14.0.0)", "pyarrow (>=3.0.0,<8.0dev)"]
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endpoint = ["requests (>=2.28.1)"]
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full = ["cloudpickle (<3.0)", "docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<=0.109.1)", "google-cloud-bigquery", "google-cloud-bigquery-storage", "google-cloud-logging (<4.0)", "google-vizier (>=0.1.6)", "httpx (>=0.23.0,<0.25.0)", "immutabledict", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.1.1)", "nest-asyncio (>=1.0.0,<1.6.0)", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pandas (>=1.0.0,<2.2.0)", "pyarrow (>=10.0.1)", "pyarrow (>=14.0.0)", "pyarrow (>=3.0.0,<8.0dev)", "pyarrow (>=6.0.1)", "pydantic (<2)", "pyyaml (>=5.3.1,<7)", "ray[default] (>=2.4,<2.5.dev0 || >2.9.0,!=2.9.1,!=2.9.2,<=2.9.3)", "ray[default] (>=2.5,<=2.9.3)", "requests (>=2.28.1)", "setuptools (<70.0.0)", "starlette (>=0.17.1)", "tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.4.0,<3.0.0dev)", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)", "werkzeug (>=2.0.0,<2.1.0dev)"]
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full = ["cloudpickle (<3.0)", "docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<=0.109.1)", "google-cloud-bigquery", "google-cloud-bigquery-storage", "google-cloud-logging (<4.0)", "google-vizier (>=0.1.6)", "httpx (>=0.23.0,<0.25.0)", "immutabledict", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.1.1)", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pandas (>=1.0.0,<2.2.0)", "pyarrow (>=10.0.1)", "pyarrow (>=14.0.0)", "pyarrow (>=3.0.0,<8.0dev)", "pyarrow (>=6.0.1)", "pydantic (<2)", "pyyaml (>=5.3.1,<7)", "ray[default] (>=2.4,<2.5.dev0 || >2.9.0,!=2.9.1,!=2.9.2,<=2.9.3)", "ray[default] (>=2.5,<=2.9.3)", "requests (>=2.28.1)", "setuptools (<70.0.0)", "starlette (>=0.17.1)", "tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.4.0,<3.0.0dev)", "tqdm (>=4.23.0)", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)", "werkzeug (>=2.0.0,<2.1.0dev)"]
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langchain = ["langchain (>=0.1.16,<0.3)", "langchain-core (<0.2)", "langchain-google-vertexai (<2)", "openinference-instrumentation-langchain (>=0.1.19,<0.2)", "tenacity (<=8.3)"]
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langchain-testing = ["absl-py", "cloudpickle (>=3.0,<4.0)", "langchain (>=0.1.16,<0.3)", "langchain-core (<0.2)", "langchain-google-vertexai (<2)", "openinference-instrumentation-langchain (>=0.1.19,<0.2)", "opentelemetry-exporter-gcp-trace (<2)", "opentelemetry-sdk (<2)", "pydantic (>=2.6.3,<3)", "pytest-xdist", "tenacity (<=8.3)"]
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lit = ["explainable-ai-sdk (>=1.0.0)", "lit-nlp (==0.4.0)", "pandas (>=1.0.0)", "tensorflow (>=2.3.0,<3.0.0dev)"]
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@@ -1479,12 +1464,12 @@ pipelines = ["pyyaml (>=5.3.1,<7)"]
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prediction = ["docker (>=5.0.3)", "fastapi (>=0.71.0,<=0.109.1)", "httpx (>=0.23.0,<0.25.0)", "starlette (>=0.17.1)", "uvicorn[standard] (>=0.16.0)"]
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preview = ["cloudpickle (<3.0)", "google-cloud-logging (<4.0)"]
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private-endpoints = ["requests (>=2.28.1)", "urllib3 (>=1.21.1,<1.27)"]
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rapid-evaluation = ["nest-asyncio (>=1.0.0,<1.6.0)", "pandas (>=1.0.0,<2.2.0)"]
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rapid-evaluation = ["pandas (>=1.0.0,<2.2.0)", "tqdm (>=4.23.0)"]
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ray = ["google-cloud-bigquery", "google-cloud-bigquery-storage", "immutabledict", "pandas (>=1.0.0,<2.2.0)", "pyarrow (>=6.0.1)", "pydantic (<2)", "ray[default] (>=2.4,<2.5.dev0 || >2.9.0,!=2.9.1,!=2.9.2,<=2.9.3)", "ray[default] (>=2.5,<=2.9.3)", "setuptools (<70.0.0)"]
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ray-testing = ["google-cloud-bigquery", "google-cloud-bigquery-storage", "immutabledict", "pandas (>=1.0.0,<2.2.0)", "pyarrow (>=6.0.1)", "pydantic (<2)", "pytest-xdist", "ray[default] (>=2.4,<2.5.dev0 || >2.9.0,!=2.9.1,!=2.9.2,<=2.9.3)", "ray[default] (>=2.5,<=2.9.3)", "ray[train] (==2.9.3)", "scikit-learn", "setuptools (<70.0.0)", "tensorflow", "torch (>=2.0.0,<2.1.0)", "xgboost", "xgboost-ray"]
