Upload app.py

app.py

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+import os
+import json
+import asyncio
+
+from websearch import QueryRequest, PerplexityClient, parse_perplexity_response
+
+# load .env file
+from dotenv import load_dotenv
+load_dotenv()
+
+# Initialize Perplexity client
+perplexity_client = PerplexityClient(
+    api_key=os.environ["PERPLEXITY_AUTH_TOKEN"]
+    )
+
+
+
+import gradio as gr
+import httpx
+import json
+
+async def query_api(query: str) -> tuple:
+    try:
+        # Fetch response from Perplexity
+        response = await perplexity_client.generate_response(query)
+        
+        # Parse the response
+        parsed_response = parse_perplexity_response(response)
+        
+        response_data = json.dumps(parsed_response)
+                
+        # Parse the accumulated response data as JSON
+        response_json = json.loads(response_data)
+        
+        # Extract content and citations from the response JSON
+        content = response_json.get("content", "")
+        citations = response_json.get("citations", [])
+        
+        # Beautify content using Markdown formatting
+        beautified_content = f"# Search Results\n\n{content}"
+        
+        # Beautify citations by adding Markdown links
+        beautified_citations = "# Citations/Sources\n\n"
+        for i, citation in enumerate(citations, start=1):
+            beautified_citations += f"{i}. [{citation}]({citation})\n"
+        
+        # Yield the beautified content and citations
+        yield beautified_content, beautified_citations
+    except httpx.TimeoutException:
+        yield "# Request Timeout\n\nRequest timed out. Please try again later.", ""
+    except httpx.HTTPStatusError as e:
+        yield f"# HTTP Error\n\nHTTP error occurred: {e}", ""
+    except Exception as e:
+        yield f"# Error\n\nAn error occurred: {e}", ""
+
+# Create Gradio interface
+with gr.Blocks(css=".gradio-container { background-color: #f5f5f5; padding: 20px; border-radius: 10px; }", theme=gr.themes.Citrus()) as demo:
+    gr.Markdown("# Web Search Application")
+    
+    with gr.Row():
+        with gr.Column(
+            render=True,
+            show_progress=True
+        ):
+            query = gr.Textbox(
+                label="Enter your query",
+                placeholder="Type your search query here...",
+                lines=2,
+                max_lines=4,
+                value="",
+                elem_id="query-input"
+            )
+            submit_button = gr.Button("Search")
+        
+        with gr.Column(
+            render=True,
+            show_progress=True
+        ):
+            output_content = gr.Markdown(
+                label="Response Content",
+                value="",
+                elem_id="response-content",
+                height="600px",
+                visible=True,
+                show_label=True
+                
+            )
+            output_citations = gr.Markdown(
+                label="Citations",
+                value="",
+                elem_id="response-citations",
+                height="200px",
+                visible=True,
+                show_label=True
+            )
+    
+    # Set up event listener
+    submit_button.click(query_api, inputs=query, outputs=[output_content, output_citations])
+    
+    gr.Markdown("Powered by FastAPI and Gradio")
+
+# Launch the Gradio application
+demo.launch()