Release v2.6.7

docker/Dockerfile.chat

@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
 # Install Python packages (using latest versions)
 RUN pip install --no-cache-dir \
     praisonai_tools \
-    "praisonai>=2.6.6" \
+    "praisonai>=2.6.7" \
     "praisonai[chat]" \
     "embedchain[github,youtube]"
 

docker/Dockerfile.dev

@@ -20,7 +20,7 @@ RUN mkdir -p /root/.praison
 # Install Python packages (using latest versions)
 RUN pip install --no-cache-dir \
     praisonai_tools \
-    "praisonai>=2.6.6" \
+    "praisonai>=2.6.7" \
     "praisonai[ui]" \
     "praisonai[chat]" \
     "praisonai[realtime]" \

docker/Dockerfile.ui

@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
 # Install Python packages (using latest versions)
 RUN pip install --no-cache-dir \
     praisonai_tools \
-    "praisonai>=2.6.6" \
+    "praisonai>=2.6.7" \
     "praisonai[ui]" \
     "praisonai[crewai]"
 

examples/tools/example_pandas_tool.py

@@ -0,0 +1,128 @@
+"""
+Example: Using pandas as a custom tool with PraisonAI Agent
+
+This example shows how to wrap pandas functions as tools
+that can be used with Agent().
+"""
+
+import pandas as pd
+from io import StringIO
+
+# Define pandas wrapper tools
+def analyze_csv_data(csv_data: str) -> str:
+    """Analyze CSV data using pandas DataFrame.
+    
+    Args:
+        csv_data: CSV-formatted string data
+        
+    Returns:
+        Analysis summary including shape, columns, and statistics
+    """
+    df = pd.read_csv(StringIO(csv_data))
+    summary = f"""DataFrame Analysis:
+- Shape: {df.shape[0]} rows, {df.shape[1]} columns
+- Columns: {list(df.columns)}
+- Data Types: {dict(df.dtypes)}
+- Summary Statistics:
+{df.describe().to_string()}"""
+    return summary
+
+
+def filter_dataframe(csv_data: str, column: str, condition: str, value: str) -> str:
+    """Filter a DataFrame based on a condition.
+    
+    Args:
+        csv_data: CSV-formatted string data
+        column: Column name to filter on
+        condition: Condition type ('equals', 'greater', 'less', 'contains')
+        value: Value to compare against
+        
+    Returns:
+        Filtered data as CSV string
+    """
+    df = pd.read_csv(StringIO(csv_data))
+    
+    if condition == 'equals':
+        filtered = df[df[column] == value]
+    elif condition == 'greater':
+        filtered = df[df[column] > float(value)]
+    elif condition == 'less':
+        filtered = df[df[column] < float(value)]
+    elif condition == 'contains':
+        filtered = df[df[column].str.contains(value, na=False)]
+    else:
+        return f"Unknown condition: {condition}"
+    
+    return filtered.to_csv(index=False)
+
+
+def calculate_statistics(csv_data: str, column: str) -> str:
+    """Calculate statistics for a specific column.
+    
+    Args:
+        csv_data: CSV-formatted string data
+        column: Column name to analyze
+        
+    Returns:
+        Statistics summary for the column
+    """
+    df = pd.read_csv(StringIO(csv_data))
+    
+    if column not in df.columns:
+        return f"Column '{column}' not found. Available: {list(df.columns)}"
+    
+    col = df[column]
+    
+    if pd.api.types.is_numeric_dtype(col):
+        stats = f"""Statistics for '{column}':
+- Count: {col.count()}
+- Mean: {col.mean():.2f}
+- Std: {col.std():.2f}
+- Min: {col.min()}
+- Max: {col.max()}
+- Median: {col.median()}"""
+    else:
+        stats = f"""Statistics for '{column}':
+- Count: {col.count()}
+- Unique: {col.nunique()}
+- Top: {col.mode().iloc[0] if len(col.mode()) > 0 else 'N/A'}
+- Sample values: {list(col.head(3))}"""
+    
+    return stats
+
+
+if __name__ == "__main__":
+    # Test data
+    test_csv = """name,age,salary,department
+Alice,30,50000,Engineering
+Bob,25,45000,Marketing
+Charlie,35,60000,Engineering
+Diana,28,52000,Sales
+Eve,32,55000,Marketing"""
+
+    print("=== Test: analyze_csv_data ===")
+    print(analyze_csv_data(test_csv))
+    print()
+    
+    print("=== Test: filter_dataframe ===")
+    print(filter_dataframe(test_csv, "age", "greater", "28"))
+    print()
+    
+    print("=== Test: calculate_statistics ===")
+    print(calculate_statistics(test_csv, "salary"))
+    print()
+    
+    # Example with Agent (requires praisonaiagents)
+    print("=== Agent Usage Example ===")
+    print("""
+from praisonaiagents import Agent
+
+agent = Agent(
+    name="data_analyst",
+    role="Data Analyst",
+    goal="Analyze data using pandas tools",
+    tools=[analyze_csv_data, filter_dataframe, calculate_statistics]
+)
+
+result = agent.start("Analyze this data and find the average salary")
+""")

