Implemented sequential execution

.env.example

@@ -0,0 +1,2 @@
+OPENAI_KEY_PERSONAL=<openai_key>
+GOOGLE_APPLICATION_KEY=<gcp_key_json>

.gitignore

@@ -1,2 +1,3 @@
 venv
-.vscode
+.vscode
+.env

ai/__init__.py

@@ -0,0 +1 @@
+from . import image, llm

ai/image.py

@@ -0,0 +1,19 @@
+import os
+from typing import Any, Dict, List
+
+import openai
+from dotenv import load_dotenv
+
+load_dotenv()
+
+
+openai.api_key = os.environ["OPENAI_KEY_PERSONAL"]
+
+
+def gen(prompt: str, n: int, size: str) -> Dict[str, Any]:
+    return openai.Image.create(prompt=prompt, n=n, size=size)  # type: ignore
+
+
+def urls(prompt: str, n: int = 1, size: str = "512x512") -> List[str]:
+    images = gen(prompt, n, size)
+    return [i["url"] for i in images["data"]]  # type: ignore

ai/llm.py

@@ -0,0 +1,40 @@
+import os
+from typing import Any, Dict, List, Optional
+
+import openai
+from dotenv import load_dotenv
+
+load_dotenv()
+
+
+openai.api_key = os.environ["OPENAI_KEY_PERSONAL"]
+MODEL = "gpt-3.5-turbo"
+TEMPERATURE = 0.7
+
+
+def call(
+    messages: List[Dict[str, str]],
+    model: Optional[str] = None,
+    temperature: Optional[float] = None,
+    stop: Optional[str] = None,
+) -> Dict[str, Any]:
+    if not model:
+        model = MODEL
+    if not temperature:
+        temperature = TEMPERATURE
+
+    return openai.ChatCompletion.create(  # type: ignore
+        model=model,
+        messages=messages,
+        temperature=temperature,
+        stop=stop,
+    )
+
+
+def next(
+    messages: List[Dict[str, str]],
+    model: Optional[str] = None,
+    temperature: Optional[float] = None,
+    stop: Optional[str] = None,
+) -> str:
+    return call(messages, model, temperature, stop)["choices"][0]["message"]["content"]

app.py

@@ -1,8 +1,10 @@
-from typing import NamedTuple, Type, Union
-
+from typing import NamedTuple, Optional, Type, Union
 
 import gradio as gr
 
+import ai
+from utils.io import print_system
+
 
 MAX_INPUTS = 10
 MAX_TASKS = 50
@@ -23,6 +25,9 @@ class Input:
             )
             return gr_component
 
+    def execute(self) -> None:
+        pass
+
 
 class AITask:
     @property
@@ -53,16 +58,23 @@ class AITask:
                     )
             return gr_component
 
+    def execute(self, prompt: str) -> Optional[str]:
+        if prompt:
+            return ai.llm.next([{"role": "user", "content": prompt}])
+
 
 class Component:
-    def __init__(self, id_: int, internal: Union[Input, AITask], visible: bool = False):
+    def __init__(
+        self, id_: float, internal: Union[Input, AITask], visible: bool = False
+    ):
         # Internal state
         self._id = id_
         self.internal = internal
+        self._source = self.internal.__class__.__name__
         self._initial_visibility = visible
 
         # Gradio state
-        self.component_id: gr.Textbox
+        self.component_id: gr.Number
         self.source: gr.Textbox
         self.visible: gr.Number
         self.gr_component = gr.Box
@@ -70,13 +82,17 @@ class Component:
         self.output: gr.Textbox
 
     def render(self) -> None:
-        self.component_id = gr.Textbox(value=str(self._id), visible=False)
-        self.source = gr.Textbox(value=self.internal.__class__.__name__, visible=False)
+        self.component_id = gr.Number(value=self._id, visible=False)
+        self.source = gr.Textbox(value=self._source, visible=False)
         self.visible = gr.Number(int(self._initial_visibility), visible=False)
         self.gr_component = self.internal.render(self._initial_visibility)
         self.output_name = self.internal.output_name
         self.output = self.internal.output
 
