Merge pull request #120 from tyfiero/Add-interactive-local-mode

Local mode fixes

software/poetry.lock

@@ -9241,4 +9241,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<3.12"
-content-hash = "6b18421685454d8e4824c4639e3982954de10f355a3ee423c1f63a0325d935e7"
+content-hash = "348676102c6be6a2bf6b2cb8b2f75f0594b8f1e3ff19efff248c5862490e73a0"

software/pyproject.toml

@@ -32,6 +32,7 @@ open-interpreter = {extras = ["os"], version = "^0.2.3"}
 dateparser = "^1.2.0"
 pytimeparse = "^1.1.8"
 python-crontab = "^3.0.0"
+inquirer = "^3.2.4"
 
 [build-system]
 requires = ["poetry-core"]

software/source/server/utils/local_mode.py

@@ -0,0 +1,137 @@
+import sys
+import os
+import platform
+import subprocess
+import time
+import inquirer
+from interpreter import interpreter
+
+
+def select_local_model():
+
+    # START OF LOCAL MODEL PROVIDER LOGIC
+    interpreter.display_message("> 01 is compatible with several local model providers.\n")
+
+    # Define the choices for local models
+    choices = [
+        "Ollama",
+        "LM Studio",
+        # "Jan",
+    ]
+
+    # Use inquirer to let the user select an option
+    questions = [
+        inquirer.List(
+            "model",
+            message="Which one would you like to use?",
+            choices=choices,
+        ),
+    ]
+    answers = inquirer.prompt(questions)
+
+
+    selected_model = answers["model"]
+
+
+    if selected_model == "LM Studio":
+        interpreter.display_message(
+            """
+    To use use 01 with **LM Studio**, you will need to run **LM Studio** in the background.
+
+    1. Download **LM Studio** from [https://lmstudio.ai/](https://lmstudio.ai/), then start it.
+    2. Select a language model then click **Download**.
+    3. Click the **<->** button on the left (below the chat button).
+    4. Select your model at the top, then click **Start Server**.
+
+
+    Once the server is running, you can begin your conversation below.
+
+    """
+        )
+        time.sleep(1)
+        
+        interpreter.llm.api_base = "http://localhost:1234/v1"
+        interpreter.llm.max_tokens = 1000
+        interpreter.llm.context_window = 8000
+        interpreter.llm.api_key = "x"
+
+    elif selected_model == "Ollama":
+        try:
+            
+            # List out all downloaded ollama models. Will fail if ollama isn't installed
+            result = subprocess.run(["ollama", "list"], capture_output=True, text=True, check=True)
+            lines = result.stdout.split('\n')
+            names = [line.split()[0].replace(":latest", "") for line in lines[1:] if line.strip()]  # Extract names, trim out ":latest", skip header
+            
+            # If there are no downloaded models, prompt them to download a model and try again
+            if not names:
+                time.sleep(1)
+                
+                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")
+                
+                print("Please download a model then try again\n")
+                time.sleep(2)
+                sys.exit(1)
+            
+            # If there are models, prompt them to select one
+            else:
+                time.sleep(1)
+                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")
+
+                # Create a new inquirer selection from the names
+                name_question = [
+                    inquirer.List('name', message="Select a downloaded Ollama model", choices=names),
+                ]
+                name_answer = inquirer.prompt(name_question)
+                selected_name = name_answer['name'] if name_answer else None
+                
+                # Set the model to the selected model
+                interpreter.llm.model = f"ollama/{selected_name}"
+                interpreter.display_message(f"\nUsing Ollama model: `{selected_name}` \n")
+                time.sleep(1)
+            
+        # If Ollama is not installed or not recognized as a command, prompt the user to download Ollama and try again
+        except (subprocess.CalledProcessError, FileNotFoundError) as e:
+            print("Ollama is not installed or not recognized as a command.")
+            time.sleep(1)
+            interpreter.display_message(f"\nPlease visit [https://ollama.com/](https://ollama.com/) to download Ollama and try again\n")
+            time.sleep(2)
+            sys.exit(1)
+            
+    # elif selected_model == "Jan":
+    #     interpreter.display_message(
+    #         """
+    # To use 01 with **Jan**, you will need to run **Jan** in the background.
+
+    # 1. Download **Jan** from [https://jan.ai/](https://jan.ai/), then start it.
+    # 2. Select a language model from the "Hub" tab, then click **Download**.
+    # 3. Copy the ID of the model and enter it below.
+    # 3. Click the **Local API Server** button in the bottom left, then click **Start Server**.
+
+
+    # Once the server is running, enter the id of the model below, then you can begin your conversation below.
+
+    # """
+    #     )
+    #     interpreter.llm.api_base = "http://localhost:1337/v1"
+    #     interpreter.llm.max_tokens = 1000
+    #     interpreter.llm.context_window = 3000
+    #     time.sleep(1)
+        
+    #     # Prompt the user to enter the name of the model running on Jan
+    #     model_name_question = [
+    #         inquirer.Text('jan_model_name', message="Enter the id of the model you have running on Jan"),
+    #     ]
+    #     model_name_answer = inquirer.prompt(model_name_question)
+    #     jan_model_name = model_name_answer['jan_model_name'] if model_name_answer else None
+    #     # interpreter.llm.model = f"jan/{jan_model_name}"
+    #     interpreter.llm.model = ""
+    #     interpreter.display_message(f"\nUsing Jan model: `{jan_model_name}` \n")
+    #     time.sleep(1)
+        
+
+    # Set the system message to a minimal version for all local models.
+    # Set offline for all local models
+    interpreter.offline = True
+
+    

software/start.py

@@ -7,6 +7,7 @@ import os
 import importlib
 from source.server.tunnel import create_tunnel
 from source.server.server import main
+from source.server.utils.local_mode import select_local_model
 
 import signal
 app = typer.Typer()
@@ -93,6 +94,7 @@ def _run(
         tts_service = "piper"
         # llm_service = "llamafile"
         stt_service = "local-whisper"
+        select_local_model()
     
     if not server_url:
         server_url = f"{server_host}:{server_port}"