added observation from using tools, added customAgentExecutor class w…

…ith extended logging capabilities

my-app/src/components/chat-interface.tsx

@@ -15,7 +15,7 @@ type Message = {
     useTools: boolean,
     tool?: string,
     toolInput?: string,
-    action?: string,
+    actionOutput?: string,
     actionInput?: string
   };
 };
@@ -33,7 +33,7 @@ export function ChatInterface() {
     conversationalStage: string,
     tool?: string,
     toolInput?: string,
-    action?: string,
+    actionOutput?: string,
     actionInput?: string
   }[]>([]);
   const [maxHeight, setMaxHeight] = useState('80vh'); // Default to 100% of the viewport height
@@ -110,42 +110,7 @@ export function ChatInterface() {
       }
 
       if (stream) {
-        const reader = response.body?.getReader();
-        const decoder = new TextDecoder();
-
-        const botMessage: Message = { id: session_id, text: '', sender: 'bot' };
-        setMessages((prevMessages) => [...prevMessages, botMessage]);
-
-        reader.read().then(function processText({ done, value }) {
-          if (done) {
-            console.log("Stream complete");
-            return;
-          }   
-          const str = decoder.decode(value, { stream: true });
-
-          str.split('\n').forEach((line) => {
-            if (!line.trim()) return;
-            try {
-              const data = JSON.parse(line);
-              setMessages((prevMessages) => {
-                const newMessages = [...prevMessages];
-                const lastMessageIndex = newMessages.length - 1;
-                const lastMessage = newMessages[lastMessageIndex];
-                if (lastMessage.sender === 'bot') {
-                  if (!lastMessage.text.endsWith(data.token)) {
-                    lastMessage.text += data.token;
-                  }
-                  newMessages[lastMessageIndex] = lastMessage;
-                }
-                return newMessages;
-              });
-            } catch (error) {
-              console.error('Error parsing JSON:', error);
-            }
-          });
-
-          reader.read().then(processText);
-        });
+        {/*Not implemented*/}
       } else {
         if (!stream) {
           const data = await response.json();
@@ -157,7 +122,7 @@ export function ChatInterface() {
             conversationalStage: data.conversational_stage,
             tool: data.tool,
             toolInput: data.tool_input,
-            action: data.action,
+            actionOutput: data.action_output,
             actionInput: data.action_input
           }]);
           const botMessageText = `${data.response}`;
@@ -248,12 +213,12 @@ export function ChatInterface() {
                   {process.toolInput && (
                     <div><strong>Tool Input:</strong> {process.toolInput}</div>
                   )}
-                  {process.action && (
-                    <div><strong>Action:</strong> {process.action}</div>
-                  )}
                   {process.actionInput && (
                     <div><strong>Action Input:</strong> {process.actionInput}</div>
                   )}
+                  {process.actionOutput && (
+                    <div><strong>Action Output:</strong> {process.actionOutput}</div>
+                  )}
                 </div>
               ))}
             </div>

salesgpt/agents.py

@@ -19,7 +19,7 @@
 from salesgpt.templates import CustomPromptTemplateForTools
 from salesgpt.tools import get_tools, setup_knowledge_base
 
-
+from salesgpt.custom_invoke import CustomAgentExecutor
 def _create_retry_decorator(llm: Any) -> Callable[[Any], Any]:
     import openai
 
@@ -40,7 +40,7 @@ class SalesGPT(Chain):
     conversation_stage_id: str = "1"
     current_conversation_stage: str = CONVERSATION_STAGES.get("1")
     stage_analyzer_chain: StageAnalyzerChain = Field(...)
-    sales_agent_executor: Union[AgentExecutor, None] = Field(...)
+    sales_agent_executor: Union[CustomAgentExecutor, None] = Field(...)
     knowledge_base: Union[RetrievalQA, None] = Field(...)
     sales_conversation_utterance_chain: SalesConversationChain = Field(...)
     conversation_stage_dict: Dict = CONVERSATION_STAGES
@@ -336,7 +336,7 @@ def from_llm(cls, llm: ChatLiteLLM, verbose: bool = False, **kwargs) -> "SalesGP
                 allowed_tools=tool_names,
             )
 
-            sales_agent_executor = AgentExecutor.from_agent_and_tools(
+            sales_agent_executor = CustomAgentExecutor.from_agent_and_tools(
                 agent=sales_agent_with_tools, tools=tools, verbose=verbose,return_intermediate_steps=True
             )
         else:

salesgpt/custom_invoke.py

@@ -2,6 +2,7 @@
 from langchain.chains.base import Chain
 from typing import Dict, Any, Optional
 # Corrected import path for RunnableConfig
+from langchain.agents import AgentExecutor
 from langchain_core.runnables import RunnableConfig, ensure_config
 from langchain_core.outputs import RunInfo
 from langchain.callbacks.manager import (
@@ -10,7 +11,7 @@
 from langchain_core.load.dump import dumpd
 import inspect
 
-class CustomChain(Chain):
+class CustomAgentExecutor(AgentExecutor):
     def invoke(
         self,
         input: Dict[str, Any],
@@ -79,4 +80,8 @@ def invoke(
         # Include intermediate steps in the final outputs
         final_outputs["intermediate_steps"] = intermediate_steps
 
-        return final_outputs
+        return final_outputs
+
+
+if __name__=="__main__":
+    agent = CustomAgentExecutor()

salesgpt/salesgptapi.py

@@ -79,19 +79,19 @@ def do(self, human_input=None):
                 agent_action = res_str[0]
                 tool,tool_input,log = agent_action.tool, agent_action.tool_input, agent_action.log
                 actions = re.search(r"Action: (.*?)[\n]*Action Input: (.*)",log)
-                action = actions.group(1)
-                action_input = actions.group(2)
+                action_input= actions.group(2)
+                action_output = ai_log['intermediate_steps'][1]['outputs']['intermediate_steps'][0][1]
             except:
-                tool,tool_input,action,action_input = "","","",""
+                tool,tool_input,action,action_input,action_output = "","","","",""
         else:   
-            tool,tool_input,action,action_input = "","","",""
+            tool,tool_input,action,action_input,action_output = "","","","",""
         return {
             "bot_name": reply.split(": ")[0],
             "response": reply.split(": ")[1].rstrip('<END_OF_TURN>'),
             "conversational_stage": self.sales_agent.current_conversation_stage,
             "tool": tool,
             "tool_input": tool_input,
-            "action": action,
+            "action_output": action_output,
             "action_input": action_input
         }