Add greeting handler for agent interactions

.gitignore

@@ -0,0 +1,45 @@
+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# Virtual environments
+.venv/
+venv/
+ENV/
+env/
+
+# IDE
+.vscode/
+.idea/
+*.swp
+*.swo
+*~
+
+# OS
+.DS_Store
+Thumbs.db
+
+# SQLite
+*.db-journal
+
+# Temporary files
+*.tmp
+.cache/

README.md

@@ -44,9 +44,10 @@ Detailed ETL notes live in `markdown/project_overview.md`, while `markdown/view_
 - See `markdown/view_scoring_details.md` for the full breakdown.
 
 ## Agent Workflow
-1. **System prompt** (`utils/prompts.py`): enforces plan-first tool usage, schema inspection, SQL-only answers, and markdown outputs containing identifiers, geography, RAUM, component scores, and contact info.
-2. **Tools**: the Agno agent loads two tools—`SequentialThinkingTools` (custom planner) and `SQLTools` (runs queries against `data/staging.sqlite`).
-3. **Run**: edit `USER_INPUT` in `main.py` or wrap the agent in your own CLI/web interface; when executed, it stores responses under `markdown/output_<timestamp>.md`.
+1. **Greeting Handler**: The agent now includes a friendly greeting handler that responds to simple greetings (hi, hello, hey, etc.) with a welcome message and usage guide, making it more user-friendly for first-time interactions.
+2. **System prompt** (`utils/prompts.py`): enforces plan-first tool usage, schema inspection, SQL-only answers, and markdown outputs containing identifiers, geography, RAUM, component scores, and contact info.
+3. **Tools**: the Agno agent loads two tools—`SequentialThinkingTools` (custom planner) and `SQLTools` (runs queries against `data/staging.sqlite`).
+4. **Run**: edit `USER_INPUT` in `main.py` or wrap the agent in your own CLI/web interface; when executed, it stores responses under `markdown/output_<timestamp>.md`.
 
 ## Getting Started
 1. Install dependencies (example):

main.py

@@ -10,6 +10,48 @@
 from agno.os import AgentOS
 
 
+def handle_greeting(user_input: str) -> str | None:
+    """
+    Handle simple greetings and return a friendly welcome message.
+
+    Args:
+        user_input: The user's input string
+
+    Returns:
+        A welcome message string if greeting detected, None otherwise
+    """
+    greetings = ["hi", "hello", "hey", "greetings", "good morning", "good afternoon", "good evening"]
+    user_lower = user_input.lower().strip()
+
+    # Check if input is exactly a greeting or starts with a greeting
+    is_greeting = (
+        user_lower in greetings or
+        any(user_lower.startswith(greeting + " ") for greeting in greetings) or
+        any(user_lower.startswith(greeting + ",") for greeting in greetings)
+    )
+
+    if is_greeting:
+        return """# Welcome to the Matchmaking Agent!
+
+I'm here to help you pair SEC Form D / Reg CF deals with Form ADV advisers using our comprehensive database.
+
+## What I Can Do
+
+- **Find advisers for a deal**: Provide a Form D accession number, and I'll find the top matching advisers
+- **Find deals for an adviser**: Provide an adviser FilingID, and I'll show suitable deals
+- **Analyze fit scores**: I'll explain why advisers match specific deals based on geography, capital, audience, and more
+- **Query the database**: Ask about specific deals, advisers, or market trends
+
+## Example Queries
+
+- "Find the top 5 advisers for Form D accession 0000005108-25-000002"
+- "Show deals that adviser FilingID 1620806 is a fit for"
+- "List Reg CF offerings that allow retail investors"
+
+How can I assist you today?"""
+    return None
+
+
 db_path = Path("data/staging.sqlite").resolve()
 db_url = f"sqlite:///{db_path}"
 
@@ -37,13 +79,24 @@
 plus the geography/capital/audience component scores. 
 Explain briefly why each adviser is a good fit.
 """
-    res = agno_agent.run(USER_INPUT)
+
+    # Check if input is a simple greeting
+    greeting_response = handle_greeting(USER_INPUT)
+
+    if greeting_response:
+        # Handle greeting without invoking the agent
+        print(greeting_response)
+        res_content = greeting_response
+    else:
+        # Run the agent for actual queries
+        res = agno_agent.run(USER_INPUT)
+        res_content = res.content
 
     markdown_dir = Path("markdown")
     os.makedirs(markdown_dir, exist_ok=True)
 
     timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
     output_path = markdown_dir / f"output_{timestamp}.md"
     with open(output_path, "w", encoding="utf-8") as md_file:
-        md_file.write(res.content)
+        md_file.write(res_content)