feat: working gradio demo

agent.py

@@ -1,19 +1,12 @@
-from openai import OpenAI
 import streamlit as st
-from typing import TypedDict, Literal, Optional
-from pydantic import BaseModel
-import base64
+from typing import TypedDict, Literal
 from pydantic_ai.messages import (
-    ModelMessage,
     ModelRequest,
     ModelResponse,
-    SystemPromptPart,
     UserPromptPart,
     TextPart,
     ToolCallPart,
     ToolReturnPart,
-    RetryPromptPart,
-    ModelMessagesTypeAdapter
 )
 import asyncio
 from src.agents.mask_generation_agent import mask_generation_agent, ImageEditDeps
@@ -21,14 +14,22 @@ from src.hopter.client import Hopter, Environment
 import os
 from src.services.generate_mask import GenerateMaskService
 from dotenv import load_dotenv
-
+from src.utils import image_path_to_uri
 load_dotenv()
 
+st.set_page_config(
+    page_title="Conversational Image Editor",
+    page_icon="🧊",
+    layout="wide",
+    initial_sidebar_state="collapsed"
+)
+
 hopter = Hopter(
     api_key=os.getenv("HOPTER_API_KEY"),
     environment=Environment.STAGING
 )
 mask_service = GenerateMaskService(hopter=hopter)
+user_msg_input_key = "input_user_msg"
 
 class ChatMessage(TypedDict):
     """Format of messages sent to the browser/API."""
@@ -57,6 +58,16 @@ def display_message_part(part):
         with st.chat_message("assistant"):
             st.markdown(part.content) 
 
+    # tool call
+    elif part.part_kind == 'tool-call':
+        with st.chat_message("assistant"):
+            st.markdown(f"**{part.tool_name}**: {part.args}")
+
+    # tool return
+    elif part.part_kind == 'tool-return':
+        with st.chat_message("assistant"):
+            st.markdown(f"**{part.tool_name}**: {part.content}")
+
 async def run_agent(user_input: str, image_b64: str):
     messages = [
         {
@@ -99,15 +110,10 @@ async def run_agent(user_input: str, image_b64: str):
         st.session_state.messages.append(
             ModelResponse(parts=[TextPart(content=partial_text)])
         )
+    st.rerun()
 
 async def main():
-    st.title("ChatGPT-like clone")
-
-    def encode_image(uploaded_file):
-        # Read the file directly from the UploadedFile object
-        return base64.b64encode(uploaded_file.read()).decode("utf-8")
-
-    image = st.file_uploader("Upload an image", type=["png", "jpg", "jpeg"])
+    st.title("Conversational Image Editor")
 
     if "openai_model" not in st.session_state:
         st.session_state["openai_model"] = "gpt-4o"
@@ -118,42 +124,35 @@ async def main():
     if "image" not in st.session_state:
         st.session_state.image = None
 
-    # Display all messages from the conversation so far
-    # Each message is either a ModelRequest or ModelResponse.
-    # We iterate over their parts to decide how to display them.
-    for msg in st.session_state.messages:
-        if isinstance(msg, ModelRequest) or isinstance(msg, ModelResponse):
-            for part in msg.parts:
-                display_message_part(part)
+    chat_col, image_col = st.columns(2)
+    with chat_col:
+        # Display all messages from the conversation so far
+        # Each message is either a ModelRequest or ModelResponse.
+        # We iterate over their parts to decide how to display them.
+        for msg in st.session_state.messages:
+            if isinstance(msg, ModelRequest) or isinstance(msg, ModelResponse) or isinstance(msg, ToolCallPart) or isinstance(msg, ToolReturnPart):
+                for part in msg.parts:
+                    display_message_part(part)
+
+    with image_col:
+        st.session_state.image = st.file_uploader("Upload an image", type=["png", "jpg", "jpeg"])
+        if st.session_state.image:
+            st.image(st.session_state.image)
+        else:
+            st.write("Upload an image to get started")
 
     # Chat input for the user
-    user_input = st.chat_input("What would you like to edit your image?")
-
-    if user_input:
-        if image is not None:
-            st.session_state.image = image
-
-        # We append a new request to the conversation explicitly
+    user_input = st.chat_input("What would you like to edit your image?", disabled=not st.session_state.image)
+    if user_input and st.session_state.image:
         st.session_state.messages.append(
             ModelRequest(parts=[UserPromptPart(content=user_input)])
         )
-        
-        # Display user prompt in the UI
-        with st.chat_message("user"):
-            if st.session_state.image:
-                st.image(st.session_state.image)
-            st.markdown(user_input)
 
