data_store system added

app.py

@@ -19,7 +19,11 @@ def new_chat():
         "assistant_state": "primary_assistant",
         "previous_state": "primary_assistant",
         "tts_audio": None,
-    }, []
+    }
+
+def button_pressed():
+   new_chat = new_chat()
+   return new_chat, None, [], None, None
 
 # Main processing function
 def run(audio, state):
@@ -39,21 +43,22 @@ def run(audio, state):
                     _printed = set()
                     assistant_states, assistant_messages = _print_event(value, _printed)
                     assistant_message = assistant_messages.content
-                    print("State:", assistant_states)
-                    print("Message:", assistant_messages)
+                    if assistant_messages.content != "":
+                        assistant_message_true = assistant_messages.content
+                    else:
+                        assistant_message_true = "..."
                     if assistant_states is None:
                         state["assistant_state"] = state["previous_state"]
                     else:
                         state["previous_state"] = assistant_states
                         state["assistant_state"] = assistant_states
-                    if assistant_states is None and "tool_call_id" not in assistant_messages:
+                    if assistant_message != "" and assistant_states is None and "tool_call_id" not in assistant_messages:
                         state["tts_audio"] = tts(assistant_message)
                     if assistant_message == "" and assistant_states is None:
-                        # print("\u001b[31mTool Call ID:\u001b[0m", assistant_messages.additional_kwargs)
                         state["tool_output"] = assistant_messages.additional_kwargs["tool_calls"]
 
         state["message_history"].append({"role": "user", "content": user_input})
-        state["message_history"].append({"role": "assistant", "content": assistant_message})
+        state["message_history"].append({"role": "assistant", "content": assistant_message_true})
         
         return (
             state["assistant_state"],
@@ -86,10 +91,10 @@ with gr.Blocks() as demo:
         outputs=[assistant_state_output, chatbot, tts_output, audio_input, tool_output],
     )
 
-    button = gr.Button("Start Chat/New Chat")
+    button = gr.Button("Click Here to Start a Chat")
     button.click(
-        fn=new_chat,
-        outputs=[chatbot_state, chatbot]  # Reset state
+        fn=button_pressed,
+        outputs=[chatbot_state, assistant_state_output, chatbot, tts_output, tool_output]  # Reset state
     )
-
+# new_chat()
 demo.launch(share=True)

erp_core/Tools/finalcial_management.py

@@ -1,26 +1,39 @@
 from langchain_core.tools import tool
-
+import csv
 @tool
-def register_purchase_request(user_info: str):
+def register_purchase_request(product: str, price: float):
     """Register a purchase request."""
+    try:
+        with open("purchase_requests.csv", "a") as f:    
+            writer = csv.writer(f)
+            writer.writerow([product, price])
+    except Exception as e:
+        pass
+
     return {
         "dialog_state": ["Financial_Management"],
         "messages": [
             {
                 "type": "text",
-                "content": "Registering a purchase request"
+                "content": f"Registering a purchase request for {product} at {price}"
             }
         ]
     }  
 @tool
-def view_expense_report(user_info: str):
+def view_expense_report(info: str):
     """View an expense report."""
+    try:
+        with open("expense_reports.csv", "r") as f:
+            reader = csv.reader(f)
+            expense_reports = list(reader)
+    except Exception as e:
+        expense_reports = []
     return {
         "dialog_state": ["Financial_Management"],
         "messages": [
             {
                 "type": "text",
-                "content": "Viewing an expense report"
+                "content": f"Expense report: {expense_reports}"
             }
         ]
     }

erp_core/_event.py

@@ -24,8 +24,8 @@ def create_tool_node_with_fallback(tools: list) -> dict:
 
