freemo
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Add missing provider: field to all actor examples in examples/actors/. Fix llm_with_tools.yaml actor name from assistants/file_analyzer to local/assistants-file_analyzer (custom actors must use local/ namespace and cannot contain two slashes). Add validate-all command to helper_actor_examples.py that uses ActorLoader to validate all examples via business logic checks. Add integration test Validate All Actor Examples Import Without Errors to actor_examples.robot that confirms every example in examples/actors/ can be imported without errors. ISSUES CLOSED: #1504
80 lines
1.9 KiB
YAML
80 lines
1.9 KiB
YAML
# Simple Graph Actor - Sequential Processing
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# Demonstrates a simple 3-node graph with linear execution
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name: workflows/document_processor
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type: graph
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description: Simple document processing workflow (extract → analyze → summarize)
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version: "1.0"
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# LLM model
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provider: openai
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model: gpt-3.5-turbo
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# Graph topology
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route:
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nodes:
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# Node 1: Extract text from document
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- id: extractor
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type: tool
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name: Text Extractor
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description: Extracts text from various document formats
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config:
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tool_name: documents/extract_text
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parameters:
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formats:
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- pdf
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- docx
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- txt
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# Node 2: Analyze content
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- id: analyzer
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type: agent
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name: Content Analyzer
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description: Analyzes document structure and content
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config:
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model: gpt-3.5-turbo
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prompt: |
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Analyze the document content and identify:
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- Main topics and themes
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- Key entities (people, places, organizations)
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- Sentiment and tone
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- Document structure
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tools:
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- analysis/extract_entities
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- analysis/sentiment_analysis
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# Node 3: Generate summary
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- id: summarizer
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type: agent
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name: Summarizer
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description: Creates concise summary of document
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config:
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model: gpt-3.5-turbo
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prompt: |
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Create a concise summary of the document including:
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- Main points (3-5 bullet points)
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- Key findings
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- Actionable insights
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Keep it under 200 words.
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# Linear edges
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edges:
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- from_node: extractor
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to_node: analyzer
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- from_node: analyzer
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to_node: summarizer
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# Entry and exit
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entry_node: extractor
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exit_nodes:
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- summarizer
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# Context settings
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context_view: executor
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memory:
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enabled: true
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max_messages: 10
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context:
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max_context_tokens: 4000
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