Create app.py

app.py

@@ -0,0 +1,180 @@
+import os
+import requests
+from markdownify import markdownify as md
+from requests.exceptions import RequestException
+import re
+from transformers.agents import (
+    ReactCodeAgent,
+    ReactJsonAgent,
+    HfApiEngine,
+    ManagedAgent,
+    stream_to_gradio,
+    Tool,
+)
+from transformers.agents.search import DuckDuckGoSearchTool
+import gradio as gr
+import datetime
+from huggingface_hub import login
+
+# Log in to Hugging Face
+hf_token = os.getenv("hf_token")
+login(hf_token)
+model = "meta-llama/Meta-Llama-3.1-70B-Instruct"
+
+# Define the VisitWebpageTool
+class VisitWebpageTool(Tool):
+    name = "visit_webpage"
+    description = "Visits a webpage at the given url and returns its content as a markdown string."
+    inputs = {
+        "url": {
+            "type": "text",
+            "description": "The url of the webpage to visit.",
+        }
+    }
+    output_type = "text"
+
+    def forward(self, url: str) -> str:
+        try:
+            response = requests.get(url)
+            response.raise_for_status()
+            markdown_content = md(response.text).strip()
+            markdown_content = re.sub(r"\n{3,}", "\n\n", markdown_content)
+            return markdown_content
+        except RequestException as e:
+            return f"Error fetching the webpage: {str(e)}"
+        except Exception as e:
+            return f"An unexpected error occurred: {str(e)}"
+
+visit_page_tool = VisitWebpageTool()
+
+# Set up the multi-agent system
+llm_engine = HfApiEngine(model)
+
+# Agent to clarify specifics
+clarify_agent = ReactJsonAgent(
+    tools=[],
+    llm_engine=llm_engine,
+    max_iterations=20,
+)
+
+# Agent to plan the project
+plan_agent = ReactJsonAgent(
+    tools=[],
+    llm_engine=llm_engine,
+    max_iterations=20,
+)
+
+# Agent to break the plan into tasks
+task_agent = ReactJsonAgent(
+    tools=[],
+    llm_engine=llm_engine,
+    max_iterations=20,
+)
+
+# Agent to execute tasks
+execute_agent = ReactCodeAgent(
+    tools=[],
+    llm_engine=llm_engine,
+    max_iterations=20,
+    additional_authorized_imports=['requests', 'bs4']
+)
+
+# Agent to review code
+review_agent = ReactCodeAgent(
+    tools=[],
+    llm_engine=llm_engine,
+    max_iterations=20,
+    additional_authorized_imports=['requests', 'bs4', 'transformers']
+    )
+
+# Agent to revise code
+revise_agent = ReactCodeAgent(
+    tools=[],
+    llm_engine=llm_engine,
+    max_iterations=20,
+)
+
+# Managed agents
+managed_clarify_agent = ManagedAgent(
+    agent=clarify_agent,
+    name="clarify_agent",
+    description="Clarifies project specifics if not given in the project description.",
+)
+
+managed_plan_agent = ManagedAgent(
+    agent=plan_agent,
+    name="plan_agent",
+    description="Plans the project.",
+)
+
+managed_task_agent = ManagedAgent(
+    agent=task_agent,
+    name="task_agent",
+    description="Breaks the plan into tasks.",
+)
+
+managed_execute_agent = ManagedAgent(
+    agent=execute_agent,
+    name="execute_agent",
+    description="Executes the tasks.",
+)
+
+managed_review_agent = ManagedAgent(
+    agent=review_agent,
+    name="review_agent",
+    description="Reviews the code written in completion of tasks.",
+)
+
+managed_revise_agent = ManagedAgent(
+    agent=revise_agent,
+    name="revise_agent",
+    description="Revises the code if needed.",
+)
+
+# Manager agent
+manager_agent = ReactCodeAgent(
+    tools=[],
+    llm_engine=llm_engine,
+    managed_agents=[
+        managed_clarify_agent,
+        managed_plan_agent,
+        managed_task_agent,
+        managed_execute_agent,
+        managed_review_agent,
+        managed_revise_agent,
+    ],
+    additional_authorized_imports=["time", "datetime"],
+)
+
+# Implement the Gradio interface
+def interact_with_agent(task):
+    messages = []
+    messages.append(gr.ChatMessage(role="user", content=task))
+    yield messages
+    try:
+        for msg in stream_to_gradio(manager_agent, task):
+            messages.append(msg)
+            yield messages + [
+                gr.ChatMessage(role="assistant", content="⏳ Task not finished yet!")
+            ]
+    except Exception as e:
+        messages.append(gr.ChatMessage(role="assistant", content=f"Error: {str(e)}"))
+    yield messages
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Multi-agent Software Team")
+    gr.Markdown("Gradio space based on the multiagent_web_assistant cookbook https://huggingface.co/learn/cookbook/multiagent_web_assistant")
+    text_input = gr.Textbox(lines=1, label="Project Description", value="Create a simple web app that allows users to upload images and apply filters.")
+    submit = gr.Button("Start Project Development")
+    chatbot = gr.Chatbot(
+        label="Agent",
+        type="messages",
+        avatar_images=(
+            None,
+            "https://em-content.zobj.net/source/twitter/53/robot-face_1f916.png",
+        ),
+    )
+    submit.click(interact_with_agent, [text_input], [chatbot])
+
+if __name__ == "__main__":
+    demo.launch(share=True)