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Update app.py
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app.py
CHANGED
@@ -10,6 +10,7 @@ from langchain_community.vectorstores.neo4j_vector import remove_lucene_chars
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from langchain_community.graphs import Neo4jGraph
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from langchain_experimental.graph_transformers import LLMGraphTransformer
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from langchain_core.prompts import ChatPromptTemplate
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# Neo4j setup
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graph = Neo4jGraph(
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@@ -18,6 +19,16 @@ graph = Neo4jGraph(
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password="_x8f-_aAQvs2NB0x6s0ZHSh3W_y-HrENDbgStvsUCM0"
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)
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# Define the ASR model with Whisper
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model_id = 'openai/whisper-large-v3'
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device = "cuda:0" if torch.cuda.is_available() else "cpu"
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@@ -174,4 +185,4 @@ interface = gr.Interface(
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)
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# Launch the Gradio app
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interface.launch()
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from langchain_community.graphs import Neo4jGraph
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from langchain_experimental.graph_transformers import LLMGraphTransformer
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from langchain_core.prompts import ChatPromptTemplate
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import time
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# Neo4j setup
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graph = Neo4jGraph(
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password="_x8f-_aAQvs2NB0x6s0ZHSh3W_y-HrENDbgStvsUCM0"
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)
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# Function to generate a full-text search query for Neo4j
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def generate_full_text_query(input: str) -> str:
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full_text_query = ""
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words = [el for el in input.split() if el]
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for word in words[:-1]:
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full_text_query += f" {word}~2 AND"
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full_text_query += f" {words[-1]}~2"
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return full_text_query.strip()
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# Define the ASR model with Whisper
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model_id = 'openai/whisper-large-v3'
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device = "cuda:0" if torch.cuda.is_available() else "cpu"
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)
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# Launch the Gradio app
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interface.launch(show_error=True)
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