         # Display the assistant's partial response while streaming
         with st.chat_message("assistant"):
             # Actually run the agent now, streaming the text
-            if st.session_state.image:
-                image_data = encode_image(st.session_state.image)
-                image_url = f"data:image/jpeg;base64,{image_data}"
-                await run_agent(user_input, image_url)
-            else:
-                await run_agent(user_input)
-
+            image_url = image_path_to_uri(st.session_state.image)
+            await run_agent(user_input, image_url)
 
 if __name__ == "__main__":
     asyncio.run(main())

app.py

@@ -1,13 +1,9 @@
 from openai import OpenAI
 import streamlit as st
-import base64
+from src.utils import image_path_to_uri
 
 st.title("ChatGPT-like clone")
 
-def encode_image(uploaded_file):
-    # Read the file directly from the UploadedFile object
-    return base64.b64encode(uploaded_file.read()).decode("utf-8")
-
 client = OpenAI(api_key=st.secrets["OPENAI_API_KEY"])
 image = st.file_uploader("Upload an image", type=["png", "jpg", "jpeg"])
 
@@ -33,8 +29,7 @@ if prompt := st.chat_input("What is up?"):
     if image is not None:
         st.session_state.image = image
     if st.session_state.image:
-        image_data = encode_image(st.session_state.image)
-        image_url = f"data:image/jpeg;base64,{image_data}"
+        image_url = image_path_to_uri(st.session_state.image)
         st.session_state.messages.append({"role": "user", "content": [
             {"type": "text", "text": prompt},
             {"type": "image_url", "image_url": {"url": image_url}}

gradio_app.py

@@ -0,0 +1,162 @@
+import gradio as gr
+from src.agents.mask_generation_agent import mask_generation_agent, ImageEditDeps
+import os
+from src.hopter.client import Hopter, Environment
+from src.services.generate_mask import GenerateMaskService
+from dotenv import load_dotenv
+from src.utils import image_path_to_uri
+from pydantic_ai.messages import (
+    ToolCallPart,
+    ToolReturnPart
+)
+from src.agents.mask_generation_agent import EditImageResult
+from pydantic_ai.agent import Agent 
+from pydantic_ai.models.openai import OpenAIModel
+
+model = OpenAIModel(
+    "gpt-4o",
+    api_key=os.environ.get("OPENAI_API_KEY"),
+)
+
+simple_agent = Agent(
+    model,
+    system_prompt="You are a helpful assistant that can answer questions and help with tasks.",
+    deps_type=ImageEditDeps
+)
+
+load_dotenv()
+
+def build_user_message(chat_input):
+    text = chat_input["text"]
+    images = chat_input["files"]
+    messages = [
+        {
+            "role": "user",
+            "content": text
+        }
+    ]
+    if images:
+        messages.extend([
+            {
+                "role": "user",
+                "content": {"path": image}
+            }
+            for image in images
+        ])
+    return messages
+
+async def stream_from_agent(chat_input, chatbot, past_messages):
+    chatbot.extend(build_user_message(chat_input))
+    # Clear the input immediately after submission
+    yield {"text": "", "files": []}, chatbot, gr.skip
+
+    # for agent
+    text = chat_input["text"]
+    images = [image_path_to_uri(image) for image in chat_input["files"]]
+    messages = [
+        {
+            "type": "text",
+            "text": text
+        },
+    ]
+    if images:
+        messages.extend([
+            {"type": "image_url", "image_url": {"url": image}}
+            for image in images
+        ])
+
+    hopter = Hopter(os.environ.get("HOPTER_API_KEY"), environment=Environment.STAGING)
+    mask_service = GenerateMaskService(hopter=hopter)
+    deps = ImageEditDeps(
+        edit_instruction=text,
+        image_url=images[0],
+        hopter_client=hopter,
+        mask_service=mask_service
+    )
+    async with mask_generation_agent.run_stream(
+        messages,
+        deps=deps
+    ) as result:
+        for message in result.new_messages():
+            for call in message.parts:
+                if isinstance(call, ToolCallPart):
+                    call_args = (
+                        call.args.args_json
+                        if hasattr(call.args, 'args_json')
+                        else call.args
+                    )
+                    metadata = {
+                        'title': f'🛠️ Using {call.tool_name}',
+                    }
+                    if call.tool_call_id is not None:
+                        metadata['id'] = call.tool_call_id
+
+                    gr_message = {
+                        'role': 'assistant',
+                        'content': 'Parameters: ' + call_args,
+                        'metadata': metadata,
+                    }
+                    chatbot.append(gr_message)
+                if isinstance(call, ToolReturnPart):
+                    for gr_message in chatbot:
+                        if (
+                            gr_message.get('metadata', {}).get('id', '')
+                            == call.tool_call_id
+                        ):
+                            if isinstance(call.content, EditImageResult):
+                                chatbot.append({
+                                    "role": "assistant",
+                                    "content": gr.Image(call.content.edited_image_url),
+                                    "files": [call.content.edited_image_url]
+                                })
+                            else:
+                                gr_message['content'] += (
+                                    f'\nOutput: {call.content}'
+                                )
+                yield gr.skip(), chatbot, gr.skip()
+
+        chatbot.append({'role': 'assistant', 'content': ''})
+        async for message in result.stream_text():
+            chatbot[-1]['content'] = message
+            yield gr.skip(), chatbot, gr.skip()
+        past_messages = result.all_messages()
+
+        yield gr.Textbox(interactive=True), gr.skip(), past_messages
+
+with gr.Blocks() as demo:
+    gr.HTML(
+        """
+<div style="display: flex; justify-content: center; align-items: center; gap: 2rem; padding: 1rem; width: 100%">
+    <img src="https://ai.pydantic.dev/img/logo-white.svg" style="max-width: 200px; height: auto">
+    <div>
+        <h1 style="margin: 0 0 1rem 0">Image Editing Assistant</h1>
+        <h3 style="margin: 0 0 0.5rem 0">
+            This assistant edits images according to your instructions.
+        </h3>
+    </div>
+</div>
+"""
+    )
+
+    past_messages = gr.State([])
+    chatbot = gr.Chatbot(
+        label='Image Editing Assistant',
+        type='messages',
+        avatar_images=(None, 'https://ai.pydantic.dev/img/logo-white.svg'),
+    )
+    with gr.Row():
+        chat_input = gr.MultimodalTextbox(
+            interactive=True,
+            file_count="multiple",
+            show_label=False,
+            placeholder='How would you like to edit this image?',
+            sources=["upload", "microphone"]
+        )
+    generation = chat_input.submit(
+        stream_from_agent,
+        inputs=[chat_input, chatbot, past_messages],
+        outputs=[chat_input, chatbot, past_messages],
+    )
+
+if __name__ == '__main__':
+    demo.launch()

