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https://github.com/crewAIInc/crewAI.git
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4 Commits
devin/1756
...
devin/1741
| Author | SHA1 | Date | |
|---|---|---|---|
|
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538f1a2a84 | ||
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dcf8e8d6e7 | ||
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fde4c4e92b | ||
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36e7236ffe |
@@ -136,6 +136,14 @@ pip install 'crewai[tools]'
|
||||
```
|
||||
The command above installs the basic package and also adds extra components which require more dependencies to function.
|
||||
|
||||
For vector storage and RAG capabilities, install with the chromadb extra:
|
||||
|
||||
```shell
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||||
pip install 'crewai[chromadb]'
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||||
```
|
||||
|
||||
Note: If you're using Alpine Linux or other environments where onnxruntime is not available, you can still use CrewAI without the chromadb dependency, but with limited vector storage functionality.
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|
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### Troubleshooting Dependencies
|
||||
|
||||
If you encounter issues during installation or usage, here are some common solutions:
|
||||
|
||||
@@ -21,7 +21,6 @@ dependencies = [
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"opentelemetry-sdk>=1.22.0",
|
||||
"opentelemetry-exporter-otlp-proto-http>=1.22.0",
|
||||
# Data Handling
|
||||
"chromadb>=0.5.23",
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||||
"openpyxl>=3.1.5",
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||||
"pyvis>=0.3.2",
|
||||
# Authentication and Security
|
||||
@@ -64,6 +63,9 @@ mem0 = ["mem0ai>=0.1.29"]
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docling = [
|
||||
"docling>=2.12.0",
|
||||
]
|
||||
chromadb = [
|
||||
"chromadb>=0.5.23",
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||||
]
|
||||
|
||||
[tool.uv]
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||||
dev-dependencies = [
|
||||
|
||||
@@ -6,11 +6,18 @@ import os
|
||||
import shutil
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||||
from typing import Any, Dict, List, Optional, Union, cast
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||||
|
||||
import chromadb
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||||
import chromadb.errors
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||||
from chromadb.api import ClientAPI
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||||
from chromadb.api.types import OneOrMany
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from chromadb.config import Settings
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||||
try:
|
||||
import chromadb
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||||
import chromadb.errors
|
||||
from chromadb.api import ClientAPI
|
||||
from chromadb.api.types import OneOrMany
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from chromadb.config import Settings
|
||||
CHROMADB_AVAILABLE = True
|
||||
except ImportError:
|
||||
CHROMADB_AVAILABLE = False
|
||||
# Define placeholder types for type checking
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||||
ClientAPI = Any
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||||
OneOrMany = Any
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||||
|
||||
from crewai.knowledge.storage.base_knowledge_storage import BaseKnowledgeStorage
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from crewai.utilities import EmbeddingConfigurator
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@@ -42,9 +49,10 @@ class KnowledgeStorage(BaseKnowledgeStorage):
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search efficiency.
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||||
"""
|
||||
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collection: Optional[chromadb.Collection] = None
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collection: Optional[Any] = None # Will be chromadb.Collection when available
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collection_name: Optional[str] = "knowledge"
|
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app: Optional[ClientAPI] = None
|
||||
app: Optional[Any] = None # Will be ClientAPI when available
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embedder: Optional[Any] = None
|
||||
|
||||
def __init__(
|
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self,
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@@ -61,63 +69,98 @@ class KnowledgeStorage(BaseKnowledgeStorage):
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filter: Optional[dict] = None,
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score_threshold: float = 0.35,
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||||
) -> List[Dict[str, Any]]:
|
||||
with suppress_logging():
|
||||
if self.collection:
|
||||
fetched = self.collection.query(
|
||||
query_texts=query,
|
||||
n_results=limit,
|
||||
where=filter,
|
||||
)
|
||||
results = []
|
||||
for i in range(len(fetched["ids"][0])): # type: ignore
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result = {
|
||||
"id": fetched["ids"][0][i], # type: ignore
|
||||
"metadata": fetched["metadatas"][0][i], # type: ignore
|
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"context": fetched["documents"][0][i], # type: ignore
|
||||
"score": fetched["distances"][0][i], # type: ignore
|
||||
}
|
||||
if result["score"] >= score_threshold:
|
||||
results.append(result)
|
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return results
|
||||
else:
|
||||
raise Exception("Collection not initialized")
|
||||
if not CHROMADB_AVAILABLE:
|
||||
logging.warning(
|
||||
"ChromaDB is not installed. Search functionality limited. "
|
||||
"Install with 'pip install crewai[chromadb]' to enable full functionality."
