aaa

app.py

@@ -1,39 +1,57 @@
 from transformers import pipeline
-import openai
+from openai import OpenAI
+import requests
+from PIL import Image
+
 import gradio as gr
 import os
+import json
 
 #pipe = pipeline(model="jdowling/whisper-small-hi")  # change to "your-username/the-name-you-picked"
 #generator = pipeline('text-generation', model='openai-gpt')
 #set_seed(42)
 # Use the API key as needed
 
+client = OpenAI(
+    api_key=os.environ.get('OPEN_AI_KEY')
+
+)
 
 
-openai.api_key = os.environ.get('OPEN_AI_KEY')
 
-def generate_chat(prompt):
-    response = openai.Completion.create(
-        model="text-davinci-003",  # Choose the appropriate model
-        messages=[
-            {"role": "system", "content": "You are a psychologist."},
-            {"role": "user", "content": prompt}
-        ]
-    )
-    return response['choices'][0]['message']['content']
+psychologist_url = "https://raw.githubusercontent.com/rogoran/id2223kth.github.io/master/src/serverless-ml-intro/serverless-ml-lab/wine_images/360_F_169387942_tUJn9ADX31sRDFCuK9nlBuRR4gO6a1TK.jpg"
+IMG = Image.open(requests.get(psychologist_url, stream=True).raw)
+latest_messages = [{"role": "system", "content": "Du är en svensktalande psykolog."}]
+
 
 def transcribe(audio):
-    prompt = "Im very sad because my dog died."
-    response = generate_chat(prompt)
     #text = pipe(audio)["text"]
-    return response
-
-iface = gr.Interface(
-    fn=transcribe, 
-    inputs=gr.Audio(sources="microphone", type="filepath"), 
-    outputs="text",
-    title="Whisper Small Swedish",
-    description="Realtime demo for Swedish speech recognition using a fine-tuned Whisper small model.",
-)
-
-iface.launch()
+    if audio is None:
+        return
+    #prompt = "Jag är ledsen eftersom jag tappade min klubba."
+    print(audio)
+    return chat(audio)
+    
+    
+def chat(prompt):
+    #response = generate_chat(prompt)
+    latest_messages.append({"role": "user", "content": prompt})
+    response = client.chat.completions.create(
+        model="gpt-3.5-turbo-1106",
+        messages=latest_messages
+    )
+    latest_messages.append({"role": "assistant", "content": response.choices[0].message.content})
+    return response.choices[0].message.content  
+    
+with gr.Blocks() as demo:
+    with gr.Row():
+        with gr.Column():
+            #inp = gr.Audio(sources="microphone", type="filepath")
+            inp = gr.Textbox()
+            btn = gr.Button("Send transcribed msg")
+        with gr.Column():
+            gr.Image(value=IMG, label="Doctor Amanda")
+            out = gr.Textbox(label="Doctor Amandas answers")
+            btn.click(fn=transcribe, inputs=inp, outputs=out)
+            
+demo.launch()

flagged/log.csv

@@ -0,0 +1,2 @@
+audio,output,flag,username,timestamp
+,,,,2023-12-03 15:54:26.312403