Update SECURIT.md

.gitignore

@@ -1,5 +1,6 @@
 # Sensitive files
 config.py
+*.png
 
 # ---> Python
 # Byte-compiled / optimized / DLL files

README.md

@@ -27,6 +27,7 @@ You can manipulate the main abstractions of the OpenAI model:
   | --------------------------------------- | ----------------- | --------------- | --------------- | -------------------------------------------------------- |
   | `cancel_model_response.py`              | `response_id`     |                 |                 | Cancel a Response running in the background              |
   | `create_conversation.py`                |                   |                 |                 | Create a new Conversation                                |
+  | `create_image.py`                       | `model_id`        | `prompt`        |                 | Create an image based on the prompt description          |
   | `create_model_response.py`              | `conversation_id` | `model_id`      | `input_message` | Create a Response within a Conversation                  |
   | `create_text_item.py`                   | `conversation_id` | `input_message` |                 | Create a user input or instruction within a Conversation |
   | `create_vector_store.py`                |                   |                 |                 | Create a Vector Store                                    |

SECURITY.md

@@ -4,6 +4,8 @@
 
 | Version | Supported          |
 | ------- | ------------------ |
+| 0.5.x   | :heavy_check_mark: |
+| 0.4.x   | :heavy_check_mark: |
 | 0.3.x   | :heavy_check_mark: |
 | 0.2.x   | :heavy_check_mark: |
 | 0.1.x   | :heavy_check_mark: |

config-sample.py

@@ -1,4 +1,4 @@
 base_url = "https://api.openai.com/v1/"
 secret_key = "YOUR-OPENAI-SECRET-KEY-HERE"
-vector_store = "YOUR-VECTOR-STORE-ID-HERE"
+vector_store = ["YOUR-VECTOR-STORE-IDs-HERE","SEPARATED-BY-COMMAS"]
 

create_image.py

@@ -0,0 +1,33 @@
+from config import *
+import requests
+import json
+import sys
+import base64
+from PIL import Image
+from io import BytesIO
+from datetime import datetime
+
+def create_image(model,prompt):
+    url = base_url+"images/generations"
+
+    payload = json.dumps({
+      "prompt": prompt,
+      "model": model
+    })
+    headers = {
+      'Content-Type': 'application/json',
+      'Authorization': 'Bearer '+secret_key,
+    }
+    date_time_string = datetime.now().strftime("%Y-%m-%d-%H-%M-%S")
+
+    response = requests.request("POST", url, headers=headers, data=payload)
+    decoded_bytes = base64.b64decode(response.json()["data"][0]["b64_json"])
+    byte_stream = BytesIO(decoded_bytes)
+    image = Image.open(byte_stream)
+    image.save("./output_images/output-"+date_time_string+".png", "PNG")
+
+    print("Image ./output_images/output-"+date_time_string+".png has been generated.")
+
+
+if __name__ == '__main__':
+    create_image(str(sys.argv[1]),str(sys.argv[2]))

create_model_response.py

@@ -10,7 +10,7 @@ def create_model_response(conversation,model,message):
       "model": model,
       "tools": [
       {"type": "web_search"},
-      {"type": "file_search", "vector_store_ids" :[vector_store]}
+      {"type": "file_search", "vector_store_ids" :vector_store}
       ],
       "input": message,
       "conversation": conversation
@@ -23,5 +23,7 @@ def create_model_response(conversation,model,message):
     response = requests.request("POST", url, headers=headers, data=payload)
 
     print(response.text)
+    print(response.json()["output"][-1]["content"][0]["text"])
+
 if __name__ == '__main__':
     create_model_response(str(sys.argv[1]),str(sys.argv[2]),str(sys.argv[3]))

retrieve_item.py

@@ -13,6 +13,7 @@ def retrieve_item(conversation,message):
     response = requests.request("GET", url, headers=headers, data=payload)
 
     print(response.text)
+    print(response.json()["content"][0]["text"])
 
 
 if __name__ == '__main__':

retrieve_model_response.py

@@ -13,6 +13,7 @@ def retrieve_model_response(response):
     response = requests.request("GET", url, headers=headers, data=payload)
 
     print(response.text)
+    print(response.json()["output"][-1]["content"][0]["text"])
 
 if __name__ == '__main__':
     retrieve_model_response(str(sys.argv[1]))