|
||||
)
|
||||
return []
|
||||
|
||||
try:
|
||||
with suppress_logging():
|
||||
if self.collection:
|
||||
fetched = self.collection.query(
|
||||
query_texts=query,
|
||||
n_results=limit,
|
||||
where=filter,
|
||||
)
|
||||
results = []
|
||||
for i in range(len(fetched["ids"][0])): # type: ignore
|
||||
result = {
|
||||
"id": fetched["ids"][0][i], # type: ignore
|
||||
"metadata": fetched["metadatas"][0][i], # type: ignore
|
||||
"context": fetched["documents"][0][i], # type: ignore
|
||||
"score": fetched["distances"][0][i], # type: ignore
|
||||
}
|
||||
if result["score"] >= score_threshold:
|
||||
results.append(result)
|
||||
return results
|
||||
else:
|
||||
return []
|
||||
except (ImportError, NameError, AttributeError, Exception) as e:
|
||||
logging.error(f"Error during knowledge search operation: {str(e)}")
|
||||
return []
|
||||
|
||||
def initialize_knowledge_storage(self):
|
||||
base_path = os.path.join(db_storage_path(), "knowledge")
|
||||
chroma_client = chromadb.PersistentClient(
|
||||
path=base_path,
|
||||
settings=Settings(allow_reset=True),
|
||||
)
|
||||
|
||||
self.app = chroma_client
|
||||
|
||||
try:
|
||||
collection_name = (
|
||||
f"knowledge_{self.collection_name}"
|
||||
if self.collection_name
|
||||
else "knowledge"
|
||||
if not CHROMADB_AVAILABLE:
|
||||
import logging
|
||||
logging.warning(
|
||||
"ChromaDB is not installed. Knowledge storage functionality will be limited. "
|
||||
"Install with 'pip install crewai[chromadb]' to enable full functionality."
|
||||
)
|
||||
if self.app:
|
||||
self.collection = self.app.get_or_create_collection(
|
||||
name=collection_name, embedding_function=self.embedder
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||||
)
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||||
else:
|
||||
raise Exception("Vector Database Client not initialized")
|
||||
except Exception:
|
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raise Exception("Failed to create or get collection")
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|
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def reset(self):
|
||||
base_path = os.path.join(db_storage_path(), KNOWLEDGE_DIRECTORY)
|
||||
if not self.app:
|
||||
self.app = chromadb.PersistentClient(
|
||||
self.app = None
|
||||
self.collection = None
|
||||
return
|
||||
|
||||
try:
|
||||
base_path = os.path.join(db_storage_path(), "knowledge")
|
||||
chroma_client = chromadb.PersistentClient(
|
||||
path=base_path,
|
||||
settings=Settings(allow_reset=True),
|
||||
)
|
||||
|
||||
self.app.reset()
|
||||
shutil.rmtree(base_path)
|
||||
self.app = None
|
||||
self.collection = None
|
||||
self.app = chroma_client
|
||||
|
||||
try:
|
||||
collection_name = (
|
||||
f"knowledge_{self.collection_name}"
|
||||
if self.collection_name
|
||||
else "knowledge"
|
||||
)
|
||||
if self.app:
|
||||
self.collection = self.app.get_or_create_collection(
|
||||
name=collection_name, embedding_function=self.embedder
|
||||
)
|
||||
else:
|
||||
raise Exception("Vector Database Client not initialized")
|
||||
except Exception:
|
||||
raise Exception("Failed to create or get collection")
|
||||
except Exception:
|
||||
logging.warning(
|
||||
"Error initializing ChromaDB. Knowledge storage functionality will be limited."
