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