Update gpt.py

gpt.py

@@ -1,198 +1,197 @@
-from openai import OpenAI
-import os
-import base64
-import requests
-from prompts import prompts
-from constants import JSON_SCHEMA_FOR_GPT
-
-OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
-
-client = OpenAI(api_key=OPENAI_API_KEY)
-model = "gpt-4o"
-title = "Caimera Mood board Expert"
-
-
-def createAssistant(instruction_prompt):
-    instructions = instruction_prompt
-    assistant = client.beta.assistants.create(
-        name=title,
-        instructions=instructions,
-        model=model
-    )
-    return assistant.id
-
-
-def saveFileOpenAI(location):
-    with open(location, "rb") as f:
-        file = client.files.create(file=f, purpose="vision")
-    os.remove(location)
-    return file.id
-
-
-def startAssistantThread(file_id_enum, prompt_n, image_needed, json_mode_needed_or_not):
-    if json_mode_needed_or_not == "yes":
-        if image_needed == "yes":
-            messages = [
-                {
-                    "role": "user",
-                    "content": [
-                        {
-                            "type": "text",
-                            "text": prompt_n
-                        }
-                    ],
-                }
-            ]
-            for file_id in file_id_enum:
-                messages[0]["content"].append({
-                    "type": "image_file",
-                    "image_file": {"file_id": file_id}
-                })
-        else:
-            messages = [
-                {
-                    "role": "user",
-                    "content": prompt_n}]
-        thread = client.beta.threads.create(messages=messages)
-    else:
-        if image_needed == "yes":
-            messages = [
-                {
-                    "role": "user",
-                    "content": [
-                        {
-                            "type": "text",
-                            "text": prompt_n
-                        }
-                    ],
-                }
-            ]
-            for file_id in file_id_enum:
-                messages[0]["content"].append({
-                    "type": "image_file",
-                    "image_file": {"file_id": file_id}
-                })
-        else:
-            messages = [
-                {
-                    "role": "user",
-                    "content": prompt_n}]
-        thread = client.beta.threads.create(messages=messages)
-    return thread.id
-
-
-def runAssistant(thread_id, assistant_id):
-    run = client.beta.threads.runs.create(thread_id=thread_id, assistant_id=assistant_id)
-    return run.id
-
-
-def checkRunStatus(thread_id, run_id):
-    run = client.beta.threads.runs.retrieve(thread_id=thread_id, run_id=run_id)
-    return run.status
-
-
-def retrieveThread(thread_id):
-    thread_messages = client.beta.threads.messages.list(thread_id)
-    list_messages = thread_messages.data
-    thread_messages = []
-    for message in list_messages:
-        obj = {}
-        obj['content'] = message.content[0].text.value
-        obj['role'] = message.role
-        thread_messages.append(obj)
-    return thread_messages[::-1]
-
-
-def addMessageToThread(thread_id, prompt_n):
-    thread_message = client.beta.threads.messages.create(thread_id, role="user", content=prompt_n)
-
-
-def create_chat_completion_request_open_ai_for_summary(prompt, json_mode, schema_name="",
-                                                       json_schema="",
-                                                       system_message="You are expert in Fashion "
-                                                                      "Shoots"):
-    import requests
-    if json_mode == "No":
-        url = "https://api.openai.com/v1/chat/completions"
-        headers = {
-            "Content-Type": "application/json",
-            "Authorization": f"Bearer {OPENAI_API_KEY}"
-        }
-        data = {
-            "model": "gpt-4o",
-            "messages": [
-                {
-                    "role": "system",
-                    "content": system_message
-                },
-                {
-                    "role": "user",
-                    "content": prompt
-                }
-            ]
-        }
-        response = requests.post(url, headers=headers, json=data)
-        json_response = response.json()
-    else:
-        url = "https://api.openai.com/v1/chat/completions"
-        headers = {
-            "Content-Type": "application/json",
-            "Authorization": f"Bearer {OPENAI_API_KEY}"
-        }
-        data = {
-            "model": "gpt-4o",
-            "messages": [
-                {
-                    "role": "system",
-                    "content": "You are expert in creating prompts for Fashion Shoots."
