Release v4.5.22

Author: MervinPraison

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>=4.5.21" \
+    "praisonai>=4.5.22" \
     "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>=4.5.21" \
+    "praisonai>=4.5.22" \
     "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>=4.5.21" \
+    "praisonai>=4.5.22" \
     "praisonai[ui]" \
     "praisonai[crewai]"
 

src/praisonai-agents/praisonaiagents/agent/agent.py

@@ -5166,7 +5166,9 @@ def _chat_completion(self, messages, temperature=1.0, tools=None, stream=True, r
                     "display_fn": self._display_generating if self.verbose else None,
                     "reasoning_steps": reasoning_steps,
                     "verbose": self.verbose,
-                    "max_iterations": 10
+                    "max_iterations": 10,
+                    "stream_callback": self.stream_emitter.emit,
+                    "emit_events": True,
                 }
                 if response_format:
                     chat_kwargs["response_format"] = response_format
@@ -7419,11 +7421,31 @@ def _start_stream(self, prompt: str, **kwargs) -> Generator[str, None, None]:
                     if formatted_tools:
                         completion_args["tools"] = formatted_tools
 
+                    # Import StreamEvent types for event emission
+                    from ..streaming.events import StreamEvent, StreamEventType
+                    import time as time_module
+                    
+                    # Emit REQUEST_START event
+                    request_start_perf = time_module.perf_counter()
+                    self.stream_emitter.emit(StreamEvent(
+                        type=StreamEventType.REQUEST_START,
+                        timestamp=request_start_perf,
+                        metadata={"model": self.llm, "message_count": len(messages)}
+                    ))
+                    
                     completion = self._openai_client.sync_client.chat.completions.create(**completion_args)
 
+                    # Emit HEADERS_RECEIVED event
+                    self.stream_emitter.emit(StreamEvent(
+                        type=StreamEventType.HEADERS_RECEIVED,
+                        timestamp=time_module.perf_counter()
+                    ))
+                    
                     # Stream the response chunks without display
                     response_text = ""
                     tool_calls_data = []
+                    first_token_emitted = False
+                    last_content_time = None
 
                     for chunk in completion:
                         delta = chunk.choices[0].delta
@@ -7432,6 +7454,24 @@ def _start_stream(self, prompt: str, **kwargs) -> Generator[str, None, None]:
                         if delta.content is not None:
                             chunk_content = delta.content
                             response_text += chunk_content
+                            last_content_time = time_module.perf_counter()
+                            
+                            # Emit FIRST_TOKEN on first content
+                            if not first_token_emitted:
+                                self.stream_emitter.emit(StreamEvent(
+                                    type=StreamEventType.FIRST_TOKEN,
+                                    timestamp=last_content_time,
+                                    content=chunk_content
+                                ))
+                                first_token_emitted = True
+                            else:
+                                # Emit DELTA_TEXT for subsequent tokens
+                                self.stream_emitter.emit(StreamEvent(
+                                    type=StreamEventType.DELTA_TEXT,
+                                    timestamp=last_content_time,
+                                    content=chunk_content
+                                ))
+                            
                             yield chunk_content
 
                         # Handle tool calls (accumulate but don't yield as chunks)
@@ -7449,6 +7489,18 @@ def _start_stream(self, prompt: str, **kwargs) -> Generator[str, None, None]:
                                 if tool_call_delta.function.arguments:
                                     tool_calls_data[tool_call_delta.index]['function']['arguments'] += tool_call_delta.function.arguments
 
+                    # Emit LAST_TOKEN and STREAM_END events after streaming loop
+                    if last_content_time:
+                        self.stream_emitter.emit(StreamEvent(
+                            type=StreamEventType.LAST_TOKEN,
+                            timestamp=last_content_time
+                        ))
+                    self.stream_emitter.emit(StreamEvent(
+                        type=StreamEventType.STREAM_END,
+                        timestamp=time_module.perf_counter(),
+                        metadata={"response_length": len(response_text)}
+                    ))
+                    
                     # Handle any tool calls that were accumulated
                     if tool_calls_data:
                         # Add assistant message with tool calls to chat history