poetry.lock

@@ -1,5 +1,16 @@
 # This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
 
+[[package]]
+name = "aiofiles"
+version = "23.2.1"
+description = "File support for asyncio."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "aiofiles-23.2.1-py3-none-any.whl", hash = "sha256:19297512c647d4b27a2cf7c34caa7e405c0d60b5560618a29a9fe027b18b0107"},
+    {file = "aiofiles-23.2.1.tar.gz", hash = "sha256:84ec2218d8419404abcb9f0c02df3f34c6e0a68ed41072acfb1cef5cbc29051a"},
+]
+
 [[package]]
 name = "altair"
 version = "5.5.0"
@@ -351,6 +362,26 @@ files = [
 [package.extras]
 tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipython", "littleutils", "pytest", "rich"]
 
+[[package]]
+name = "fastapi"
+version = "0.115.8"
+description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "fastapi-0.115.8-py3-none-any.whl", hash = "sha256:753a96dd7e036b34eeef8babdfcfe3f28ff79648f86551eb36bfc1b0bf4a8cbf"},
+    {file = "fastapi-0.115.8.tar.gz", hash = "sha256:0ce9111231720190473e222cdf0f07f7206ad7e53ea02beb1d2dc36e2f0741e9"},
+]
+
+[package.dependencies]
+pydantic = ">=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<2.0.0 || >2.0.0,<2.0.1 || >2.0.1,<2.1.0 || >2.1.0,<3.0.0"
+starlette = ">=0.40.0,<0.46.0"
+typing-extensions = ">=4.8.0"
+
+[package.extras]
+all = ["email-validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.5)", "httpx (>=0.23.0)", "itsdangerous (>=1.1.0)", "jinja2 (>=3.1.5)", "orjson (>=3.2.1)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.18)", "pyyaml (>=5.3.1)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0)", "uvicorn[standard] (>=0.12.0)"]
+standard = ["email-validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.5)", "httpx (>=0.23.0)", "jinja2 (>=3.1.5)", "python-multipart (>=0.0.18)", "uvicorn[standard] (>=0.12.0)"]
+
 [[package]]
 name = "fastavro"
 version = "1.10.0"
@@ -397,6 +428,17 @@ lz4 = ["lz4"]
 snappy = ["cramjam"]
 zstandard = ["zstandard"]
 
+[[package]]
+name = "ffmpy"
+version = "0.5.0"
+description = "A simple Python wrapper for FFmpeg"
+optional = false
+python-versions = "<4.0,>=3.8"
+files = [
+    {file = "ffmpy-0.5.0-py3-none-any.whl", hash = "sha256:df3799cf5816daa56d4959a023630ee53c6768b66009dae6d131519ba4b80233"},
+    {file = "ffmpy-0.5.0.tar.gz", hash = "sha256:277e131f246d18e9dcfee9bb514c50749031c43582ce5ef82c57b51e3d3955c3"},
+]
+
 [[package]]
 name = "filelock"
 version = "3.17.0"
@@ -525,6 +567,67 @@ protobuf = ">=3.20.2,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4
 [package.extras]
 grpc = ["grpcio (>=1.44.0,<2.0.0.dev0)"]
 
