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ControllerFlow_ExtLib.py

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+import json
+from copy import deepcopy
+from typing import Any, Dict, List
+
+from flow_modules.aiflows.ChatFlowModule import ChatAtomicFlow
+
+from dataclasses import dataclass
+
+
+@dataclass
+class Command:
+    name: str
+    description: str
+    input_args: List[str]
+
+class ControllerFlow_ExtLib(ChatAtomicFlow):
+    def __init__(
+            self,
+            commands: List[Command],
+            **kwargs):
+        super().__init__(**kwargs)
+        self.system_message_prompt_template = self.system_message_prompt_template.partial(
+            commands=self._build_commands_manual(commands),
+            plan_file_location="no location yet",
+            plan="no plan yet",
+            logs="no logs yet",
+        )
+        self.hint_for_model = """
+        Make sure your response is in the following format:
+              Response Format:
+              {
+              "command": "call one of the commands you have e.g. `write_code`",
+              "command_args": {
+                  "arg name": "value"
+                  }
+              }
+        """
+
+    @staticmethod
+    def _build_commands_manual(commands: List[Command]) -> str:
+        ret = ""
+        for i, command in enumerate(commands):
+            command_input_json_schema = json.dumps(
+                {input_arg: f"YOUR_{input_arg.upper()}" for input_arg in command.input_args})
+            ret += f"{i + 1}. {command.name}: {command.description} Input arguments (given in the JSON schema): {command_input_json_schema}\n"
+        return ret
+
+    def _get_plan_file_location(self, input_data: Dict[str, Any]):
+        assert "memory_files" in input_data, "memory_files not passed to Extlib/Controller"
+        assert "plan" in input_data["memory_files"], "plan not in memory files"
+        return input_data["memory_files"]["plan"]
+
+    def _get_plan_content(self, input_data: Dict[str, Any]):
+        assert "plan" in input_data, "plan not passed to Extlib/Controller"
+        plan_content = input_data["plan"]
+        if len(plan_content) == 0:
+            plan_content = 'No plan yet'
+        return plan_content
+
+    def _get_logs_content(self, input_data: Dict[str, Any]):
+        assert "logs" in input_data, "logs not passed to Extlib/Controller"
+        logs_content = input_data["logs"]
+        if len(logs_content) == 0:
+            logs_content = "No logs yet"
+        return logs_content
+
+    @classmethod
+    def instantiate_from_config(cls, config):
+        flow_config = deepcopy(config)
+
+        kwargs = {"flow_config": flow_config}
+
+        # ~~~ Set up prompts ~~~
+        kwargs.update(cls._set_up_prompts(flow_config))
+
+        # ~~~Set up backend ~~~
+        kwargs.update(cls._set_up_backend(flow_config))
+
+        # ~~~ Set up commands ~~~
+        commands = flow_config["commands"]
+        commands = [
+            Command(name, command_conf["description"], command_conf["input_args"]) for name, command_conf in
+            commands.items()
+        ]
+        kwargs.update({"commands": commands})
+
+        # ~~~ Instantiate flow ~~~
+        return cls(**kwargs)
+
+    def _update_prompts_and_input(self, input_data: Dict[str, Any]):
+        if 'goal' in input_data:
+            input_data['goal'] += self.hint_for_model
+        if 'result' in input_data:
+            input_data['result'] += self.hint_for_model
+        plan_file_location = self._get_plan_file_location(input_data)
+        plan_content = self._get_plan_content(input_data)
+        logs_content = self._get_logs_content(input_data)
+        self.system_message_prompt_template = self.system_message_prompt_template.partial(
+            plan_file_location=plan_file_location,
+            plan=plan_content,
+            logs=logs_content
+        )
+
+    def run(self, input_data: Dict[str, Any]) -> Dict[str, Any]:
+        self._update_prompts_and_input(input_data)
+        api_output = super().run(input_data)["api_output"].strip()
+        try:
+            response = json.loads(api_output)
+            return response
+        except json.decoder.JSONDecodeError:
+            new_input_data = input_data.copy()
+            new_input_data['result'] = "The previous respond cannot be parsed with json.loads. Make sure your next response is in JSON format."
+            new_api_output = super().run(new_input_data)["api_output"].strip()
+            return json.loads(new_api_output)

