Refa: add result to callback for agent tool use. (#9137)

### What problem does this PR solve?


### Type of change

- [x] Refactoring

agent/component/llm.py

@@ -22,6 +22,8 @@ from typing import Any
 import json_repair
 from copy import deepcopy
 from functools import partial
+
+from api.db import LLMType
 from api.db.services.llm_service import LLMBundle, TenantLLMService
 from agent.component.base import ComponentBase, ComponentParamBase
 from api.utils.api_utils import timeout
@@ -49,27 +51,33 @@ class LLMParam(ComponentParamBase):
         self.visual_files_var = None
 
     def check(self):
-        self.check_decimal_float(self.temperature, "[Agent] Temperature")
-        self.check_decimal_float(self.presence_penalty, "[Agent] Presence penalty")
-        self.check_decimal_float(self.frequency_penalty, "[Agent] Frequency penalty")
-        self.check_nonnegative_number(self.max_tokens, "[Agent] Max tokens")
-        self.check_decimal_float(self.top_p, "[Agent] Top P")
+        self.check_decimal_float(float(self.temperature), "[Agent] Temperature")
+        self.check_decimal_float(float(self.presence_penalty), "[Agent] Presence penalty")
+        self.check_decimal_float(float(self.frequency_penalty), "[Agent] Frequency penalty")
+        self.check_nonnegative_number(int(self.max_tokens), "[Agent] Max tokens")
+        self.check_decimal_float(float(self.top_p), "[Agent] Top P")
         self.check_empty(self.llm_id, "[Agent] LLM")
         self.check_empty(self.sys_prompt, "[Agent] System prompt")
         self.check_empty(self.prompts, "[Agent] User prompt")
 
     def gen_conf(self):
         conf = {}
-        if self.max_tokens > 0:
-            conf["max_tokens"] = self.max_tokens
-        if self.temperature > 0:
-            conf["temperature"] = self.temperature
-        if self.top_p > 0:
-            conf["top_p"] = self.top_p
-        if self.presence_penalty > 0:
-            conf["presence_penalty"] = self.presence_penalty
-        if self.frequency_penalty > 0:
-            conf["frequency_penalty"] = self.frequency_penalty
+        def get_attr(nm):
+            try:
+                return getattr(self, nm)
+            except Exception:
+                pass
+
+        if int(self.max_tokens) > 0 and get_attr("maxTokensEnabled"):
+            conf["max_tokens"] = int(self.max_tokens)
+        if float(self.temperature) > 0 and get_attr("temperatureEnabled"):
+            conf["temperature"] = float(self.temperature)
+        if float(self.top_p) > 0 and get_attr("topPEnabled"):
+            conf["top_p"] = float(self.top_p)
+        if float(self.presence_penalty) > 0 and get_attr("presencePenaltyEnabled"):
+            conf["presence_penalty"] = float(self.presence_penalty)
+        if float(self.frequency_penalty) > 0 and get_attr("frequencyPenaltyEnabled"):
+            conf["frequency_penalty"] = float(self.frequency_penalty)
         return conf
 
 
@@ -112,6 +120,12 @@ class LLM(ComponentBase):
             if not self.imgs:
                 self.imgs = []
             self.imgs = [img for img in self.imgs if img[:len("data:image/")] == "data:image/"]
+            if self.imgs and TenantLLMService.llm_id2llm_type(self._param.llm_id) == LLMType.CHAT.value:
+                self.chat_mdl = LLMBundle(self._canvas.get_tenant_id(), LLMType.IMAGE2TEXT.value,
+                                          self._param.llm_id, max_retries=self._param.max_retries,
+                                          retry_interval=self._param.delay_after_error
+                                          )
+
 
         args = {}
         vars = self.get_input_elements() if not self._param.debug_inputs else self._param.debug_inputs
@@ -207,7 +221,8 @@ class LLM(ComponentBase):
             return
 
         downstreams = self._canvas.get_component(self._id)["downstream"] if self._canvas.get_component(self._id) else []
-        if any([self._canvas.get_component_obj(cid).component_name.lower()=="message" for cid in downstreams]) and not self._param.output_structure:
+        ex = self.exception_handler()
+        if any([self._canvas.get_component_obj(cid).component_name.lower()=="message" for cid in downstreams]) and not self._param.output_structure and not (ex and ex["goto"]):
             self.set_output("content", partial(self._stream_output, prompt, msg))
             return
 
@@ -224,14 +239,22 @@ class LLM(ComponentBase):
             break
 
         if error:
-            self.set_output("_ERROR", error)
             if self.get_exception_default_value():
                 self.set_output("content", self.get_exception_default_value())
+            else:
+                self.set_output("_ERROR", error)
 
     def _stream_output(self, prompt, msg):
         _, msg = message_fit_in([{"role": "system", "content": prompt}, *msg], int(self.chat_mdl.max_length * 0.97))
         answer = ""
         for ans in self._generate_streamly(msg):
+            if ans.find("**ERROR**") >= 0:
+                if self.get_exception_default_value():
+                    self.set_output("content", self.get_exception_default_value())
+                    yield self.get_exception_default_value()
+                else:
+                    self.set_output("_ERROR", ans)
+                return
             yield ans
             answer += ans
         self.set_output("content", answer)
@@ -243,4 +266,4 @@ class LLM(ComponentBase):
 
     def thoughts(self) -> str:
         _, msg = self._prepare_prompt_variables()
-        return f"I’m thinking and planning the next move, starting from the prompt:<br/>“{msg[-1]['content']}”<span class=\"collapse\"> (tap to see full text)</span>"
+        return "⌛Give me a moment—starting from: \n\n" + re.sub(r"(User's query:|[\\]+)", '', msg[-1]['content'], flags=re.DOTALL) + "\n\nI’ll figure out our best next move."