+[[package]]
+name = "gradio"
+version = "5.16.1"
+description = "Python library for easily interacting with trained machine learning models"
+optional = false
+python-versions = ">=3.10"
+files = [
+    {file = "gradio-5.16.1-py3-none-any.whl", hash = "sha256:a49f194ca314a09e4f7655a8fbcf8efae961a2bbf37877afc546fb506027f4dd"},
+]
+
+[package.dependencies]
+aiofiles = ">=22.0,<24.0"
+anyio = ">=3.0,<5.0"
+fastapi = ">=0.115.2,<1.0"
+ffmpy = "*"
+gradio-client = "1.7.0"
+httpx = ">=0.24.1"
+huggingface-hub = ">=0.28.1"
+jinja2 = "<4.0"
+markupsafe = ">=2.0,<3.0"
+numpy = ">=1.0,<3.0"
+orjson = ">=3.0,<4.0"
+packaging = "*"
+pandas = ">=1.0,<3.0"
+pillow = ">=8.0,<12.0"
+pydantic = ">=2.0"
+pydub = "*"
+python-multipart = ">=0.0.18"
+pyyaml = ">=5.0,<7.0"
+ruff = {version = ">=0.9.3", markers = "sys_platform != \"emscripten\""}
+safehttpx = ">=0.1.6,<0.2.0"
+semantic-version = ">=2.0,<3.0"
+starlette = {version = ">=0.40.0,<1.0", markers = "sys_platform != \"emscripten\""}
+tomlkit = ">=0.12.0,<0.14.0"
+typer = {version = ">=0.12,<1.0", markers = "sys_platform != \"emscripten\""}
+typing-extensions = ">=4.0,<5.0"
+urllib3 = {version = ">=2.0,<3.0", markers = "sys_platform == \"emscripten\""}
+uvicorn = {version = ">=0.14.0", markers = "sys_platform != \"emscripten\""}
+
+[package.extras]
+oauth = ["authlib", "itsdangerous"]
+
+[[package]]
+name = "gradio-client"
+version = "1.7.0"
+description = "Python library for easily interacting with trained machine learning models"
+optional = false
+python-versions = ">=3.10"
+files = [
+    {file = "gradio_client-1.7.0-py3-none-any.whl", hash = "sha256:b403570c67f121ebbbc19ac1f0afa2ab1bab085ce60d96eb190832fe871aa946"},
+    {file = "gradio_client-1.7.0.tar.gz", hash = "sha256:87f6ade197951f38bac0431b2a436a8ebb2f33b2ceba2ef8e1e5bef8d8b238e4"},
+]
+
+[package.dependencies]
+fsspec = "*"
+httpx = ">=0.24.1"
+huggingface-hub = ">=0.19.3"
+packaging = "*"
+typing-extensions = ">=4.0,<5.0"
+websockets = ">=10.0,<15.0"
+
 [[package]]
 name = "griffe"
 version = "1.5.7"
@@ -924,72 +1027,71 @@ testing = ["coverage", "pytest", "pytest-cov", "pytest-regressions"]
 
 [[package]]
 name = "markupsafe"
-version = "3.0.2"
+version = "2.1.5"
 description = "Safely add untrusted strings to HTML/XML markup."
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
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 name = "packaging"
 version = "24.2"
@@ -1762,6 +1952,17 @@ numpy = ">=1.16.4"
 carto = ["pydeck-carto"]
 jupyter = ["ipykernel (>=5.1.2)", "ipython (>=5.8.0)", "ipywidgets (>=7,<8)", "traitlets (>=4.3.2)"]
 
+[[package]]
+name = "pydub"
+version = "0.25.1"
+description = "Manipulate audio with an simple and easy high level interface"
+optional = false
+python-versions = "*"
+files = [
+    {file = "pydub-0.25.1-py2.py3-none-any.whl", hash = "sha256:65617e33033874b59d87db603aa1ed450633288aefead953b30bded59cb599a6"},
+    {file = "pydub-0.25.1.tar.gz", hash = "sha256:980a33ce9949cab2a569606b65674d748ecbca4f0796887fd6f46173a7b0d30f"},
+]
+
 [[package]]
 name = "pygments"
 version = "2.19.1"
@@ -1804,6 +2005,17 @@ files = [
 [package.extras]
 cli = ["click (>=5.0)"]
 
+[[package]]
+name = "python-multipart"
+version = "0.0.20"
+description = "A streaming multipart parser for Python"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "python_multipart-0.0.20-py3-none-any.whl", hash = "sha256:8a62d3a8335e06589fe01f2a3e178cdcc632f3fbe0d492ad9ee0ec35aab1f104"},
+    {file = "python_multipart-0.0.20.tar.gz", hash = "sha256:8dd0cab45b8e23064ae09147625994d090fa46f5b0d1e13af944c331a7fa9d13"},
+]
+
 [[package]]
 name = "pytz"
 version = "2025.1"
@@ -2059,6 +2271,76 @@ files = [
 [package.dependencies]
 pyasn1 = ">=0.1.3"
 