ControllerFlow_ExtLib.yaml

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+_target_: Tachi67.ExtendLibraryFlowModule.ControllerFlow_ExtLib.instantiate_from_default_config
+name: "ControllerFlow_ExtendLibrary"
+description: "Proposes the next action to take towards achieving the goal, and prepares the input for the branching flow"
+enable_cache: True
+
+#######################################################
+# Input keys
+#######################################################
+
+input_interface_non_initialized: # initial input keys
+  - "goal"
+
+input_interface_initialized:
+  - "result"
+
+#######################################################
+# Output keys
+#######################################################
+
+output_interface:
+  - 'command'
+  - 'command_args'
+
+backend:
+  api_infos: ???
+  model_name:
+    openai: gpt-4
+    azure: azure/gpt-4
+
+commands:
+  write_code:
+    description: "Write code to finish the current step of plan with user interaction"
+    input_args: ["goal"]
+  save_code:
+    description: "When code is written by the coder, save the code to the library"
+    input_args: []
+  re_plan:
+    description: "When something is wrong with current plan, draft another plan based on the old plan and information about why it's bad or how to refine it."
+    input_args: ["goal"]
+  finish:
+    description: "Signal that the objective has been satisfied, return the summary of what was done"
+    input_args: ["summary"]
+  manual_finish:
+    description: "The user demands to quit and terminate the current process"
+    input_args: []
+  ask_user:
+    description: "Ask user a question for confirmation or assistance"
+    input_args: ["question"]
+  update_plan:
+    description: "Pass the updated plan to edit plan file and override current plan"
+    input_args: ["updated_plan"]
+
+
+system_message_prompt_template:
+  _target_: langchain.PromptTemplate
+  template: |2-
+          Your department is in charge of writing code and extending the code library with the code written. You are the leader of this department.
+    
+          You work with several subordinates, they will be in charge of the specific tasks, including writing code, saving code to the library, etc.
+          
+          You are given a step-by-step plan to finish the goal, **notice that, if you are informed that the plan is overriden, this plan is the new plan you should stick to.**, the plan is located in a plan file {{plan_file_location}}:
+            {{plan}}
+          
+          Your **ONLY** task is to take the user's goal for you, to decide which command to call.
+                             
+          You **must not** write code nor write plan yourself. You only decide whether to call the coder with specified goals or to finish.
+    
+          Each step of the plan should involve writing one function, **for each step in the plan, your workflow**:
+          0.1 Whenever the user demands to quit or terminate the current process, call `manual_finish` command.
+          0.2 Whenever in double, or you have something to ask, or confirm to the user, call `ask_user` with your question.
+          0.3 During the execution of the plan, if something goes wrong, call the `re_plan` with detailed information about what was wrong.
+          1. Based on the current step of plan, call `write_code` with the current goal in the step of plan, the code writer will write some code.
+          2. After code is written, call `save_code` to save the code to the code library, **you do not need to worry about the details of the code nor the library, they will be handled by your subordinates.**
+          3. **When workflow 1 and workflow 2 are successfully executed, that means the current step of plan is done.** Do the following:
+            3.1 Reflect on what plan you are having right now.
+            3.2 Reflect on which step of the plan you just finished.
+            3.3 Generate a plan, **it is exactly the same as the plan you have now, but with the current step of plan marked as done**
+            3.4 Call `update_plan` with the plan you just generated.
+          4. Proceed to the next step of the plan, go back to workflow 1.
+          5. When every step of the plan is done, call the `finish` command, with a summary of what functions are written and saved.
+            
+          ### Beginning of an example execution: ###
+          Plan: 1. Write a function that fetches weather data from google; 2. Write a function that prints the weather data in a formatted way.
+          You start from step 1 of the plan, execute workflow 1, code is written.
+          You are informed that code is written, you go to workflow 2 to save the code.
+          You are informed that the code is saved, you go to workflow 3 to update the plan:
+              3.1 You recall the plan you have.
+              3.2 You realize step 1 of the plan is done.
+              3.3 You generate the updated plan: 1. Write a function that fetches weather data from google;(DONE) 2. Write a function that prints the weather data in a formatted way.
+              3.4 You call `update_plan` with the generated plan.
+          The updated plan will override the existing plan, you are informed of the behaviour of override.
+          You go on with the next step of the plan, do the same as above.
+          All steps are done, you call `finish`, with a summary of what functions are written and saved to the library.
+          ### End of an example of execution ###
+    
+          Here is a list of history actions you have taken, for your reference:
+            {{logs}}
+    
+          Constraints:
+          1. Exclusively use the commands listed in double quotes e.g. "command name"
+          
+          Your response **MUST** be in the following format:
+              Response Format:
+              {
+              "command": "call code writer, the tester, or to finish",
+              "command_args": {
+                  "arg name": "value"
+                  }
+              }
+          Ensure your responses can be parsed by Python json.loads
+          
+  
+          Available Functions:
+          {{commands}}
+  input_variables: ["commands", "plan_file_location", "plan", "logs"]
+  template_format: jinja2
+
+human_message_prompt_template:
+  _target_: flows.prompt_template.JinjaPrompt
+  template: |2-
+    Here is the result of your previous action:
+    {{result}}
+  input_variables:
+    - "result"
+  template_format: jinja2
+
+init_human_message_prompt_template:
+  _target_: flows.prompt_template.JinjaPrompt
+  template: |2-
+    Here is the goal you need to achieve, follow your plan to finish the goal:
+    {{goal}}
+  input_variables:
+    - "goal"
+  template_format: jinja2

