fix: allow agents to continue with sequential tool calls

After executing tool calls, the agent now continues the iteration loop
instead of immediately trying to get a final response. This allows the
LLM to decide if more tools are needed to complete the task.

Fixes issue where agents would return empty responses after the first
tool call instead of continuing with additional required tool calls.

Resolves #839

Co-authored-by: Mervin Praison <[email protected]>

Author: claude[bot]

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

@@ -857,8 +857,6 @@ def get_response(
                             iteration_count += 1
                             continue
 
-                        # If we reach here, no more tool calls needed - get final response
-                        # Make one more call to get the final summary response
                         # Special handling for Ollama models that don't automatically process tool results
                         ollama_handled = False
                         ollama_params = self._handle_ollama_model(response_text, tool_results, messages, original_prompt)
@@ -924,97 +922,10 @@ def get_response(
                             else:
                                 logging.warning("[OLLAMA_DEBUG] Ollama follow-up returned empty response")
 
-                        # If reasoning_steps is True and we haven't handled Ollama already, do a single non-streaming call
-                        if reasoning_steps and not ollama_handled:
-                            resp = litellm.completion(
-                                **self._build_completion_params(
-                                    messages=messages,
-                                    temperature=temperature,
-                                    stream=False,  # force non-streaming
-                                    **{k:v for k,v in kwargs.items() if k != 'reasoning_steps'}
-                                )
-                            )
-                            reasoning_content = resp["choices"][0]["message"].get("provider_specific_fields", {}).get("reasoning_content")
-                            response_text = resp["choices"][0]["message"]["content"]
-                            
-                            # Optionally display reasoning if present
-                            if verbose and reasoning_content:
-                                display_interaction(
-                                    original_prompt,
-                                    f"Reasoning:\n{reasoning_content}\n\nAnswer:\n{response_text}",
-                                    markdown=markdown,
-                                    generation_time=time.time() - start_time,
-                                    console=console
-                                )
-                            else:
-                                display_interaction(
-                                    original_prompt,
-                                    response_text,
-                                    markdown=markdown,
-                                    generation_time=time.time() - start_time,
-                                    console=console
-                                )
-                        
-                        # Otherwise do the existing streaming approach if not already handled
-                        elif not ollama_handled:
-                            # Get response after tool calls
-                            if stream:
-                                # Streaming approach
-                                if verbose:
-                                    with Live(display_generating("", current_time), console=console, refresh_per_second=4) as live:
-                                        final_response_text = ""
-                                        for chunk in litellm.completion(
-                                            **self._build_completion_params(
-                                                messages=messages,
-                                                tools=formatted_tools,
-                                                temperature=temperature,
-                                                stream=True,
-                                                **kwargs
-                                            )
-                                        ):
-                                            if chunk and chunk.choices and chunk.choices[0].delta.content:
-                                                content = chunk.choices[0].delta.content
-                                                final_response_text += content
-                                                live.update(display_generating(final_response_text, current_time))
-                                else:
-                                    final_response_text = ""
-                                    for chunk in litellm.completion(
-                                        **self._build_completion_params(
-                                            messages=messages,
-                                            tools=formatted_tools,
-                                            temperature=temperature,
-                                            stream=True,
-                                            **kwargs
-                                        )
-                                    ):
-                                        if chunk and chunk.choices and chunk.choices[0].delta.content:
-                                            final_response_text += chunk.choices[0].delta.content
-                            else:
-                                # Non-streaming approach
-                                resp = litellm.completion(
-                                    **self._build_completion_params(
-                                        messages=messages,
-                                        tools=formatted_tools,
-                                        temperature=temperature,
-                                        stream=False,
-                                        **kwargs
-                                    )
-                                )
-                                final_response_text = resp.get("choices", [{}])[0].get("message", {}).get("content", "") or ""
-                            
-                            final_response_text = final_response_text.strip()
-                        
-                        # Display final response
-                        if verbose:
-                            display_interaction(
-                                original_prompt,
-                                final_response_text,
-                                markdown=markdown,
-                                generation_time=time.time() - start_time,
-                                console=console
-                            )
-                        
-                        return final_response_text
+                        # After tool execution, continue the loop to check if more tools are needed
+                        # instead of immediately trying to get a final response
+                        iteration_count += 1
+                        continue
                     else:
                         # No tool calls, we're done with this iteration
                         # If we've executed tools in previous iterations, this response contains the final answer