Release v2.3.35

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>=2.3.34" \
+    "praisonai>=2.3.35" \
     "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>=2.3.34" \
+    "praisonai>=2.3.35" \
     "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>=2.3.34" \
+    "praisonai>=2.3.35" \
     "praisonai[ui]" \
     "praisonai[crewai]"
 

src/praisonai-agents/benchmarks/execution_benchmark.py

@@ -8,10 +8,12 @@ Tests single agent running a simple task across frameworks.
 Usage:
     export OPENAI_API_KEY=your_key
     python benchmarks/execution_benchmark.py
+    python benchmarks/execution_benchmark.py --no-save
 """
 
 import time
 import os
+import argparse
 from importlib.metadata import version as get_version
 
 # Check API key
@@ -220,6 +222,10 @@ def save_results(results: dict):
 
 
 if __name__ == '__main__':
+    parser = argparse.ArgumentParser(description='PraisonAI Agents - Real Execution Benchmark')
+    parser.add_argument('--no-save', action='store_true', help='Do not save results to file')
+    args = parser.parse_args()
+    
     print('=' * 60)
     print('PraisonAI Agents - Real Execution Benchmark')
     print('=' * 60)
@@ -228,7 +234,7 @@ if __name__ == '__main__':
     print(f'Prompt: "{PROMPT}"')
     
     versions = get_package_versions()
-    print(f'\nPackage versions:')
+    print('\nPackage versions:')
     for pkg, ver in versions.items():
         print(f'  {pkg}: {ver}')
     
@@ -273,6 +279,8 @@ if __name__ == '__main__':
     
     print('\n' + '=' * 60)
     
-    # Save results
-    if results:
+    # Save results (unless --no-save)
+    if results and not args.no_save:
         save_results(results)
+    elif args.no_save:
+        print('\nResults not saved (--no-save flag used)')

src/praisonai/agents_n8n.json

@@ -33,7 +33,7 @@
         "url": "http://127.0.0.1:8005/agents/researcher",
         "sendBody": true,
         "specifyBody": "json",
-        "jsonBody": "={{ JSON.stringify({ query:  $json.body?.query || $json.query || 'Research about Mars environment and cat behavior for the movie concept' } }) }}",
+        "jsonBody": "={{ JSON.stringify({ query: $json.body?.query || $json.query || 'Research about Mars environment and cat behavior for the movie concept' }) }}",
         "options": {
           "timeout": 300000
         }
@@ -54,7 +54,7 @@
         "url": "http://127.0.0.1:8005/agents/narrative_designer",
         "sendBody": true,
         "specifyBody": "json",
-        "jsonBody": "={{ JSON.stringify({ query:  $json.response || 'Create story concept based on research: {{previous_output}}' } }) }}",
+        "jsonBody": "={{ JSON.stringify({ query: $json.response || 'Create story concept based on research: previous_output' }) }}",
         "options": {
           "timeout": 300000
         }
@@ -75,7 +75,7 @@
         "url": "http://127.0.0.1:8005/agents/scriptwriter",
         "sendBody": true,
         "specifyBody": "json",
-        "jsonBody": "={{ JSON.stringify({ query:  $json.response || 'Write the final movie script based on the story concept: {{previous_output}}' } }) }}",
+        "jsonBody": "={{ JSON.stringify({ query: $json.response || 'Write the final movie script based on the story concept: previous_output' }) }}",
         "options": {
           "timeout": 300000
         }