CtrlExMem_ExtLib.py

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+from typing import Dict, Any
+
+from flow_modules.Tachi67.AbstractBossFlowModule import CtrlExMemFlow
+from flows.base_flows import CircularFlow
+
+class CtrlExMem_ExtLib(CtrlExMemFlow):
+    def _on_reach_max_round(self):
+        self._state_update_dict({
+            "answer": "the maximum amount of rounds was reached before the extend library flow has done the job",
+            "summary": "ExtendLibraryFlow: the maximum amount of rounds was reached before the flow has done the job",
+            "status": "unfinished"
+        })
+
+    @CircularFlow.output_msg_payload_processor
+    def detect_finish_or_continue(self, output_payload: Dict[str, Any], src_flow) -> Dict[str, Any]:
+        command = output_payload["command"]
+        if command == "finish":
+            return {
+                "EARLY_EXIT": True,
+                "answer": output_payload["command_args"]["summary"],
+                "summary": "ExtendLibrary: " + output_payload["command_args"]["summary"],
+                "status": "finished"
+            }
+        elif command == "manual_finish":
+            # ~~~ return the manual quit status ~~~
+            return {
+                "EARLY_EXIT": True,
+                "answer": "ExtendLibraryFlow was terminated explicitly by the user, process is unfinished",
+                "summary": "ExtendLibrary: process terminated by the user explicitly, nothing generated",
+                "status": "unfinished"
+            }
+        elif command == "save_code":
+            keys_to_fetch_from_state = ["code", "memory_files"]
+            fetched_state = self._fetch_state_attributes_by_keys(keys=keys_to_fetch_from_state)
+            output_payload["command_args"]["code"] = fetched_state["code"]
+            output_payload["command_args"]["memory_files"] = fetched_state["memory_files"]
+            return output_payload
+
+        elif command == "update_plan":
+            keys_to_fetch_from_state = ["memory_files"]
+            fetched_state = self._fetch_state_attributes_by_keys(keys=keys_to_fetch_from_state)
+            output_payload["command_args"]["memory_files"] = fetched_state["memory_files"]
+            return output_payload
+
+        elif command == "re_plan":
+            keys_to_fetch_from_state = ["plan", "memory_files"]
+            fetched_state = self._fetch_state_attributes_by_keys(keys=keys_to_fetch_from_state)
+            output_payload["command_args"]["plan_file_location"] = fetched_state["memory_files"]["plan"]
+            output_payload["command_args"]["plan"] = fetched_state["plan"]
+            return output_payload
+
+        else:
+            return output_payload