 def _print_event(event: dict, _printed: set, max_length=1500):
     current_state = event.get("dialog_state")
-    # if current_state:
-    #     print("Currently in: ", current_state)
+    if current_state:
+        print("Currently in: ", current_state)
     message = event.get("messages")
     if message:
         if isinstance(message, list):
@@ -34,6 +34,6 @@ def _print_event(event: dict, _printed: set, max_length=1500):
             msg_repr = message.pretty_repr(html=True)
             if len(msg_repr) > max_length:
                 msg_repr = msg_repr[:max_length] + " ... (truncated)"
-            # print(msg_repr)
+            print(msg_repr)
             _printed.add(message.id)
     return current_state, message

erp_core/asr_and_tts.py

@@ -3,16 +3,16 @@ import os
 import tempfile
 import scipy.io.wavfile as wavfile
 from openai import OpenAI
-from elevenlabs import ElevenLabs, VoiceSettings, play, stream
+# from elevenlabs import ElevenLabs, VoiceSettings, play, stream
 
 # Load API keys from .env file
 # load_dotenv(override=True)
 openai_api_key = os.getenv('OPENAI_API_KEY')
-elevenlabs_api_key = os.getenv('ELEVENLABS_API_KEY')
+# elevenlabs_api_key = os.getenv('ELEVENLABS_API_KEY')
 
 # Initialize clients
 openai_client = OpenAI()
-elevenlabs_client = ElevenLabs(api_key=elevenlabs_api_key)
+# elevenlabs_client = ElevenLabs(api_key=elevenlabs_api_key)
 
 # Function to transcribe audio using OpenAI Whisper API
 def transcribe(audio):
@@ -40,23 +40,34 @@ def transcribe(audio):
 
 def tts(response_text):
     # Now, use ElevenLabs to convert the transcription text to speech
-    tts_response = elevenlabs_client.text_to_speech.convert(
-        voice_id="CwhRBWXzGAHq8TQ4Fs17",
-        optimize_streaming_latency="0",
-        output_format="mp3_22050_32",
-        text=response_text,
-        voice_settings=VoiceSettings(
-            stability=0.1,
-            similarity_boost=0.3,
-            style=0.2,
-        ),
-    )
+    # tts_response = elevenlabs_client.text_to_speech.convert(
+    #     voice_id="CwhRBWXzGAHq8TQ4Fs17",
+    #     optimize_streaming_latency="0",
+    #     output_format="mp3_22050_32",
+    #     text=response_text,
+    #     voice_settings=VoiceSettings(
+    #         stability=0.1,
+    #         similarity_boost=0.3,
+    #         style=0.2,
+    #     ),
+    # )
     
-    audio_file_path = "output_audio.mp3"
-    with open(audio_file_path, "wb") as audio_file:
-        for chunk in tts_response:
-            audio_file.write(chunk)
+    # audio_file_path = "output_audio.mp3"
+    # with open(audio_file_path, "wb") as audio_file:
+    #     for chunk in tts_response:
+    #         audio_file.write(chunk)
     
-    return audio_file_path
+    # return audio_file_path
+
+    tts_client = OpenAI()
+
+    response = tts_client.audio.speech.create(
+        model="tts-1",
+        voice="onyx",
+        input=response_text,
+    )
+
+    response.stream_to_file("output.mp3")
+    return "output.mp3"
 
 

erp_core/runnable/fm_prompt.py

@@ -17,6 +17,7 @@ financial_management_prompt = ChatPromptTemplate.from_messages(
             "While ready to call tool ask the user for confirmation once again by repeating the user's query. This is very important"
             "If the user confirms that it is correct only then call proper tool to solve user query. It is very important."
             "Remember that an issue isn't resolved until the relevant tool or method has successfully been used."
+            "Remember always provide a response while calling a tool or after calling a tool."
             "\nCurrent time: {time}."
             '\n\nIf the user needs help, and none of your tools are appropriate for it, then "CompleteOrEscalate" the dialog to the host assistant.'
             "Do not make up invalid tools or functions."

purchase_requests.csv

@@ -0,0 +1 @@
+Product,Price