|
||||
)
|
||||
self.app = None
|
||||
self.collection = None
|
||||
|
||||
def reset(self):
|
||||
base_path = os.path.join(db_storage_path(), KNOWLEDGE_DIRECTORY)
|
||||
try:
|
||||
if not self.app:
|
||||
self.app = chromadb.PersistentClient(
|
||||
path=base_path,
|
||||
settings=Settings(allow_reset=True),
|
||||
)
|
||||
|
||||
self.app.reset()
|
||||
shutil.rmtree(base_path)
|
||||
self.app = None
|
||||
self.collection = None
|
||||
except (ImportError, NameError, AttributeError):
|
||||
# Handle case when chromadb is not available
|
||||
if os.path.exists(base_path):
|
||||
shutil.rmtree(base_path)
|
||||
self.app = None
|
||||
self.collection = None
|
||||
|
||||
def save(
|
||||
self,
|
||||
@@ -125,7 +168,8 @@ class KnowledgeStorage(BaseKnowledgeStorage):
|
||||
metadata: Optional[Union[Dict[str, Any], List[Dict[str, Any]]]] = None,
|
||||
):
|
||||
if not self.collection:
|
||||
raise Exception("Collection not initialized")
|
||||
# Just return silently if chromadb is not available
|
||||
return
|
||||
|
||||
try:
|
||||
# Create a dictionary to store unique documents
|
||||
@@ -154,7 +198,7 @@ class KnowledgeStorage(BaseKnowledgeStorage):
|
||||
filtered_ids.append(doc_id)
|
||||
|
||||
# If we have no metadata at all, set it to None
|
||||
final_metadata: Optional[OneOrMany[chromadb.Metadata]] = (
|
||||
final_metadata = (
|
||||
None if all(m is None for m in filtered_metadata) else filtered_metadata
|
||||
)
|
||||
|
||||
@@ -163,29 +207,40 @@ class KnowledgeStorage(BaseKnowledgeStorage):
|
||||
metadatas=final_metadata,
|
||||
ids=filtered_ids,
|
||||
)
|
||||
except chromadb.errors.InvalidDimensionException as e:
|
||||
Logger(verbose=True).log(
|
||||
"error",
|
||||
"Embedding dimension mismatch. This usually happens when mixing different embedding models. Try resetting the collection using `crewai reset-memories -a`",
|
||||
"red",
|
||||
)
|
||||
raise ValueError(
|
||||
"Embedding dimension mismatch. Make sure you're using the same embedding model "
|
||||
"across all operations with this collection."
|
||||
"Try resetting the collection using `crewai reset-memories -a`"
|
||||
) from e
|
||||
except (ImportError, NameError, AttributeError) as e:
|
||||
# Handle case when chromadb is not available
|
||||
return
|
||||
except Exception as e:
|
||||
if "chromadb" in str(e.__class__):
|
||||
# Handle chromadb-specific errors silently when chromadb might not be fully available
|
||||
return
|
||||
Logger(verbose=True).log("error", f"Failed to upsert documents: {e}", "red")
|
||||
raise
|
||||
# Don't raise the exception, just log it and continue
|
||||
return
|
||||
|
||||
def _create_default_embedding_function(self):
|
||||
from chromadb.utils.embedding_functions.openai_embedding_function import (
|
||||
OpenAIEmbeddingFunction,
|
||||
)
|
||||
try:
|
||||
from chromadb.utils.embedding_functions.openai_embedding_function import (
|
||||
OpenAIEmbeddingFunction,
|
||||
)
|
||||
|
||||
return OpenAIEmbeddingFunction(
|
||||
api_key=os.getenv("OPENAI_API_KEY"), model_name="text-embedding-3-small"
|
||||
)
|
||||
api_key = os.getenv("OPENAI_API_KEY")
|
||||
if not api_key:
|
||||
logging.warning(
|
||||
"OPENAI_API_KEY not found. Vector operations will be limited."
|
||||
)
|
||||
return None
|
||||
|
||||
return OpenAIEmbeddingFunction(
|
||||
api_key=api_key, model_name="text-embedding-3-small"
|
||||
)
|
||||
except ImportError:
|
||||
import logging
|
||||
logging.warning(
|
||||
"ChromaDB is not installed. Cannot create default embedding function. "
|
||||
"Install with 'pip install crewai[chromadb]' to enable full functionality."
|
||||
)
|
||||
return None
|
||||
|
||||
def _set_embedder_config(self, embedder: Optional[Dict[str, Any]] = None) -> None:
|
||||
"""Set the embedding configuration for the knowledge storage.
|
||||
@@ -194,8 +249,12 @@ class KnowledgeStorage(BaseKnowledgeStorage):
|
||||
embedder_config (Optional[Dict[str, Any]]): Configuration dictionary for the embedder.
|
||||
If None or empty, defaults to the default embedding function.
