Add all CF flow modulo the ones that require debugging.

DirectCode.py → CF_Code.py

@@ -3,6 +3,6 @@ OpenAIChatAtomicFlow = load_class("martinjosifoski/OpenAIChatAtomicFlow", "OpenA
 # OpenAIChatAtomicFlow = load_class("/Users/josifosk/Documents/PhD/OpenAIChatAtomicFlow", "OpenAIChatAtomicFlow")
 
 
-class DirectCode(OpenAIChatAtomicFlow):
+class CF_Code(OpenAIChatAtomicFlow):
     def __init__(self, **kwargs):
         super().__init__(**kwargs)

DirectCode.yaml → CF_Code.yaml

@@ -1,4 +1,4 @@
-name: "CodeAgent"
+name: "Code_Flow"
 verbose: True
 description: "ToDO: add description"
 
@@ -65,12 +65,22 @@ query_message_prompt_template:
     code_placeholder: "{{python_code}}"
   template_format: jinja2
 
+expected_inputs:
+  - "problem_description"
+  - "input_description"
+  - "output_description"
+  - "io_examples_and_explanation"
+  - "api_key"
+
+expected_outputs:
+  - "code"
+
 response_annotators:
   code_extractor:
     _target_: flows.message_annotators.RegexFirstOccurrenceExtractor
     regex: '(?<=```python)([\s\S]*?)(?=```)'
     regex_fallback: '(?<=```)([\s\S]*?)(?=```)'
-    key: code
+    key: "code"
     strip: True
     assert_unique: True
     verbose: True

CF_CodeCollab.py

@@ -0,0 +1,6 @@
+from flows.base_flows import GeneratorCriticFlow
+
+
+class CF_CodeCollab(GeneratorCriticFlow):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)

CF_CodeCollab.yaml

@@ -0,0 +1,49 @@
+name: "CodeCollab_Flow"
+verbose: True
+description: "ToDO: add description"
+
+reset_generator_every_round: False
+reset_critic_every_round: True
+max_rounds: 2 # ToDO: To increase to 4
+early_exit_key: "end_of_interaction"
+
+subflows_config:
+  - _target_: flows.flow_verse.instantiate_flow
+    # repository_id: "/Users/josifosk/Documents/PhD/CC_flows" 
+    repository_id: "martinjosifoski/CC_flows"
+    class_name: CF_Code
+    overrides:
+      name: "CodeGenerator"
+      human_message_prompt_template:
+        _target_: langchain.PromptTemplate
+        template: |2-
+          # Feedback on the last proposed solution
+          {{query}}
+
+
+          Consider the original problem statement, the last proposed solution and the provided feedback. Does the solution need to be updated? If so, provide the corrected version of the code in the following format:
+          ```python
+          {{code_placeholder}}
+          ```
+          otherwise, reply:
+          "Final answer."
+        input_variables:
+          - query
+        partial_variables:
+          code_placeholder: "{{python_code}}"
+        template_format: jinja2
+      response_annotators:
+        end_of_interaction_annotator:
+          _target_: flows.message_annotators.EndOfInteraction
+          end_of_interaction_message: "Final answer"
+          key: "end_of_interaction"
+          verbose: True
+      expected_outputs:
+        - "code"
+        - "end_of_interaction"
+  - _target_: flows.flow_verse.instantiate_flow
+    repository_id: "martinjosifoski/CC_flows"
+    # repository_id: "/Users/josifosk/Documents/PhD/CC_flows"
+    class_name: CF_CodeCritic
+    overrides:
+      name: CodeCritic

CF_CodeCritic.py

@@ -0,0 +1,8 @@
+from flows.flow_verse import load_class
+OpenAIChatAtomicFlow = load_class("martinjosifoski/OpenAIChatAtomicFlow", "OpenAIChatAtomicFlow")
+# OpenAIChatAtomicFlow = load_class("/Users/josifosk/Documents/PhD/OpenAIChatAtomicFlow", "OpenAIChatAtomicFlow")
+
+
+class CF_CodeCritic(OpenAIChatAtomicFlow):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)

