upgraded ollama

lollms/server/endpoints/lollms_generator.py

@@ -8,7 +8,7 @@ description:
 
 """
 
-from fastapi import APIRouter
+from fastapi import APIRouter, Request
 from lollms.server.elf_server import LOLLMSElfServer
 from pydantic import BaseModel
 from starlette.responses import StreamingResponse
@@ -16,21 +16,7 @@ from lollms.types import MSG_TYPE
 from lollms.utilities import detect_antiprompt, remove_text_from_string
 from ascii_colors import ASCIIColors
 class GenerateRequest(BaseModel):
-    """
-    Data model for the Generate Request.
-
-    Attributes:
-    - text: str representing the input text prompt for text generation.
-    - n_predict: int representing the number of predictions to generate.
-    - stream: bool indicating whether to stream the generated text or not.
-    - temperature: float representing the temperature parameter for text generation.
-    - top_k: int representing the top_k parameter for text generation.
-    - top_p: float representing the top_p parameter for text generation.
-    - repeat_penalty: float representing the repeat_penalty parameter for text generation.
-    - repeat_last_n: int representing the repeat_last_n parameter for text generation.
-    - seed: int representing the seed for text generation.
-    - n_threads: int representing the number of threads for text generation.
-    """    
+ 
     text: str
     n_predict: int = 1024
     stream: bool = False
@@ -92,22 +78,35 @@ def get_generation_status():
 
 # ----------------------------------- Generation -----------------------------------------
 @router.post("/generate")
-def lollms_generate(request_data: GenerateRequest):
+def lollms_generate(request_data: Request):
     """
     Endpoint for generating text from prompts using the lollms fastapi server.
 
     Args:
-    - request_data: GenerateRequest object containing the input text, number of predictions, and stream flag.
+    Data model for the Generate Request.
 
+    Attributes:
+    - text: str representing the input text prompt for text generation.
+    - n_predict: int representing the number of predictions to generate.
+    - stream: bool indicating whether to stream the generated text or not.
+    - temperature: float representing the temperature parameter for text generation.
+    - top_k: int representing the top_k parameter for text generation.
+    - top_p: float representing the top_p parameter for text generation.
+    - repeat_penalty: float representing the repeat_penalty parameter for text generation.
+    - repeat_last_n: int representing the repeat_last_n parameter for text generation.
+    - seed: int representing the seed for text generation.
+    - n_threads: int representing the number of threads for text generation.
+
+    
     Returns:
     - If the elf_server binding is not None:
         - If stream is True, returns a StreamingResponse of generated text chunks.
         - If stream is False, returns the generated text as a string.
     - If the elf_server binding is None, returns None.
-    """    
-    text = request_data.text
-    n_predict = request_data.n_predict
-    stream = request_data.stream
+    """ 
+    text = request_data["text"]
+    n_predict = request_data.get("n_predict", 1024)
+    stream = request_data.get("stream", False)
     
     if elf_server.binding is not None:
         if stream:

lollms/services/ollama/.gitignore

@@ -0,0 +1 @@
+models.txt

lollms/services/ollama/lollms_ollama.py

@@ -42,31 +42,21 @@ def verify_ollama(lollms_paths:LollmsPaths):
     sd_folder = shared_folder / "auto_sd"
     return sd_folder.exists()
     
+
 def install_ollama():
     if platform.system() == 'Windows':
         if os.path.exists('C:\\Windows\\System32\\wsl.exe'):
-            subprocess.run(['wsl', 'bash', str(Path(__file__).parent / 'install.sh')])
+            subprocess.run(['wsl', 'bash', '-c', 'cp {} ~'.format(str(Path(__file__).parent / 'install.sh'))])
+            subprocess.run(['wsl', 'bash', '-c', 'cp {} ~'.format(str(Path(__file__).parent / 'run_ollama.sh'))])
+            subprocess.run(['wsl', 'bash', str(Path.home() / 'install.sh')])
         else:
             subprocess.run(['wsl', '--install', 'Ubuntu'])
-            subprocess.run(['wsl', 'bash', str(Path(__file__).parent / 'install.sh')])
+            subprocess.run(['wsl', 'bash', '-c', 'cp {} ~'.format(str(Path(__file__).parent / 'install.sh'))])
+            subprocess.run(['wsl', 'bash', '-c', 'cp {} ~'.format(str(Path(__file__).parent / 'run_ollama.sh'))])
+            subprocess.run(['wsl', 'bash', str(Path.home() / 'install.sh')])
     else:
         subprocess.run(['bash', str(Path(__file__).parent / 'install.sh')])
 
-def get_sd(lollms_paths:LollmsPaths):
-    root_dir = lollms_paths.personal_path
-    shared_folder = root_dir/"shared"
-    sd_folder = shared_folder / "auto_sd"
-    sd_script_path = sd_folder / "lollms_sd.py"
-    git_pull(sd_folder)
-    
-    if sd_script_path.exists():
-        ASCIIColors.success("lollms_sd found.")
-        ASCIIColors.success("Loading source file...",end="")
-        # use importlib to load the module from the file path
-        from lollms.services.sd.lollms_sd import LollmsSD
-        ASCIIColors.success("ok")
-        return LollmsSD
-
 class Service:
     def __init__(
                     self, 
@@ -74,7 +64,7 @@ class Service:
                     base_url="http://127.0.0.1:11434",
                     wait_max_retries = 5
                 ):
-        if base_url=="" or base_url=="http://127.0.0.1:7860":
+        if base_url=="" or base_url=="http://127.0.0.1:11434":
             base_url = None
         # Get the current directory
         lollms_paths = app.lollms_paths
@@ -93,6 +83,14 @@ class Service:
         if not self.wait_for_service(1,False) and base_url is None:
             ASCIIColors.info("Loading ollama service")
 
+        # run ollama
+        if platform.system() == 'Windows':
+            if os.path.exists('C:\\Windows\\System32\\wsl.exe'):
+                subprocess.run(['wsl', 'bash', str(Path(__file__).parent / 'run_ollama.sh')])
+        else:
+            subprocess.run(['bash', str(Path(__file__).parent / 'install.sh')])
+                        
+
         # Wait until the service is available at http://127.0.0.1:7860/
         self.wait_for_service(max_retries=wait_max_retries)
 

lollms/services/ollama/run_ollama.sh

@@ -1,2 +1,23 @@
-ollama serve&
-ollama run mistral
+#!/bin/bash
+
+# Set the OLLAMA_HOST address
+OLLAMA_HOST="0.0.0.0:11434"
+
+# Start the OLLAMA server
+ollama serve &
+
+# Check if models.txt exists
+if [ ! -f models.txt ]; then
+    # Create models.txt and add "mixtral" to it
+    echo "mixtral" > models.txt
+fi
+
+# Read the models from the file
+while IFS= read -r model
+do
+    # Run each model in the background
+    ollama run "$model" &
+done < models.txt
+
+# Wait for all background processes to finish
+wait