Create app.py

app.py

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+from autogen import AssistantAgent, UserProxyAgent, config_list_from_json
+import autogen
+import replicate
+import requests
+from datetime import datetime
+import http.client
+import json
+import base64
+
+config_list = config_list_from_json(env_or_file="OAI_CONFIG_LIST")
+llm_config = {"config_list": config_list, "request_timeout": 120}
+
+# function to use llava model to review image
+
+
+def img_review(image_url, prompt):
+    data = {
+        "data": [
+            {
+                "image": "https://picsum.photos/200",
+                "features": [],
+            },
+        ]}
+
+    headers = {
+        "x-api-key": "token 8uOw4ntevc8JKo0Q3tQq:2975e2827ebeb4e103f7b58c1410ba58fa47bc27b1302de614a000bf51bd2114",
+        "content-type": "application/json",
+    }
+
+    connection = http.client.HTTPSConnection("api.scenex.jina.ai")
+    connection.request("POST", "/v1/describe", json.dumps(data), headers)
+    response = connection.getresponse()
+
+    print(response.status, response.reason)
+    response_data = response.read().decode("utf-8")
+    print(response_data)
+
+    connection.close()
+
+    return response_data
+
+
+result = img_review(
+    "https://cdn.discordapp.com/attachments/1083723388712919182/1089909178266558554/HannaD_A_captivating_digital_artwork_features_a_red-haired_girl_664d73dc-b537-490e-b044-4fbf22733559.png", "a llama driving a car")
+print(result)
+
+# def img_review(image_path, prompt):
+#     output = replicate.run(
+#         "yorickvp/llava-13b:6bc1c7bb0d2a34e413301fee8f7cc728d2d4e75bfab186aa995f63292bda92fc",
+#         input={
+#             "image": open(image_path, "rb"),
+#             "prompt": f"What is happening in the image? From scale 1 to 10, decide how similar the image is to the text prompt {prompt}?",
+#         }
+#     )
+
+#     result = ""
+#     for item in output:
+#         result += item
+
+#     return result
+
+
+# function to use stability-ai model to generate image
+def text_to_image_generation(prompt):
+    output = replicate.run(
+        "stability-ai/sdxl:c221b2b8ef527988fb59bf24a8b97c4561f1c671f73bd389f866bfb27c061316",
+        input={
+            "prompt": prompt
+        }
+    )
+
+    if output and len(output) > 0:
+        # Get the image URL from the output
+        image_url = output[0]
+        print(f"generated image for {prompt}: {image_url}")
+
+        # Download the image and save it with a filename based on the prompt and current time
+        current_time = datetime.now().strftime("%Y%m%d%H%M%S")
+        shortened_prompt = prompt[:50]
+        filename = f"imgs/{shortened_prompt}_{current_time}.png"
+
+        response = requests.get(image_url)
+        if response.status_code == 200:
+            with open(filename, "wb") as file:
+                file.write(response.content)
+            return f"Image saved as '{filename}'"
+        else:
+            return "Failed to download and save the image."
+    else:
+        return "Failed to generate the image."
+
+
+# Create llm config
+llm_config_assistants = {
+    "functions": [
+        {
+            "name": "text_to_image_generation",
+            "description": "use latest AI model to generate image based on a prompt, return the file path of image generated",
+            "parameters": {
+                    "type": "object",
+                    "properties": {
+                        "prompt": {
+                            "type": "string",
+                            "description": "a great text to image prompt that describe the image",
+                        }
+                    },
+                "required": ["prompt"],
+            },
+        },
+        {
+            "name": "image_review",
+            "description": "review & critique the AI generated image based on original prompt, decide how can images & prompt can be improved",
+            "parameters": {
+                    "type": "object",
+                    "properties": {
+                        "prompt": {
+                            "type": "string",
+                            "description": "the original prompt used to generate the image",
+                        },
+                        "image_path": {
+                            "type": "string",
+                            "description": "the image file path, make sure including the full file path & file extension",
+                        }
+                    },
+                "required": ["prompt", "image_path"],
+            },
+        },
+    ],
+    "config_list": config_list,
+    "request_timeout": 120}
+
+# Create assistant agent
+img_gen_assistant = AssistantAgent(
+    name="text_to_img_prompt_expert",
+    system_message="You are a text to image AI model expert, you will use text_to_image_generation function to generate image with prompt provided, and also improve prompt based on feedback provided until it is 10/10.",
+    llm_config=llm_config_assistants,
+    function_map={
+        "image_review": img_review,
+        "text_to_image_generation": text_to_image_generation
+    }
+)
+
+img_critic_assistant = AssistantAgent(
+    name="img_critic",
+    system_message="You are an AI image critique, you will use img_review function to review the image generated by the text_to_img_prompt_expert against the original prompt, and provide feedback on how to improve the prompt.",
+    llm_config=llm_config_assistants,
+    function_map={
+        "image_review": img_review,
+        "text_to_image_generation": text_to_image_generation
+    }
+)
+
+# Create user proxy agent
+user_proxy = UserProxyAgent(
+    name="user_proxy",
+    human_input_mode="ALWAYS",
+)
+
+# Create groupchat
+groupchat = autogen.GroupChat(
+    agents=[user_proxy, img_gen_assistant, img_critic_assistant], messages=[], max_round=50)
+
+manager = autogen.GroupChatManager(
+    groupchat=groupchat,
+    llm_config=llm_config)
+
+# # Start the conversation
+# user_proxy.initiate_chat(
+#     manager, message="Generate a photo realistic image of llama driving a car")