src/praisonai-agents/praisonaiagents/llm/openai_client.py

@@ -1156,6 +1156,8 @@ def chat_completion_with_tools(
         reasoning_steps: bool = False,
         verbose: bool = True,
         max_iterations: int = 10,
+        stream_callback: Optional[Callable] = None,
+        emit_events: bool = False,
         **kwargs
     ) -> Optional[ChatCompletion]:
         """
@@ -1179,6 +1181,8 @@ def chat_completion_with_tools(
             reasoning_steps: Whether to show reasoning
             verbose: Whether to show verbose output
             max_iterations: Maximum tool calling iterations
+            stream_callback: Optional callback for StreamEvent emission
+            emit_events: Whether to emit StreamEvents (requires stream_callback)
             **kwargs: Additional API parameters
             
         Returns:
@@ -1208,6 +1212,8 @@ def chat_completion_with_tools(
                     console=console,
                     display_fn=display_fn,
                     reasoning_steps=reasoning_steps,
+                    stream_callback=stream_callback,
+                    emit_events=emit_events,
                     **kwargs
                 )
             else:
@@ -1377,6 +1383,8 @@ async def achat_completion_with_tools(
         reasoning_steps: bool = False,
         verbose: bool = True,
         max_iterations: int = 10,
+        stream_callback: Optional[Callable] = None,
+        emit_events: bool = False,
         **kwargs
     ) -> Optional[ChatCompletion]:
         """
@@ -1394,6 +1402,8 @@ async def achat_completion_with_tools(
             reasoning_steps: Whether to show reasoning
             verbose: Whether to show verbose output
             max_iterations: Maximum tool calling iterations
+            stream_callback: Optional callback for StreamEvent emission (can be sync or async)
+            emit_events: Whether to emit StreamEvents (requires stream_callback)
             **kwargs: Additional API parameters
             
         Returns:
@@ -1419,6 +1429,8 @@ async def achat_completion_with_tools(
                     console=console,
                     display_fn=display_fn,
                     reasoning_steps=reasoning_steps,
+                    stream_callback=stream_callback,
+                    emit_events=emit_events,
                     **kwargs
                 )
             else:

src/praisonai-agents/praisonaiagents/output/__init__.py

@@ -49,6 +49,15 @@
     "disable_trace_output",
     "is_trace_output_enabled",
     "get_trace_output",
+    # Editor output (for editor preset - beginner-friendly numbered steps)
+    "EditorOutput",
+    "enable_editor_output",
+    "disable_editor_output",
+    "is_editor_output_enabled",
+    "get_editor_output",
+    "TOOL_LABELS",
+    "BlockType",
+    "DisplayBlock",
 ]
 
 
@@ -112,4 +121,37 @@ def __getattr__(name: str):
         from .trace import get_trace_output
         return get_trace_output
 
+    # Editor output (for editor preset - beginner-friendly numbered steps)
+    if name == "EditorOutput":
+        from .editor import EditorOutput
+        return EditorOutput
+    
+    if name == "enable_editor_output":
+        from .editor import enable_editor_output
+        return enable_editor_output
+    
+    if name == "disable_editor_output":
+        from .editor import disable_editor_output
+        return disable_editor_output
+    
+    if name == "is_editor_output_enabled":
+        from .editor import is_editor_output_enabled
+        return is_editor_output_enabled
+    
+    if name == "get_editor_output":
+        from .editor import get_editor_output
+        return get_editor_output
+    
+    if name == "TOOL_LABELS":
+        from .editor import TOOL_LABELS
+        return TOOL_LABELS
+    
+    if name == "BlockType":
+        from .editor import BlockType
+        return BlockType
+    
+    if name == "DisplayBlock":
+        from .editor import DisplayBlock
+        return DisplayBlock
+    
     raise AttributeError(f"module {__name__!r} has no attribute {name!r}")

src/praisonai-agents/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "praisonaiagents"
-version = "1.5.21"
+version = "1.5.22"
 description = "Praison AI agents for completing complex tasks with Self Reflection Agents"
 readme = "README.md"
 requires-python = ">=3.10"