Update app.py

app.py

@@ -1,116 +1,97 @@
 import streamlit as st
 import os
-import re
 from crewai import Agent, Task, Crew, LLM
 from pydantic import BaseModel, Field
 from typing import List
 
-# 1. SETUP & SECRETS 🔑
+# 1. DATA STRUCTURE 📐
+# This ensures the AI gives us a clean "story" instead of raw JSON code.
+class MatchReport(BaseModel):
+    match_title: str = Field(description="The formal title of the match.")
+    player_of_the_match: str = Field(description="The standout performer and why.")
+    deep_narrative: str = Field(description="A 3-paragraph story of the match events.")
+    key_highlights: List[str] = Field(description="3-5 bullet points of critical moments.")
+
+# 2. SETUP & SECRETS 🔑
 GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
 
 if not GROQ_API_KEY:
-    st.error("API Key missing! Please set GROQ_API_KEY in your Hugging Face Secrets.")
+    st.error("Please set GROQ_API_KEY in your secrets.")
     st.stop()
 
-# 2. DATA STRUCTURE 📐
-class MatchReport(BaseModel):
-    match_title: str = Field(description="The formal title, e.g., 'DC vs MI, Match 43, IPL 2024'. Do not include any other text.")
-    player_of_the_match: str = Field(description="Name and a 1-sentence reason.")
-    deep_narrative: str = Field(description="A 3-paragraph story of the match events.")
-    key_stats: List[str] = Field(description="A list of 3-5 specific bullet points (e.g., 'DC: 257/4')")
-
-write_report_task = Task(
-    description=(
-        "Based on the analysis, create a deep narrative match report. "
-        "IMPORTANT: Provide ONLY the structured information required. "
-        "Do not include conversational filler like 'Here is the report' or 'Okay, I will do that'."
-    ),
-    agent=writer,
-    output_pydantic=MatchReport
-)
-
 # 3. LLM CONFIGURATION 🧠
-# Using a current, supported model
 cricket_llm = LLM(
     model="groq/llama-3.3-70b-8192",
     api_key=GROQ_API_KEY
 )
 
 # 4. AGENT DEFINITIONS 🤖
+# We define these FIRST so the tasks can find them.
 scout = Agent(
     role="Cricket Match Scout",
-    goal="Extract ball-by-ball data, Powerplay scores, and partnership details from {url}.",
-    backstory="You are a meticulous data collector who never misses a boundary or a dot ball.",
+    goal="Extract ball-by-ball data and Powerplay scores from {url}.",
+    backstory="You are an expert at finding specific match facts.",
     llm=cricket_llm
 )
 
 analyst = Agent(
     role="Technical Match Analyst",
-    goal="Identify momentum shifts and explain how the Powerplay performance impacted the final result.",
-    backstory="You are a strategist who understands the 'why' behind the numbers.",
+    goal="Identify momentum shifts and the Player of the Match.",
+    backstory="You interpret data to find the 'why' behind the win.",
     llm=cricket_llm
 )
 
 writer = Agent(
     role="International Sports Journalist",
-    goal="Write a deep, dramatic narration of the match based on technical insights.",
-    backstory="You write for a global audience, making the game's drama accessible and exciting.",
+    goal="Write a deep, dramatic narration of the match.",
+    backstory="You turn technical insights into a compelling story.",
     llm=cricket_llm
 )
 
 # 5. TASK DEFINITIONS 📋
 scrape_task = Task(
-    description="Analyze the commentary at {url}. Find the Powerplay score and the most impactful partnership.",
+    description="Analyze the commentary at {url}. Find key stats and partnerships.",
     agent=scout,
-    expected_output="A detailed list of match events and statistics."
+    expected_output="A list of match stats."
 )
 
 analyze_task = Task(
-    description="Review the scout's data. Determine who the 'Player of the Match' was based on high-impact moments.",
+    description="Determine the turning points and the Player of the Match.",
     agent=analyst,
-    expected_output="Technical analysis and selection of the standout performer."
+    expected_output="A technical summary of the game."
 )
 
 write_report_task = Task(
-    description=(
-        "Draft a 'Deep Narrative' report. Start with the atmosphere and the Powerplay battle, "
-        "then describe the middle-over shifts, ending with the climax. Use the provided data "
-        "to ensure accuracy, but prioritize storytelling."
-    ),
+    description="Draft a deep narrative report. Focus on the drama and the Powerplay.",
     agent=writer,
-    output_pydantic=MatchReport
+    output_pydantic=MatchReport # This links to our data structure above
 )
 
 # 6. STREAMLIT UI 🖥️
-st.set_page_config(page_title="Cricket Intel", page_icon="🏏")
-st.title("🏏 Deep Match Intelligence")
+st.title("🏏 Cricket Intelligence")
 
 url_input = st.text_input("Enter Match Commentary URL:")
 
-if st.button("Generate Deep Narrative"):
+if st.button("Generate Report"):
     if url_input:
-        with st.spinner("Writing the match story..."):
+        with st.spinner("Analyzing match data..."):
             match_crew = Crew(
                 agents=[scout, analyst, writer],
                 tasks=[scrape_task, analyze_task, write_report_task]
             )
             
-            # Crew returns the Pydantic object directly
-            report = match_crew.kickoff(inputs={'url': url_input}).pydantic
+            result = match_crew.kickoff(inputs={'url': url_input})
+            report = result.pydantic
             
-            # Displaying the structured narrative
             st.header(report.match_title)
             st.subheader(f"🏆 {report.player_of_the_match}")
             
-            st.markdown("### ⚡ Quick Highlights")
-            cols = st.columns(len(report.key_stats))
-            for i, stat in enumerate(report.key_stats):
-                cols[i % len(cols)].info(stat)
+            st.markdown("### ⚡ Highlights")
+            for point in report.key_highlights:
+                st.write(f"- {point}")
+                
             st.divider()
-            st.markdown("### 📖 The Deep Narrative")
+            st.markdown("### 📖 Match Story")
             st.write(report.deep_narrative)
-            st.markdown("### 📊 Key Statistics")
-            for stat in report.key_stats:
-                st.write(f"- {stat}")
     else:
-        st.warning("Please provide a URL to begin.")
+        st.warning("Please provide a URL.")