From f91ab1d72988d3495275d1f6801cc3c8c280456f Mon Sep 17 00:00:00 2001
From: ImpactFrames <jvoxel@gmail.com>
Date: Fri, 15 Nov 2024 18:13:41 +0000
Subject: [PATCH] Delete get_models.py

---
 get_models.py | 137 --------------------------------------------------
 1 file changed, 137 deletions(-)
 delete mode 100644 get_models.py

diff --git a/get_models.py b/get_models.py
deleted file mode 100644
index e564277..0000000
--- a/get_models.py
+++ /dev/null
@@ -1,137 +0,0 @@
-import requests
-import json
-
-from .get_api import get_api_key
-
-def get_models(engine, base_ip, port):
-        
-        if engine == "ollama":
-            api_url = f'http://{base_ip}:{port}/api/tags'
-            try:
-                response = requests.get(api_url)
-                response.raise_for_status()
-                models = [model['name'] for model in response.json().get('models', [])]
-                return models
-            except Exception as e:
-                print(f"Failed to fetch models from Ollama: {e}")
-                return []
-            
-        elif engine == "lmstudio":
-            api_url = f'http://{base_ip}:{port}/v1/models'
-            try:
-                response = requests.get(api_url)
-                if response.status_code == 200:
-                    data = response.json()
-                    models = [model['id'] for model in data['data']]
-                    return models
-                else:
-                    print(f"Failed to fetch models from LM Studio. Status code: {response.status_code}")
-                    return []
-            except requests.exceptions.RequestException as e:
-                print(f"Error connecting to LM Studio server: {e}")
-                return []
-            
-        elif engine == "textgen":
-            api_url = f'http://{base_ip}:{port}/v1/internal/model/list'
-            try:
-                response = requests.get(api_url)
-                response.raise_for_status()
-                models = response.json()['model_names']
-                return models
-            except Exception as e:
-                print(f"Failed to fetch models from text-generation-webui: {e}")
-                return []
-            
-        elif engine == "kobold":
-            api_url = f'http://{base_ip}:{port}/api/v1/model'
-            try:
-                response = requests.get(api_url)
-                response.raise_for_status()
-                model = response.json()['result']
-                return [model]
-            except Exception as e:
-                print(f"Failed to fetch models from Kobold: {e}")
-                return []
-        
-        elif engine == "llamacpp":
-            api_url = f'http://{base_ip}:{port}/v1/models'
-            try:
-                response = requests.get(api_url)
-                response.raise_for_status()
-                models = [model["id"] for model in response.json()["data"]]
-                return models
-            except Exception as e:
-                print(f"Failed to fetch models from llama.cpp: {e}")
-                return []
-
-        elif engine == "vllm":
-            api_url = f"http://{base_ip}:{port}/v1/models"
-            try:
-                response = requests.get(api_url)
-                response.raise_for_status()
-                # Adapt this based on vLLM's actual API response structure 
-                models = [model['id'] for model in response.json()['data']] 
-                return models
-            except Exception as e:
-                print(f"Failed to fetch models from vLLM: {e}")
-                return []
-        
-        elif engine == "openai":
-            api_key = get_api_key("OPENAI_API_KEY", engine)
-            headers = {
-                "Authorization": f"Bearer {api_key}",
-                "Content-Type": "application/json"
-            }
-            api_url = "https://api.openai.com/v1/models"
-            try:
-                response = requests.get(api_url, headers=headers)
-                response.raise_for_status()
-                models = [model["id"] for model in response.json()["data"]]
-                return models
-            except Exception as e:
-                print(f"Failed to fetch models from OpenAI: {e}")
-                return []
-        
-        elif engine == "mistral":
-            api_key = get_api_key("MISTRAL_API_KEY", engine)
-            headers = {
-                "Authorization": f"Bearer {api_key}",
-                "Content-Type": "application/json"
-            }
-            api_url = "https://api.mistral.ai/v1/models"
-            try:
-                response = requests.get(api_url, headers=headers)
-                response.raise_for_status()
-                models = [model["id"] for model in response.json()["data"]]
-                return models
-            except Exception as e:
-                print(f"Failed to fetch models from Mistral: {e}")
-                return []
-
-        elif engine == "groq":
-            api_key = get_api_key("GROQ_API_KEY", engine)
-            headers = {
-                "Authorization": f"Bearer {api_key}",
-                "Content-Type": "application/json"
-            }
-            api_url = "https://api.groq.com/openai/v1/models"
-            try:
-                response = requests.get(api_url, headers=headers)
-                response.raise_for_status()
-                models = [model["id"] for model in response.json()["data"]]
-                return models
-            except Exception as e:
-                print(f"Failed to fetch models from GROQ: {e}")
-                return []
-        
-        
-        elif engine == "anthropic":
-            return ["claude-3-5-sonnet-20240620", "claude-3-opus-20240229", "claude-3-sonnet-20240229", "claude-3-haiku-20240307"]
-        
-        elif engine == "gemini":
-            return ["gemini-1.5-flash", "gemini-1.5-pro-latest", "gemini-1.5-latest", "gemini-pro", "gemini-pro-vision"] 
-        
-        else:
-            print(f"Unsupported engine - {engine}")
-            return []
-