Spaces:
Sleeping
Sleeping
File size: 4,358 Bytes
0aca678 0dbfea5 0aca678 0dbfea5 0aca678 0dbfea5 0aca678 0dbfea5 0aca678 0dbfea5 0aca678 0dbfea5 0aca678 0dbfea5 0aca678 0dbfea5 0aca678 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 |
import streamlit as st
import json
class Streamlit_UI() :
def __init__(self):
pass
# Function to load JSON files
def load_json(self,file_path):
try:
with open(file_path, 'r') as f:
return json.load(f)
except Exception as e:
st.error(f"Error loading {file_path}: {e}")
return []
def load_streamlit_ui(self):
# Load configuration files
anthropic_file = "./LLMCONFIG/ANTROPIC_CLAUDE_CONFIG_LIST.json"
google_file = "./LLMCONFIG/GOOGLE_GEMINI_CONFIG_LIST.json"
mistral_file = "./LLMCONFIG/MISTRAL_AI_CONFIG_LIST.json"
ollama_file = "./LLMCONFIG/OLLAMA_LLM_CONFIG_LIST.json"
groq_file = "./LLMCONFIG/GROQ_CONFIG_LIST.json"
bedrock_file = "./LLMCONFIG/BEDROCK_CONFIG_LIST.json"
togetherai_file = "./LLMCONFIG/TOGETHERAI_CONFIG_LIST.json"
# Load model configurations
anthropic_models = self.load_json(anthropic_file)
google_models = self.load_json(google_file)
mistral_models = self.load_json(mistral_file)
ollama_models = self.load_json(ollama_file)
groq_models = self.load_json(groq_file)
bedrock_models = self.load_json(bedrock_file)
togetherai_models = self.load_json(togetherai_file)
# Combine all API types into a single dictionary
api_data = {
"groq": groq_models,
"together":togetherai_models,
"openai": [],
"mistral": mistral_models,
"ollama": ollama_models,
"anthropic": anthropic_models,
"bedrock": bedrock_models,
"google": google_models
}
user_inputs = {}
st.set_page_config(page_title= "AUTOGEN ~ 0.2", layout="wide",page_icon='🤖')
st.header("🤖 " + "AUTOGEN ~ 0.2")
with st.sidebar:
# Streamlit UI
st.title("LLM Configuraton ⚙️")
# Dropdown to select API type
user_inputs['api_type'] = api_type = st.selectbox("Select API Type", options=api_data.keys())
# Input handling for OpenAI
if api_type == "openai":
st.write("### Provide OpenAI Configuration Details")
selected_model_name = st.text_input("Enter Model Name", value="")
st.session_state['api_key'] = st.text_input("Enter API Key", value="", type="password")
else:
# Get models based on selected API type
selected_models = api_data.get(api_type, [])
# Dropdown to select model
model_names = [model["model"] for model in selected_models]
if st.checkbox("Select Model from list : ",True):
selected_model_name = st.selectbox("Select Model", options=model_names)
# Find the selected model configuration
selected_model_config = next(
(model for model in selected_models if model["model"] == selected_model_name), {}
)
# Input fields for the selected model configuration
for key, value in selected_model_config.items():
if key not in ["api_type", "model"]:
# Use a password field for API keys, otherwise a text input
input_label = f"Enter {key}"
if "key" in key.lower():
st.session_state['api_key'] = user_inputs[key] = st.text_input(input_label, value="", type="password")
elif isinstance(value, bool):
user_inputs[key] = st.checkbox(input_label, value=value)
else:
user_inputs[key] = st.text_input(input_label, value=str(value))
else :
selected_model_name = st.text_input("Enter Model Name", value="")
st.session_state['api_key'] = st.text_input("Enter api_key", value="", type="password",key='input_modelname')
user_inputs['selected_model_name']= selected_model_name
return user_inputs
|