chore: import upstream snapshot with attribution
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wehub-resource-sync
Executable
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version: 0.4.0
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graph:
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id: paper_gen
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description: Subgraph that gathers multi-style revision suggestions for an article.
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is_majority_voting: false
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log_level: INFO
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start:
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- Romanticism Writer
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- Realism Writer
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- Magical Realism Writer
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nodes:
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- id: Romanticism Writer
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type: agent
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config:
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provider: openai
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base_url: ${BASE_URL}
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api_key: ${API_KEY}
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name: gpt-4o
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role: 'You are a Romanticism writer, advocating intense emotions, loving and deifying nature, pursuing the extraordinary and the ideal, while emphasizing individualism and a spirit of rebellion.
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Please provide revision suggestions for the work according to your style.
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'
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params:
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temperature: 0.1
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max_tokens: 4000
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- id: Realism Writer
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type: agent
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config:
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provider: openai
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base_url: ${BASE_URL}
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api_key: ${API_KEY}
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name: gpt-4o
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role: 'You are a Realism writer, seeking to objectively and truly reflect life, focusing on social issues and ordinary people, shaping typical characters in typical environments, with a cool and precise narrative style.
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Please provide revision suggestions for the work according to your style.
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'
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params:
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temperature: 0.1
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max_tokens: 4000
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- id: Magical Realism Writer
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type: agent
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config:
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provider: openai
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base_url: ${BASE_URL}
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api_key: ${API_KEY}
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name: gpt-4o
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role: 'You are a Magical Realism writer, seamlessly blending magic and reality, using exaggeration and absurdity as expressive techniques, blurring the boundaries between reality and fantasy.
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Please provide revision suggestions for the work according to your style.
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'
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params:
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temperature: 0.1
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max_tokens: 4000
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- id: Editor
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type: agent
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config:
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provider: openai
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base_url: ${BASE_URL}
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api_key: ${API_KEY}
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name: gpt-4o
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role: 'You are an excellent editor, skilled at providing basic article revision suggestions.
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You will synthesize suggestions from writers of different styles, balance various plans, and propose practical revision plans to improve the quality of the article.
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'
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params:
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temperature: 0.1
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max_tokens: 4000
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edges:
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- from: Romanticism Writer
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to: Editor
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- from: Realism Writer
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to: Editor
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- from: Magical Realism Writer
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to: Editor
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Executable
+115
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version: 0.4.0
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vars: {}
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graph:
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id: react_agent_subgraph
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description: ReAct control loop subgraph for tool calls and answer synthesis.
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is_majority_voting: false
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log_level: INFO
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start:
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- ReAct Brain
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end:
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- ReAct Answer Synthesizer
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nodes:
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- id: ReAct Brain
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type: agent
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description: ReAct controller, responsible for thinking, deciding whether to call tools, and providing final answers.
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context_window: -1
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config:
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provider: openai
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base_url: ${BASE_URL}
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api_key: ${API_KEY}
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name: gpt-4o
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input_mode: messages
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role: |
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You are a ReAct controller, needing to make decisions between the toolbox (web_search, get_webpage_content, execute_code, get_city_num, get_weather) and the final answer.
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- Organize the entire context into a rolling Thought/Observation process, ensuring references to the latest Observation.
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- Only when you need to call a tool, output Control: continue, and attach Action and ActionInput (JSON).
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- If you are ready to answer the user directly, output Final Answer and set Action=FINAL.
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- Always follow this format:
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Thought: <your thinking>
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Action: <tool_name or FINAL>
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ActionInput: <JSON or NONE>
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Control: <DONE or CONTINUE>
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- When Action=FINAL, write the final response in Final Answer: ....
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- Never fabricate an Observation, you must wait for the Tool Executor's Observation.
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params:
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temperature: 0.2
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max_tokens: 1200
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- id: Tool Executor
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type: agent
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description: Receives control instructions and actually calls function tools, returning Observations.
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config:
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provider: openai
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base_url: ${BASE_URL}
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api_key: ${API_KEY}
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name: gpt-4o
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input_mode: messages
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role: |
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You are the tool executor.
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- Parse the Action and ActionInput fields from the previous node.
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- Only when Action belongs to {web_search, get_webpage_content, execute_code, get_city_num, get_weather}, call the corresponding function tool; otherwise, reply directly with "Observation: No tool needed".
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- After a successful call, return using the following template:
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Tool: <called tool>
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Observation: <concise summary>
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Raw Output:
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```
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<raw function return>
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```
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- Do not include trigger in the output to avoid affecting upstream condition judgment.
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- Do not provide a final answer.
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tooling:
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type: function
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config:
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auto_load: true
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tools:
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- name: web_search
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- name: get_webpage_content
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- name: execute_code
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- name: get_city_num
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- name: get_weather
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params:
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temperature: 0.1
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max_tokens: 1200
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- id: ReAct Answer Synthesizer
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type: agent
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description: Cleans up ReAct formatting and outputs a user-readable final response.