CtrlExMem_ExtLib.yaml

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+_target_: Tachi67.ExtendLibraryFlowModule.CtrlExMem_ExtLib.instantiate_from_default_config
+name: "CtrlExMem_ExtLibFlow"
+description: "MemorizedControllerExecutor flow for ExtendLibrary flow"
+
+subflows_config:
+  Controller:
+    _target_: Tachi67.ExtendLibraryFlowModule.ControllerFlow_ExtLib.instantiate_from_default_config
+    backend:
+      api_infos: ???
+      model_name:
+        openai: gpt-4
+        azure: azure/gpt-4
+  Executor:
+    _target_: flows.base_flows.BranchingFlow.instantiate_from_default_config
+    subflows_config:
+      write_code:
+        _target_: Tachi67.CodeWriterFlowModule.CodeWriterFlow.instantiate_from_default_config
+        subflows_config:
+          Controller:
+            backend:
+              api_infos: ???
+              model_name:
+                openai: gpt-4
+                azure: azure/gpt-4
+          Executor:
+            subflows_config:
+              write_code:
+                subflows_config:
+                  CodeGenerator:
+                    backend:
+                      api_infos: ???
+                      model_name:
+                        openai: gpt-4
+                        azure: azure/gpt-4
+      save_code:
+        _target_: Tachi67.ExtendLibraryFlowModule.SaveCodeAtomicFlow.instantiate_from_default_config
+      ask_user:
+        _target_: Tachi67.ExtendLibraryFlowModule.ExtLibAskUserFlow.instantiate_from_default_config
+      re_plan:
+        _target_: Tachi67.ReplanningFlowModule.ReplanningFlow.instantiate_from_default_config
+        subflows_config:
+          Controller:
+            backend:
+              api_infos: ???
+              model_name:
+                openai: gpt-4
+                azure: azure/gpt-4
+          Executor:
+            subflows_config:
+              write_plan:
+                subflows_config:
+                  PlanGenerator:
+                    backend:
+                      api_infos: ???
+                      model_name:
+                        openai: gpt-4
+                        azure: azure/gpt-4
+
+      update_plan:
+        _target_: Tachi67.ExtendLibraryFlowModule.UpdatePlanAtomicFlow.instantiate_from_default_config
+
+topology:
+  - goal: "Select the next action and prepare the input for the executor."
+    input_interface:
+      _target_: flows.interfaces.KeyInterface
+      additional_transformations:
+        - _target_: flows.data_transformations.KeyMatchInput
+    flow: Controller
+    output_interface:
+      _target_: CtrlExMem_ExtLib.detect_finish_or_continue
+    reset: false
+
+  - goal: "Execute the action specified by the Controller."
+    input_interface:
+      _target_: flows.interfaces.KeyInterface
+      keys_to_rename:
+        command: branch
+        command_args: branch_input_data
+      keys_to_select: ["branch", "branch_input_data"]
+    flow: Executor
+    output_interface:
+      _target_: flows.interfaces.KeyInterface
+      keys_to_rename:
+        branch_output_data: observation
+      keys_to_unpack: ["observation"]
+    reset: false
+
+  - goal: "Write memory to memory files"
+    input_interface:
+      _target_: flows.interfaces.KeyInterface
+      additional_transformations:
+        - _target_: flows.data_transformations.KeyMatchInput
+    flow: MemoryWriting
+    reset: false
+
+  - goal: "Read memory from memory files (flow_state)"
+    input_interface:
+      _target_: flows.interfaces.KeyInterface
+      additional_transformations:
+        - _target_: flows.data_transformations.KeyMatchInput
+    flow: MemoryReading
+    reset: false

