mirror of
https://github.com/crewAIInc/crewAI.git
synced 2026-07-01 21:28:10 +00:00
c5a9a8da50
Extract duplicated Redis URL parsing into a shared cache_config utility. Introduce ValkeyCache as a lightweight async key/value cache using valkey-glide. Wire it into A2A task handling, agent card caching, and file upload caching. Part 1/4 of Valkey storage implementation. fix: async-safe embeddings and resilient drain_writes Add bytes→float validators on MemoryRecord and ItemState to handle Valkey returning embeddings as raw bytes. Make embed_texts() safe when called from an async context by using a thread pool. Improve drain_writes() with per-save timeouts and error logging instead of raising on failure. Part 3/4 of Valkey storage implementation. feat(valkey): ValkeyStorage vector memory backend Add ValkeyStorage, a distributed StorageBackend implementation using Valkey-GLIDE with Valkey Search for vector similarity. Wire it into Memory as the 'valkey' storage option. Pin scrapegraph-py<2 to fix unrelated upstream breakage. Part 4/4 of Valkey storage implementation. fix: use datetime.utcnow() for last_accessed consistency MemoryRecord defaults use utcnow() for created_at and last_accessed. Match that in ValkeyStorage.update_record() to avoid timezone inconsistency in recency scoring. feat(valkey): shared cache config + ValkeyCache for A2A and file uploads Extract duplicated Redis URL parsing into a shared cache_config utility. Introduce ValkeyCache as a lightweight async key/value cache using valkey-glide. Wire it into A2A task handling, agent card caching, and file upload caching. Part 1/4 of Valkey storage implementation. fix: handle non-numeric database path in cache URL parsing Extract _parse_db_from_path() helper that catches ValueError for paths like /mydb and defaults to 0 with a warning, instead of crashing. fix: async-safe embeddings and resilient drain_writes Add bytes→float validators on MemoryRecord and ItemState to handle Valkey returning embeddings as raw bytes. Make embed_texts() safe when called from an async context by using a thread pool. Improve drain_writes() with per-save timeouts and error logging instead of raising on failure. Part 3/4 of Valkey storage implementation. fix: catch concurrent.futures.TimeoutError for Python 3.10 compat In Python <3.11, concurrent.futures.TimeoutError is distinct from the builtin TimeoutError. Catch both so the timeout warning path works on all supported Python versions.
150 lines
3.2 KiB
TOML
150 lines
3.2 KiB
TOML
[project]
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name = "crewai"
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dynamic = ["version"]
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description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
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readme = "README.md"
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authors = [
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{ name = "Joao Moura", email = "joao@crewai.com" }
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]
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requires-python = ">=3.10, <3.14"
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dependencies = [
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"crewai-core==1.14.5a5",
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"crewai-cli==1.14.5a5",
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# Core Dependencies
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"pydantic>=2.11.9,<2.13",
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"openai>=2.30.0,<3",
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"instructor>=1.3.3",
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# Text Processing
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"pdfplumber~=0.11.4",
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"regex~=2026.1.15",
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# Telemetry and Monitoring
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"opentelemetry-api~=1.34.0",
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"opentelemetry-sdk~=1.34.0",
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"opentelemetry-exporter-otlp-proto-http~=1.34.0",
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# Data Handling
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"chromadb~=1.1.0",
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"tokenizers>=0.21,<1",
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"openpyxl~=3.1.5",
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# Authentication and Security
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"python-dotenv>=1.2.2,<2",
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"pyjwt>=2.9.0,<3",
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# Configuration and Utils
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"click~=8.1.7",
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"appdirs~=1.4.4",
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"jsonref~=1.1.0",
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"json-repair~=0.25.2",
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"tomli-w~=1.1.0",
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"tomli~=2.0.2",
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"json5~=0.10.0",
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"portalocker~=2.7.0",
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"pydantic-settings~=2.10.1",
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"httpx~=0.28.1",
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"mcp~=1.26.0",
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"aiosqlite~=0.21.0",
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"pyyaml~=6.0",
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"aiofiles~=24.1.0",
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"lancedb>=0.29.2,<0.30.1",
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]
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[project.urls]
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Homepage = "https://crewai.com"
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Documentation = "https://docs.crewai.com"
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Repository = "https://github.com/crewAIInc/crewAI"
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[project.optional-dependencies]
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tools = [
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"crewai-tools==1.14.5a5",
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]
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embeddings = [
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"tiktoken>=0.8.0,<0.13"
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]
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pandas = [
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"pandas~=2.2.3",
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]
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openpyxl = [
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"openpyxl~=3.1.5",
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]
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mem0 = ["mem0ai>=2.0.0,<3"]
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docling = [
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"docling~=2.84.0",
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]
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qdrant = [
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"qdrant-client[fastembed]~=1.14.3",
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]
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aws = [
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"boto3~=1.42.79",
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"aiobotocore~=3.4.0",
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]
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watson = [
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"ibm-watsonx-ai~=1.3.39",
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]
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voyageai = [
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"voyageai~=0.3.5",
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]
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litellm = [
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"litellm>=1.83.7,<1.84",
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]
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bedrock = [
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"boto3~=1.42.79",
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]
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google-genai = [
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"google-genai~=1.65.0",
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]
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azure-ai-inference = [
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"azure-ai-inference~=1.0.0b9",
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"azure-identity>=1.17.0,<2",
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]
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anthropic = [
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"anthropic~=0.73.0",
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]
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a2a = [
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"a2a-sdk~=0.3.10",
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"httpx-auth~=0.23.1",
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"httpx-sse~=0.4.0",
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"aiocache[redis,memcached]~=0.12.3",
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]
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file-processing = [
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"crewai-files==1.14.5a5",
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]
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qdrant-edge = [
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"qdrant-edge-py>=0.6.0",
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]
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valkey = [
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"valkey-glide>=1.3.0",
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]
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[tool.uv]
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exclude-newer = "3 days"
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# PyTorch index configuration, since torch 2.5.0 is not compatible with python 3.13
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[[tool.uv.index]]
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name = "pytorch-nightly"
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url = "https://download.pytorch.org/whl/nightly/cpu"
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explicit = true
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[[tool.uv.index]]
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name = "pytorch"
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url = "https://download.pytorch.org/whl/cpu"
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explicit = true
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[tool.uv.sources]
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torch = [
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{ index = "pytorch-nightly", marker = "python_version >= '3.13'" },
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{ index = "pytorch", marker = "python_version < '3.13'" },
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]
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torchvision = [
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{ index = "pytorch-nightly", marker = "python_version >= '3.13'" },
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{ index = "pytorch", marker = "python_version < '3.13'" },
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]
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crewai-files = { workspace = true }
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[build-system]
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requires = ["hatchling"]
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build-backend = "hatchling.build"
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[tool.hatch.version]
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path = "src/crewai/__init__.py"
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