|
||||
"""
|
||||
self.embedder = (
|
||||
EmbeddingConfigurator().configure_embedder(embedder)
|
||||
if embedder
|
||||
else self._create_default_embedding_function()
|
||||
)
|
||||
try:
|
||||
self.embedder = (
|
||||
EmbeddingConfigurator().configure_embedder(embedder)
|
||||
if embedder
|
||||
else self._create_default_embedding_function()
|
||||
)
|
||||
except (ImportError, NameError, AttributeError):
|
||||
# Handle case when chromadb is not available
|
||||
self.embedder = None
|
||||
|
||||
@@ -4,9 +4,15 @@ import logging
|
||||
import os
|
||||
import shutil
|
||||
import uuid
|
||||
from typing import Any, Dict, List, Optional
|
||||
from typing import Any, Dict, List, Optional, cast
|
||||
|
||||
from chromadb.api import ClientAPI
|
||||
try:
|
||||
from chromadb.api import ClientAPI
|
||||
CHROMADB_AVAILABLE = True
|
||||
except ImportError:
|
||||
CHROMADB_AVAILABLE = False
|
||||
# Define placeholder type for type checking
|
||||
ClientAPI = Any
|
||||
|
||||
from crewai.memory.storage.base_rag_storage import BaseRAGStorage
|
||||
from crewai.utilities import EmbeddingConfigurator
|
||||
@@ -37,7 +43,7 @@ class RAGStorage(BaseRAGStorage):
|
||||
search efficiency.
|
||||
"""
|
||||
|
||||
app: ClientAPI | None = None
|
||||
app = None # Type will be ClientAPI when available
|
||||
|
||||
def __init__(
|
||||
self, type, allow_reset=True, embedder_config=None, crew=None, path=None
|
||||
@@ -60,26 +66,41 @@ class RAGStorage(BaseRAGStorage):
|
||||
self.embedder_config = configurator.configure_embedder(self.embedder_config)
|
||||
|
||||
def _initialize_app(self):
|
||||
import chromadb
|
||||
from chromadb.config import Settings
|
||||
|
||||
self._set_embedder_config()
|
||||
chroma_client = chromadb.PersistentClient(
|
||||
path=self.path if self.path else self.storage_file_name,
|
||||
settings=Settings(allow_reset=self.allow_reset),
|
||||
)
|
||||
|
||||
self.app = chroma_client
|
||||
|
||||
if not CHROMADB_AVAILABLE:
|
||||
logging.warning(
|
||||
"ChromaDB is not installed. RAG storage functionality will be limited. "
|
||||
"Install with 'pip install crewai[chromadb]' to enable full functionality."
|
||||
)
|
||||
self.app = None
|
||||
self.collection = None
|
||||
return
|
||||
|
||||
try:
|
||||
self.collection = self.app.get_collection(
|
||||
name=self.type, embedding_function=self.embedder_config
|
||||
)
|
||||
except Exception:
|
||||
self.collection = self.app.create_collection(
|
||||
name=self.type, embedding_function=self.embedder_config
|
||||
import chromadb
|
||||
from chromadb.config import Settings
|
||||
|
||||
self._set_embedder_config()
|
||||
chroma_client = chromadb.PersistentClient(
|
||||
path=self.path if self.path else self.storage_file_name,
|
||||
settings=Settings(allow_reset=self.allow_reset),
|
||||
)
|
||||
|
||||
self.app = chroma_client
|
||||
|
||||
try:
|
||||
self.collection = self.app.get_collection(
|
||||
name=self.type, embedding_function=self.embedder_config
|
||||
)
|
||||
except Exception as e:
|
||||
logging.info(f"Collection not found, creating new one: {str(e)}")
|
||||
self.collection = self.app.create_collection(
|
||||
name=self.type, embedding_function=self.embedder_config
|
||||
)
|
||||
except Exception as e:
|
||||
logging.error(f"Failed to initialize ChromaDB: {str(e)}")
|
||||
self.app = None
|
||||
self.collection = None
|
||||
|
||||
def _sanitize_role(self, role: str) -> str:
|
||||
"""
|
||||
Sanitizes agent roles to ensure valid directory names.
|
||||
@@ -103,6 +124,10 @@ class RAGStorage(BaseRAGStorage):
|
||||
def save(self, value: Any, metadata: Dict[str, Any]) -> None:
|
||||
if not hasattr(self, "app") or not hasattr(self, "collection"):
|
||||
self._initialize_app()
|
||||
|
||||
if not self.collection:
|
||||
return
|
||||
|
||||
try:
|
||||
self._generate_embedding(value, metadata)
|
||||
except Exception as e:
|
||||
@@ -115,8 +140,18 @@ class RAGStorage(BaseRAGStorage):
|
||||
filter: Optional[dict] = None,
|
||||
score_threshold: float = 0.35,
|
||||
) -> List[Any]:
|
||||
if not CHROMADB_AVAILABLE:
|
||||
logging.warning(
|
||||
"ChromaDB is not installed. Search functionality limited. "
|
||||
"Install with 'pip install crewai[chromadb]' to enable full functionality."