src/praisonai/examples/workflow_example.yaml

@@ -1,93 +0,0 @@
-# Advanced Workflow Example
-# Demonstrates: conditional routing, decision tasks, and multi-agent coordination
-
-name: Content Creation Pipeline
-description: A workflow that researches, writes, reviews, and publishes content
-
-workflow:
-  process: workflow  # Use workflow process for conditional execution
-  verbose: true
-
-agents:
-  researcher:
-    name: Researcher
-    role: Research Specialist
-    goal: Gather comprehensive information on topics
-    backstory: Expert at finding and synthesizing information from various sources
-    instructions: |
-      Research the given topic thoroughly.
-      Provide detailed findings with key points.
-    llm: gpt-4o-mini
-
-  writer:
-    name: Writer
-    role: Content Writer
-    goal: Create engaging and informative content
-    backstory: Skilled writer who transforms research into readable content
-    instructions: |
-      Write clear, engaging content based on the research.
-      Structure the content with introduction, body, and conclusion.
-    llm: gpt-4o-mini
-
-  reviewer:
-    name: Reviewer
-    role: Quality Reviewer
-    goal: Ensure content meets quality standards
-    backstory: Meticulous editor who ensures accuracy and clarity
-    instructions: |
-      Review the content for accuracy, clarity, and engagement.
-      Decide if it's ready for publication or needs revision.
-    llm: gpt-4o-mini
-
-  publisher:
-    name: Publisher
-    role: Content Publisher
-    goal: Finalize and format content for publication
-    backstory: Expert at preparing content for various platforms
-    instructions: |
-      Format the approved content for publication.
-      Add metadata and prepare final deliverable.
-    llm: gpt-4o-mini
-
-steps:
-  # Step 1: Research (starting point)
-  - name: research_task
-    agent: researcher
-    action: "Research the topic: AI trends in 2025"
-    expected_output: "Comprehensive research findings with key points and sources"
-    is_start: true
-    next_tasks: [write_task]
-
-  # Step 2: Write content based on research
-  - name: write_task
-    agent: writer
-    action: "Write an article based on the research findings"
-    expected_output: "Well-structured article with introduction, body, and conclusion"
-    context: [research_task]
-    next_tasks: [review_task]
-
-  # Step 3: Review with decision (conditional routing)
-  - name: review_task
-    agent: reviewer
-    action: "Review the article for quality and accuracy"
-    expected_output: "Quality assessment with approval or revision recommendation"
-    context: [write_task]
-    task_type: decision
-    condition:
-      approved: [publish_task]
-      needs_revision: [revise_task]
-
-  # Step 4a: Revision (conditional - only if review fails)
-  - name: revise_task
-    agent: writer
-    action: "Revise the article based on reviewer feedback"
-    expected_output: "Revised article addressing all feedback"
-    context: [write_task, review_task]
-    next_tasks: [review_task]  # Loop back to review
-
-  # Step 4b: Publish (conditional - only if review passes)
-  - name: publish_task
-    agent: publisher
-    action: "Prepare the approved article for publication"
-    expected_output: "Final formatted article ready for publication"
-    context: [write_task, review_task]

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/v2.3.34.tar.gz"
-    sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.3.34.tar.gz | shasum -a 256`.split.first
+    url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.3.35.tar.gz"
+    sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.3.35.tar.gz | shasum -a 256`.split.first
     license "MIT"
   
     depends_on "[email protected]"

src/praisonai/praisonai/cli/features/n8n.py

@@ -412,12 +412,14 @@ class N8nHandler(FlagHandler):
         agent_url_id = agent_id.lower().replace(' ', '_')
         
         # Build the query - first agent uses webhook input, others use previous response
+        # Escape single quotes and double braces (n8n expression syntax)
+        escaped_action = action.replace("'", "\\'").replace("{{", "").replace("}}", "")
         if is_first:
             # First agent: use query from webhook body
-            query_expr = f"={{ $json.body?.query || $json.query || '{action}' }}"
+            query_expr = "$json.body?.query || $json.query || '" + escaped_action + "'"
         else:
             # Subsequent agents: use previous agent's response + original action context
-            query_expr = f"={{ $json.response || '{action}' }}"
+            query_expr = "$json.response || '" + escaped_action + "'"
         
         return {
             "id": f"agent_{index}",
@@ -430,7 +432,7 @@ class N8nHandler(FlagHandler):
                 "url": f"{self.praisonai_api_url}/agents/{agent_url_id}",
                 "sendBody": True,
                 "specifyBody": "json",
-                "jsonBody": f"={{{{ JSON.stringify({{ query: {query_expr[2:]} }}) }}}}",
+                "jsonBody": f"={{{{ JSON.stringify({{ query: {query_expr} }}) }}}}",
                 "options": {
                     "timeout": 300000  # 5 minute timeout per agent
                 }

src/praisonai/praisonai/cli/main.py

@@ -3060,6 +3060,11 @@ Now, {final_instruction.lower()}:"""
         """
         Handle the serve command - start API server for agents.
         