+[[package]]
+name = "ruff"
+version = "0.9.6"
+description = "An extremely fast Python linter and code formatter, written in Rust."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "ruff-0.9.6-py3-none-linux_armv6l.whl", hash = "sha256:2f218f356dd2d995839f1941322ff021c72a492c470f0b26a34f844c29cdf5ba"},
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+]
+
+[[package]]
+name = "safehttpx"
+version = "0.1.6"
+description = "A small Python library created to help developers protect their applications from Server Side Request Forgery (SSRF) attacks."
+optional = false
+python-versions = ">3.9"
+files = [
+    {file = "safehttpx-0.1.6-py3-none-any.whl", hash = "sha256:407cff0b410b071623087c63dd2080c3b44dc076888d8c5823c00d1e58cb381c"},
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+]
+
+[package.dependencies]
+httpx = "*"
+
+[package.extras]
+dev = ["pytest"]
+
+[[package]]
+name = "semantic-version"
+version = "2.10.0"
+description = "A library implementing the 'SemVer' scheme."
+optional = false
+python-versions = ">=2.7"
+files = [
+    {file = "semantic_version-2.10.0-py2.py3-none-any.whl", hash = "sha256:de78a3b8e0feda74cabc54aab2da702113e33ac9d9eb9d2389bcf1f58b7d9177"},
+    {file = "semantic_version-2.10.0.tar.gz", hash = "sha256:bdabb6d336998cbb378d4b9db3a4b56a1e3235701dc05ea2690d9a997ed5041c"},
+]
+
+[package.extras]
+dev = ["Django (>=1.11)", "check-manifest", "colorama (<=0.4.1)", "coverage", "flake8", "nose2", "readme-renderer (<25.0)", "tox", "wheel", "zest.releaser[recommended]"]
+doc = ["Sphinx", "sphinx-rtd-theme"]
+
+[[package]]
+name = "shellingham"
+version = "1.5.4"
+description = "Tool to Detect Surrounding Shell"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "shellingham-1.5.4-py2.py3-none-any.whl", hash = "sha256:7ecfff8f2fd72616f7481040475a65b2bf8af90a56c89140852d1120324e8686"},
+    {file = "shellingham-1.5.4.tar.gz", hash = "sha256:8dbca0739d487e5bd35ab3ca4b36e11c4078f3a234bfce294b0a0291363404de"},
+]
+
 [[package]]
 name = "six"
 version = "1.17.0"
@@ -2092,6 +2374,23 @@ files = [
     {file = "sniffio-1.3.1.tar.gz", hash = "sha256:f4324edc670a0f49750a81b895f35c3adb843cca46f0530f79fc1babb23789dc"},
 ]
 
+[[package]]
+name = "starlette"
+version = "0.45.3"
+description = "The little ASGI library that shines."
+optional = false
+python-versions = ">=3.9"
+files = [
+    {file = "starlette-0.45.3-py3-none-any.whl", hash = "sha256:dfb6d332576f136ec740296c7e8bb8c8a7125044e7c6da30744718880cdd059d"},
+    {file = "starlette-0.45.3.tar.gz", hash = "sha256:2cbcba2a75806f8a41c722141486f37c28e30a0921c5f6fe4346cb0dcee1302f"},
+]
+
+[package.dependencies]
+anyio = ">=3.6.2,<5"
+
+[package.extras]
+full = ["httpx (>=0.27.0,<0.29.0)", "itsdangerous", "jinja2", "python-multipart (>=0.0.18)", "pyyaml"]
+
 [[package]]
 name = "streamlit"
 version = "1.42.0"
@@ -2226,6 +2525,17 @@ files = [
     {file = "tomli-2.2.1.tar.gz", hash = "sha256:cd45e1dc79c835ce60f7404ec8119f2eb06d38b1deba146f07ced3bbc44505ff"},
 ]
 
+[[package]]
+name = "tomlkit"
+version = "0.13.2"
+description = "Style preserving TOML library"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "tomlkit-0.13.2-py3-none-any.whl", hash = "sha256:7a974427f6e119197f670fbbbeae7bef749a6c14e793db934baefc1b5f03efde"},
+    {file = "tomlkit-0.13.2.tar.gz", hash = "sha256:fff5fe59a87295b278abd31bec92c15d9bc4a06885ab12bcea52c71119392e79"},
+]
+
 [[package]]
 name = "tornado"
 version = "6.4.2"
@@ -2267,6 +2577,23 @@ notebook = ["ipywidgets (>=6)"]
 slack = ["slack-sdk"]
 telegram = ["requests"]
 