CF_CodeCritic.yaml

@@ -0,0 +1,79 @@
+name: "CodeCritic_Flow"
+verbose: True
+description: "ToDO: add description"
+
+model_name: "gpt-4"
+generation_parameters:
+  n: 1
+  max_tokens: 3000
+  temperature: 0.3
+
+  model_kwargs:
+    top_p: 0.2
+    frequency_penalty: 0
+    presence_penalty: 0
+
+system_message_prompt_template:
+  _target_: langchain.PromptTemplate
+  template: |2-
+    Your goal is to identify potential issues with a competitive programming solution attempt.
+
+    The user will specify the problem by providing you with:
+      - the problem statement
+      - input description
+      - output description
+      - example test cases
+      - (optional) explanation of the test cases
+      - a Python solution attempt
+
+    Crucially, your goal is to correctly identify potential issues with the solution attempt, and not to provide the code implementation yourself.
+    The user will provide you with a task and an output format that you will strictly follow.
+  input_variables: []
+  template_format: jinja2
+
+human_message_prompt_template:
+  _target_: langchain.PromptTemplate
+  template: "{{query}}"
+  input_variables:
+    - "query"
+  template_format: jinja2
+
+query_message_prompt_template:
+  _target_: langchain.PromptTemplate
+  template: |2-
+    # Problem statement
+    {{problem_description}}
+
+    # Input description
+    {{input_description}}
+
+    # Output description
+    {{output_description}}
+
+    {{io_examples_and_explanation}}
+
+    # Python solution attempt:
+    ```python
+    {{code}}
+    ```
+
+
+    Consider the problem statement and the solution attempt. Are there any issues with the proposed solution or it is correct? Explain your reasoning very concisely, and do not provide code.
+  input_variables:
+    - "problem_description"
+    - "input_description"
+    - "output_description"
+    - "io_examples_and_explanation"
+    - "code"
+  template_format: jinja2
+
+expected_inputs:
+  - "problem_description"
+  - "input_description"
+  - "output_description"
+  - "io_examples_and_explanation"
+  - "code"
+  - "api_key"
+
+expected_outputs:
+  - "query"

CF_CodeReflect.py

@@ -0,0 +1,6 @@
+from flows.base_flows import GeneratorCriticFlow
+
+
+class CF_CodeReflect(GeneratorCriticFlow):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)

CF_CodeReflect.yaml

@@ -0,0 +1,40 @@
+name: "CodeReflect_Flow"
+verbose: True
+description: "ToDO: add description"
+
+reset_generator_every_round: False
+reset_critic_every_round: True
+max_rounds: 2 # ToDo: To increase to 4
+early_exit_key: "end_of_interaction"
+
+subflows_config:
+  - _target_: flows.flow_verse.instantiate_flow
+    repository_id: "martinjosifoski/CC_flows"
+    # repository_id: "/Users/josifosk/Documents/PhD/CC_flows"
+    class_name: CF_Code
+    overrides:
+      name: "CodeGenerator"
+      model_name: "gpt-4"
+      expected_outputs:
+        - "code"
+        - "end_of_interaction"
+      response_annotators:
+        end_of_interaction_annotator:
+          _target_: flows.message_annotators.EndOfInteraction
+          end_of_interaction_message: "Final answer"
+          key: "end_of_interaction"
+          verbose: True
+  - _target_: flows.base_flows.FixedReplyAtomicFlow.instantiate_with_overrides
+    overrides:
+      name: "CodeCritic"
+      description: "ToDo: Add description"
+      expected_outputs:
+        - "query"
+      fixed_reply: |2-
+        Consider the problem statement and the last proposed solution. Are you sure that the solution is provided in the requested format, and crucially, solves the problem?
+        If that is not the case, provide the corrected version of the code in the following format:
+        ```python
+        {{python_code}}
+        ```
+        otherwise, reply:
+        "Final answer."