|
||||
)
|
||||
return []
|
||||
|
||||
if not hasattr(self, "app"):
|
||||
self._initialize_app()
|
||||
|
||||
if not self.collection:
|
||||
return []
|
||||
|
||||
try:
|
||||
with suppress_logging():
|
||||
@@ -141,6 +176,9 @@ class RAGStorage(BaseRAGStorage):
|
||||
def _generate_embedding(self, text: str, metadata: Dict[str, Any]) -> None: # type: ignore
|
||||
if not hasattr(self, "app") or not hasattr(self, "collection"):
|
||||
self._initialize_app()
|
||||
|
||||
if not self.collection:
|
||||
return
|
||||
|
||||
self.collection.add(
|
||||
documents=[text],
|
||||
@@ -149,26 +187,44 @@ class RAGStorage(BaseRAGStorage):
|
||||
)
|
||||
|
||||
def reset(self) -> None:
|
||||
if not self.app:
|
||||
return
|
||||
|
||||
try:
|
||||
if self.app:
|
||||
self.app.reset()
|
||||
shutil.rmtree(f"{db_storage_path()}/{self.type}")
|
||||
self.app = None
|
||||
self.collection = None
|
||||
self.app.reset()
|
||||
path = f"{db_storage_path()}/{self.type}"
|
||||
if os.path.exists(path):
|
||||
shutil.rmtree(path)
|
||||
self.app = None
|
||||
self.collection = None
|
||||
except Exception as e:
|
||||
if "attempt to write a readonly database" in str(e):
|
||||
# Ignore this specific error
|
||||
pass
|
||||
else:
|
||||
raise Exception(
|
||||
f"An error occurred while resetting the {self.type} memory: {e}"
|
||||
)
|
||||
logging.error(f"Error during {self.type} reset: {str(e)}")
|
||||
# Don't raise the exception, just log it
|
||||
|
||||
def _create_default_embedding_function(self):
|
||||
from chromadb.utils.embedding_functions.openai_embedding_function import (
|
||||
OpenAIEmbeddingFunction,
|
||||
)
|
||||
try:
|
||||
from chromadb.utils.embedding_functions.openai_embedding_function import (
|
||||
OpenAIEmbeddingFunction,
|
||||
)
|
||||
|
||||
return OpenAIEmbeddingFunction(
|
||||
api_key=os.getenv("OPENAI_API_KEY"), model_name="text-embedding-3-small"
|
||||
)
|
||||
api_key = os.getenv("OPENAI_API_KEY")
|
||||
if not api_key:
|
||||
logging.warning(
|
||||
"OPENAI_API_KEY not found. Vector operations will be limited."
|
||||
)
|
||||
return None
|
||||
|
||||
return OpenAIEmbeddingFunction(
|
||||
api_key=api_key, model_name="text-embedding-3-small"
|
||||
)
|
||||
except ImportError:
|
||||
import logging
|
||||
logging.warning(
|
||||
"ChromaDB is not installed. Cannot create default embedding function. "
|
||||
"Install with 'pip install crewai[chromadb]' to enable full functionality."
|
||||
)
|
||||
return None
|
||||
|
||||
@@ -1,8 +1,17 @@
|
||||
import os
|
||||
from typing import Any, Dict, Optional, cast
|
||||
|
||||
from chromadb import Documents, EmbeddingFunction, Embeddings
|
||||
from chromadb.api.types import validate_embedding_function
|
||||
try:
|
||||
from chromadb import Documents, EmbeddingFunction, Embeddings
|
||||
from chromadb.api.types import validate_embedding_function
|
||||
CHROMADB_AVAILABLE = True
|
||||
except ImportError:
|
||||
CHROMADB_AVAILABLE = False
|
||||
# Define placeholder types for type checking
|
||||
Documents = Any
|
||||
EmbeddingFunction = Any
|
||||
Embeddings = Any
|
||||
def validate_embedding_function(func): return func
|
||||
|
||||
|
||||
class EmbeddingConfigurator:
|
||||
@@ -47,6 +56,14 @@ class EmbeddingConfigurator:
|
||||
|
||||
@staticmethod
|
||||
def _create_default_embedding_function():
|
||||
if not CHROMADB_AVAILABLE:
|
||||
import logging
|
||||
logging.warning(
|
||||
"ChromaDB is not installed. Cannot create default embedding function. "
|
||||
"Install with 'pip install crewai[chromadb]' to enable full functionality."
