implementing simple ui & seperate brain cli and service

brain/service_fastapi.py

@@ -0,0 +1,34 @@
+import sys
+
+from fastapi import FastAPI
+import uvicorn
+
+from brain_openai import CloudChatBrain
+
+
+
+#def start_application():
+#    app = FastAPI()
+#    # app.include_router(api_router)
+#    # brain = CloudChatBrain()
+#    return app
+
+
+
+
+if __name__ == "__main__":
+    if len(sys.argv) == 1: 
+        port = 8890
+    else:
+        port = int(sys.argv[1])
+
+    app = FastAPI()
+
+    @app.post("/command/")
+    def post_command(payload: dict):
+        prompt = payload.get("prompt")
+        return {"response": prompt}
+
+    
+    #app = start_application()
+    uvicorn.run(app, host="0.0.0.0", port=port, log_level="debug")

brain/service_gradio.py

@@ -0,0 +1,33 @@
+import random
+
+import gradio as gr
+from loguru import logger
+
+
+
+def make_completion(history):
+    return "ok"
+
+def answer(input, history):
+    history.append({"role": "user", "content": input})
+    response = random.choice(["How are you?", "I love you", "I'm very hungry"])
+    history.append({"role": "assistant", "content": response})
+    messages = [(history[i]["content"], history[i+1]["content"]) for i in range(0, len(history)-1, 2)]
+    logger.debug(history)
+    return messages, history
+
+
+
+with gr.Blocks() as demo:
+    chatbot = gr.Chatbot(label="Fly my drone with chatGPT as copilot")
+    state = gr.State([])
+    with gr.Row():
+        prompt = gr.Textbox(
+                    show_label=True,
+                    label="what should I do now?\n(enter q for emergency)",
+                    placeholder="Enter text and press enter")\
+                .style(container=True)
+    prompt.submit(answer, [prompt, state], [chatbot, state])
+
+
+demo.launch(server_name="0.0.0.0", server_port=8890, debug=True)

brain/service_gradio_nicetry_1.py

@@ -0,0 +1,37 @@
+import gradio as gr
+import requests
+
+
+conversation = []
+
+def generate_response(prompt, params):
+    #response = requests.get(f"http://localhost:8000/command/{prompt}").json()
+    response = f"I got {prompt}"
+    conversation.append({"prompt": prompt, "response": response})
+    print(params)
+    #params["conversation_history"].description = f"Conversation History:\n\n{populate_chat_history(conversation)}"
+    return f"I got: {prompt}"
+
+def populate_chat_history(conversation):
+    history = ""
+    for i, chat in enumerate(conversation):
+        history += f"User: {chat['prompt']}\nBot: {chat['response']}\n\n"
+    return history
+
+iface = gr.Interface(
+    fn=generate_response,
+    inputs=["text"],
+    outputs=["text"],
+    parameters=[
+        {
+            "type": "textbox", 
+            "key": "conversation_history", 
+            "label": "Conversation:", 
+            "default": ""
+        }
+    ],
+    title="fly my drone by talking",
+    description="what should I do now?\n(enter q for emergency)"
+)
+
+iface.launch(server_name="0.0.0.0", server_port=8890, debug=True)

commander/commander.py

@@ -23,4 +23,5 @@ if __name__ == "__main__":
         port = int(sys.argv[1])
     
     app = start_application()
+
     uvicorn.run(app, host="0.0.0.0", port=port, log_level="debug")

manage.sh

@@ -69,8 +69,12 @@ start_commander_service() {
 	venv/bin/python commander/commander.py $1
 }
 
+start_brain_service() {
+    venv/bin/python brain/service.py $1
+}
+
 talk_to_drone() {
-    ENV_FOR_DYNACONF=$1 python brain/brain.py
+    ENV_FOR_DYNACONF=$1 python brain/cli.py
 }
 
 kill_everything() {