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config:
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provider: openai
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base_url: ${BASE_URL}
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api_key: ${API_KEY}
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name: gpt-4o
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input_mode: messages
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role: |
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You are responsible for receiving the Final Answer from ReAct Brain and combining it with the most recent Observation (if any) to generate a natural language response.
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- Focus on answering the user's question, including sources/action summaries where necessary.
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- Remove all template fields (Thought/Action/Control, etc.).
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params:
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temperature: 0.2
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max_tokens: 800
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edges:
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- from: ReAct Brain
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to: Tool Executor
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trigger: true
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condition:
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type: keyword
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config:
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any: [ ]
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none:
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- FINAL
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regex: [ ]
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case_sensitive: true
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- from: Tool Executor
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to: ReAct Brain
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trigger: true
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condition: 'true'
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- from: ReAct Brain
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to: ReAct Answer Synthesizer
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trigger: true
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condition:
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type: keyword
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config:
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any:
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- FINAL
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none: [ ]
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regex: [ ]
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case_sensitive: true
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Executable
+128
@@ -0,0 +1,128 @@
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version: 0.4.0
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graph:
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id: reflexion_loop
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description: Reflexion loop subgraph with actor/evaluator and memory storage.
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log_level: INFO
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is_majority_voting: false
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start:
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- Task
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end:
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- Final Synthesizer
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memory:
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- name: reflexion_blackboard
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type: blackboard
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config:
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max_items: 500
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nodes:
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- id: Task
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type: passthrough
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config: {}
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- id: Reflexion Actor
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type: agent
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description: Actor (πθ) generates a strategy draft based on blackboard experience and short-term context.
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config:
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provider: openai
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base_url: ${BASE_URL}
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api_key: ${API_KEY}
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name: gpt-4o-mini
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input_mode: messages
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role: |
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You are the Actor. If there are relevant memories, refer to that experience and output the latest action draft; if there are no relevant memories, provide an action draft to the best of your ability.
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- Structure:
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Thought: ...
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Draft: ...
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memories:
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- name: reflexion_blackboard
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retrieve_stage:
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- gen
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top_k: 5
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read: true
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write: false
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params:
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temperature: 0.2
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max_tokens: 1200
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- id: Reflexion Evaluator
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type: agent
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description: Evaluator (Me) provides scores and improvement directions for the Actor's draft.
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config:
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provider: openai
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base_url: ${BASE_URL}
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api_key: ${API_KEY}
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name: gpt-4o-mini
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input_mode: messages
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role: |
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You are the Evaluator. Receive and read the Actor's latest output and task objectives, and evaluate whether they meet the goals.
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Append `Verdict: CONTINUE` or `Verdict: STOP` at the end of the output.
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When you think the current plan is good enough, you should give `Verdict: STOP`. Other fields can be skipped.
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Output:
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- Score: <0-1>
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- Reason: <Failure reasons or highlights>
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- Next Focus: <Key points to focus on in the next round>
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- Verdict: CONTINUE|STOP
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params:
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temperature: 0.1
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max_tokens: 800
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- id: Self Reflection Writer
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type: agent
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description: Self-Reflection (Msr) converts Evaluator results into reusable experience.
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config:
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provider: openai
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base_url: ${BASE_URL}
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api_key: ${API_KEY}
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name: gpt-4o-mini
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input_mode: messages
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role: |
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You are responsible for refining the Evaluator output and Actor Draft into JSON experience:
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{
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"issues": [..],
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"fix_plan": [..],
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"memory_cue": "A short reminder"
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}
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- JSON must not contain extra text.
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memories:
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- name: reflexion_blackboard
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read: false
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write: true
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params:
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temperature: 0.1
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max_tokens: 500
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- id: Final Synthesizer
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type: agent
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description: Converge the final answer, absorbing the latest Draft and Evaluator tips.
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config:
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provider: openai
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base_url: ${BASE_URL}
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api_key: ${API_KEY}
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name: gpt-4o
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input_mode: messages
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role: |
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Please synthesize all inputs and provide a final answer. Be comprehensive. Do not include any extra text other than the final answer.
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params:
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temperature: 0.1
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max_tokens: 1000
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edges:
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- from: Task
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to: Reflexion Actor
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keep_message: True
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- from: Task
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to: Reflexion Evaluator
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keep_message: True
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trigger: false
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- from: Reflexion Actor
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to: Reflexion Actor
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trigger: false
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- from: Reflexion Actor
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to: Reflexion Evaluator
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- from: Reflexion Evaluator
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to: Self Reflection Writer
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condition: need_reflection_loop
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- from: Self Reflection Writer
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to: Reflexion Actor
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carry_data: true
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- from: Reflexion Actor
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to: Final Synthesizer
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trigger: false
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- from: Reflexion Evaluator
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to: Final Synthesizer
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condition: should_stop_loop
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carry_data: false
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