ExtLibAskUserFlow.py

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+from flow_modules.aiflows.HumanStandardInputFlowModule import HumanStandardInputFlow
+
+from typing import Dict, Any
+
+from flows.messages import UpdateMessage_Generic
+
+from flows.utils import logging
+
+log = logging.get_logger(f"flows.{__name__}")
+
+
+class ExtLibAskUserFlow(HumanStandardInputFlow):
+    def run(self,
+            input_data: Dict[str, Any]) -> Dict[str, Any]:
+
+        query_message = self._get_message(self.query_message_prompt_template, input_data)
+        state_update_message = UpdateMessage_Generic(
+            created_by=self.flow_config['name'],
+            updated_flow=self.flow_config["name"],
+            data={"query_message": query_message},
+        )
+        self._log_message(state_update_message)
+
+        log.info(query_message)
+        human_input = self._read_input()
+
+        response = {}
+        response["result"] = human_input
+
+        return response

ExtLibAskUserFlow.yaml

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+_target_: Tachi67.ExtendLibraryFlowModule.ExtLibAskUserFlow.instantiate_from_default_config
+request_multi_line_input_flag: False
+end_of_input_string: EOI
+
+query_message_prompt_template:
+  template: |2-
+    {{question}}
+  input_variables:
+    - "question"

ExtendLibraryFlow.py

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+from flow_modules.Tachi67.AbstractBossFlowModule import AbstractBossFlow
+
+class ExtendLibraryFlow(AbstractBossFlow):
+    pass

ExtendLibraryFlow.yaml

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+name: ExtendLibraryFlow
+description: "A flow used to extend the content in the code library"
+
+_target_: Tachi67.ExtendLibraryFlowModule.ExtendLibraryFlow.instantiate_from_default_config
+
+subflows_config:
+  MemoryReading:
+    _target_: Tachi67.MemoryReadingFlowModule.MemoryReadingAtomicFlow.instantiate_from_default_config
+
+  Planner:
+    _target_: Tachi67.PlanWriterFlowModule.PlanWriterFlow.instantiate_from_default_config
+    subflows_config:
+      Controller:
+        backend:
+          api_infos: ???
+          model_name:
+            openai: gpt-4
+            azure: azure/gpt-4
+      Executor:
+        subflows_config:
+          write_plan:
+            subflows_config:
+              PlanGenerator:
+                backend:
+                  api_infos: ???
+                  model_name:
+                    openai: gpt-4
+                    azure: azure/gpt-4
+
+  CtrlExMem:
+    _target_: Tachi67.ExtendLibraryFlowModule.CtrlExMem_ExtLib.instantiate_from_default_config
+    subflows_config:
+      Controller:
+        backend:
+          api_infos: ???
+          model_name:
+            openai: gpt-4
+            azure: azure/gpt-4
+      Executor:
+        subflows_config:
+          write_code:
+            subflows_config:
+              Controller:
+                backend:
+                  api_infos: ???
+                  model_name:
+                    openai: gpt-4
+                    azure: azure/gpt-4
+              Executor:
+                subflows_config:
+                  write_code:
+                    subflows_config:
+                      CodeGenerator:
+                        backend:
+                          api_infos: ???
+                          model_name:
+                            openai: gpt-4
+                            azure: azure/gpt-4
+          re_plan:
+            subflows_config:
+              Controller:
+                backend:
+                  api_infos: ???
+                  model_name:
+                    openai: gpt-4
+                    azure: azure/gpt-4
+              Executor:
+                subflows_config:
+                  write_plan:
+                    subflows_config:
+                      PlanGenerator:
+                        backend:
+                          api_infos: ???
+                          model_name:
+                            openai: gpt-4
+                            azure: azure/gpt-4
+