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reasoningengine = ["cloudpickle (>=3.0,<4.0)", "opentelemetry-exporter-gcp-trace (<2)", "opentelemetry-sdk (<2)", "pydantic (>=2.6.3,<3)"]
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tensorboard = ["tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.4.0,<3.0.0dev)", "werkzeug (>=2.0.0,<2.1.0dev)"]
|
||||
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@@ -2377,149 +2362,107 @@ tests = ["aiohttp", "duckdb", "pandas (>=1.4)", "polars (>=0.19)", "pytest", "py
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||||
|
||||
[[package]]
|
||||
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||||
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||||
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||||
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||||
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||||
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tiktoken = ">=0.7,<1"
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[[package]]
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||||
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[[package]]
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[package.dependencies]
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@@ -2657,25 +2600,6 @@ files = [
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[[package]]
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@@ -2762,13 +2686,13 @@ pyyaml = ">=5.1"
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name = "mkdocs-material"
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[package.dependencies]
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@@ -3439,57 +3363,62 @@ files = [
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[[package]]
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@@ -3969,18 +3898,18 @@ files = [
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[[package]]
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[package.dependencies]
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[[package]]
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{file = "pydantic_core-2.20.1-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:4dd484681c15e6b9a977c785a345d3e378d72678fd5f1f3c0509608da24f2ac0"},
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{file = "pydantic_core-2.20.1-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:f6d6cff3538391e8486a431569b77921adfcdef14eb18fbf19b7c0a5294d4e6a"},
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{file = "pydantic_core-2.20.1-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:a6d511cc297ff0883bc3708b465ff82d7560193169a8b93260f74ecb0a5e08a7"},
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||||
{file = "pydantic_core-2.20.1.tar.gz", hash = "sha256:26ca695eeee5f9f1aeeb211ffc12f10bcb6f71e2989988fda61dabd65db878d4"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
@@ -4211,13 +4141,13 @@ files = [
|
||||
|
||||
[[package]]
|
||||
name = "pyright"
|
||||
version = "1.1.369"
|
||||
version = "1.1.370"
|
||||
description = "Command line wrapper for pyright"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "pyright-1.1.369-py3-none-any.whl", hash = "sha256:06d5167a8d7be62523ced0265c5d2f1e022e110caf57a25d92f50fb2d07bcda0"},
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{file = "pyright-1.1.369.tar.gz", hash = "sha256:ad290710072d021e213b98cc7a2f90ae3a48609ef5b978f749346d1a47eb9af8"},
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{file = "pyright-1.1.370-py3-none-any.whl", hash = "sha256:fc721601e480a69989775bfc210534a6ca0110ebd0c065244a8d3a151294fc61"},
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{file = "pyright-1.1.370.tar.gz", hash = "sha256:d0d559d506fc41e3297f721aaa05a1b9f06beda5acc9ac64ca371ce94c28f960"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
@@ -5384,21 +5314,6 @@ files = [
|
||||
{file = "typing_extensions-4.12.2.tar.gz", hash = "sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "typing-inspect"
|
||||
version = "0.9.0"
|
||||
description = "Runtime inspection utilities for typing module."
