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Merge pull request #2 from Isulion/revert-1-main

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Revert "new node for you"
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Isulion
2024-10-31 19:23:39 +01:00
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parent 5f73a0efd1 926c00de0f
commit 6f6fdf150b
19 changed files with 71 additions and 7909 deletions
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README.md
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@@ -1,18 +1,16 @@
# ComfyUI Isulion LLM Chain
An advanced ComfyUI extension that enables multi-agent LLM conversations using Ollama models.
# ComfyUI_Isulion Random Prompt Generator
![Example Workflow](https://github.com/user-attachments/assets/ba6d7eaa-c068-4f88-a2c9-fb07aa95052b)
--------------
ComfyUI Nodes that generate prompts with the help of LLM from local or remote Ollama.
--------------
## 🌟 Features
- Create complex multi-agent conversations using different LLM personas
- Support for local Ollama models
- Flexible chain configurations from simple to complex (3-agent, 5-agent, or 10-agent chains)
- Each agent can be assigned unique roles and perspectives
- Real-time conversation visualization
-system prompt for each agent/node
# Requirement :
Recomanded environnement variables :
- OLLAMA_KEEP_ALIVE 0
- OLLAMA_ORIGINS *
ComfyUI installed node :
- Ollama_generator
__init__.py
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@@ -1,15 +1,13 @@
from .isulion_prompt_generator import IsulionPromptGenerator
from .isulion_OllamaGenerate import OllamaGenerate
from .ixulion_ollamaModelSelect import OllamaModelSelector
NODE_CLASS_MAPPINGS = {
"IsulionPromptGenerator": IsulionPromptGenerator,
"OllamaGenerate": OllamaGenerate,
"OllamaModelSelector": OllamaModelSelector
}
NODE_DISPLAY_NAME_MAPPINGS = {
"IsulionPromptGenerator": "Isulion Prompt Generator",
"OllamaGenerate": "Ollama Generate",
"OllamaModelSelector": "Ixulion Ollama Model Selector"
}
from .isulion_prompt_generator import IsulionPromptGenerator
from .isulion_OllamaGenerate import OllamaGenerate
NODE_CLASS_MAPPINGS = {
"IsulionPromptGenerator": IsulionPromptGenerator,
"OllamaGenerate": OllamaGenerate
}
# Optional: Provide a custom display name for the node
NODE_DISPLAY_NAME_MAPPINGS = {
"IsulionPromptGenerator": "Isulion Prompt Generator",
"OllamaGenerate": "Isulion Ollama Generate"
}
isulion_OllamaGenerate.py
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from ollama import Client
import logging
class OllamaGenerate:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"text": ("STRING", {
"multiline": True,
"default": "What is Art?",
"tooltip": "Input text to send to Ollama"
}),
"system": ("STRING", {
"multiline": True,
"default": "",
"tooltip": "System prompt to set the behavior and context for the model"
}),
"model_name": ("STRING", {
"default": "dolphin-llama3",
"tooltip": "Name of the Ollama model to use"
}),
"host_url": ("STRING", {
"default": " http://localhost:11434",
"tooltip": "Ollama server URL (e.g., http://localhost:11434)"
}),
"keep_alive": (["true", "false"], {
"default": "true",
"tooltip": "Keep model loaded in memory (true) or unload after each generation (false)"
}),
},
}
RETURN_TYPES = ("STRING",)
RETURN_NAMES = ("response",)
FUNCTION = "generate"
CATEGORY = "Isulion/Ollama"
def generate(self, text, system, model_name, host_url, keep_alive):
try:
# Create client with provided host URL
client = Client(host=host_url)
# Convert keep_alive string to appropriate value
keep_alive_value = "5m" if keep_alive == "true" else "0m"
# Generate response using the specified model
response = client.generate(
model=model_name,
prompt=text,
system=system, # Added system prompt
keep_alive=keep_alive_value
)
return (response['response'],)
except Exception as e:
logging.error(f"Error generating response from Ollama: {str(e)}")
return (f"Error: {str(e)}",)
NODE_CLASS_MAPPINGS = {
"OllamaGenerate": OllamaGenerate,
}
NODE_DISPLAY_NAME_MAPPINGS = {
"OllamaGenerate": "Ollama Generate",
}
from ollama import Client
class OllamaGenerate:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"prompt": ("STRING", {
"multiline": True,
"default": "What is Art?"
