moved imports
Browse files
app.py
CHANGED
@@ -3,25 +3,13 @@ import os
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import tiktoken
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import streamlit as st
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from llama_index.llms.gemini import Gemini
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from llama_index.llms.huggingface import HuggingFaceLLM
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from llama_index.llms.huggingface_api import HuggingFaceInferenceAPI
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from llama_index.llms.mistralai import MistralAI
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from llama_index.llms.openai import OpenAI
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from llama_index.embeddings.openai import OpenAIEmbedding
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from llama_index.embeddings.huggingface import HuggingFaceEmbedding, HuggingFaceInferenceAPIEmbedding
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from llama_index.embeddings.mistralai import MistralAIEmbedding
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from llama_index.core import (
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VectorStoreIndex,
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Settings,
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)
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from llama_parse import LlamaParse
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from transformers import AutoTokenizer
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from streamlit_pdf_viewer import pdf_viewer
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MAX_OUTPUT_TOKENS = 2048
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@@ -97,6 +85,10 @@ def main():
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raise NotImplementedError(f"{provider} is not supported yet")
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elif provider == 'huggingface':
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if llm_name is not None and embed_name is not None:
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os.environ['HFTOKEN'] = str(llm_key)
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Settings.llm = HuggingFaceInferenceAPI(
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model_name=llm_name,
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@@ -114,6 +106,9 @@ def main():
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)
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Settings.context_window = 4096
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elif provider == 'mistralai':
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os.environ['MISTRAL_API_KEY'] = str(llm_key)
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Settings.llm = MistralAI(
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model=llm_name,
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@@ -130,6 +125,9 @@ def main():
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)
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Settings.context_window = 4096 # max possible
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elif provider == 'openai':
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os.environ["OPENAI_API_KEY"] = str(llm_key)
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Settings.llm = OpenAI(
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model=llm_name,
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import tiktoken
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import streamlit as st
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# from llama_index.llms.gemini import Gemini
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from llama_index.core import (
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VectorStoreIndex,
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Settings,
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)
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from llama_parse import LlamaParse
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from streamlit_pdf_viewer import pdf_viewer
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MAX_OUTPUT_TOKENS = 2048
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raise NotImplementedError(f"{provider} is not supported yet")
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elif provider == 'huggingface':
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if llm_name is not None and embed_name is not None:
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from llama_index.llms.huggingface_api import HuggingFaceInferenceAPI
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from llama_index.embeddings.huggingface import HuggingFaceInferenceAPIEmbedding
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from transformers import AutoTokenizer
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os.environ['HFTOKEN'] = str(llm_key)
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Settings.llm = HuggingFaceInferenceAPI(
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model_name=llm_name,
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)
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Settings.context_window = 4096
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elif provider == 'mistralai':
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from llama_index.llms.mistralai import MistralAI
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from llama_index.embeddings.mistralai import MistralAIEmbedding
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os.environ['MISTRAL_API_KEY'] = str(llm_key)
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Settings.llm = MistralAI(
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model=llm_name,
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)
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Settings.context_window = 4096 # max possible
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elif provider == 'openai':
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from llama_index.llms.openai import OpenAI
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from llama_index.embeddings.openai import OpenAIEmbedding
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os.environ["OPENAI_API_KEY"] = str(llm_key)
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Settings.llm = OpenAI(
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model=llm_name,
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