+[[package]]
+name = "typer"
+version = "0.15.1"
+description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "typer-0.15.1-py3-none-any.whl", hash = "sha256:7994fb7b8155b64d3402518560648446072864beefd44aa2dc36972a5972e847"},
+    {file = "typer-0.15.1.tar.gz", hash = "sha256:a0588c0a7fa68a1978a069818657778f86abe6ff5ea6abf472f940a08bfe4f0a"},
+]
+
+[package.dependencies]
+click = ">=8.0.0"
+rich = ">=10.11.0"
+shellingham = ">=1.3.0"
+typing-extensions = ">=3.7.4.3"
+
 [[package]]
 name = "types-requests"
 version = "2.32.0.20241016"
@@ -2335,6 +2662,25 @@ h2 = ["h2 (>=4,<5)"]
 socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
 zstd = ["zstandard (>=0.18.0)"]
 
+[[package]]
+name = "uvicorn"
+version = "0.34.0"
+description = "The lightning-fast ASGI server."
+optional = false
+python-versions = ">=3.9"
+files = [
+    {file = "uvicorn-0.34.0-py3-none-any.whl", hash = "sha256:023dc038422502fa28a09c7a30bf2b6991512da7dcdb8fd35fe57cfc154126f4"},
+    {file = "uvicorn-0.34.0.tar.gz", hash = "sha256:404051050cd7e905de2c9a7e61790943440b3416f49cb409f965d9dcd0fa73e9"},
+]
+
+[package.dependencies]
+click = ">=7.0"
+h11 = ">=0.8"
+typing-extensions = {version = ">=4.0", markers = "python_version < \"3.11\""}
+
+[package.extras]
+standard = ["colorama (>=0.4)", "httptools (>=0.6.3)", "python-dotenv (>=0.13)", "pyyaml (>=5.1)", "uvloop (>=0.14.0,!=0.15.0,!=0.15.1)", "watchfiles (>=0.13)", "websockets (>=10.4)"]
+
 [[package]]
 name = "watchdog"
 version = "6.0.0"
@@ -2377,6 +2723,84 @@ files = [
 [package.extras]
 watchmedo = ["PyYAML (>=3.10)"]
 
+[[package]]
+name = "websockets"
+version = "14.2"
+description = "An implementation of the WebSocket Protocol (RFC 6455 & 7692)"
+optional = false
+python-versions = ">=3.9"
+files = [
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+    {file = "websockets-14.2.tar.gz", hash = "sha256:5059ed9c54945efb321f097084b4c7e52c246f2c869815876a69d1efc4ad6eb5"},
+]
+
 [[package]]
 name = "wrapt"
 version = "1.17.2"
@@ -2487,4 +2911,4 @@ type = ["pytest-mypy"]
 [metadata]
 lock-version = "2.0"
 python-versions = "3.10"
-content-hash = "bafe1276871675a1d904b4309d57185b79d491027371bcd5afda1aa59551457e"
+content-hash = "83c3d0c47f98107284fb95080f8f9a6ba3c17d9a89f13ccbd66b73ca99863b4d"

pyproject.toml

@@ -13,6 +13,7 @@ watchdog = "^6.0.0"
 pydantic-ai = "^0.0.24"
 python-dotenv = "^1.0.1"
 logfire = "^3.5.3"
+gradio = "^5.16.1"
 
 
 [build-system]

src/agents/image-edit-agent.py

@@ -4,7 +4,7 @@ from pydantic_ai.models.openai import OpenAIModel
 from dotenv import load_dotenv
 import os
 import asyncio
-import base64
+from src.utils import image_path_to_base64
 from dataclasses import dataclass
 
 load_dotenv()
@@ -76,31 +76,29 @@ async def generate_mask(ctx: RunContext[ImageEditDeps], mask_subject: str) -> st
 
 async def main():
     image_file_path = "./assets/lakeview.jpg"
-    with open(image_file_path, "rb") as image_file:
-        image_bytes = image_file.read()
-        image_base64 = base64.b64encode(image_bytes).decode("utf-8")
-        image_url = f"data:image/jpeg;base64,{image_base64}"
+    image_base64 = image_path_to_base64(image_file_path)
+    image_url = f"data:image/jpeg;base64,{image_base64}"
 
-        prompt = "remove the light post"
-        messages = [
-            {
-                "type": "text",
-                "text": prompt
-            },
-            {
-                "type": "image_url",
-                "image_url": {
-                    "url": image_url
-                }
+    prompt = "remove the light post"
+    messages = [
+        {
+            "type": "text",
+            "text": prompt
+        },
+        {
+            "type": "image_url",
+            "image_url": {
+                "url": image_url
             }
-        ]
+        }
+    ]
 
-        deps = ImageEditDeps(
-            edit_instruction=prompt,
-            image_url=image_url
-        )
-        r = await mask_generation_agent.run(messages, deps=deps)
-        print(r.data)
+    deps = ImageEditDeps(
+        edit_instruction=prompt,
+        image_url=image_url
+    )
+    r = await mask_generation_agent.run(messages, deps=deps)
+    print(r.data)
 
 
 if __name__ == "__main__":

src/agents/mask_generation_agent.py

@@ -3,11 +3,12 @@ from pydantic_ai.models.openai import OpenAIModel
 from dotenv import load_dotenv
 import os
 import asyncio
-import base64
 from dataclasses import dataclass
 import logfire
 from src.services.generate_mask import GenerateMaskService
 from src.hopter.client import Hopter, Environment, MagicReplaceInput
+from src.services.image_uploader import ImageUploader
+from src.utils import image_path_to_uri
 
 load_dotenv()
 