}),
"url": ("STRING", {
"multiline": False,
"default": "http://127.0.0.1:11434"
}),
"model": ((), {}),
},
}
RETURN_TYPES = ("STRING",)
RETURN_NAMES = ("response",)
FUNCTION = "ollama_generate"
CATEGORY = "Ollama"
def ollama_generate(self, prompt, url, model):
# Keep_alive is now hardcoded to 0 (not visible to user)
keep_alive = 0
client = Client(host=url)
# Generate the response from the model
response = client.generate(
model=model,
prompt=prompt,
keep_alive=f"{keep_alive}m" # keep_alive is always 0
)
return (response['response'],)
# Register the node with your node mapping system
NODE_CLASS_MAPPINGS = {
"OllamaGenerate": OllamaGenerate,
}
NODE_DISPLAY_NAME_MAPPINGS = {
"OllamaGenerate": "Ollama Generate",
}
isulion_model_selector.py
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import subprocess
import logging
class OllamaModelSelector:
@classmethod
def INPUT_TYPES(s):
try:
# Run ollama list command
result = subprocess.run(['ollama', 'list'], capture_output=True, text=True)
if result.returncode == 0:
# Parse the output, skipping the header line
lines = result.stdout.strip().split('\n')[1:]
models = []
for line in lines:
if line.strip(): # Skip empty lines
# First column before whitespace is the model name
model_name = line.split()[0]
# Remove ':latest' suffix if present
model_name = model_name.replace(':latest', '')
models.append(model_name)
# Sort models alphabetically for better UX
models.sort()
if not models: # If no models found after parsing
models = ["No models installed - Use 'ollama pull' to install models"]
else:
models = ["Error running ollama list command"]
logging.warning(f"Failed to get models from ollama list: {result.stderr}")
except FileNotFoundError:
models = ["Ollama not found - Is it installed?"]
logging.error("Ollama command not found. Please ensure Ollama is installed and in PATH")
except Exception as e:
models = ["Error getting model list"]
logging.error(f"Error getting Ollama models: {str(e)}")
return {
"required": {
"model_name": (models, {
"default": models[2] if models else "No models found",
"tooltip": "Select an Ollama model to use"
}),
}
}
RETURN_TYPES = ("STRING",) # Simple string return type
RETURN_NAMES = ("MODEL",)
FUNCTION = "get_model"
CATEGORY = "Isulion/Ollama"
DESCRIPTION = "Select an Ollama model from installed models"
def get_model(self, model_name):
# Return just the model name string
return (model_name,) # Return as tuple with single string value
NODE_CLASS_MAPPINGS = {
"OllamaModelSelector": OllamaModelSelector
}
NODE_DISPLAY_NAME_MAPPINGS = {
"OllamaModelSelector": "Ollama Model Selector"
}
ixulion_ollamaModelSelect.py
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import subprocess
import logging
class OllamaModelSelector:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(s):
try:
# Run ollama list command
result = subprocess.run(['ollama', 'list'], capture_output=True, text=True)
if result.returncode == 0:
# Parse the output, skipping the header line
lines = result.stdout.strip().split('\n')[1:]
models = []
for line in lines:
if line.strip(): # Skip empty lines
# First column before whitespace is the model name
model_name = line.split()[0]
# Remove ':latest' suffix if present
model_name = model_name.replace(':latest', '')
models.append(model_name)
# Sort models alphabetically for better UX
models.sort()
if not models: # If no models found after parsing
models = ["No models installed - Use 'ollama pull' to install models"]
else:
models = ["Error running ollama list command"]
logging.warning(f"Failed to get models from ollama list: {result.stderr}")
except FileNotFoundError:
models = ["Ollama not found - Is it installed?"]
logging.error("Ollama command not found. Please ensure Ollama is installed and in PATH")
except Exception as e:
models = ["Error getting model list"]
logging.error(f"Error getting Ollama models: {str(e)}")
return {
"required": {
"model_name": (models, {
"default": "dolphin-llama3" if models else "No models found",
"tooltip": "Select an Ollama model to use"
}),
}
}
RETURN_TYPES = ("STRING",)
RETURN_NAMES = ("MODEL_NAME",)
FUNCTION = "get_model"
CATEGORY = "Isulion/Ollama"
DESCRIPTION = "Select an Ollama model from installed models"
def get_model(self, model_name):
return (model_name,)
# Fix: Make sure the key in NODE_CLASS_MAPPINGS matches the key in NODE_DISPLAY_NAME_MAPPINGS
NODE_CLASS_MAPPINGS = {
"OllamaModelSelector": OllamaModelSelector
}
NODE_DISPLAY_NAME_MAPPINGS = {
"OllamaModelSelector": "Ollama Model Selector"
}
workflowsJsonTrainingData/10chain.json
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workflowsJsonTrainingData/10chain_agents.json
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workflowsJsonTrainingData/llm_chain_agents_10chain.json
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workflowsJsonTrainingData/llm_chain_agents_10chain_aligned.json
-228
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workflowsJsonTrainingData/llm_chain_agents_10chain_corrected.json
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workflowsJsonTrainingData/llm_chain_agents_roles.json
-433
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