Create app.py

app.py

@@ -0,0 +1,206 @@
+"""
+This application provides an interface for generating text using the CrewAI framework 
+for orchestrating agents, and models powered by Groq.
+The interface allows users to input a topic and receive a generated research article.
+"""
+
+import gradio as gr
+from crewai import Agent, Task, Crew, LLM, Process
+from crewai_tools import tool
+from langchain_community.tools import DuckDuckGoSearchRun
+
+# Use DuckDuckGo Search component
+@tool('DuckDuckGoSearch')
+def search(query: str) -> str:
+    """
+    Perform a web search using DuckDuckGo.
+
+    Args:
+        query (str): The search query to be executed.
+
+    Returns:
+        str: The search result from DuckDuckGo.
+
+    Raises:
+        ValueError: If the query is an empty string.
+        Exception: For any unexpected error during the search execution.
+    """
+    if not query.strip():
+        raise ValueError("Query must not be empty.")
+
+    try:
+        result = DuckDuckGoSearchRun().run(query)
+    except Exception as error:
+        raise Exception(f"Search execution error: {error}")
+    
+    return result
+
+def generate_response(topic: str, api_key: str) -> str:
+    """
+    Generates a research article based on the input topic using a Groq model.
+
+    Args:
+        topic (str): The text of the topic to be researched.
+        api_key (str): The API key to authenticate the request to Groq.
+
+    Returns:
+        str: The generated research article or an error message.
+    """
+    if not topic:
+        return "Error: No topic provided. Please input a valid topic."
+    
+    try:
+        # Configure the large language model LLM
+        llm = LLM(
+            model="groq/llama-3.1-8b-instant",
+            temperature=0.2,
+            top_p=0.5,
+            max_tokens=500,
+            presence_penalty=0.1,
+            frequency_penalty=0.1,
+            api_key=api_key
+        )
+    except Exception as error:
+        return f"Error configuring LLM: {str(error)}"
+    
+    # Create the 'Researcher' agent
+    researcher = Agent(
+        role="Researcher",
+        goal="Conduct foundational research on {topic}.",
+        backstory="A researcher who identifies trends and patterns.",
+        llm=llm,
+        max_iter=3,
+        max_rpm=15,
+        max_execution_time=30,
+        verbose=True,
+        allow_delegation=False
+    )
+    
+    # Create the 'Writer' agent
+    writer = Agent(
+        role="Writer",
+        goal="Write a clear and concise research article on {topic}.",
+        backstory="A writer who provides objective and impartial insights.",
+        llm=llm,
+        max_iter=3,
+        max_rpm=15,
+        max_execution_time=30,
+        verbose=True,
+        allow_delegation=False
+    )
+    
+    # Create the research task
+    research = Task(
+        description="Find current and relevant information on {topic}.",
+        agent=researcher,
+        expected_output="A bullet list outline for a concise research article.",
+        tools=[search]
+    )
+    
+    # Create the writing task
+    write = Task(
+        description="Write a clear and concise research article on {topic}.",
+        expected_output="An article with an introduction, main points, and a conclusion.",
+        agent=writer,
+        context=[research]
+    )
+    
+    # Define the crew of agents and tasks
+    crew = Crew(
+        agents=[researcher, writer],
+        tasks=[research, write],
+        process=Process.sequential,
+        verbose=True
+    )
+    
+    try:
+        # Inputs for the crew process
+        inputs = {"topic": topic}
+    
+        # Execute the crew kickoff process
+        crew_output = crew.kickoff(inputs=inputs)
+    
+        # Access the crew output
+        article = crew_output.raw if crew_output else "Error: No output from crew."
+    
+        # Return the crew output
+        return article
+    except Exception as error:
+        return f"Error during crew execution: {str(e)}"
+
+# Custom CSS for the Groq badge and color scheme
+custom_css = """
+.gradio-container {
+    background-color: #f5f5f5;
+}
+.gr-button-primary {
+    background-color: #f55036 !important;
+    border-color: #f55036 !important;
+}
+.gr-button-secondary {
+    color: #f55036 !important;
+    border-color: #f55036 !important;
+}
+#groq-badge {
+    position: fixed;
+    bottom: 20px;
+    right: 20px;
+    z-index: 1000;
+}
+"""
+
+# Define the Gradio interface
+with gr.Blocks(theme=gr.themes.Default()) as demo:
+    gr.Markdown("# CrewAI + Groq Research Assistant")
+    
+    # Textbox to input the Groq API key
+    api_key_input = gr.Textbox(
+        type="password",
+        label="Enter Groq API key",
+        placeholder="Enter your API key...",
+        lines=1
+    )
+    
+    # Textbox to input the research topic
+    with gr.Row():
+        topic_input = gr.Textbox(
+            label="Enter Topic",
+            placeholder="Type a topic here...",
+            lines=1
+        )
+    
+    # Markdown output to display the generated article
+    with gr.Row():
+        article_output = gr.Markdown(label="Generated Research Article")
+    
+    # Submit button
+    submit_button = gr.Button("Generate Article", variant="primary")
+    
+    # Add the Groq badge
+    gr.HTML(
+        """
+        <div id="groq-badge">
+            <div style="color: #f55036; font-weight: bold;">POWERED BY GROQ</div>
+        </div>
+        """
+    )
+    
+    # Connect button click to the generate_response function
+    submit_button.click(
+        generate_response,
+        inputs=[topic_input, api_key_input],
+        outputs=[article_output]
+    )
+    
+    # Markdown instructions for using the app
+    gr.Markdown(
+        """
+        ## How to use this app:
+        1. Enter your [Groq API Key](https://console.groq.com/keys) in the provided field.
+        2. Enter a topic.
+        3. Click the "Generate Article" button to generate a research article.
+        """
+    )
+
+# Launch the Gradio interface
+demo.launch()