@@ -38,7 +39,7 @@ class MaskGenerationResult:
 
 @dataclass
 class EditImageResult:
-    edited_image_base64: str
+    edited_image_url: str
 
 mask_generation_agent = Agent(
     model,
@@ -74,53 +75,52 @@ async def edit_object(ctx: RunContext[ImageEditDeps]) -> EditImageResult:
 
     # Generate mask
     print("Generating mask")
-    mask_instruction = await mask_service.get_mask_generation_instruction(edit_instruction, image_url)
-    mask = await mask_service.generate_mask(mask_instruction, image_url)
+    mask_instruction = mask_service.get_mask_generation_instruction(edit_instruction, image_url)
+    mask = mask_service.generate_mask(mask_instruction, image_url)
 
     # Magic replace
     input = MagicReplaceInput(image=image_url, mask=mask, prompt=mask_instruction.target_caption)
-    result = await hopter_client.magic_replace(input)
+    result = hopter_client.magic_replace(input)
     print("Exiting edit_object tool: ", result)
-    return EditImageResult(edited_image_base64=result.base64_image)
+    uploader = ImageUploader(os.environ.get("IMG_BB_API_KEY"))
+    uploaded_image = uploader.upload_url(result.base64_image)
+    return EditImageResult(edited_image_url=uploaded_image.data.url)
 
 async def main():
     image_file_path = "./assets/lakeview.jpg"
-    with open(image_file_path, "rb") as image_file:
-        image_bytes = image_file.read()
-        image_base64 = base64.b64encode(image_bytes).decode("utf-8")
-        image_url = f"data:image/jpeg;base64,{image_base64}"
-
-        prompt = "remove the light post"
-        messages = [
-            {
-                "type": "text",
-                "text": prompt
-            },
-            {
-                "type": "image_url",
-                "image_url": {
-                    "url": image_url
-                }
+    image_url = image_path_to_uri(image_file_path)
+
+    prompt = "remove the light post"
+    messages = [
+        {
+            "type": "text",
+            "text": prompt
+        },
+        {
+            "type": "image_url",
+            "image_url": {
+                "url": image_url
             }
-        ]
-
-        # Initialize services
-        hopter = Hopter(api_key=os.environ.get("HOPTER_API_KEY"), environment=Environment.STAGING)
-        mask_service = GenerateMaskService(hopter=hopter)
-
-        # Initialize dependencies
-        deps = ImageEditDeps(
-            edit_instruction=prompt,
-            image_url=image_url,
-            hopter_client=hopter,
-            mask_service=mask_service
-        )
-        async with mask_generation_agent.run_stream(
-            messages, 
-            deps=deps
-        ) as result:
-            async for message in result.stream():
-                print(message)
+        }
+    ]
+
+    # Initialize services
+    hopter = Hopter(api_key=os.environ.get("HOPTER_API_KEY"), environment=Environment.STAGING)
+    mask_service = GenerateMaskService(hopter=hopter)
+
+    # Initialize dependencies
+    deps = ImageEditDeps(
+        edit_instruction=prompt,
+        image_url=image_url,
+        hopter_client=hopter,
+        mask_service=mask_service
+    )
+    async with mask_generation_agent.run_stream(
+        messages, 
+        deps=deps
+    ) as result:
+        async for message in result.stream():
+            print(message)
 
 
 if __name__ == "__main__":

src/hopter/client.py

@@ -1,8 +1,7 @@
 import asyncio
 import httpx
 from enum import Enum
-from src.models.generate_mask_instruction import GenerateMaskInstruction
-import base64
+from src.utils import image_path_to_uri
 from dotenv import load_dotenv
 import os
 from pydantic import BaseModel, Field
@@ -48,12 +47,12 @@ class Hopter:
     ):
         self.api_key = api_key
         self.base_url = environment.base_url
-        self.client = httpx.AsyncClient()
+        self.client = httpx.Client()
 
-    async def generate_mask(self, input: RamGroundedSamInput) -> RamGroundedSamResult:
+    def generate_mask(self, input: RamGroundedSamInput) -> RamGroundedSamResult:
         print(f"Generating mask with input: {input.text_prompt}")
         try:
-            response = await self.client.post(
+            response = self.client.post(
                 f"{self.base_url}/api/v1/services/ram-grounded-sam-api/predictions",
                 headers={
                     "Authorization": f"Bearer {self.api_key}",
@@ -61,7 +60,8 @@ class Hopter:
                 },
                 json={
                     "input": input.model_dump()
-                }
+                },
+                timeout=None
             )
             response.raise_for_status()  # Raise an error for bad responses
             instance = response.json().get("output").get("instances")[0]
@@ -72,10 +72,10 @@ class Hopter:
         except Exception as exc:
             print(f"An unexpected error occurred: {exc}")
     