CF_CodeWithPlan.py

@@ -0,0 +1,8 @@
+from flows.flow_verse import load_class
+OpenAIChatAtomicFlow = load_class("martinjosifoski/OpenAIChatAtomicFlow", "OpenAIChatAtomicFlow")
+# OpenAIChatAtomicFlow = load_class("/Users/josifosk/Documents/PhD/OpenAIChatAtomicFlow", "OpenAIChatAtomicFlow")
+
+
+class CF_CodeWithPlan(OpenAIChatAtomicFlow):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)

CF_CodeWithPlan.yaml

@@ -0,0 +1,93 @@
+name: "CodeFlowWithPlan_Flow"
+verbose: True
+description: "ToDO: add description"
+
+model_name: "gpt-4"
+generation_parameters:
+  n: 1
+  max_tokens: 3000
+  temperature: 0.3
+
+  model_kwargs:
+    top_p: 0.2
+    frequency_penalty: 0
+    presence_penalty: 0
+
+system_message_prompt_template:
+  _target_: langchain.PromptTemplate
+  template: |2-
+    Your goal is to provide executable Python code that solves a competitive programming problem. The code should correctly handle all corner cases in order to pass the hidden test cases, which are used to evaluate the correctness of the solution.
+
+    The user will specify the problem by providing you with:
+      - the problem statement
+      - input description
+      - output description
+      - example test cases
+      - (optional) explanation of the test cases
+
+    Additionally, the user will provide you with a conceptual solution to the problem which should guide your reasoning and the code implementation.
+
+    The user will provide you with a task and an output format that you will strictly follow.
+  input_variables: []
+  template_format: jinja2
+
+human_message_prompt_template:
+  _target_: langchain.PromptTemplate
+  template: "{{query}}"
+  input_variables:
+    - "query"
+  template_format: jinja2
+
+query_message_prompt_template:
+  _target_: langchain.PromptTemplate
+  template: |2-
+    # Problem statement
+    {{problem_description}}
+
+    # Input description
+    {{input_description}}
+
+    # Output description
+    {{output_description}}
+
+    {{io_examples_and_explanation}}
+
+    # Conceptual solution
+    {{plan}}
+
+
+    The input should be read from the standard input and the output should be passed to the standard output.
+    Consider the problem statement and the conceptual solution, and return Python code that solves the problem. Reply in the following format:
+    ```python
+    {{code_placeholder}}
+    ```
+  input_variables:
+    - "problem_description"
+    - "input_description"
+    - "output_description"
+    - "io_examples_and_explanation"
+    - "plan"
+  partial_variables:
+    code_placeholder: "{{python_code}}"
+  template_format: jinja2
+
+expected_inputs:
+  - "problem_description"
+  - "input_description"
+  - "output_description"
+  - "io_examples_and_explanation"
+  - "plan"
+  - "api_key"
+
+expected_outputs:
+  - "code"
+
+response_annotators:
+  code_extractor:
+    _target_: flows.message_annotators.RegexFirstOccurrenceExtractor
+    regex: '(?<=```python)([\s\S]*?)(?=```)'
+    regex_fallback: '(?<=```)([\s\S]*?)(?=```)'
+    key: "code"
+    strip: True
+    assert_unique: True
+    verbose: True

CF_Plan.py

@@ -0,0 +1,8 @@
+from flows.flow_verse import load_class
+OpenAIChatAtomicFlow = load_class("martinjosifoski/OpenAIChatAtomicFlow", "OpenAIChatAtomicFlow")
+# OpenAIChatAtomicFlow = load_class("/Users/josifosk/Documents/PhD/OpenAIChatAtomicFlow", "OpenAIChatAtomicFlow")
+
+
+class CF_Plan(OpenAIChatAtomicFlow):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)

