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README.md

@@ -1,13 +1,14 @@
 ---
-title: AI Agent Language
-emoji: 👁
-colorFrom: blue
-colorTo: red
-sdk: streamlit
-sdk_version: 1.36.0
+title: Multi-Agent AI - Coding
+emoji: ✨
+colorFrom: yellow
+colorTo: gray
+sdk: gradio
+sdk_version: 4.36.1
 app_file: app.py
-pinned: false
-license: mit
+pinned: true
+license: apache-2.0
+short_description: Multi-Agent AI with Microsoft AutoGen
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+import datetime, os, threading
+
+from multi_agent import run_multi_agent
+
+lock = threading.Lock()
+
+LLM = "gpt-4o"
+
+def invoke(openai_api_key, task):
+    if not openai_api_key:
+        raise gr.Error("OpenAI API Key is required.")
+
+    if not task:
+        raise gr.Error("Task is required.")
+
+    raise gr.Error("Please clone space due to local code execution.")
+    
+    with lock:
+        os.environ["OPENAI_API_KEY"] = openai_api_key
+        result = run_multi_agent(LLM, task)
+        del os.environ["OPENAI_API_KEY"]
+        return result
+
+gr.close_all()
+
+demo = gr.Interface(fn = invoke, 
+                    inputs = [gr.Textbox(label = "OpenAI API Key", type = "password", lines = 1),
+                              gr.Textbox(label = "Task", value = f"Today is {datetime.date.today()}. {os.environ['INPUT']}")],
+                    outputs = [gr.Markdown(label = "Output", value = os.environ["OUTPUT"], line_breaks = True, sanitize_html = False)],
+                    title = "Multi-Agent AI: Coding",
+                    description = os.environ["DESCRIPTION"])
+
+demo.launch()

multi_agent.py

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+import base64, datetime, json, os
+
+from autogen import ConversableAgent, AssistantAgent
+from autogen.coding import LocalCommandLineCodeExecutor
+
+def read_file(file_path: str) -> str:
+    with open(file_path, "r", encoding="utf-8") as file:
+        return file.read()
+
+def read_image_file(image_file_path: str) -> str:
+    with open(image_file_path, "rb") as image_file:
+        image_data = image_file.read()
+        return base64.b64encode(image_data).decode("utf-8")
+
+def generate_markdown_image(image_data: str) -> str:
+    return f"![Image](data:image/png;base64,{image_data})"
+
+def format_as_markdown(code: str) -> str:
+    markdown_code = '```\n'
+    markdown_code += code
+    markdown_code += '\n```'
+    return markdown_code
+
+def get_latest_file(directory, file_extension):
+    latest_file = None
+    latest_date = datetime.datetime.min
+
+    for file in os.listdir(directory):
+        if file:
+            _, file_ext = os.path.splitext(file)
+
+            if file_ext == file_extension:
+                file_path = os.path.join(directory, file)
+                file_date = datetime.datetime.fromtimestamp(os.path.getmtime(file_path))
+
+                if file_date > latest_date:
+                    latest_date = file_date
+                    latest_file = file
+
+    return latest_file
+    
+def run_multi_agent(llm, task):
+    llm_config = {"model": llm}
+    
+    executor = LocalCommandLineCodeExecutor(
+        timeout=60,
+        work_dir="coding",
+    )
+
+    code_executor_agent = ConversableAgent(
+        name="code_executor_agent",
+        llm_config=False,
+        code_execution_config={"executor": executor},
+        human_input_mode="NEVER",
+        default_auto_reply="TERMINATE",
+    )
+
+    code_writer_agent = AssistantAgent(
+        name="code_writer_agent",
+        llm_config=llm_config,
+        code_execution_config=False,
+        human_input_mode="NEVER",
+    )
+    
+    chat_result = code_executor_agent.initiate_chat(
+        code_writer_agent,
+        message=task,
+        max_turns=10
+    )
+
+    chat = ""
+    first_message = True
+    
+    for message in chat_result.chat_history:
+        if not first_message:
+            chat += f"**{message['role'].replace('assistant', 'Code Executor').replace('user', 'Code Writer')}**\n{message['content']}\n\n"
+        first_message = False
+
+    file_name_png = get_latest_file("coding", ".png")
+    
+    image_data = read_image_file(f"/home/user/app/coding/{file_name_png}")
+    markdown_code_png = generate_markdown_image(image_data)
+
+    result = f"{markdown_code_png}\n\n{chat}"
+
+    print("===")
+    print(result)
+    print("===")
+    
+    return result

requirements.txt

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+chess==1.10.0
+markdown==3.6
+pyautogen==0.2.25