SaveCodeAtomicFlow.py

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+from typing import Dict, Any
+from flows.base_flows.atomic import AtomicFlow
+
+
+class SaveCodeAtomicFlow(AtomicFlow):
+    def _check_input(self, input_data: Dict[str, Any]):
+        assert "code" in input_data, "code is not passed to SaveCodeAtomicFlow"
+        assert "memory_files" in input_data, "memory_files is not passed to SaveCodeFlow"
+        assert "code_library" in input_data["memory_files"], "code_library not in memory_files"
+        # create the code library if it doesn't exist yet
+        code_library_location = input_data["memory_files"]["code_library"]
+        with open(code_library_location, 'a') as file:
+            pass
+
+    def _call(self, input_data: Dict[str, Any]):
+        try:
+            code_to_append = input_data["code"]
+            code_lib_loc = input_data["memory_files"]["code_library"]
+            with open(code_lib_loc, 'a') as file:
+                file.write(code_to_append + '\n')
+            return {
+                "result": "code successfully written to the library",
+                "summary": f"ExtendLibrayFlow/SaveCodeAtomicFlow: code written to {code_lib_loc}"
+            }
+        except Exception as e:
+            error_msg = str(e)
+            return {
+                "result": f"error occurred: {error_msg}",
+                "summary": f"ExtendLibrayFlow/SaveCodeAtomicFlow: error occurred: {error_msg}"
+            }
+
+    def run(
+            self,
+            input_data: Dict[str, Any]
+    ):
+        self._check_input(input_data)
+        return self._call(input_data)

SaveCodeAtomicFlow.yaml

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+_target_: Tachi67.ExtendLibraryFlowModule.SaveCodeAtomicFlow.instantiate_from_default_config
+name: "SaveCodeAtomicFlow"
+description: "In extend library flow, once the code is written and tested, the controller calls this flow to save the code to the library."
+
+input_interface:
+  - "memory_files"
+  - "code"
+
+output_interface:
+  - "result"
+  - "summary"

UpdatePlanAtomicFlow.py

@@ -0,0 +1,29 @@
+from typing import Dict, Any
+from flows.base_flows.atomic import AtomicFlow
+class UpdatePlanAtomicFlow(AtomicFlow):
+    def _check_input(self, input_data: Dict[str, Any]):
+        assert "memory_files" in input_data, "memory_files not passed to UpdatePlanAtomicFlow"
+        assert "plan" in input_data["memory_files"], "plan not in memory_files"
+
+    def _call(self, input_data: Dict[str, Any]):
+        try:
+            plan_file_location = input_data["memory_files"]["plan"]
+            plan_to_write = input_data["updated_plan"]
+            with open(plan_file_location, 'w') as file:
+                file.write(plan_to_write + "\n")
+            return {
+                "result": "updated plan saved to the plan file and has overriden the previous plan",
+                "summary": f"ExtendLibrary/UpdatePlanFlow: updated plan saved to {plan_file_location}"
+            }
+        except Exception as e:
+            return {
+                "result": f"Error occurred: {str(e)}",
+                "summary": f"ExtendLibrary/UpdatePlanFlow: error occurred while writing updated plan: {str(e)}"
+            }
+
+    def run(
+            self,
+            input_data: Dict[str, Any]
+    ):
+        self._check_input(input_data)
+        return self._call(input_data)

UpdatePlanAtomicFlow.yaml

@@ -0,0 +1,9 @@
+_target_: Tachi67.ExtendLibraryFlowModule.UpdatePlanAtomicFlow.instantiate_from_default_config
+name: "UpdatePlanAtomicFlow"
+description: "Writes new plan to plan file"
+
+input_interface:
+  - "updated_plan"
+
+output_interface:
+  - "result"

__init__.py

@@ -0,0 +1,16 @@
+dependencies = [
+    {"url": "Tachi67/AbstractBossFlowModule", "revision": "main"},
+    {"url": "Tachi67/MemoryReadingFlowModule", "revision": "main"},
+    {"url": "Tachi67/PlanWriterFlowModule", "revision": "main"},
+    {"url": "Tachi67/ReplanningFlowModule", "revision": "main"},
+    {"url": "Tachi67/CodeWriterFlowModule", "revision": "main"},
+]
+
+from flows import flow_verse
+flow_verse.sync_dependencies(dependencies)
+from .ControllerFlow_ExtLib import ControllerFlow_ExtLib
+from .CtrlExMem_ExtLib import CtrlExMem_ExtLib
+from .ExtendLibraryFlow import ExtendLibraryFlow
+from .ExtLibAskUserFlow import ExtLibAskUserFlow
+from .SaveCodeAtomicFlow import SaveCodeAtomicFlow
+from .UpdatePlanAtomicFlow import UpdatePlanAtomicFlow