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Merge branch 'main' into feat/trace-ui-exec-3

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Eduardo Chiarotti
2025-04-11 12:06:31 -04:00
committed by GitHub
parent aa9f35bdbc 0cd524af86
commit 12054b63db
2 changed files with 6 additions and 2 deletions
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4
docs/guides/flows/first-flow.mdx
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@@ -263,6 +263,7 @@ Let's create our flow in the `main.py` file:
```python ```python
#!/usr/bin/env python #!/usr/bin/env python
import json import json
import os
from typing import List, Dict from typing import List, Dict
from pydantic import BaseModel, Field from pydantic import BaseModel, Field
from crewai import LLM from crewai import LLM
@@ -341,6 +342,9 @@ class GuideCreatorFlow(Flow[GuideCreatorState]):
outline_dict = json.loads(response) outline_dict = json.loads(response)
self.state.guide_outline = GuideOutline(**outline_dict) self.state.guide_outline = GuideOutline(**outline_dict)
# Ensure output directory exists before saving
os.makedirs("output", exist_ok=True)
# Save the outline to a file # Save the outline to a file
with open("output/guide_outline.json", "w") as f: with open("output/guide_outline.json", "w") as f:
json.dump(outline_dict, f, indent=2) json.dump(outline_dict, f, indent=2)

4
docs/tools/weaviatevectorsearchtool.mdx
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@@ -25,7 +25,7 @@ uv add weaviate-client
To effectively use the `WeaviateVectorSearchTool`, follow these steps: To effectively use the `WeaviateVectorSearchTool`, follow these steps:
1. **Package Installation**: Confirm that the `crewai[tools]` and `weaviate-client` packages are installed in your Python environment. 1. **Package Installation**: Confirm that the `crewai[tools]` and `weaviate-client` packages are installed in your Python environment.
2. **Weaviate Setup**: Set up a Weaviate cluster. You can follow the [Weaviate documentation](https://weaviate.io/developers/wcs/connect) for instructions. 2. **Weaviate Setup**: Set up a Weaviate cluster. You can follow the [Weaviate documentation](https://weaviate.io/developers/wcs/manage-clusters/connect) for instructions.
3. **API Keys**: Obtain your Weaviate cluster URL and API key. 3. **API Keys**: Obtain your Weaviate cluster URL and API key.
4. **OpenAI API Key**: Ensure you have an OpenAI API key set in your environment variables as `OPENAI_API_KEY`. 4. **OpenAI API Key**: Ensure you have an OpenAI API key set in your environment variables as `OPENAI_API_KEY`.
@@ -161,4 +161,4 @@ rag_agent = Agent(
## Conclusion ## Conclusion
The `WeaviateVectorSearchTool` provides a powerful way to search for semantically similar documents in a Weaviate vector database. By leveraging vector embeddings, it enables more accurate and contextually relevant search results compared to traditional keyword-based searches. This tool is particularly useful for applications that require finding information based on meaning rather than exact matches. The `WeaviateVectorSearchTool` provides a powerful way to search for semantically similar documents in a Weaviate vector database. By leveraging vector embeddings, it enables more accurate and contextually relevant search results compared to traditional keyword-based searches. This tool is particularly useful for applications that require finding information based on meaning rather than exact matches.