Create app.py

app.py

@@ -0,0 +1,302 @@
+import gradio as gr
+from crewai import Agent, Task, Crew
+from crewai_tools import ScrapeWebsiteTool
+import os
+import queue
+import threading
+import asyncio
+from typing import List, Dict, Generator
+
+class SupportMessageQueue:
+    def __init__(self):
+        self.message_queue = queue.Queue()
+        self.last_agent = None
+
+    def add_message(self, message: Dict):
+        print(f"Adding message to queue: {message}")
+        self.message_queue.put(message)
+
+    def get_messages(self) -> List[Dict]:
+        messages = []
+        while not self.message_queue.empty():
+            messages.append(self.message_queue.get())
+        return messages
+
+class SupportCrew:
+    def __init__(self, api_key: str = None):
+        self.api_key = api_key
+        self.message_queue = SupportMessageQueue()
+        self.support_agent = None
+        self.qa_agent = None
+        self.current_agent = None
+        self.scrape_tool = None
+
+    def initialize_agents(self, website_url: str):
+        if not self.api_key:
+            raise ValueError("OpenAI API key is required")
+
+        os.environ["OPENAI_API_KEY"] = self.api_key
+        self.scrape_tool = ScrapeWebsiteTool(website_url=website_url)
+
+        self.support_agent = Agent(
+            role="Senior Support Representative",
+            goal="Be the most friendly and helpful support representative in your team",
+            backstory=(
+                "You work at crewAI and are now working on providing support to customers. "
+                "You need to make sure that you provide the best support! "
+                "Make sure to provide full complete answers, and make no assumptions."
+            ),
+            allow_delegation=False,
+            verbose=True
+        )
+
+        self.qa_agent = Agent(
+            role="Support Quality Assurance Specialist",
+            goal="Get recognition for providing the best support quality assurance in your team",
+            backstory=(
+                "You work at crewAI and are now working with your team on customer requests "
+                "ensuring that the support representative is providing the best support possible. "
+                "You need to make sure that the support representative is providing full "
+                "complete answers, and make no assumptions."
+            ),
+            verbose=True
+        )
+
+    def create_tasks(self, inquiry: str) -> List[Task]:
+        inquiry_resolution = Task(
+            description=(
+                f"A customer just reached out with a super important ask:\n{inquiry}\n\n"
+                "Make sure to use everything you know to provide the best support possible. "
+                "You must strive to provide a complete and accurate response to the customer's inquiry."
+            ),
+            expected_output=(
+                "A detailed, informative response to the customer's inquiry that addresses "
+                "all aspects of their question.\n"
+                "The response should include references to everything you used to find the answer, "
+                "including external data or solutions. Ensure the answer is complete, "
+                "leaving no questions unanswered, and maintain a helpful and friendly tone throughout."
+            ),
+            tools=[self.scrape_tool],
+            agent=self.support_agent
+        )
+
+        quality_assurance_review = Task(
+            description=(
+                "Review the response drafted by the Senior Support Representative for the customer's inquiry. "
+                "Ensure that the answer is comprehensive, accurate, and adheres to the "
+                "high-quality standards expected for customer support.\n"
+                "Verify that all parts of the customer's inquiry have been addressed "
+                "thoroughly, with a helpful and friendly tone.\n"
+                "Check for references and sources used to find the information, "
+                "ensuring the response is well-supported and leaves no questions unanswered."
+            ),
+            expected_output=(
+                "A final, detailed, and informative response ready to be sent to the customer.\n"
+                "This response should fully address the customer's inquiry, incorporating all "
+                "relevant feedback and improvements.\n"
+                "Don't be too formal, maintain a professional and friendly tone throughout."
+            ),
+            agent=self.qa_agent
+        )
+
+        return [inquiry_resolution, quality_assurance_review]
+
+    async def process_support(self, inquiry: str, website_url: str) -> Generator[List[Dict], None, None]:
+        def add_agent_messages(agent_name: str, tasks: str, emoji: str = "🤖"):
+            self.message_queue.add_message({
+                "role": "assistant",
+                "content": agent_name,
+                "metadata": {"title": f"{emoji} {agent_name}"}
+            })
+            
+            self.message_queue.add_message({
+                "role": "assistant",
+                "content": tasks,
+                "metadata": {"title": f"📋 Task for {agent_name}"}
+            })
+
+        def setup_next_agent(current_agent: str) -> None:
+            if current_agent == "Senior Support Representative":
+                self.current_agent = "Support Quality Assurance Specialist"
+                add_agent_messages(
+                    "Support Quality Assurance Specialist",
+                    "Review and improve the support representative's response"
+                )
+
+        def task_callback(task_output) -> None:
+            print(f"Task callback received: {task_output}")
+            
+            raw_output = task_output.raw
+            if "## Final Answer:" in raw_output:
+                content = raw_output.split("## Final Answer:")[1].strip()
+            else:
+                content = raw_output.strip()
+            
+            if self.current_agent == "Support Quality Assurance Specialist":
+                self.message_queue.add_message({
+                    "role": "assistant",
+                    "content": "Final response is ready!",
+                    "metadata": {"title": "✅ Final Response"}
+                })
+                
+                formatted_content = content
+                formatted_content = formatted_content.replace("\n#", "\n\n#")
+                formatted_content = formatted_content.replace("\n-", "\n\n-")
+                formatted_content = formatted_content.replace("\n*", "\n\n*")
+                formatted_content = formatted_content.replace("\n1.", "\n\n1.")