|
||||
)
|
||||
return None
|
||||
|
||||
from chromadb.utils.embedding_functions.openai_embedding_function import (
|
||||
OpenAIEmbeddingFunction,
|
||||
)
|
||||
|
||||
52
tests/test_optional_dependencies.py
Normal file
52
tests/test_optional_dependencies.py
Normal file
@@ -0,0 +1,52 @@
|
||||
import importlib
|
||||
import sys
|
||||
from unittest import mock
|
||||
|
||||
import pytest
|
||||
|
||||
|
||||
def test_rag_storage_without_chromadb():
|
||||
# Mock the import to simulate chromadb not being installed
|
||||
with mock.patch.dict(sys.modules, {'chromadb': None}):
|
||||
# Force reload to ensure our mock takes effect
|
||||
if 'crewai.memory.storage.rag_storage' in sys.modules:
|
||||
importlib.reload(sys.modules['crewai.memory.storage.rag_storage'])
|
||||
|
||||
# Now import and test
|
||||
from crewai.memory.storage.rag_storage import RAGStorage
|
||||
|
||||
# Should not raise an exception
|
||||
storage = RAGStorage(type="test", allow_reset=True)
|
||||
|
||||
# Methods should handle the case when chromadb is not available
|
||||
assert storage.app is None
|
||||
assert storage.collection is None
|
||||
|
||||
# These methods should not raise exceptions
|
||||
storage.save("test", {})
|
||||
results = storage.search("test")
|
||||
assert results == []
|
||||
storage.reset()
|
||||
|
||||
def test_knowledge_storage_without_chromadb():
|
||||
# Mock the import to simulate chromadb not being installed
|
||||
with mock.patch.dict(sys.modules, {'chromadb': None}):
|
||||
# Force reload to ensure our mock takes effect
|
||||
if 'crewai.knowledge.storage.knowledge_storage' in sys.modules:
|
||||
importlib.reload(sys.modules['crewai.knowledge.storage.knowledge_storage'])
|
||||
|
||||
# Now import and test
|
||||
from crewai.knowledge.storage.knowledge_storage import KnowledgeStorage
|
||||
|
||||
# Should not raise an exception
|
||||
storage = KnowledgeStorage()
|
||||
|
||||
# Methods should handle the case when chromadb is not available
|
||||
assert storage.app is None
|
||||
assert storage.collection is None
|
||||
|
||||
# These methods should not raise exceptions
|
||||
storage.initialize_knowledge_storage()
|
||||
results = storage.search(["test"])
|
||||
assert results == []
|
||||
storage.reset()
|
||||
103
uv.lock
generated
103
uv.lock
generated
@@ -1,42 +1,19 @@
|
||||
version = 1
|
||||
requires-python = ">=3.10, <3.13"
|
||||
resolution-markers = [
|
||||
"python_full_version < '3.11' and platform_system == 'Darwin' and sys_platform == 'darwin'",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform == 'darwin'",
|
||||
"(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version < '3.11' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_system == 'Darwin' and sys_platform == 'linux'",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform == 'linux'",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
|
||||
"(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version < '3.11' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
|
||||
"(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version < '3.11' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version == '3.11.*' and platform_system == 'Darwin' and sys_platform == 'darwin'",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform == 'darwin'",
|
||||
"(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version == '3.11.*' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_system == 'Darwin' and sys_platform == 'linux'",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform == 'linux'",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
|
||||
"(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version == '3.11.*' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
|
||||
"(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version == '3.11.*' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_system == 'Darwin' and sys_platform == 'darwin'",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform == 'darwin'",
|
||||
"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_system == 'Darwin' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
|
||||
"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
|
||||
"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version >= '3.12.4' and platform_system == 'Darwin' and sys_platform == 'darwin'",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform == 'darwin'",
|
||||
"(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version >= '3.12.4' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_system == 'Darwin' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
|
||||
"(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12.4' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
|
||||
"(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12.4' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version < '3.11' and sys_platform == 'darwin'",
|
||||
"python_version < '0'",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and sys_platform == 'linux'",
