gpt-o1-mini and mistral-nemo
You'll have to do `pip install --upgrade -r requirements.txt` to install latest: * mistralai client * openai client modified: app.py
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Russell Ballestrini
parent
9246565407
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e310217166
2 changed files with 28 additions and 29 deletions
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@ -104,13 +104,15 @@ To interact with the various language models, you can use the following commands
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- For GPT-4o, send a message with ``gpt-4`` and include your prompt.
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- For GPT-4o cheapest version, send a message with ``gpt-4o-2024-08-06`` and include your prompt.
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- For GPT-4o-mini, send a message with ``gpt-mini`` and include your prompt.
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- For GPT-o1-mini, send a message with ``gpt-o1-mini`` and include your prompt.
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- For Claude-haiku, send a message with ``claude-haiku`` and include your prompt.
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- For Claude-sonnet, send a message with ``claude-sonnet`` and include your prompt.
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- For Claude-opus, send a message with ``claude-opus`` and include your prompt.
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- For Mistral-tiny, send a message with ``mistral-tiny`` and include your prompt.
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- For Mistral-small, send a message with ``mistral-small`` and include your prompt.
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- For Mistral-medium, send a message with ``mistral-medium`` and include your prompt.
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- For Mistral-medium, send a message with ``mistral-large`` and include your prompt.
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- For Mistral-large, send a message with ``mistral-large`` and include your prompt.
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- For Mistral-nemo, send a message with ``mistral-nemo`` and include your prompt.
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- For Together OpenChat, send a message with ``together/openchat`` and include your prompt.
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- For Together Mistral, send a message with ``together/mistral`` and include your prompt.
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- For Together Mixtral, send a message with ``together/mixtral`` and include your prompt.
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53
app.py
53
app.py
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@ -24,8 +24,7 @@ from flask_sqlalchemy import SQLAlchemy
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from sqlalchemy.exc import InvalidRequestError
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from groq import Groq
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from mistralai.client import MistralClient
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from mistralai.models.chat_completion import ChatMessage
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from mistralai import Mistral
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from openai import OpenAI
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app = Flask(__name__)
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@ -55,6 +54,7 @@ system_users = [
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"gpt-4-1106-preview",
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"gpt-4-turbo-preview",
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"gpt-4-turbo",
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"o1-mini",
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"mistral",
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"mistral-tiny",
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"mistral-small",
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@ -63,6 +63,7 @@ system_users = [
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"mistralai/Mixtral-8x7B-v0.1",
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"mistralai/Mistral-7B-Instruct-v0.1",
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"mixtral-8x7b-32768",
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"open-mistral-nemo",
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"llama2-70b-4096",
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"llama3-70b-8192",
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"gemma-7b-it",
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@ -95,6 +96,7 @@ HELP_MESSAGE = """
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- `gpt-4`: For GPT-4, send a message with `gpt-4` and include your prompt.
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- `gpt-4o-2024-08-06`: For the cheapest version of GPT-4o, send a message with `gpt-4o-2024-08-06` and include your prompt.
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- `gpt-mini`: For GPT-4o-mini, send a message with `gpt-mini` and include your prompt.
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- `gpt-o1-mini`: For GPT-4o-mini, send a message with `gpt-mini` and include your prompt.
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- `claude-haiku`: For Claude-haiku, send a message with `claude-haiku` and include your prompt.
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- `claude-sonnet`: For Claude-sonnet, send a message with `claude-sonnet` and include your prompt.
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- `claude-opus`: For Claude-opus, send a message with `claude-opus` and include your prompt.
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@ -102,6 +104,7 @@ HELP_MESSAGE = """
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- `mistral-small`: For Mistral-small, send a message with `mistral-small` and include your prompt.
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- `mistral-medium`: For Mistral-medium, send a message with `mistral-medium` and include your prompt.
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- `mistral-large`: For Mistral-large, send a message with `mistral-large` and include your prompt.
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- `mistral-nemo`: For Mistral-large, send a message with `mistral-nemo` and include your prompt.
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- `together/openchat`: For Together OpenChat, send a message with `together/openchat` and include your prompt.
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- `together/mistral`: For Together Mistral, send a message with `together/mistral` and include your prompt.
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- `together/mixtral`: For Together Mixtral, send a message with `together/mixtral` and include your prompt.
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@ -543,7 +546,13 @@ def handle_message(data):
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# model_name="gpt-4o",
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model_name="gpt-4o-2024-08-06",
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)
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if "gpt-o1-mini" in data["message"]:
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gevent.spawn(
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chat_gpt,
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data["username"],
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room.name,
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model_name="o1-mini",
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)
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if "gpt-mini" in data["message"]:
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gevent.spawn(
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chat_gpt,
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@ -572,6 +581,13 @@ def handle_message(data):
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room.name,
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model_name="mistral-medium",
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)
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if "mistral-nemo" in data["message"]:
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gevent.spawn(
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chat_mistral,
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data["username"],
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room.name,
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model_name="open-mistral-nemo",
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)
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if "mistral-large" in data["message"]:
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gevent.spawn(
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chat_mistral,
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@ -1011,11 +1027,6 @@ def chat_mistral(username, room_name, model_name="mistral-tiny"):
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combined_content = ""
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last_role = None
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# Function to add a ChatMessage to the history
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def add_message(role, content):
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if content:
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chat_history.append(ChatMessage(role=role, content=content))
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# Iterate over messages to combine consecutive assistant messages
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for msg in reversed(last_messages):
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if msg.is_base64_image():
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@ -1023,24 +1034,10 @@ def chat_mistral(username, room_name, model_name="mistral-tiny"):
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current_role = "assistant" if msg.username in system_users else "user"
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formatted_content = f"{msg.username}: {msg.content}"
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if current_role == last_role and current_role == "assistant":
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# Combine messages if the current and last messages are from the assistant
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combined_content += "\n" + formatted_content
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else:
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# Add the previous combined message to chat history if roles switch
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add_message(last_role, combined_content)
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combined_content = formatted_content # Start new combination
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last_role = current_role
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# Add the last combined message to the chat history
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add_message(last_role, combined_content)
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# Remove trailing assistant messages until a user message is found.
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while chat_history and chat_history[-1].role == "assistant":
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chat_history.pop()
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chat_history.append({"role": current_role, "content": formatted_content})
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# Initialize the Mistral client
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mistral_client = MistralClient(api_key=os.environ["MISTRAL_API_KEY"])
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mistral_client = Mistral(api_key=os.environ["MISTRAL_API_KEY"])
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buffer = "" # Content buffer for accumulating the chunks
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@ -1055,17 +1052,17 @@ def chat_mistral(username, room_name, model_name="mistral-tiny"):
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try:
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# Use the Mistral client to stream the chat completion
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for chunk in mistral_client.chat_stream(
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for chunk in mistral_client.chat.stream(
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model=model_name, messages=chat_history
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):
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content_chunk = chunk.data.choices[0].delta.content
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# Check if there has been a cancellation request, break if there is.
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if cancellation_requests.get(msg_id):
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del cancellation_requests[msg_id]
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break
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content_chunk = chunk.choices[0].delta.content
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if content_chunk:
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if chunk:
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buffer += content_chunk # Accumulate content
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if first_chunk:
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