+        Supports:
+        - Sequential workflows with agents and steps
+        - Workflow patterns: route, parallel, loop, repeat
+        - All process types: sequential, workflow, hierarchical
+        
         Usage:
             praisonai serve agents.yaml
             praisonai serve agents.yaml --port 8005 --host 0.0.0.0
@@ -3090,7 +3095,7 @@ Now, {final_instruction.lower()}:"""
             print("  praisonai agents.yaml --serve")
             sys.exit(1)
         
-        print(f"📄 Loading agents from: {yaml_file}")
+        print(f"📄 Loading workflow from: {yaml_file}")
         
         # Load YAML file
         with open(yaml_file, 'r') as f:
@@ -3124,6 +3129,20 @@ Now, {final_instruction.lower()}:"""
         steps = config.get('steps', [])
         tasks_list = []
         
+        # Detect advanced workflow patterns
+        has_route = any(isinstance(s, dict) and 'route' in s for s in steps)
+        has_parallel = any(isinstance(s, dict) and 'parallel' in s for s in steps)
+        has_loop = any(isinstance(s, dict) and 'loop' in s for s in steps)
+        has_repeat = any(isinstance(s, dict) and 'repeat' in s for s in steps)
+        
+        if has_route or has_parallel or has_loop or has_repeat:
+            patterns = []
+            if has_route: patterns.append("route")
+            if has_parallel: patterns.append("parallel")
+            if has_loop: patterns.append("loop")
+            if has_repeat: patterns.append("repeat")
+            print(f"\n🔀 Detected workflow patterns: {', '.join(patterns)}")
+        
         if steps:
             from praisonaiagents import Task
             print(f"\n📋 Loading workflow steps...")
@@ -3132,6 +3151,38 @@ Now, {final_instruction.lower()}:"""
             task_name_map = {}  # Map step names to Task objects for context/next_tasks
             for i, step in enumerate(steps):
                 if isinstance(step, dict):
+                    # Handle advanced patterns
+                    if 'route' in step:
+                        print(f"  ✓ Loaded routing step: {step.get('name', f'route_{i+1}')}")
+                        continue  # Route steps are handled by workflow process
+                    if 'parallel' in step:
+                        parallel_tasks = step.get('parallel', [])
+                        print(f"  ✓ Loaded parallel step: {len(parallel_tasks)} concurrent tasks")
+                        for j, pt in enumerate(parallel_tasks):
+                            if isinstance(pt, dict):
+                                agent_id = pt.get('agent', '')
+                                action = pt.get('action', pt.get('description', ''))
+                                if agent_id in agents_dict:
+                                    task = Task(
+                                        name=f"parallel_{i}_{j}",
+                                        description=action,
+                                        agent=agents_dict[agent_id],
+                                        expected_output=pt.get('expected_output', 'Completed task output'),
+                                        async_execution=True,  # Parallel tasks run async
+                                    )
+                                    tasks_list.append(task)
+                                    task_name_map[f"parallel_{i}_{j}"] = task
+                        continue
+                    if 'loop' in step:
+                        loop_config = step.get('loop', {})
+                        print(f"  ✓ Loaded loop step: over '{loop_config.get('over', 'items')}'")
+                        continue  # Loop steps are handled by workflow process
+                    if 'repeat' in step:
+                        repeat_config = step.get('repeat', {})
+                        print(f"  ✓ Loaded repeat step: until '{repeat_config.get('until', 'done')}'")
+                        continue  # Repeat steps are handled by workflow process
+                    
+                    # Standard step
                     agent_id = step.get('agent', '')
                     action = step.get('action', step.get('description', ''))
                     task_name = step.get('name', f"step_{i+1}")
@@ -3153,7 +3204,7 @@ Now, {final_instruction.lower()}:"""
             
             # Second pass: set up next_tasks and context relationships
             for i, step in enumerate(steps):
-                if isinstance(step, dict):
+                if isinstance(step, dict) and 'agent' in step:
                     task_name = step.get('name', f"step_{i+1}")
                     if task_name in task_name_map:
                         task = task_name_map[task_name]

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==2.3.34 gunicorn markdown\n")
+            file.write("RUN pip install flask praisonai==2.3.35 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__ = "2.3.34"
+__version__ = "2.3.35"