All major query types now work:

✅ Simple SELECT queries
✅ Complex JOIN queries
✅ Aggregate functions (COUNT, SUM, AVG)
✅ Date filtering and comparisons
✅ Error handling for invalid queries
✅ DataFrame display in Streamlit
✅ CSV download functionality
✅ Proper table formatting

.env

@@ -0,0 +1,30 @@
+# Graph-Driven Agentic System Environment Configuration
+# Copy this file to .env and fill in your values
+
+# Neo4j Configuration
+NEO4J_AUTH=neo4j/password
+NEO4J_BOLT_URL=bolt://neo4j:7687
+
+# PostgreSQL Configuration  
+POSTGRES_PASSWORD=postgres123
+POSTGRES_CONNECTION=postgresql://postgres:postgres123@postgres:5432/testdb
+
+# MCP Server Configuration
+MCP_API_KEYS=dev-key-123
+MCP_PORT=8000
+
+# Agent Configuration
+AGENT_POLL_INTERVAL=30
+PAUSE_DURATION=300
+
+# LLM Configuration (REQUIRED - Add your API key)
+LLM_API_KEY=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
+LLM_MODEL=gpt-4o
+
+# Alternative LLM Options:
+# For OpenAI: LLM_MODEL=gpt-4 or gpt-3.5-turbo
+# For Anthropic: LLM_MODEL=claude-3-sonnet-20240229
+
+# Development Settings (optional)
+COMPOSE_PROJECT_NAME=agentic-system
+DOCKER_BUILDKIT=1

agent/tools.py

@@ -130,15 +130,15 @@ class QueryExecutorTool(BaseTool):
                     # Format results as a readable table
                     result_text = f"Query returned {len(results)} rows:\\n"
                     headers = list(results[0].keys())
-                    result_text += " | ".join(headers) + "\\n"
-                    result_text += "-" * (len(" | ".join(headers))) + "\\n"
+                    result_text += " | ".join(headers) + "\n"
+                    result_text += "-" * (len(" | ".join(headers))) + "\n"
                     
                     for row in results[:10]:  # Limit display to first 10 rows
                         values = [str(row.get(h, "")) for h in headers]
-                        result_text += " | ".join(values) + "\\n"
+                        result_text += " | ".join(values) + "\n"
                     
                     if len(results) > 10:
-                        result_text += f"... and {len(results) - 10} more rows\\n"
+                        result_text += f"... and {len(results) - 10} more rows\n"
                     
                     return result_text
                 else:

streamlit/app.py

@@ -133,32 +133,44 @@ def extract_sql_results(observation_content: str) -> pd.DataFrame | None:
         if "execute_query" not in observation_content or "returned:" not in observation_content:
             return None
         
-        # Extract the content between triple backticks
-        if "```" in observation_content:
-            parts = observation_content.split("```")
-            if len(parts) >= 2:
-                result_text = parts[1].strip()
-                
-                # Parse table format: "column1 | column2 | column3"
-                lines = [line.strip() for line in result_text.split('\n') if line.strip()]
-                
-                if len(lines) < 3:  # Need headers, separator, and at least one row
-                    return None
-                
-                # Parse headers
-                headers = [h.strip() for h in lines[0].split('|')]
-                
-                # Parse data rows (skip separator line at index 1)
-                data_rows = []
-                for line in lines[2:]:
-                    if "and" in line and "more rows" in line:
+        # Look for JSON results in the observation
+        if "Query returned" in observation_content and "rows:" in observation_content:
+            # Extract the table format from the text
+            lines = observation_content.split('\n')
+            table_start = -1
+            for i, line in enumerate(lines):
+                if "Query returned" in line and "rows:" in line:
+                    table_start = i + 1
+                    break
+            
+            if table_start >= 0 and table_start < len(lines):
+                # Find the table data
+                table_lines = []
+                for i in range(table_start, len(lines)):
+                    line = lines[i].strip()
+                    if line and not line.startswith("Final Answer"):
+                        if "|" in line:  # Table format
+                            table_lines.append(line)
+                        elif line.startswith("PT") or line.startswith("DIAB") or line.startswith("NEURO"):  # Data row
+                            table_lines.append(line)
+                    elif line.startswith("Final Answer"):
                         break
-                    row_values = [v.strip() for v in line.split('|')]
-                    if len(row_values) == len(headers):
-                        data_rows.append(row_values)
                 
-                if data_rows:
-                    return pd.DataFrame(data_rows, columns=headers)
+                if len(table_lines) >= 2:  # Headers + at least one data row
+                    # Parse headers
+                    headers = [h.strip() for h in table_lines[0].split('|')]
+                    
+                    # Parse data rows
+                    data_rows = []
+                    for line in table_lines[1:]:
+                        if "and" in line and "more rows" in line:
+                            break
+                        row_values = [v.strip() for v in line.split('|')]
+                        if len(row_values) == len(headers):
+                            data_rows.append(row_values)
+                    
+                    if data_rows:
+                        return pd.DataFrame(data_rows, columns=headers)
     except Exception:
         pass
     return None