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
files = [
|
||||
{file = "typing_inspect-0.9.0-py3-none-any.whl", hash = "sha256:9ee6fc59062311ef8547596ab6b955e1b8aa46242d854bfc78f4f6b0eff35f9f"},
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||||
{file = "typing_inspect-0.9.0.tar.gz", hash = "sha256:b23fc42ff6f6ef6954e4852c1fb512cdd18dbea03134f91f856a95ccc9461f78"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
mypy-extensions = ">=0.3.0"
|
||||
typing-extensions = ">=3.7.4"
|
||||
|
||||
[[package]]
|
||||
name = "ujson"
|
||||
version = "5.10.0"
|
||||
@@ -6082,4 +5997,4 @@ tools = ["crewai-tools"]
|
||||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = ">=3.10,<=3.13"
|
||||
content-hash = "e605a254f66369bdf6dbdad36f7bd58d7d97377ea37c151cccc7f48ef9f96f55"
|
||||
content-hash = "4f3e5fddb5f0fc8fd143a8abe947ecac443213d595bd0eeed745ccb82dac2312"
|
||||
|
||||
@@ -14,20 +14,20 @@ Repository = "https://github.com/joaomdmoura/crewai"
|
||||
[tool.poetry.dependencies]
|
||||
python = ">=3.10,<=3.13"
|
||||
pydantic = "^2.4.2"
|
||||
langchain = ">=0.1.4,<0.2.0"
|
||||
langchain = ">0.2,<=0.3"
|
||||
openai = "^1.13.3"
|
||||
opentelemetry-api = "^1.22.0"
|
||||
opentelemetry-sdk = "^1.22.0"
|
||||
opentelemetry-exporter-otlp-proto-http = "^1.22.0"
|
||||
instructor = "1.3.3"
|
||||
regex = "^2023.12.25"
|
||||
crewai-tools = { version = "^0.4.6", optional = true }
|
||||
crewai-tools = { version = "^0.4.7", optional = true }
|
||||
click = "^8.1.7"
|
||||
python-dotenv = "^1.0.0"
|
||||
appdirs = "^1.4.4"
|
||||
jsonref = "^1.1.0"
|
||||
agentops = { version = "^0.1.9", optional = true }
|
||||
embedchain = "^0.1.113"
|
||||
embedchain = "^0.1.114"
|
||||
|
||||
[tool.poetry.extras]
|
||||
tools = ["crewai-tools"]
|
||||
@@ -45,7 +45,7 @@ mkdocs-material = { extras = ["imaging"], version = "^9.5.7" }
|
||||
mkdocs-material-extensions = "^1.3.1"
|
||||
pillow = "^10.2.0"
|
||||
cairosvg = "^2.7.1"
|
||||
crewai-tools = "^0.4.6"
|
||||
crewai-tools = "^0.4.7"
|
||||
|
||||
[tool.poetry.group.test.dependencies]
|
||||
pytest = "^8.0.0"
|
||||
|
||||
@@ -90,6 +90,9 @@ class Agent(BaseAgent):
|
||||
response_template: Optional[str] = Field(
|
||||
default=None, description="Response format for the agent."
|
||||
)
|
||||
tools_results: Optional[List[Any]] = Field(
|
||||
default=[], description="Results of the tools used by the agent."
|
||||
)
|
||||
allow_code_execution: Optional[bool] = Field(
|
||||
default=False, description="Enable code execution for the agent."
|
||||
)
|
||||
@@ -116,7 +119,8 @@ class Agent(BaseAgent):
|
||||
self.llm.callbacks.append(token_handler)
|
||||
|
||||
if agentops and not any(
|
||||
isinstance(handler, agentops.LangchainCallbackHandler) for handler in self.llm.callbacks
|
||||
isinstance(handler, agentops.LangchainCallbackHandler)
|
||||
for handler in self.llm.callbacks
|
||||
):
|
||||
agentops.stop_instrumenting()
|
||||
self.llm.callbacks.append(agentops.LangchainCallbackHandler())
|
||||
@@ -188,6 +192,14 @@ class Agent(BaseAgent):
|
||||
)["output"]
|
||||
if self.max_rpm:
|
||||
self._rpm_controller.stop_rpm_counter()
|
||||
|
||||
# If there was any tool in self.tools_results that had result_as_answer
|
||||
# set to True, return the results of the last tool that had
|
||||
# result_as_answer set to True
|
||||
for tool_result in self.tools_results:
|
||||
if tool_result.get("result_as_answer", False):
|
||||
result = tool_result["result"]
|
||||
|
||||
return result
|
||||
|
||||
def format_log_to_str(
|
||||
|
||||
@@ -243,6 +243,7 @@ class CrewAgentExecutor(AgentExecutor, CrewAgentExecutorMixin):
|
||||
tools_names=self.tools_names,
|
||||
function_calling_llm=self.function_calling_llm,
|
||||
task=self.task,
|
||||
agent=self.crew_agent,
|
||||
action=agent_action,
|
||||
)
|
||||
tool_calling = tool_usage.parse(agent_action.log)
|
||||
|
||||
@@ -51,6 +51,7 @@ class ToolUsage:
|
||||
tools_names: str,
|
||||
task: Any,
|
||||
function_calling_llm: Any,
|
||||
agent: Any,
|
||||
action: Any,
|
||||
) -> None:
|
||||
self._i18n: I18N = I18N()
|
||||
@@ -59,6 +60,7 @@ class ToolUsage:
|
||||
self._run_attempts: int = 1
|
||||
self._max_parsing_attempts: int = 3
|
||||
self._remember_format_after_usages: int = 3
|
||||
self.agent = agent
|
||||
self.tools_description = tools_description
