Update agents.py

agents.py

@@ -49,7 +49,7 @@ class Llama2:
             self.cont = st.empty()        
             self.status = self.cont.status(label="Fireworks Llama2", state="complete", expanded=False)
         
-    async def chatFireworks(self, system_instruction, question):
+    async def chatFireworks(self, instruction, question):
 
         fireworks.client.api_key = self.fireworksAPI
        
@@ -71,13 +71,18 @@ class Llama2:
                 else:
                     generated_responses.append(message[2])
 
+            # Create a list of message dictionaries for the conversation history
+            conversation_history = []
+            for user_input, generated_response in zip(past_user_inputs, generated_responses):
+                conversation_history.append({"role": "user", "content": str(user_input)})
+                conversation_history.append({"role": "assistant", "content": str(generated_response)})
+
             # Prepare data to send to the chatgpt-api.shn.hk           
             response = fireworks.client.ChatCompletion.create(
                 model="accounts/fireworks/models/llama-v2-7b-chat",
                 messages=[
-                {"role": "system", "content": system_instruction},
-                *[{"role": "user", "content": input} for input in past_user_inputs],
-                *[{"role": "assistant", "content": response} for response in generated_responses],
+                {"role": "system", "content": instruction},
+                conversation_history,
                 {"role": "user", "content": question}
                 ],
                 stream=False,
@@ -524,6 +529,12 @@ class Copilot:
                 else:
                     generated_responses.append(message[2])
                         
+            # Create a list of message dictionaries for the conversation history
+            conversation_history = []
+            for user_input, generated_response in zip(past_user_inputs, generated_responses):
+                conversation_history.append({"role": "user", "content": str(user_input)})
+                conversation_history.append({"role": "assistant", "content": str(generated_response)})
+
             response = await g4f.ChatCompletion.create_async(
                 model=g4f.models.gpt_4,
                 provider=g4f.Provider.Bing,
@@ -533,7 +544,7 @@ class Copilot:
                 *[{"role": "assistant", "content": message} for message in generated_responses],
                 {"role": "user", "content": question}
                 ])
-        
+
             answer = f"Bing/Copilot: {response}"
             print(answer)
             return answer
@@ -972,13 +983,19 @@ class ChatGPT:
                 else:
                     generated_responses.append(message[2])
                         
+            # Create a list of message dictionaries for the conversation history
+            conversation_history = []
+            for user_input, generated_response in zip(past_user_inputs, generated_responses):
+                conversation_history.append({"role": "user", "content": str(user_input)})
+                conversation_history.append({"role": "assistant", "content": str(generated_response)})
+            
             response = await g4f.ChatCompletion.create_async(
                 model="gpt-3.5-turbo",
-                provider=g4f.Provider.Koala,
+                provider=g4f.Provider.ChatgptX,
                 messages=[
                 {"role": "system", "content": instruction},
-                *[{"role": "user", "content": message} for message in past_user_inputs],
-                *[{"role": "assistant", "content": message} for message in generated_responses],
+                *[{"role": "user", "content": str(message)} for message in past_user_inputs],
+                *[{"role": "assistant", "content": str(message)} for message in generated_responses],
                 {"role": "user", "content": question}
                 ])
         
@@ -1009,7 +1026,13 @@ class ChatGPT:
                     past_user_inputs.append(message[2])
                 else:
                     generated_responses.append(message[2])
-                       
+
+            # Create a list of message dictionaries for the conversation history
+            conversation_history = []
+            for user_input, generated_response in zip(past_user_inputs, generated_responses):
+                conversation_history.append({"role": "user", "content": str(user_input)})
+                conversation_history.append({"role": "assistant", "content": str(generated_response)})
+
             url = f"https://api.pawan.krd/v1/chat/completions"        
       
             headers = {
@@ -1021,14 +1044,15 @@ class ChatGPT:
                 "max_tokens": 2000,
                 "messages": [
                 {"role": "system", "content": instruction},
-                {"role": "user", "content": str(past_user_inputs[-1])},
-                {"role": "assistant", "content": str(generated_responses[-1])},
+                *[{"role": "user", "content": str(message)} for message in past_user_inputs],
+                *[{"role": "assistant", "content": str(message)} for message in generated_responses],
                 {"role": "user", "content": question}
                 ]
             }
 
             response = requests.request("POST", url, json=payload, headers=headers)
             response_data = response.json()
+            print(response_data)
             generated_answer = response_data["choices"][0]["message"]["content"]
             answer = f"GPT-3,5: {generated_answer}"
             print(answer)
@@ -1410,13 +1434,13 @@ class ChatGPT:
 
     async def askLlama(self, question):
         api = "WZGOkHQbZULIzA6u83kyLGBKPigs1HmK9Ec8DEKmGOtu45zx"
-        llama = AgentLlama2(api)
+        llama = Llama2(api)
         response = await llama.handleInput(question)
         print(response)
         return response
 
