gpaasch commited on
Commit
bb5eec7
·
1 Parent(s): 6afe259

added import

Browse files
Files changed (1) hide show
  1. src/app.py +8 -14
src/app.py CHANGED
@@ -1,16 +1,15 @@
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  import os
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  from pathlib import Path
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- from huggingface_hub import snapshot_download
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  import gradio as gr
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- from llama_index.core import Settings, ServiceContext
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  from llama_index.embeddings.huggingface import HuggingFaceEmbedding
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  from llama_index.llms.llama_cpp import LlamaCPP
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  from parse_tabular import create_symptom_index
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  import json
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- import torch
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  import psutil
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- import subprocess
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  from typing import Tuple, Dict
 
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  # Model options mapped to their requirements
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  MODEL_OPTIONS = {
@@ -109,11 +108,6 @@ def ensure_model():
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  # Ensure model is downloaded
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  model_path = ensure_model()
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- # Configure embeddings globally
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- Settings.embed_model = HuggingFaceEmbedding(
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- model_name="sentence-transformers/all-MiniLM-L6-v2"
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- )
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-
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  # Configure local LLM with LlamaCPP
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  llm = LlamaCPP(
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  model_path=model_path,
@@ -122,13 +116,13 @@ llm = LlamaCPP(
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  context_window=2048
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  )
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- # Create service context with local LLM
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- service_context = ServiceContext.from_defaults(
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- llm=llm,
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- embed_model=Settings.embed_model
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  )
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- # Create the index at startup with local service context
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  symptom_index = create_symptom_index()
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  # --- System prompt ---
 
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  import os
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  from pathlib import Path
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+ from huggingface_hub import hf_hub_download
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  import gradio as gr
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+ from llama_index.core import Settings
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  from llama_index.embeddings.huggingface import HuggingFaceEmbedding
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  from llama_index.llms.llama_cpp import LlamaCPP
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  from parse_tabular import create_symptom_index
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  import json
 
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  import psutil
 
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  from typing import Tuple, Dict
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+ import torch
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  # Model options mapped to their requirements
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  MODEL_OPTIONS = {
 
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  # Ensure model is downloaded
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  model_path = ensure_model()
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  # Configure local LLM with LlamaCPP
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  llm = LlamaCPP(
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  model_path=model_path,
 
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  context_window=2048
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  )
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+ # Configure global settings
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+ Settings.llm = llm
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+ Settings.embed_model = HuggingFaceEmbedding(
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+ model_name="sentence-transformers/all-MiniLM-L6-v2"
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  )
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+ # Create the index at startup
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  symptom_index = create_symptom_index()
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  # --- System prompt ---