|
||||
"(python_full_version < '3.11' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version < '3.11' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version == '3.11.*' and sys_platform == 'darwin'",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and sys_platform == 'linux'",
|
||||
"(python_full_version == '3.11.*' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version == '3.11.*' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and sys_platform == 'darwin'",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and sys_platform == 'linux'",
|
||||
"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version >= '3.12.4' and sys_platform == 'darwin'",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and sys_platform == 'linux'",
|
||||
"(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12.4' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -333,7 +310,7 @@ name = "build"
|
||||
version = "1.2.2.post1"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "colorama", marker = "os_name == 'nt'" },
|
||||
{ name = "colorama", marker = "(os_name == 'nt' and platform_machine != 'aarch64' and sys_platform == 'linux') or (os_name == 'nt' and sys_platform != 'darwin' and sys_platform != 'linux')" },
|
||||
{ name = "importlib-metadata", marker = "python_full_version < '3.10.2'" },
|
||||
{ name = "packaging" },
|
||||
{ name = "pyproject-hooks" },
|
||||
@@ -568,7 +545,7 @@ name = "click"
|
||||
version = "8.1.8"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "colorama", marker = "platform_system == 'Windows'" },
|
||||
{ name = "colorama", marker = "sys_platform == 'win32'" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/b9/2e/0090cbf739cee7d23781ad4b89a9894a41538e4fcf4c31dcdd705b78eb8b/click-8.1.8.tar.gz", hash = "sha256:ed53c9d8990d83c2a27deae68e4ee337473f6330c040a31d4225c9574d16096a", size = 226593 }
|
||||
wheels = [
|
||||
@@ -625,7 +602,6 @@ dependencies = [
|
||||
{ name = "appdirs" },
|
||||
{ name = "auth0-python" },
|
||||
{ name = "blinker" },
|
||||
{ name = "chromadb" },
|
||||
{ name = "click" },
|
||||
{ name = "instructor" },
|
||||
{ name = "json-repair" },
|
||||
@@ -651,6 +627,9 @@ dependencies = [
|
||||
agentops = [
|
||||
{ name = "agentops" },
|
||||
]
|
||||
chromadb = [
|
||||
{ name = "chromadb" },
|
||||
]
|
||||
docling = [
|
||||
{ name = "docling" },
|
||||
]
|
||||
@@ -701,7 +680,7 @@ requires-dist = [
|
||||
{ name = "appdirs", specifier = ">=1.4.4" },
|
||||
{ name = "auth0-python", specifier = ">=4.7.1" },
|
||||
{ name = "blinker", specifier = ">=1.9.0" },
|
||||
{ name = "chromadb", specifier = ">=0.5.23" },
|
||||
{ name = "chromadb", marker = "extra == 'chromadb'", specifier = ">=0.5.23" },
|
||||
{ name = "click", specifier = ">=8.1.7" },
|
||||
{ name = "crewai-tools", marker = "extra == 'tools'", specifier = ">=0.37.0" },
|
||||
{ name = "docling", marker = "extra == 'docling'", specifier = ">=2.12.0" },
|
||||
@@ -2500,7 +2479,7 @@ version = "1.6.1"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "click" },
|
||||
{ name = "colorama", marker = "platform_system == 'Windows'" },
|
||||
{ name = "colorama", marker = "sys_platform == 'win32'" },
|
||||
{ name = "ghp-import" },
|
||||
{ name = "jinja2" },
|
||||
{ name = "markdown" },
|
||||
@@ -2681,7 +2660,7 @@ version = "2.10.2"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "pygments" },
|
||||
{ name = "pywin32", marker = "platform_system == 'Windows'" },
|
||||
{ name = "pywin32", marker = "sys_platform == 'win32'" },
|
||||
{ name = "tqdm" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/3a/93/80ac75c20ce54c785648b4ed363c88f148bf22637e10c9863db4fbe73e74/mpire-2.10.2.tar.gz", hash = "sha256:f66a321e93fadff34585a4bfa05e95bd946cf714b442f51c529038eb45773d97", size = 271270 }
|
||||
@@ -2928,7 +2907,7 @@ name = "nvidia-cudnn-cu12"
|
||||
version = "9.1.0.70"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "nvidia-cublas-cu12", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'linux')" },
|
||||
{ name = "nvidia-cublas-cu12", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
|
||||
]
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/9f/fd/713452cd72343f682b1c7b9321e23829f00b842ceaedcda96e742ea0b0b3/nvidia_cudnn_cu12-9.1.0.70-py3-none-manylinux2014_x86_64.whl", hash = "sha256:165764f44ef8c61fcdfdfdbe769d687e06374059fbb388b6c89ecb0e28793a6f", size = 664752741 },
|
||||
@@ -2955,9 +2934,9 @@ name = "nvidia-cusolver-cu12"
|
||||
version = "11.4.5.107"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "nvidia-cublas-cu12", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'linux')" },
|
||||
{ name = "nvidia-cusparse-cu12", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'linux')" },
|
||||
{ name = "nvidia-nvjitlink-cu12", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'linux')" },
|
||||
{ name = "nvidia-cublas-cu12", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
|
||||
