FP / app.py
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Update app.py
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import os
import gradio as gr
from groq import Groq
from datetime import datetime
import time
class RealTimeFactChecker:
def __init__(self):
self.client = None
self.model_options = ["compound-beta", "compound-beta-mini"]
def initialize_client(self, api_key):
"""Initialize Groq client with API key"""
try:
self.client = Groq(api_key=api_key)
return True, "βœ… API Key validated successfully!"
except Exception as e:
return False, f"❌ Error initializing client: {str(e)}"
def get_system_prompt(self):
"""Get the system prompt for consistent behavior"""
return """You are a Real-time Fact Checker and News Agent. Your primary role is to provide accurate, up-to-date information by leveraging web search when needed.
CORE RESPONSIBILITIES:
1. **Fact Verification**: Always verify claims with current, reliable sources
2. **Real-time Information**: Use web search for any information that changes frequently (news, stocks, weather, current events)
3. **Source Transparency**: When using web search, mention the sources or indicate that you've searched for current information
4. **Accuracy First**: If information is uncertain or conflicting, acknowledge this clearly
RESPONSE GUIDELINES:
- **Structure**: Start with a clear, direct answer, then provide supporting details
- **Recency**: Always prioritize the most recent, reliable information
- **Clarity**: Use clear, professional language while remaining accessible
- **Completeness**: Provide comprehensive answers but stay focused on the query
- **Source Awareness**: When you've searched for information, briefly indicate this (e.g., "Based on current reports..." or "Recent data shows...")
WHEN TO SEARCH:
- Breaking news or current events
- Stock prices, market data, or financial information
- Weather conditions or forecasts
- Recent scientific discoveries or research
- Current political developments
- Real-time statistics or data
- Verification of recent claims or rumors
RESPONSE FORMAT:
- Lead with key facts
- Include relevant context
- Mention timeframe when relevant (e.g., "as of today", "this week")
- If multiple sources conflict, acknowledge this
- End with a clear summary for complex topics
Remember: Your goal is to be the most reliable, up-to-date source of information possible."""
def query_compound_model(self, query, model, temperature=0.7):
"""Query the compound model and return response with tool execution info"""
if not self.client:
return "❌ Please set a valid API key first.", None, None
try:
start_time = time.time()
system_prompt = self.get_system_prompt()
chat_completion = self.client.chat.completions.create(
messages=[
{
"role": "system",
"content": system_prompt
},
{
"role": "user",
"content": query,
}
],
model=model,
temperature=temperature,
max_tokens=1500
)
end_time = time.time()
response_time = round(end_time - start_time, 2)
response_content = chat_completion.choices[0].message.content
executed_tools = getattr(chat_completion.choices[0].message, 'executed_tools', None)
tool_info = self.format_tool_info(executed_tools)
return response_content, tool_info, response_time
except Exception as e:
return f"❌ Error querying model: {str(e)}", None, None
def format_tool_info(self, executed_tools):
"""Format executed tools information for display"""
if not executed_tools:
return "πŸ” Tools Used: None (Used existing knowledge)"
tool_info = "πŸ” Tools Used:\n"
for i, tool in enumerate(executed_tools, 1):
try:
if hasattr(tool, 'name'):
tool_name = tool.name
elif hasattr(tool, 'tool_name'):
tool_name = tool.tool_name
elif isinstance(tool, dict):
tool_name = tool.get('name', 'Unknown')
else:
tool_name = str(tool)
tool_info += f"{i}. {tool_name}\n"
if hasattr(tool, 'parameters'):
params = tool.parameters
if isinstance(params, dict):
for key, value in params.items():
tool_info += f" - {key}: {value}\n"
elif hasattr(tool, 'input'):
tool_info += f" - Input: {tool.input}\n"
except Exception as e:
tool_info += f"{i}. Tool {i} (Error parsing details)\n"
return tool_info
def create_interface():
fact_checker = RealTimeFactChecker()
def validate_api_key(api_key):
if not api_key or api_key.strip() == "":
return "❌ Please enter a valid API key", False
success, message = fact_checker.initialize_client(api_key.strip())
return message, success
def process_query(query, model, temperature, api_key):
if not api_key or api_key.strip() == "":
return "❌ Please set your API key first", "", ""
if not query or query.strip() == "":
return "❌ Please enter a query", "", ""
if not fact_checker.client:
success, message = fact_checker.initialize_client(api_key.strip())
if not success:
return message, "", ""
response, tool_info, response_time = fact_checker.query_compound_model(
query.strip(), model, temperature
)
timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
formatted_response = f"**Query:** {query}\n\n**Response:**\n{response}\n\n---\n*Generated at {timestamp} in {response_time}s*"
return formatted_response, tool_info or "", f"Response time: {response_time}s"
with gr.Blocks(title="Real-time Fact Checker & News Agent", theme=gr.themes.Ocean()) as demo:
gr.Markdown("# Real-time Fact Checker & News Agent")
gr.Markdown("Powered by Groq's Compound Models with Built-in Web Search")
with gr.Row():
with gr.Column():
api_key_input = gr.Textbox(
label="Groq API Key",
placeholder="Enter your Groq API key here...",
type="password",
info="Get your free API key from https://console.groq.com/"
)
api_status = gr.Textbox(
label="Status",
value="Please enter your API key",
interactive=False
)
validate_btn = gr.Button("Validate API Key")
query_input = gr.Textbox(
label="Query",
placeholder="e.g., What are the latest AI developments today?",
lines=4
)
with gr.Row():
model_choice = gr.Dropdown(
choices=fact_checker.model_options,
value="compound-beta",
label="Model",
info="compound-beta: More capable | compound-beta-mini: Faster"
)
temperature = gr.Slider(
minimum=0.0,
maximum=1.0,
value=0.7,
step=0.1,
label="Temperature",
info="Higher = more creative, Lower = more focused"
)
with gr.Row():
submit_btn = gr.Button("Get Real-time Information")
clear_btn = gr.Button("Clear")
with gr.Column():
response_output = gr.Markdown(
label="Response",
value="*Your response will appear here...*"
)
tool_info_output = gr.Markdown(
label="Tool Execution Info",
value="*Tool execution details will appear here...*"
)
performance_output = gr.Textbox(
label="Performance",
value="",
interactive=False
)
validate_btn.click(
fn=validate_api_key,
inputs=[api_key_input],
outputs=[api_status, gr.State()]
)
submit_btn.click(
fn=process_query,
inputs=[query_input, model_choice, temperature, api_key_input],
outputs=[response_output, tool_info_output, performance_output]
)
clear_btn.click(
fn=lambda: ("", "*Your response will appear here...*", "*Tool execution details will appear here...*", ""),
outputs=[query_input, response_output, tool_info_output, performance_output]
)
gr.Markdown("""
### Useful Links
- [Groq Console](https://console.groq.com/) - Get your free API key
- [Groq Documentation](https://console.groq.com/docs/quickstart) - Learn more about Groq models
- [Compound Models Info](https://console.groq.com/docs/models) - Details about compound models
### Tips
- The compound models automatically use web search when real-time information is needed
- Try different temperature settings: 0.1 for factual queries, 0.7-0.9 for creative questions
- compound-beta is more capable but slower, compound-beta-mini is faster but less capable
- Check the Tool Execution Info to see when web search was used
""")
return demo
if __name__ == "__main__":
demo = create_interface()
demo.launch(
share=True
)