First commit.

OpenAIChatHumanFlowModule.py

@@ -0,0 +1,14 @@
+from flows.base_flows import CircularFlow
+from flows.utils import logging
+
+log = logging.get_logger(__name__)
+
+
+class OpenAIChatHumanFlowModule(CircularFlow):
+
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+
+    @classmethod
+    def type(cls):
+        return "OpenAIChatHumanFlowModule"

OpenAIChatHumanFlowModule.yaml

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+name: "OpenAIChatInteractiveFlow"
+description: "Flow for chatting with an OpenAI Flow and a user providing the input."
+
+max_rounds: null # Run until early exit is detected
+
+input_keys: null # Should be specified by the user
+
+output_keys: null # Should be specified by the user
+
+subflows_config:
+  Assistant:
+    _target_: aiflows.OpenAIChatFlowModule.OpenAIChatAtomicFlow.instantiate_from_default_config
+    model_name: "gpt-4"
+  User:
+    _target_: aiflows.HumanStandardInputFlowModule.HumanStandardInputFlow.instantiate_from_default_config
+
+topology:
+  - goal: "Query the assistant"
+
+    ### Input Interface
+    input_interface:
+      _target_: flows.interfaces.KeyInterface
+      additional_transformations:
+        - _target_: flows.data_transformations.KeyMatchInput
+
+    ### Flow Specification
+    flow: Assistant
+    reset_every_round: false
+
+    ### Output Interface
+    output_interface:
+      _target_: flows.interfaces.KeyInterface
+      additional_transformations:
+        - _target_: flows.data_transformations.PrintPreviousMessages
+
+  - goal: "Ask the user for input"
+
+    ### Input Interface
+    input_interface:
+      _target_: flows.interfaces.KeyInterface
+      additional_transformations:
+        - _target_: flows.data_transformations.KeyMatchInput
+
+    ### Flow Specification
+    flow: User
+    reset_every_round: true
+
+    ### Output Interface
+    output_interface:
+      _target_: flows.interfaces.KeyInterface
+      additional_transformations:
+        - _target_: flows.data_transformations.RegexFirstOccurrenceExtractor
+          regex: '(?<=```answer)([\s\S]*?)(?=```)'
+          input_key: "human_input"
+          output_key: "answer"
+          strip: True
+          assert_unique: True
+        - _target_: flows.data_transformations.EndOfInteraction
+          end_of_interaction_string: "<END>"
+          input_key: "human_input"
+          output_key: "end_of_interaction"
+
+early_exit_key: "end_of_interaction"

README.md

@@ -1,3 +1,24 @@
 ---
 license: mit
 ---
+## Description
+
+< Flow description >
+
+## Configuration parameters
+
+< Name 1 > (< Type 1 >): < Description 1 >. Required parameter.
+
+< Name 2 > (< Type 2 >): < Description 2 >. Default value is: < value 2 >
+
+## Input interface
+
+< Name 1 > (< Type 1 >): < Description 1 >. 
+
+(Note that the interface might depend on the state of the Flow.)
+
+## Output interface
+
+< Name 1 > (< Type 1 >): < Description 1 >. 
+
+(Note that the interface might depend on the state of the Flow.)

__init__.py

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+# ~~~ Specify the dependencies ~~~
+dependencies = [
+    {"url": "aiflows/OpenAIChatFlowModule", "revision": "6a1e351a915f00193f18f3da3b61c497df1d31a3"},
+    {"url": "aiflows/HumanStandardInputFlowModule", "revision": "890e92da1fefbae642fd84296e31bca7f61ea710"},
+]
+from flows import flow_verse
+
+flow_verse.sync_dependencies(dependencies)
+# ~~~
+
+from .OpenAIChatHumanFlowModule import OpenAIChatHumanFlowModule

run.py

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+"""A simple script to run a Flow that can be used for development and debugging."""
+
+import os
+
+import hydra
+
+import flows
+from flows.flow_launchers import FlowLauncher, ApiInfo
+from flows.utils.general_helpers import read_yaml_file
+
+from flows import logging
+from flows.flow_cache import CACHING_PARAMETERS, clear_cache
+
+CACHING_PARAMETERS.do_caching = False  # Set to True to enable caching
+# clear_cache() # Uncomment this line to clear the cache
+
+logging.set_verbosity_debug()
+
+
+if __name__ == "__main__":
+    # ~~~ Set the API information ~~~
+    # OpenAI backend
+    # api_information = ApiInfo("openai", os.getenv("OPENAI_API_KEY"))
+    # Azure backend
+    api_information = ApiInfo("azure", os.getenv("AZURE_OPENAI_KEY"), os.getenv("AZURE_OPENAI_ENDPOINT"))
+
+    # ~~~ Instantiate the Flow ~~~
+    root_dir = "."
+    cfg_path = os.path.join(root_dir, "FlowName.yaml")
+    cfg = read_yaml_file(cfg_path)
+
+    flow_with_interfaces = {
+        "flow": hydra.utils.instantiate(cfg['flow'], _recursive_=False, _convert_="partial"),
+        "input_interface": (
+            None
+            if getattr(cfg, "input_interface", None) is None
+            else hydra.utils.instantiate(cfg['input_interface'], _recursive_=False)
+        ),
+        "output_interface": (
+            None
+            if getattr(cfg, "output_interface", None) is None
+            else hydra.utils.instantiate(cfg['output_interface'], _recursive_=False)
+        ),
+    }
+
+    # ~~~ Get the data ~~~
+    # This can be a list of samples
+    data = {"id": 0}  # Add your data here
+
+    # ~~~ Run inference ~~~
+    path_to_output_file = None
+    # path_to_output_file = "output.jsonl"  # Uncomment this line to save the output to disk
+
+    _, outputs = FlowLauncher.launch(
+        flow_with_interfaces=flow_with_interfaces,
+        data=data,
+        path_to_output_file=path_to_output_file,
+        api_information=api_information,
+    )
+
+    # ~~~ Print the output ~~~
+    flow_output_data = outputs[0]
+    print(flow_output_data)