andre/crewAI
1
0
Fork 0
mirror of https://github.com/crewAIInc/crewAI.git synced 2026-01-09 08:08:32 +00:00
Code Issues Actions 1 Packages Projects Releases Wiki Activity

fix linting

Browse Source
This commit is contained in:
Brandon Hancock
2024-12-05 14:06:02 -05:00
parent b65eab4fb6
commit 23a78472db
2 changed files with 1 additions and 17 deletions
Download Patch File Download Diff File Expand all files Collapse all files

17
docs/concepts/knowledge.mdx
View File

@@ -48,7 +48,6 @@ from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSourc
content = "Users name is John. He is 30 years old and lives in San Francisco." content = "Users name is John. He is 30 years old and lives in San Francisco."
string_source = StringKnowledgeSource( string_source = StringKnowledgeSource(
content=content, content=content,
metadata={"preference": "personal"}
) )
# Create an LLM with a temperature of 0 to ensure deterministic outputs # Create an LLM with a temperature of 0 to ensure deterministic outputs
@@ -76,7 +75,6 @@ crew = Crew(
process=Process.sequential, process=Process.sequential,
knowledge={ knowledge={
"sources": [string_source], "sources": [string_source],
"metadata": {"preference": "personal"}
}, # Enable knowledge by adding the sources here. You can also add more sources to the sources list. }, # Enable knowledge by adding the sources here. You can also add more sources to the sources list.
) )
@@ -85,17 +83,6 @@ result = crew.kickoff(inputs={"question": "What city does John live in and how o
## Knowledge Configuration ## Knowledge Configuration
### Metadata and Filtering
Knowledge sources support metadata for better organization and filtering. Metadata is used to filter the knowledge sources when querying the knowledge store.
```python Code
knowledge_source = StringKnowledgeSource(
content="Users name is John. He is 30 years old and lives in San Francisco.",
metadata={"preference": "personal"} # Metadata is used to filter the knowledge sources
)
```
### Chunking Configuration ### Chunking Configuration
Control how content is split for processing by setting the chunk size and overlap. Control how content is split for processing by setting the chunk size and overlap.
@@ -116,13 +103,11 @@ You can also configure the embedder for the knowledge store. This is useful if y
... ...
string_source = StringKnowledgeSource( string_source = StringKnowledgeSource(
content="Users name is John. He is 30 years old and lives in San Francisco.", content="Users name is John. He is 30 years old and lives in San Francisco.",
metadata={"preference": "personal"}
) )
crew = Crew( crew = Crew(
... ...
knowledge={ knowledge={
"sources": [string_source], "sources": [string_source],
"metadata": {"preference": "personal"},
"embedder_config": { "embedder_config": {
"provider": "openai", # Default embedder provider; can be "ollama", "gemini", e.t.c. "provider": "openai", # Default embedder provider; can be "ollama", "gemini", e.t.c.
"config": {"model": "text-embedding-3-small"} # Default embedder model; can be "mxbai-embed-large", "nomic-embed-tex", e.t.c. "config": {"model": "text-embedding-3-small"} # Default embedder model; can be "mxbai-embed-large", "nomic-embed-tex", e.t.c.
@@ -326,4 +311,4 @@ recent_news = SpaceNewsKnowledgeSource(
- Configure appropriate embedding models - Configure appropriate embedding models
- Consider using local embedding providers for faster processing - Consider using local embedding providers for faster processing
</Accordion> </Accordion>
</AccordionGroup> </AccordionGroup>

1
src/crewai/knowledge/knowledge.py
View File

@@ -5,7 +5,6 @@ from pydantic import BaseModel, ConfigDict, Field
from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
from crewai.knowledge.storage.knowledge_storage import KnowledgeStorage from crewai.knowledge.storage.knowledge_storage import KnowledgeStorage
from crewai.utilities.constants import DEFAULT_SCORE_THRESHOLD
os.environ["TOKENIZERS_PARALLELISM"] = "false" # removes logging from fastembed os.environ["TOKENIZERS_PARALLELISM"] = "false" # removes logging from fastembed