+    def execute(self, *args):
+        print_system(f"Executing component :: {self._source}.{self._id}")
+        return self.internal.execute(*args)
+
 
 class Variable(NamedTuple):
     source: Type[Union[Input, AITask]]
@@ -85,8 +101,8 @@ class Variable(NamedTuple):
     value: str
 
 
-all_inputs = {i: Component(i, Input()) for i in range(MAX_INPUTS)}
-all_tasks = {i: Component(i, AITask()) for i in range(MAX_TASKS)}
+all_inputs = {float(i): Component(i, Input()) for i in range(MAX_INPUTS)}
+all_tasks = {float(i): Component(i, AITask()) for i in range(MAX_TASKS)}
 
 all_inputs[0]._initial_visibility = True
 all_tasks[0]._initial_visibility = True
@@ -105,7 +121,6 @@ def add_input(*visibility):
 
 def remove_input(*visibility):
     for i, visible in reversed(list(enumerate(visibility, 1))):
-        print(i, visible)
         if bool(visible):
             return (
                 [gr.Row.update(visible=True)] * (i - 1)
@@ -128,7 +143,6 @@ def add_task(*visibility):
 
 def remove_task(*visibility):
     for i, visible in reversed(list(enumerate(visibility, 1))):
-        print(i, visible)
         if bool(visible):
             return (
                 [gr.Box.update(visible=True)] * (i - 1)
@@ -138,6 +152,11 @@ def remove_task(*visibility):
             )
 
 
+def execute_task(id_: float, prompt: str):
+    if prompt:
+        return all_tasks[id_].execute(prompt)
+
+
 with gr.Blocks() as demo:
     # Initial layout
     for i in all_inputs.values():
@@ -166,26 +185,39 @@ with gr.Blocks() as demo:
     add_input_btn.click(
         add_input,
         inputs=[i.visible for i in all_inputs.values()],
-        outputs=[i.gr_component for i in all_inputs.values()]
+        outputs=[i.gr_component for i in all_inputs.values()]  # type: ignore
         + [i.visible for i in all_inputs.values()],
     )
     remove_input_btn.click(
         remove_input,
         inputs=[i.visible for i in all_inputs.values()],
-        outputs=[i.gr_component for i in all_inputs.values()]
+        outputs=[i.gr_component for i in all_inputs.values()]  # type: ignore
         + [i.visible for i in all_inputs.values()],
     )
     add_task_btn.click(
         add_task,
         inputs=[i.visible for i in all_tasks.values()],
-        outputs=[i.gr_component for i in all_tasks.values()]
+        outputs=[i.gr_component for i in all_tasks.values()]  # type: ignore
         + [i.visible for i in all_tasks.values()],
     )
     remove_task_btn.click(
         remove_task,
         inputs=[i.visible for i in all_tasks.values()],
-        outputs=[i.gr_component for i in all_tasks.values()]
+        outputs=[i.gr_component for i in all_tasks.values()]  # type: ignore
         + [i.visible for i in all_tasks.values()],
     )
 
+    # Sequential execution
+    execution_event = execute_btn.click(
+        execute_task,
+        inputs=[all_tasks[0].component_id, all_tasks[0].internal.prompt],  # type: ignore
+        outputs=[all_tasks[0].output],
+    )
+    for task in list(all_tasks.values())[1:]:
+        execution_event = execution_event.then(
+            execute_task,
+            inputs=[task.component_id, task.internal.prompt],  # type: ignore
+            outputs=[task.output],
+        )
+
 demo.launch()

requirements.txt

@@ -1 +1,3 @@
-gradio
+gradio
+openai
+python-dotenv

utils/io.py

@@ -0,0 +1,12 @@
+def print_system(message) -> str:
+    print(f"\033[0;0m{message}")
+    return message
+
+
+def print_assistant(message) -> str:
+    print(f"\033[92m{message}")
+    return message
+
+
+def user_input(message: str = "") -> str:
+    return input(f"\033[1;34m{message}")