CF_Plan.yaml

@@ -0,0 +1,88 @@
+name: "Plan_Flow"
+verbose: True
+description: "ToDO: add description"
+
+model_name: "gpt-4"
+generation_parameters:
+  n: 1
+  max_tokens: 3000
+  temperature: 0.3
+
+  model_kwargs:
+    top_p: 0.2
+    frequency_penalty: 0
+    presence_penalty: 0
+
+system_message_prompt_template:
+  _target_: langchain.PromptTemplate
+  template: |2-
+    Your goal is to provide a high-level conceptual solution that, if implemented, will solve a given competitive programming problem.
+
+    The user will specify the problem by providing you with:
+      - the problem statement
+      - input description
+      - output description
+      - example test cases
+      - (optional) explanation of the test cases
+
+    The proposed algorithm should be computationally efficient, logically correct and handle all corner cases.
+
+    The user will provide you with a task and an output format that you will strictly follow.
+  input_variables: []
+  template_format: jinja2
+
+human_message_prompt_template:
+  _target_: langchain.PromptTemplate
+  template: "{{query}}"
+  input_variables:
+    - "query"
+  template_format: jinja2
+
+query_message_prompt_template:
+  _target_: langchain.PromptTemplate
+  template: |2-
+    # Problem statement
+    {{problem_description}}
+
+    # Input description
+    {{input_description}}
+
+    # Output description
+    {{output_description}}
+
+    {{io_examples_and_explanation}}
+
+
+    Return a high-level conceptual solution that would solve the problem. Be very concise, and do not provide code.
+    Reply in the following format:
+    # Conceptual solution
+    {{plan_placeholder}}
+  input_variables:
+    - "problem_description"
+    - "input_description"
+    - "output_description"
+    - "io_examples_and_explanation"
+  partial_variables:
+    plan_placeholder: "{{conceptual_solution}}"
+  template_format: jinja2
+
+expected_inputs:
+  - "problem_description"
+  - "input_description"
+  - "output_description"
+  - "io_examples_and_explanation"
+  - "api_key"
+
+expected_outputs:
+  - "plan"
+
+response_annotators:
+  plan_extractor:
+    _target_: flows.message_annotators.RegexFirstOccurrenceExtractor
+    regex: '(?<=Conceptual solution)([\s\S]*?)(?=\n\n# [A-Z]|\Z)'
+    regex_fallback:
+      - '(?<=Conceptual solution:)([\s\S]*?)(?=\n\n# [A-Z]|\Z)'
+    key: "plan"
+    strip: True
+    assert_unique: True
+    verbose: True

CF_PlanCollab.py

@@ -0,0 +1,6 @@
+from flows.base_flows import GeneratorCriticFlow
+
+
+class CF_PlanCollab(GeneratorCriticFlow):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)

CF_PlanCollab.yaml

@@ -0,0 +1,58 @@
+name: "PlanCollab_Flow"
+verbose: True
+description: "ToDO: add description"
+
+reset_generator_every_round: False
+reset_critic_every_round: True
+max_rounds: 2 # ToDo: To increase to 4
+early_exit_key: "end_of_interaction"
+
+expected_inputs:
+  - "problem_description"
+  - "input_description"
+  - "output_description"
+  - "io_examples_and_explanation"
+  - "api_key"
+
+expected_outputs:
+  - "plan"
+
+subflows_config:
+  - _target_: flows.flow_verse.instantiate_flow
+    repository_id: "martinjosifoski/CC_flows"
+    # repository_id: "/Users/josifosk/Documents/PhD/CC_flows" 
+    class_name: CF_Plan
+    overrides:
+      name: "CodeGenerator"
+      human_message_prompt_template:
+        _target_: langchain.PromptTemplate
+        template: |2-
+          # Feedback on the last proposed conceptual solution
+          {{query}}
+    
+    
+          Consider the original problem statement, the last proposed solution and the provided feedback. Does the solution need to be updated? If so, provide the corrected version of the conceptual solution in the following format:
+          # Conceptual solution
+          {{plan_placeholder}}
+          otherwise, reply:
+          "Final answer."
+        input_variables:
+          - query
+        partial_variables:
+          plan_placeholder: "{{conceptual_solution}}"
+        template_format: jinja2
+      response_annotators:
+        end_of_interaction_annotator:
+          _target_: flows.message_annotators.EndOfInteraction
+          end_of_interaction_message: "Final answer"
+          key: "end_of_interaction"
+          verbose: True
+      expected_outputs:
+        - "plan"
+        - "end_of_interaction"
+  - _target_: flows.flow_verse.instantiate_flow
+    repository_id: "martinjosifoski/CC_flows"
+    # repository_id: "/Users/josifosk/Documents/PhD/CC_flows" 
+    class_name: CF_PlanCritic
+    overrides:
+      name: PlanCritic