-    async def magic_replace(self, input: MagicReplaceInput) -> MagicReplaceResult:
+    def magic_replace(self, input: MagicReplaceInput) -> MagicReplaceResult:
         print(f"Magic replacing with input: {input.prompt}")
         try:
-            response = await self.client.post(
+            response = self.client.post(
                 f"{self.base_url}/api/v1/services/sdxl-magic-replace/predictions",
                 headers={
                     "Authorization": f"Bearer {self.api_key}",
@@ -83,9 +83,9 @@ class Hopter:
                 },
                 json={
                     "input": input.model_dump()
-                }
+                },
+                timeout=None
             )
-            print(response)
             response.raise_for_status()  # Raise an error for bad responses
             instance = response.json().get("output")
             print("Magic replaced.")
@@ -100,7 +100,7 @@ async def test_generate_mask(hopter: Hopter, image_url: str) -> str:
         text_prompt="pole",
         image_b64=image_url
     )
-    mask = await hopter.generate_mask(input)
+    mask = hopter.generate_mask(input)
     return mask.mask_b64
     
 async def test_magic_replace(hopter: Hopter, image_url: str, mask: str, prompt: str) -> str:
@@ -109,7 +109,7 @@ async def test_magic_replace(hopter: Hopter, image_url: str, mask: str, prompt:
         mask=mask,
         prompt=prompt
     )
-    result = await hopter.magic_replace(input)
+    result = hopter.magic_replace(input)
     return result.base64_image
 
 async def main():
@@ -118,13 +118,11 @@ async def main():
         environment=Environment.STAGING
     )
     image_file_path = "./assets/lakeview.jpg"
-    with open(image_file_path, "rb") as image_file:
-        image_bytes = image_file.read()
-        image_base64 = base64.b64encode(image_bytes).decode("utf-8")
-        image_url = f"data:image/jpeg;base64,{image_base64}"
+    image_url = image_path_to_uri(image_file_path)
+
+    mask = await test_generate_mask(hopter, image_url)
+    magic_replace_result = await test_magic_replace(hopter, image_url, mask, "remove the pole")
+    print(magic_replace_result)
 
-        mask = await test_generate_mask(hopter, image_url)
-        magic_replace_result = await test_magic_replace(hopter, image_url, mask, "remove the pole")
-        print(magic_replace_result)
 if __name__ == "__main__":
     asyncio.run(main())

src/services/generate_mask.py

@@ -46,7 +46,7 @@ class GenerateMaskService:
         self.openai_file_upload = OpenAIFileUpload()
         self.hopter = hopter
 
-    async def get_mask_generation_instruction(self, edit_instruction: str, image_url: str) -> GenerateMaskInstruction:
+    def get_mask_generation_instruction(self, edit_instruction: str, image_url: str) -> GenerateMaskInstruction:
         messages = [
             {
                 "role": "system",
@@ -77,7 +77,7 @@ class GenerateMaskService:
         instruction = response.choices[0].message.parsed
         return instruction
     
-    async def generate_mask(self, mask_instruction: GenerateMaskInstruction, image_url: str) -> str:
+    def generate_mask(self, mask_instruction: GenerateMaskInstruction, image_url: str) -> str:
         """
         Generate a mask for the image editing instruction.
 
@@ -91,7 +91,7 @@ class GenerateMaskService:
             text_prompt=mask_instruction.subject,
             image_b64=image_url
         )
-        generate_mask_result = await self.hopter.generate_mask(input)
+        generate_mask_result = self.hopter.generate_mask(input)
         return generate_mask_result.mask_b64
     
 async def main():
@@ -101,9 +101,9 @@ async def main():
     with open(image_file_path, "rb") as image_file:
         image_url = service.openai_file_upload.upload_image(image_file.read(), "vision")
 
-    instruction = await service.get_mask_generation_instruction(edit_instruction, image_url)
+    instruction = service.get_mask_generation_instruction(edit_instruction, image_url)
     print(instruction)
-    mask = await service.generate_mask(instruction, image_url)
+    mask = service.generate_mask(instruction, image_url)
     print(mask)
 
 if __name__ == "__main__":

src/utils.py

@@ -0,0 +1,11 @@
+import base64
+from fastapi import UploadFile
+def image_path_to_base64(image_path: str) -> str:
+    with open(image_path, "rb") as image_file:
+        return base64.b64encode(image_file.read()).decode("utf-8")
+
+def upload_file_to_base64(file: UploadFile) -> str:
+    return base64.b64encode(file.file.read()).decode("utf-8")
+
+def image_path_to_uri(image_path: str) -> str:
+    return f"data:image/jpeg;base64,{image_path_to_base64(image_path)}"