update app.py

app.py

@@ -1,8 +1,94 @@
 import os
 import json
+from typing import Optional
+import gradio as gr
+from gradio import Interface, Blocks
 import networkx as nx
+from networkx import erdos_renyi_graph
+import community as community_louvain
 import pyvis
-from smolagents import CodeAgent, HfApiModel, tool, GradioUI
+from pyvis.network import Network
+from smolagents import CodeAgent, HfApiModel, tool
+from opentelemetry import trace
+from opentelemetry.sdk.trace import TracerProvider
+from opentelemetry.sdk.trace.export import BatchSpanProcessor
+from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
+from openinference.instrumentation.smolagents import SmolagentsInstrumentor
+
+# set HF_TOKEN environment variable
+os.environ["HF_TOKEN"] = os.getenv("HF_TOKEN")
+
+# Set up telemetry
+PHOENIX_API_KEY = os.getenv("PHOENIX_API_KEY")
+api_key = f"api_key={PHOENIX_API_KEY}"
+os.environ["OTEL_EXPORTER_OTLP_HEADERS"] = api_key
+os.environ["PHOENIX_CLIENT_HEADERS"] = api_key
+os.environ["PHOENIX_COLLECTOR_ENDPOINT"] = "https://app.phoenix.arize.com"
+
+# Updated endpoint from local to cloud
+endpoint = "https://app.phoenix.arize.com/v1/traces"
+trace_provider = TracerProvider()
+trace_provider.add_span_processor(BatchSpanProcessor(OTLPSpanExporter(endpoint)))
+SmolagentsInstrumentor().instrument(tracer_provider=trace_provider)
+
+# Define examples
+examples = [
+    ["Highlight the Medici family's central role in the network using all three centrality metrics."],
+    ["Focus on the Strozzi family's role in the network using betweenness centrality."],
+    ["Compare the Albizzi and Medici families' positions in the network using degree and closeness centrality."],
+    ["Visualize the overall network structure and the relative positions of the families."],
+    ["Explore the roles of other families with significant centrality values."]
+]
+
+from smolagents import GradioUI
+import gradio as gr
+
+from smolagents import GradioUI
+import gradio as gr
+
+class GradioUIWithExamples(GradioUI):
+    def __init__(self, agent, examples=None, **kwargs):
+        super().__init__(agent, **kwargs)
+        self.examples = examples
+
+    def build_interface(self):
+        with gr.Blocks() as demo:
+            gr.Markdown("## Florentine Families Network Analysis")
+
+            # Main Input/Output
+            input_box = gr.Textbox(
+                label="Your Question",
+                placeholder="Type your question about the Florentine Families graph...",
+            )
+            output_box = gr.Textbox(
+                label="Agent's Response",
+                placeholder="Response will appear here...",
+                interactive=False,
+            )
+            submit_button = gr.Button("Submit")
+
+            # Link submit button to agent logic
+            submit_button.click(
+                self.agent.run,
+                inputs=input_box,
+                outputs=output_box,
+            )
+
+            # Add Examples
+            if self.examples:
+                gr.Markdown("### Examples")
+                for example in self.examples:
+                    gr.Button(example[0]).click(
+                        lambda x=example[0]: x,  # Populate input box
+                        inputs=[],
+                        outputs=input_box,
+                    )
+        return demo
+
+    def launch(self):
+        # Use the custom-built interface instead of the base class's logic
+        demo = self.build_interface()
+        demo.launch()
 
 # Define a tool for analyzing the Florentine Families graph
 @tool
@@ -32,14 +118,69 @@ def analyze_florentine_graph(metric: str) -> str:
         analysis += f"- {node}: {value:.3f}\n"
     return analysis
 
+from smolagents import tool
+
+@tool
+def save_html_to_file(html_content: str, file_path: str) -> str:
+    """
+    Saves the provided HTML content to a file.
+
+    Args:
+        html_content: The HTML content to save.
+        file_path: The path where the HTML file will be saved.
+
+    Returns:
+        A confirmation message upon successful saving.
+    """
+    with open(file_path, 'w', encoding='utf-8') as file:
+        file.write(html_content)
+    return f"HTML content successfully saved to {file_path}"
+
+from smolagents import tool
+
+@tool
+def read_html_from_file(file_path: str) -> str:
+    """
+    Reads HTML content from a file.
+
+    Args:
+        file_path: The path of the HTML file to read.
+
+    Returns:
+        The HTML content as a string.
+    """
+    with open(file_path, 'r', encoding='utf-8') as file:
+        html_content = file.read()
+    return html_content
+
+from smolagents import tool
+import networkx as nx
+import json
+
+@tool
+def export_graph_to_json(graph_data: dict) -> str:
+    """
+    Exports a NetworkX graph represented as a dictionary to JSON format.
+
+    Args:
+        graph_data: The graph data in node-link format.
+
+    Returns:
+        str: The JSON representation of the graph.
+    """
+    graph = nx.node_link_graph(graph_data)
+    json_output = json.dumps(nx.node_link_data(graph), indent=4)
+    return json_output
+
 # Initialize the agent with proper configuration
 model = HfApiModel()
 agent = CodeAgent(
-    tools=[analyze_florentine_graph],
+    tools=[analyze_florentine_graph, save_html_to_file, read_html_from_file, export_graph_to_json],
     model=model,
-    additional_authorized_imports=["networkx","pyvis","open","json"],
+    additional_authorized_imports=["gradio","networkx","community_louvain","pyvis","matplotlib","json"],
     add_base_tools=True
 )
 
-# Launch the Gradio interface using smolagents' built-in UI component
-GradioUI(agent).launch()
+# Use the fixed GradioUIWithExamples
+interface = GradioUIWithExamples(agent, examples=examples)
+interface.launch()