CF_PlanCollab_Code.py

@@ -0,0 +1,6 @@
+from flows.base_flows import SequentialFlow
+
+
+class CF_PlanCollab_Code(SequentialFlow):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)

CF_PlanCollab_Code.yaml

@@ -0,0 +1,14 @@
+name: "PlanCollab_Code"
+description: "ToDO: add description"
+
+early_exit_key: null
+
+subflows_config:
+  - _target_: flows.flow_verse.instantiate_flow
+    repository_id: "martinjosifoski/CC_flows"
+    # repository_id: "/Users/josifosk/Documents/PhD/CC_flows"
+    class_name: CF_PlanCollab
+  - _target_: flows.flow_verse.instantiate_flow
+    repository_id: "martinjosifoski/CC_flows"
+    # repository_id: "/Users/josifosk/Documents/PhD/CC_flows"
+    class_name: CF_CodeWithPlan

CF_PlanCritic.py

@@ -0,0 +1,8 @@
+from flows.flow_verse import load_class
+OpenAIChatAtomicFlow = load_class("martinjosifoski/OpenAIChatAtomicFlow", "OpenAIChatAtomicFlow")
+# OpenAIChatAtomicFlow = load_class("/Users/josifosk/Documents/PhD/OpenAIChatAtomicFlow", "OpenAIChatAtomicFlow")
+
+
+class CF_PlanCritic(OpenAIChatAtomicFlow):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)

CF_PlanCritic.yaml

@@ -0,0 +1,78 @@
+name: "PlanCritic_Flow"
+verbose: True
+description: "ToDO: add description"
+
+model_name: "gpt-4"
+generation_parameters:
+  n: 1
+  max_tokens: 3000
+  temperature: 0.3
+
+  model_kwargs:
+    top_p: 0.2
+    frequency_penalty: 0
+    presence_penalty: 0
+
+system_message_prompt_template:
+  _target_: langchain.PromptTemplate
+  template: |2-
+      Your goal is to identify potential issues with a conceptual solution to a given competitive programming problem.
+
+      The user will specify the problem by providing you with:
+        - the problem statement
+        - input description
+        - output description
+        - example test cases
+        - (optional) explanation of the test cases
+        - a conceptual solution attempt
+
+      Crucially, your goal is to consider all aspects of the problem and pinpoint potential issues with the conceptual solution attempt (if any), and not to provide the conceptual solution or the code implementation yourself.
+      Some aspects to consider: Are there any logical mistakes with the proposed algorithm? Are the corner cases correctly handled?
+      The user will provide you with a task and an output format that you will strictly follow.
+  input_variables: []
+  template_format: jinja2
+
+human_message_prompt_template:
+  _target_: langchain.PromptTemplate
+  template: "{{query}}"
+  input_variables:
+    - "query"
+  template_format: jinja2
+
+query_message_prompt_template:
+  _target_: langchain.PromptTemplate
+  template: |2-
+    # Problem statement
+    {{problem_description}}
+
+    # Input description
+    {{input_description}}
+
+    # Output description
+    {{output_description}}
+
+    {{io_examples_and_explanation}}
+
+    # Conceptual solution attempt
+    {{plan}}
+
+
+    Consider the problem statement and the solution attempt. Are there any issues with the proposed conceptual solution or it is correct? Explain your reasoning very concisely.
+  input_variables:
+    - "problem_description"
+    - "input_description"
+    - "output_description"
+    - "io_examples_and_explanation"
+    - "plan"
+  template_format: jinja2
+
+expected_inputs:
+  - "problem_description"
+  - "input_description"
+  - "output_description"
+  - "io_examples_and_explanation"
+  - "plan"
+  - "api_key"
+
+expected_outputs:
+  - "query"