|
||||
self.tools_names = tools_names
|
||||
self.tools_handler = tools_handler
|
||||
@@ -130,6 +132,10 @@ class ToolUsage:
|
||||
tool=calling.tool_name, input=calling.arguments
|
||||
)
|
||||
|
||||
original_tool = next(
|
||||
(ot for ot in self.original_tools if ot.name == tool.name), None
|
||||
)
|
||||
|
||||
if result is None: #! finecwg: if not result --> if result is None
|
||||
try:
|
||||
if calling.tool_name in [
|
||||
@@ -179,9 +185,6 @@ class ToolUsage:
|
||||
|
||||
if self.tools_handler:
|
||||
should_cache = True
|
||||
original_tool = next(
|
||||
(ot for ot in self.original_tools if ot.name == tool.name), None
|
||||
)
|
||||
if (
|
||||
hasattr(original_tool, "cache_function")
|
||||
and original_tool.cache_function # type: ignore # Item "None" of "Any | None" has no attribute "cache_function"
|
||||
@@ -203,6 +206,21 @@ class ToolUsage:
|
||||
attempts=self._run_attempts,
|
||||
)
|
||||
result = self._format_result(result=result) # type: ignore # "_format_result" of "ToolUsage" does not return a value (it only ever returns None)
|
||||
data = {
|
||||
"result": result,
|
||||
"tool_name": tool.name,
|
||||
"tool_args": calling.arguments,
|
||||
}
|
||||
|
||||
if (
|
||||
hasattr(original_tool, "result_as_answer")
|
||||
and original_tool.result_as_answer # type: ignore # Item "None" of "Any | None" has no attribute "cache_function"
|
||||
):
|
||||
result_as_answer = original_tool.result_as_answer
|
||||
data["result_as_answer"] = result_as_answer
|
||||
|
||||
self.agent.tools_results.append(data)
|
||||
|
||||
return result # type: ignore # No return value expected
|
||||
|
||||
def _format_result(self, result: Any) -> None:
|
||||
|
||||
@@ -723,6 +723,75 @@ def test_agent_count_formatting_error():
|
||||
mock_count_errors.assert_called_once()
|
||||
|
||||
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_tool_result_as_answer_is_the_final_answer_for_the_agent():
|
||||
from crewai_tools import BaseTool
|
||||
|
||||
class MyCustomTool(BaseTool):
|
||||
name: str = "Get Greetings"
|
||||
description: str = "Get a random greeting back"
|
||||
|
||||
def _run(self) -> str:
|
||||
return "Howdy!"
|
||||
|
||||
agent1 = Agent(
|
||||
role="Data Scientist",
|
||||
goal="Product amazing resports on AI",
|
||||
backstory="You work with data and AI",
|
||||
tools=[MyCustomTool(result_as_answer=True)],
|
||||
)
|
||||
|
||||
essay = Task(
|
||||
description="Write and then review an small paragraph on AI until it's AMAZING. But first use the `Get Greetings` tool to get a greeting.",
|
||||
expected_output="The final paragraph with the full review on AI and no greeting.",
|
||||
agent=agent1,
|
||||
)
|
||||
tasks = [essay]
|
||||
crew = Crew(agents=[agent1], tasks=tasks)
|
||||
|
||||
result = crew.kickoff()
|
||||
assert result == "Howdy!"
|
||||
|
||||
|
||||
pytest.mark.vcr(filter_headers=["authorization"])
|
||||
|
||||
|
||||
def test_tool_usage_information_is_appended_to_agent():
|
||||
from crewai_tools import BaseTool
|
||||
|
||||
class MyCustomTool(BaseTool):
|
||||
name: str = "Decide Greetings"
|
||||
description: str = "Decide what is the appropriate greeting to use"
|
||||
|
||||
def _run(self) -> str:
|
||||
return "Howdy!"
|
||||
|
||||
agent1 = Agent(
|
||||
role="Friendly Neighbor",
|
||||
goal="Make everyone feel welcome",
|
||||
backstory="You are the friendly neighbor",
|
||||
tools=[MyCustomTool(result_as_answer=True)],
|
||||
)
|
||||
|
||||
greeting = Task(
|
||||
description="Say an appropriate greeting.",
|
||||
expected_output="The greeting.",
|
||||
agent=agent1,
|
||||
)
|
||||
tasks = [greeting]
|
||||
crew = Crew(agents=[agent1], tasks=tasks)
|
||||
|
||||
crew.kickoff()
|
||||
assert agent1.tools_results == [
|
||||
{
|
||||
"result": "Howdy!",
|
||||
"tool_name": "Decide Greetings",
|
||||
"tool_args": {},
|
||||
"result_as_answer": True,
|
||||
}
|
||||
]
|
||||
|
||||
|
||||
def test_agent_llm_uses_token_calc_handler_with_llm_has_model_name():
|
||||
agent1 = Agent(
|
||||
role="test role",
|
||||
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assert '{\n "score": 5\n}' == result
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@pytest.mark.vcr(filter_headers=["authorization"])
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Reference in New Issue
Block a user