     async def askBing(self, question):
-        bing = AgentBing()
+        bing = Copilot()
         response = await bing.handleInput(question)
         print(response)
         return response
@@ -1470,20 +1494,25 @@ class Claude3:
 
             for message in messages:
                 if message[1] == 'client':
-                    past_user_inputs.append(message[2])
+                    past_user_inputs.append(str(message[2]))
                 else:
-                    generated_responses.append(message[2])
+                    generated_responses.append(str(message[2]))
+
+            # Create a list of message dictionaries for the conversation history
+            conversation_history = []
+            for user_input, generated_response in zip(past_user_inputs, generated_responses):
+                conversation_history.append({"role": "user", "content": [{"type": "text", "text": str(user_input)}]})
+                conversation_history.append({"role": "assistant", "content": [{"type": "text", "text": str(generated_response)}]})
+
+            # Add the current question to the conversation history
+            conversation_history.append({"role": "user", "content": [{"type": "text", "text": question}]})
 
             message = client.messages.create(
                 model="claude-3-opus-20240229",
                 max_tokens=2500,
                 temperature=0,
-                system = instruction,
-                messages=[
-                    {"role": "user", "content": [{"type": "text", "text": str(past_user_inputs[-1])}]},
-                    {"role": "assistant", "content": [{"type": "text", "text": str(generated_responses[-1])}]},
-                    {"role": "user", "content": [{"type": "text", "text": question}]}
-                ]
+                system=instruction,
+                messages=conversation_history
             )
 
             print(message.content)
@@ -1492,7 +1521,7 @@ class Claude3:
 
         except Exception as e:
             print(f"Error: {e}")
-
+            
     async def handlerClaude(self, websocket):
         self.stat.empty()
         self.cont.empty()
@@ -1915,18 +1944,19 @@ class ForefrontAI:
                 else:
                     generated_responses.append(message[2])
 
-            last_msg = past_user_inputs[-1]
-            last_response = generated_responses[-1]
-            message = f'{{"client input: {last_msg}"}}'
-            responsed = f'{{"server answer: {last_response}"}}' 
+            # Create a list of message dictionaries for the conversation history
+            conversation_history = []
+            for user_input, generated_response in zip(past_user_inputs, generated_responses):
+                conversation_history.append({"role": "user", "content": str(user_input)})
+                conversation_history.append({"role": "assistant", "content": str(generated_response)})
 
             # Construct the message sequence for the chat model
             response = ff.chat.completions.create(
                 messages=[
-                    {"role": "system", "content": instruction},
-                    {"role": "user", "content": message},
-                    {"role": "assistant", "content": responsed},
-                    {"role": "user", "content": question}
+                {"role": "system", "content": instruction},
+                *[{"role": "user", "content": message} for message in past_user_inputs],
+                *[{"role": "assistant", "content": message} for message in generated_responses],
+                {"role": "user", "content": question}
                 ],
                 stream=False,
                 model="forefront/neural-chat-7b-v3-1-chatml",  # Replace with the actual model name
@@ -2699,13 +2729,13 @@ class CharacterAI:
 
     async def askLlama(self, question):
         api = "WZGOkHQbZULIzA6u83kyLGBKPigs1HmK9Ec8DEKmGOtu45zx"
-        llama = AgentLlama2(api)
+        llama = Llama2(api)
         response = await llama.handleInput(question)
         print(response)
         return response
 
     async def askBing(self, question):
-        bing = AgentBing()
+        bing = Copilot()
         response = await bing.handleInput(question)
         print(response)
         return response
@@ -3110,13 +3140,13 @@ class Chaindesk:
 
     async def askLlama(self, question):
         api = "WZGOkHQbZULIzA6u83kyLGBKPigs1HmK9Ec8DEKmGOtu45zx"
-        llama = AgentLlama2(api)
+        llama = Llama2(api)
         response = await llama.handleInput(question)
         print(response)
         return response
 
     async def askBing(self, question):
-        bing = AgentBing()
+        bing = Copilot()
         response = await bing.handleInput(question)
         print(response)
         return response
@@ -3494,7 +3524,7 @@ class Flowise:
             return characterID 
 
         else:
-            response = f"You didn't choose any character to establish a connection with. Do you want try again or maybe use some other copmmand-fuunction?"   
+            response = f"You didn't choose any character to establish a connection with. Do you want try once again or maybe use some other copmmand-fuunction?"   
             print(response)
             await self.handleInput(respoonse)
 
@@ -3521,13 +3551,13 @@ class Flowise:
 
     async def askLlama(self, question):
         api = "WZGOkHQbZULIzA6u83kyLGBKPigs1HmK9Ec8DEKmGOtu45zx"
-        llama = AgentLlama2(api)
+        llama = Llama2(api)
         response = await llama.handleInput(question)
         print(response)
         return response
 
     async def askBing(self, question):
-        bing = AgentBing()
+        bing = Copilot()
         response = await bing.handleInput(question)
         print(response)
         return response