Update app.py

app.py

@@ -14,7 +14,6 @@ logging.basicConfig(level=logging.DEBUG, format='%(asctime)s - %(levelname)s - %
 # =============================================================================
 # Load In-House Hugging Face Models for AI Agents with Fallbacks
 # =============================================================================
-# Replace these model IDs with your actual in-house model names and token if available.
 try:
     summarizer = pipeline("summarization", model="myorg/inhouse-summarizer")
     logging.info("Loaded in-house summarizer.")
@@ -36,6 +35,51 @@ except Exception as e:
     logging.error("In-house planner generator not found, falling back: %s", e)
     planner_generator = pipeline("text-generation", model="gpt2", max_length=150)
 
+# =============================================================================
+# In-House Agent Functions
+# =============================================================================
+def report_agent(data):
+    """
+    Generates a summary report using the in-house summarizer model.
+    """
+    if not data or len(data.strip()) == 0:
+        return "Please provide input text for summarization."
+    try:
+        summary = summarizer(data, max_length=130, min_length=30, do_sample=False)
+        logging.debug("Summary generated using in-house summarizer.")
+        return summary[0]['summary_text']
+    except Exception as e:
+        logging.error("Error generating summary: %s", e)
+        return "Error generating summary."
+
+def planning_agent(goal):
+    """
+    Generates a detailed action plan based on the provided goal using the in-house planner model.
+    """
+    if not goal or len(goal.strip()) == 0:
+        return "Please provide a goal for planning."
+    try:
+        plan = planner_generator(goal, max_length=150, num_return_sequences=1)
+        logging.debug("Plan generated using in-house planner.")
+        return plan[0]['generated_text']
+    except Exception as e:
+        logging.error("Error generating plan: %s", e)
+        return "Error generating plan."
+
+def research_agent(query):
+    """
+    Generates research insights based on the provided query using the in-house research generator.
+    """
+    if not query or len(query.strip()) == 0:
+        return "Please provide a research query."
+    try:
+        result = research_generator(query, max_length=100, num_return_sequences=1)
+        logging.debug("Research output generated using in-house research model.")
+        return result[0]['generated_text']
+    except Exception as e:
+        logging.error("Error generating research output: %s", e)
+        return "Error generating research output."
+
 # =============================================================================
 # Helper Functions: Interactive Chart Generators
 # =============================================================================