src/praisonai/praisonai.rb

@@ -3,8 +3,8 @@ class Praisonai < Formula
   
     desc "AI tools for various AI applications"
     homepage "https://github.com/MervinPraison/PraisonAI"
-    url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.6.6.tar.gz"
-    sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.6.6.tar.gz | shasum -a 256`.split.first
+    url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.6.7.tar.gz"
+    sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.6.7.tar.gz | shasum -a 256`.split.first
     license "MIT"
   
     depends_on "[email protected]"

src/praisonai/praisonai/cli/features/tools.py

@@ -137,6 +137,13 @@ Built-in tools include: internet_search, calculator, file operations, etc.
             for name in uncategorized[:10]:  # Limit to 10
                 self.print_status(f"    • {name}", "info")
         
+        # Show added tool sources from config
+        config = self._load_config()
+        if config.get("sources"):
+            self.print_status("\n  Added Sources (use with Agent):", "info")
+            for source in config["sources"]:
+                self.print_status(f"    • {source}", "info")
+        
         return list(tools.keys())
     
     def action_info(self, args: List[str], **kwargs) -> Dict[str, Any]:
@@ -575,7 +582,7 @@ Built-in tools include: internet_search, calculator, file operations, etc.
                 self.print_status(f"Failed to download from GitHub: {e}", "error")
                 return result
         
-        # Assume it's a package name
+        # Assume it's a package name - but warn that packages need wrapper tools
         else:
             try:
                 import importlib
@@ -584,20 +591,24 @@ Built-in tools include: internet_search, calculator, file operations, etc.
                 # Get callable functions from the module
                 tools = [n for n in dir(module) if not n.startswith('_') and callable(getattr(module, n, None))]
                 
-                self.print_status(f"\n✅ Package '{source}' is available", "success")
-                self.print_status(f"   Found {len(tools)} callable items", "info")
-                
-                # Add to sources config
-                config = self._load_config()
-                if "sources" not in config:
-                    config["sources"] = []
-                if source not in config["sources"]:
-                    config["sources"].append(source)
-                    self._save_config(config)
-                    self.print_status("   Added to tool sources config", "info")
+                self.print_status(f"\n⚠️  Package '{source}' is installed but NOT directly usable as tools", "warning")
+                self.print_status(f"   Found {len(tools)} callable items in package", "info")
+                self.print_status("", "info")
+                self.print_status("   To use this package with agents, create wrapper tools:", "info")
+                self.print_status("   1. Create a file: ~/.praison/tools/my_tools.py", "info")
+                self.print_status("   2. Define wrapper functions with docstrings", "info")
+                self.print_status("   3. Tools will be auto-discovered", "info")
+                self.print_status("", "info")
+                self.print_status("   Example wrapper:", "info")
+                self.print_status(f"   def my_{source}_tool(data: str) -> str:", "info")
+                self.print_status(f'       """Use {source} to process data."""', "info")
+                self.print_status(f"       import {source}", "info")
+                self.print_status("       # Your logic here", "info")
+                self.print_status("       return result", "info")
                 
                 result["success"] = True
                 result["tools"] = tools[:10]
+                result["note"] = "Package requires wrapper tools"
                 return result
             except ImportError:
                 self.print_status(f"Package '{source}' not found. Install with: pip install {source}", "error")

src/praisonai/praisonai/deploy.py

@@ -57,7 +57,7 @@ class CloudDeployer:
             file.write("FROM python:3.11-slim\n")
             file.write("WORKDIR /app\n")
             file.write("COPY . .\n")
-            file.write("RUN pip install flask praisonai==2.6.6 gunicorn markdown\n")
+            file.write("RUN pip install flask praisonai==2.6.7 gunicorn markdown\n")
             file.write("EXPOSE 8080\n")
             file.write('CMD ["gunicorn", "-b", "0.0.0.0:8080", "api:app"]\n')
             

src/praisonai/praisonai/version.py

@@ -1 +1 @@
-__version__ = "2.6.6"
+__version__ = "2.6.7"