.gitignore

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

README.md

@@ -27,7 +27,6 @@ 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

@@ -4,8 +4,6 @@
 
 | 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-IDs-HERE","SEPARATED-BY-COMMAS"]
+vector_store = "YOUR-VECTOR-STORE-ID-HERE"
 

create_image.py

@@ -1,33 +0,0 @@
-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
@@ -23,7 +23,5 @@ 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

@@ -13,7 +13,6 @@ 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

@@ -13,7 +13,6 @@ 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]))