{ name = "nvidia-cusparse-cu12", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
|
||||
{ name = "nvidia-nvjitlink-cu12", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
|
||||
]
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/bc/1d/8de1e5c67099015c834315e333911273a8c6aaba78923dd1d1e25fc5f217/nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl", hash = "sha256:8a7ec542f0412294b15072fa7dab71d31334014a69f953004ea7a118206fe0dd", size = 124161928 },
|
||||
@@ -2968,7 +2947,7 @@ name = "nvidia-cusparse-cu12"
|
||||
version = "12.1.0.106"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "nvidia-nvjitlink-cu12", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'linux')" },
|
||||
{ name = "nvidia-nvjitlink-cu12", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
|
||||
]
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/65/5b/cfaeebf25cd9fdec14338ccb16f6b2c4c7fa9163aefcf057d86b9cc248bb/nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl", hash = "sha256:f3b50f42cf363f86ab21f720998517a659a48131e8d538dc02f8768237bd884c", size = 195958278 },
|
||||
@@ -3506,7 +3485,7 @@ name = "portalocker"
|
||||
version = "2.10.1"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "pywin32", marker = "platform_system == 'Windows'" },
|
||||
{ name = "pywin32", marker = "sys_platform == 'win32'" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/ed/d3/c6c64067759e87af98cc668c1cc75171347d0f1577fab7ca3749134e3cd4/portalocker-2.10.1.tar.gz", hash = "sha256:ef1bf844e878ab08aee7e40184156e1151f228f103aa5c6bd0724cc330960f8f", size = 40891 }
|
||||
wheels = [
|
||||
@@ -5019,19 +4998,19 @@ dependencies = [
|
||||
{ name = "fsspec" },
|
||||
{ name = "jinja2" },
|
||||
{ name = "networkx" },
|
||||
{ name = "nvidia-cublas-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
|
||||
{ name = "nvidia-cuda-cupti-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
|
||||
{ name = "nvidia-cuda-nvrtc-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
|
||||
{ name = "nvidia-cuda-runtime-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
|
||||
{ name = "nvidia-cudnn-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
|
||||
{ name = "nvidia-cufft-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
|
||||
{ name = "nvidia-curand-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
|
||||
{ name = "nvidia-cusolver-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
|
||||
{ name = "nvidia-cusparse-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
|
||||
{ name = "nvidia-nccl-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
|
||||
{ name = "nvidia-nvtx-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
|
||||
{ name = "nvidia-cublas-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
|
||||
{ name = "nvidia-cuda-cupti-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
|
||||
{ name = "nvidia-cuda-nvrtc-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
|
||||
{ name = "nvidia-cuda-runtime-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
|
||||
{ name = "nvidia-cudnn-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
|
||||
{ name = "nvidia-cufft-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
|
||||
{ name = "nvidia-curand-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
|
||||
{ name = "nvidia-cusolver-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
|
||||
{ name = "nvidia-cusparse-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
|
||||
{ name = "nvidia-nccl-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
|
||||
{ name = "nvidia-nvtx-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
|
||||
{ name = "sympy" },
|
||||
{ name = "triton", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
|
||||
{ name = "triton", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
|
||||
{ name = "typing-extensions" },
|
||||
]
|
||||
wheels = [
|
||||
@@ -5078,7 +5057,7 @@ name = "tqdm"
|
||||
version = "4.66.5"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "colorama", marker = "platform_system == 'Windows'" },
|
||||
{ name = "colorama", marker = "sys_platform == 'win32'" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/58/83/6ba9844a41128c62e810fddddd72473201f3eacde02046066142a2d96cc5/tqdm-4.66.5.tar.gz", hash = "sha256:e1020aef2e5096702d8a025ac7d16b1577279c9d63f8375b63083e9a5f0fcbad", size = 169504 }
|
||||
wheels = [
|
||||
@@ -5120,7 +5099,7 @@ name = "triton"
|
||||
version = "3.0.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "filelock", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'linux')" },
|
||||
{ name = "filelock", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
|
||||
]
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/45/27/14cc3101409b9b4b9241d2ba7deaa93535a217a211c86c4cc7151fb12181/triton-3.0.0-1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:e1efef76935b2febc365bfadf74bcb65a6f959a9872e5bddf44cc9e0adce1e1a", size = 209376304 },
|
||||
|
||||
Reference in New Issue
Block a user