+                formatted_content = formatted_content.replace("\n\n\n", "\n\n")
+                
+                self.message_queue.add_message({
+                    "role": "assistant",
+                    "content": formatted_content
+                })
+            else:
+                self.message_queue.add_message({
+                    "role": "assistant",
+                    "content": content,
+                    "metadata": {"title": f"✨ Output from {self.current_agent}"}
+                })
+                setup_next_agent(self.current_agent)
+
+        try:
+            self.initialize_agents(website_url)
+            self.current_agent = "Senior Support Representative"
+
+            yield [{
+                "role": "assistant",
+                "content": "Starting to process your inquiry...",
+                "metadata": {"title": "🚀 Process Started"}
+            }]
+
+            add_agent_messages(
+                "Senior Support Representative",
+                "Analyze customer inquiry and provide comprehensive support"
+            )
+
+            crew = Crew(
+                agents=[self.support_agent, self.qa_agent],
+                tasks=self.create_tasks(inquiry),
+                verbose=True,
+                task_callback=task_callback
+            )
+
+            def run_crew():
+                try:
+                    crew.kickoff()
+                except Exception as e:
+                    print(f"Error in crew execution: {str(e)}")
+                    self.message_queue.add_message({
+                        "role": "assistant",
+                        "content": f"An error occurred: {str(e)}",
+                        "metadata": {"title": "❌ Error"}
+                    })
+
+            thread = threading.Thread(target=run_crew)
+            thread.start()
+
+            while thread.is_alive() or not self.message_queue.message_queue.empty():
+                messages = self.message_queue.get_messages()
+                if messages:
+                    print(f"Yielding messages: {messages}")
+                    yield messages
+                await asyncio.sleep(0.1)
+
+        except Exception as e:
+            print(f"Error in process_support: {str(e)}")
+            yield [{
+                "role": "assistant",
+                "content": f"An error occurred: {str(e)}",
+                "metadata": {"title": "❌ Error"}
+            }]
+
+def create_demo():
+    support_crew = None
+
+    with gr.Blocks(theme=gr.themes.Soft()) as demo:
+        gr.Markdown("# 🎯 AI Customer Support Crew")
+        
+        openai_api_key = gr.Textbox(
+            label='OpenAI API Key',
+            type='password',
+            placeholder='Enter your OpenAI API key...',
+            interactive=True
+        )
+
+        chatbot = gr.Chatbot(
+            label="Support Process",
+            height=700,
+            type="messages",
+            show_label=True,
+            visible=False,
+            avatar_images=(None, "https://avatars.githubusercontent.com/u/170677839?v=4"),
+            render_markdown=True
+        )
+
+        with gr.Row(equal_height=True):
+            inquiry = gr.Textbox(
+                label="Your Inquiry",
+                placeholder="Enter your question...",
+                scale=4,
+                visible=False
+            )
+            website_url = gr.Textbox(
+                label="Documentation URL",
+                placeholder="Enter documentation URL to search...",
+                scale=4,
+                visible=False
+            )
+            btn = gr.Button("Get Support", variant="primary", scale=1, visible=False)
+
+        async def process_input(inquiry_text, website_url_text, history, api_key):
+            nonlocal support_crew
+            if not api_key:
+                history = history or []
+                history.append({
+                    "role": "assistant",
+                    "content": "Please provide an OpenAI API key.",
+                    "metadata": {"title": "❌ Error"}
+                })
+                yield history
+                return
+
+            if support_crew is None:
+                support_crew = SupportCrew(api_key=api_key)
+
+            history = history or []
+            history.append({
+                "role": "user", 
+                "content": f"Question: {inquiry_text}\nDocumentation: {website_url_text}"
+            })
+            yield history
+
+            try:
+                async for messages in support_crew.process_support(inquiry_text, website_url_text):
+                    history.extend(messages)
+                    yield history
+            except Exception as e:
+                history.append({
+                    "role": "assistant",
+                    "content": f"An error occurred: {str(e)}",
+                    "metadata": {"title": "❌ Error"}
+                })
+                yield history
+
+        def show_interface():
+            return {
+                openai_api_key: gr.Textbox(visible=False),
+                chatbot: gr.Chatbot(visible=True),
+                inquiry: gr.Textbox(visible=True),
+                website_url: gr.Textbox(visible=True),
+                btn: gr.Button(visible=True)
+            }
+
+        openai_api_key.submit(show_interface, None, [openai_api_key, chatbot, inquiry, website_url, btn])
+        btn.click(process_input, [inquiry, website_url, chatbot, openai_api_key], [chatbot])
+        inquiry.submit(process_input, [inquiry, website_url, chatbot, openai_api_key], [chatbot])
+
+    return demo
+
+if __name__ == "__main__":
+    demo = create_demo()
+    demo.queue()
+    demo.launch(debug=True)