CF_PlanReflect.py

@@ -0,0 +1,6 @@
+from flows.base_flows import GeneratorCriticFlow
+
+
+class CF_PlanReflect(GeneratorCriticFlow):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)

CF_PlanReflect.yaml

@@ -0,0 +1,49 @@
+name: "PlanReflect_Flow"
+verbose: True
+description: "ToDO: add description"
+
+reset_generator_every_round: False
+reset_critic_every_round: True
+max_rounds: 2 # To increase to 4
+early_exit_key: "end_of_interaction"
+
+expected_inputs:
+  - "problem_description"
+  - "input_description"
+  - "output_description"
+  - "io_examples_and_explanation"
+  - "api_key"
+
+expected_outputs:
+  - "plan"
+
+subflows_config:
+  - _target_: flows.flow_verse.instantiate_flow
+    repository_id: "martinjosifoski/CC_flows"
+    # repository_id: "/Users/josifosk/Documents/PhD/CC_flows" 
+    class_name: CF_Plan
+    overrides:
+      name: "PlanGenerator"
+      model_name: "gpt-4"
+      response_annotators:
+        end_of_interaction_annotator:
+          _target_: flows.message_annotators.EndOfInteraction
+          end_of_interaction_message: "Final answer"
+          key: "end_of_interaction"
+          verbose: True
+      expected_outputs:
+        - "plan"
+        - "end_of_interaction"
+  - _target_: flows.base_flows.FixedReplyAtomicFlow.instantiate_with_overrides
+    overrides:
+      name: "PlanCritic"
+      description: "ToDo: Add description"
+      expected_outputs:
+        - "query"
+      fixed_reply: |2-
+        Consider the problem statement and the last proposed solution. Are you sure that the solution is provided in the requested format, and crucially, solves the problem?
+        If that is not the case, provide the corrected version of the conceptual solution in the following format:
+        # Conceptual solution
+        {{conceptual_solution}}
+        otherwise, reply:
+        "Final answer."

CF_PlanReflect_Code.py

@@ -0,0 +1,6 @@
+from flows.base_flows import SequentialFlow
+
+
+class CF_PlanReflect_Code(SequentialFlow):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)

CF_PlanReflect_Code.yaml

@@ -0,0 +1,14 @@
+name: "PlanReflect_Code_Flow"
+description: "ToDO: add description"
+
+early_exit_key: null
+
+subflows_config:
+  - _target_: flows.flow_verse.instantiate_flow
+    repository_id: "martinjosifoski/CC_flows"
+    # repository_id: "/Users/josifosk/Documents/PhD/CC_flows" 
+    class_name: CF_PlanReflect
+  - _target_: flows.flow_verse.instantiate_flow
+    repository_id: "martinjosifoski/CC_flows"
+    # repository_id: "/Users/josifosk/Documents/PhD/CC_flows" 
+    class_name: CF_CodeWithPlan

CF_Plan_Code.py

@@ -0,0 +1,6 @@
+from flows.base_flows import SequentialFlow
+
+
+class CF_Plan_Code(SequentialFlow):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)

