Ty Fiero
10 months ago
committed by
GitHub
commit
f9cc6bb665
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import sys
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import os
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import platform
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import subprocess
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import time
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import inquirer
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from interpreter import interpreter
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def select_local_model():
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# START OF LOCAL MODEL PROVIDER LOGIC
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interpreter.display_message("> 01 is compatible with several local model providers.\n")
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# Define the choices for local models
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choices = [
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"Ollama",
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"LM Studio",
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# "Jan",
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]
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# Use inquirer to let the user select an option
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questions = [
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inquirer.List(
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"model",
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message="Which one would you like to use?",
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choices=choices,
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),
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]
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answers = inquirer.prompt(questions)
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selected_model = answers["model"]
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if selected_model == "LM Studio":
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interpreter.display_message(
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"""
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To use use 01 with **LM Studio**, you will need to run **LM Studio** in the background.
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1. Download **LM Studio** from [https://lmstudio.ai/](https://lmstudio.ai/), then start it.
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2. Select a language model then click **Download**.
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3. Click the **<->** button on the left (below the chat button).
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4. Select your model at the top, then click **Start Server**.
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Once the server is running, you can begin your conversation below.
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"""
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)
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time.sleep(1)
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interpreter.llm.api_base = "http://localhost:1234/v1"
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interpreter.llm.max_tokens = 1000
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interpreter.llm.context_window = 8000
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interpreter.llm.api_key = "x"
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elif selected_model == "Ollama":
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try:
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# List out all downloaded ollama models. Will fail if ollama isn't installed
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result = subprocess.run(["ollama", "list"], capture_output=True, text=True, check=True)
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lines = result.stdout.split('\n')
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names = [line.split()[0].replace(":latest", "") for line in lines[1:] if line.strip()] # Extract names, trim out ":latest", skip header
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# If there are no downloaded models, prompt them to download a model and try again
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if not names:
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time.sleep(1)
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interpreter.display_message(f"\nYou don't have any Ollama models downloaded. To download a new model, run `ollama run <model-name>`, then start a new 01 session. \n\n For a full list of downloadable models, check out [https://ollama.com/library](https://ollama.com/library) \n")
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print("Please download a model then try again\n")
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time.sleep(2)
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sys.exit(1)
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# If there are models, prompt them to select one
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else:
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time.sleep(1)
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interpreter.display_message(f"**{len(names)} Ollama model{'s' if len(names) != 1 else ''} found.** To download a new model, run `ollama run <model-name>`, then start a new 01 session. \n\n For a full list of downloadable models, check out [https://ollama.com/library](https://ollama.com/library) \n")
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# Create a new inquirer selection from the names
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name_question = [
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inquirer.List('name', message="Select a downloaded Ollama model", choices=names),
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]
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name_answer = inquirer.prompt(name_question)
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selected_name = name_answer['name'] if name_answer else None
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# Set the model to the selected model
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interpreter.llm.model = f"ollama/{selected_name}"
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interpreter.display_message(f"\nUsing Ollama model: `{selected_name}` \n")
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time.sleep(1)
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# If Ollama is not installed or not recognized as a command, prompt the user to download Ollama and try again
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except (subprocess.CalledProcessError, FileNotFoundError) as e:
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print("Ollama is not installed or not recognized as a command.")
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time.sleep(1)
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interpreter.display_message(f"\nPlease visit [https://ollama.com/](https://ollama.com/) to download Ollama and try again\n")
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time.sleep(2)
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sys.exit(1)
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# elif selected_model == "Jan":
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# interpreter.display_message(
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# """
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# To use 01 with **Jan**, you will need to run **Jan** in the background.
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# 1. Download **Jan** from [https://jan.ai/](https://jan.ai/), then start it.
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# 2. Select a language model from the "Hub" tab, then click **Download**.
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# 3. Copy the ID of the model and enter it below.
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# 3. Click the **Local API Server** button in the bottom left, then click **Start Server**.
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# Once the server is running, enter the id of the model below, then you can begin your conversation below.
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# """
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# )
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# interpreter.llm.api_base = "http://localhost:1337/v1"
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# interpreter.llm.max_tokens = 1000
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# interpreter.llm.context_window = 3000
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# time.sleep(1)
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# # Prompt the user to enter the name of the model running on Jan
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# model_name_question = [
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# inquirer.Text('jan_model_name', message="Enter the id of the model you have running on Jan"),
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# ]
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# model_name_answer = inquirer.prompt(model_name_question)
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# jan_model_name = model_name_answer['jan_model_name'] if model_name_answer else None
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# # interpreter.llm.model = f"jan/{jan_model_name}"
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# interpreter.llm.model = ""
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# interpreter.display_message(f"\nUsing Jan model: `{jan_model_name}` \n")
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# time.sleep(1)
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# Set the system message to a minimal version for all local models.
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# Set offline for all local models
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interpreter.offline = True
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