-                },
-                {
-                    "role": "user",
-                    "content": prompt
-                }
-            ],
-            "response_format": {"type": "json_schema", "json_schema": {"name": schema_name, "strict": True, "schema":
-                json_schema}}
-        }
-        response = requests.post(url, headers=headers, json=data)
-        json_response = response.json()
-    print(json_response)
-    return json_response["choices"][0]["message"]["content"]
-
-
-def encode_image(image_path):
-    with open(image_path, "rb") as image_file:
-        return base64.b64encode(image_file.read()).decode('utf-8')
-
-
-def create_image_completion_request_gpt(image_path, prompt):
-    base64_image = encode_image(image_path)
-    headers = {
-        "Content-Type": "application/json",
-        "Authorization": f"Bearer {OPENAI_API_KEY}"
-    }
-    payload = {
-        "model": "gpt-4o",
-        "messages": [
-            {
-                "role": "user",
-                "content": [
-                    {
-                        "type": "text",
-                        "text": prompt
-                    },
-                    {
-                        "type": "image_url",
-                        "image_url": {
-                            "url": f"data:image/jpeg;base64,{base64_image}"
-                        }
-                    }
-                ]
-            }
-        ],
-        "max_tokens": 300
-    }
-    response = requests.post("https://api.openai.com/v1/chat/completions",
-                             headers=headers, json=payload)
-    json_resp = response.json()
-    return json_resp["choices"][0]["message"]["content"]
+from openai import OpenAI
+import os
+import base64
+import requests
+from prompts import prompts
+from constants import JSON_SCHEMA_FOR_GPT
+
+OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
+
+client = OpenAI(api_key=OPENAI_API_KEY)
+model = "gpt-4o"
+title = "Caimera Mood board Expert"
+
+
+def createAssistant(instruction_prompt):
+    instructions = instruction_prompt
+    assistant = client.beta.assistants.create(
+        name=title,
+        instructions=instructions,
+        model=model
+    )
+    return assistant.id
+
+
+def saveFileOpenAI(location):
+    with open(location, "rb") as f:
+        file = client.files.create(file=f, purpose="vision")
+    os.remove(location)
+    return file.id
+
+
+def startAssistantThread(file_id_enum, prompt_n, image_needed, json_mode_needed_or_not):
+    if json_mode_needed_or_not == "yes":
+        if image_needed == "yes":
+            messages = [
+                {
+                    "role": "user",
+                    "content": [
+                        {
+                            "type": "text",
+                            "text": prompt_n
+                        }
+                    ],
+                }
+            ]
+            for file_id in file_id_enum:
+                messages[0]["content"].append({
+                    "type": "image_file",
+                    "image_file": {"file_id": file_id}
+                })
+        else:
+            messages = [
+                {
+                    "role": "user",
+                    "content": prompt_n}]
+        thread = client.beta.threads.create(messages=messages)
+    else:
+        if image_needed == "yes":
+            messages = [
+                {
+                    "role": "user",
+                    "content": [
+                        {
+                            "type": "text",
+                            "text": prompt_n
+                        }
+                    ],
+                }
+            ]
+            for file_id in file_id_enum:
+                messages[0]["content"].append({
+                    "type": "image_file",
+                    "image_file": {"file_id": file_id}
+                })
+        else:
+            messages = [
+                {
+                    "role": "user",
+                    "content": prompt_n}]
+        thread = client.beta.threads.create(messages=messages)
+    return thread.id
+
+
+def runAssistant(thread_id, assistant_id):
+    run = client.beta.threads.runs.create(thread_id=thread_id, assistant_id=assistant_id)
+    return run.id
+
+
+def checkRunStatus(thread_id, run_id):
+    run = client.beta.threads.runs.retrieve(thread_id=thread_id, run_id=run_id)
+    return run.status
+
+
+def retrieveThread(thread_id):
+    thread_messages = client.beta.threads.messages.list(thread_id)
+    list_messages = thread_messages.data
+    thread_messages = []
+    for message in list_messages:
+        obj = {}
+        obj['content'] = message.content[0].text.value
+        obj['role'] = message.role
+        thread_messages.append(obj)
+    return thread_messages[::-1]
+
+
+def addMessageToThread(thread_id, prompt_n):
+    thread_message = client.beta.threads.messages.create(thread_id, role="user", content=prompt_n)
+
+
+def create_chat_completion_request_open_ai_for_summary(prompt, json_mode, schema_name="",
+                                                       json_schema="",
+                                                       system_message="You are expert in Fashion "
+                                                                      "Shoots"):
+    import requests
+    if json_mode == "No":
+        url = "https://api.openai.com/v1/chat/completions"
+        headers = {
+            "Content-Type": "application/json",
+            "Authorization": f"Bearer {OPENAI_API_KEY}"
+        }
+        data = {
+            "model": "gpt-4o",
+            "messages": [
+                {
+                    "role": "system",
+                    "content": system_message
+                },
+                {
+                    "role": "user",
+                    "content": prompt
+                }
+            ]
+        }
+        response = requests.post(url, headers=headers, json=data)
+        json_response = response.json()
+    else:
+        url = "https://api.openai.com/v1/chat/completions"
+        headers = {
+            "Content-Type": "application/json",
+            "Authorization": f"Bearer {OPENAI_API_KEY}"
+        }
+        data = {
+            "model": "gpt-4o",
+            "messages": [
+                {
+                    "role": "system",
+                    "content": "You are expert in creating prompts for Fashion Shoots."
+                },
+                {
+                    "role": "user",
+                    "content": prompt
+                }
+            ],
+            "response_format": {"type": "json_schema", "json_schema": {"name": schema_name, "strict": True, "schema":
+                json_schema}}
+        }
+        response = requests.post(url, headers=headers, json=data)
+        json_response = response.json()
+    print(json_response)
+    return json_response["choices"][0]["message"]["content"]
+
+
+def encode_image(image_path):
+    with open(image_path, "rb") as image_file:
+        return base64.b64encode(image_file.read()).decode('utf-8')
+
+
+def create_image_completion_request_gpt(image_path, prompt):
+    base64_image = encode_image(image_path)
+    headers = {
+        "Content-Type": "application/json",
+        "Authorization": f"Bearer {OPENAI_API_KEY}"
+    }
+    payload = {
+        "model": "gpt-4o",
+        "messages": [
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "text",
+                        "text": prompt
+                    },
+                    {
+                        "type": "image_url",
+                        "image_url": {
+                            "url": f"data:image/jpeg;base64,{base64_image}"
+                        }
+                    }
+                ]
+            }
+        ],
+    }
+    response = requests.post("https://api.openai.com/v1/chat/completions",
+                             headers=headers, json=payload)
+    json_resp = response.json()
+    return json_resp["choices"][0]["message"]["content"]