CF_Plan_Code.yaml

@@ -0,0 +1,18 @@
+name: "Plan_Code_Flow"
+description: "ToDO: add description"
+
+early_exit_key: null
+
+subflows_config:
+  - _target_: flows.flow_verse.instantiate_flow
+    # repository_id: "/Users/josifosk/Documents/PhD/CC_flows" 
+    repository_id: "martinjosifoski/CC_flows"
+    class_name: CF_Plan
+    overrides:
+      model_name: "gpt-4"
+  - _target_: flows.flow_verse.instantiate_flow
+    # repository_id: "/Users/josifosk/Documents/PhD/CC_flows" 
+    repository_id: "martinjosifoski/CC_flows"
+    class_name: CF_CodeWithPlan
+    overrides:
+      model_name: "gpt-4"

RockPaperScissorsJudge.py

@@ -1,46 +0,0 @@
-from flows.base_flows import Flow
-from typing import Dict
-
-from .RockPaperScissorsPlayer import RockPaperScissorsPlayer
-
-
-class RockPaperScissorsJudge(Flow):
-
-    def __init__(self, **kwargs):
-        super(RockPaperScissorsJudge, self).__init__(**kwargs)
-
-        self.flow_state["A"] = RockPaperScissorsPlayer(name="Player A", description="RockPaperScissorsPlayer")
-        self.flow_state["B"] = RockPaperScissorsPlayer(name="Player B", description="RockPaperScissorsPlayer")
-        self.flow_state["A_score"] = 0
-        self.flow_state["B_score"] = 0
-        self.flow_state["n_party_played"] = 0
-
-    def run(self, input_data, expected_outputs) -> Dict:
-        flow_a = self.flow_state["A"]
-        flow_b = self.flow_state["B"]
-
-        for _ in range(3):
-            A_task = self.package_task_message(flow_a, "run", {}, expected_outputs=["choice"])
-            B_task = self.package_task_message(flow_b, "run", {}, expected_outputs=["choice"])
-            # play another round
-            A_output = flow_a(A_task)
-            self._log_message(A_output)
-            B_output = flow_b(B_task)
-            self._log_message(B_output)
-
-            A_choice = A_output.data["choice"]
-            B_choice = B_output.data["choice"]
-
-            self._update_state({"n_party_played": self.flow_state["n_party_played"] + 1})
-
-            if A_choice == B_choice:
-                # neither has won
-                pass
-            elif (A_choice == "rock" and B_choice == "scissors"
-                  or A_choice == "paper" and B_choice == "rock"
-                  or A_choice == "scissors" and B_choice == "paper"):
-                self._update_state({"A_score": self.flow_state["A_score"] + 1})
-            else:
-                self._update_state({"B_score": self.flow_state["B_score"] + 1})
-
-        return self._get_keys_from_state(expected_outputs, allow_class_namespace=False)

RockPaperScissorsPlayer.py

@@ -1,15 +0,0 @@
-from flows.base_flows import Flow
-from typing import List
-
-import random
-
-
-class RockPaperScissorsPlayer(Flow):
-
-    def __init__(self, **kwargs):
-        super(RockPaperScissorsPlayer, self).__init__(**kwargs)
-
-    def run(self, input_data, expected_outputs: List[str] = None):
-        choice = random.choice(["rock", "paper", "scissors"])
-
-        return {"choice": choice}

__init__.py

@@ -1 +1,12 @@
-from .DirectCode import DirectCode
+from .CF_Code import CF_Code
+from .CF_CodeWithPlan import CF_CodeWithPlan
+from .CF_CodeReflect import CF_CodeReflect
+from .CF_Plan import CF_Plan
+from .CF_Plan_Code import CF_Plan_Code
+from .CF_CodeCritic import CF_CodeCritic
+from .CF_CodeCollab import CF_CodeCollab
+from .CF_PlanReflect import CF_PlanReflect
+from .CF_PlanReflect_Code import CF_PlanReflect_Code
+from .CF_PlanCritic import CF_PlanCritic
+from .CF_PlanCollab import CF_PlanCollab
+from .CF_PlanCollab_Code import CF_PlanCollab_Code