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Runtime error
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•
83e218d
1
Parent(s):
9e6b8ed
Fixed imports and cleaned code
Browse files- app.py +2 -9
- backend/retrieval_augmented_generation.py +0 -38
app.py
CHANGED
@@ -1,7 +1,9 @@
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from time import perf_counter
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from jinja2 import Template
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from backend.semantic_search import qd_retriever
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template_string = """
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@@ -53,9 +55,6 @@ function toggleContent(docID) {
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template = Template(template_string)
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md_template = Template(md_template_string)
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import gradio as gr
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from backend.query_llm import generate
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def add_text(history, text):
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@@ -77,12 +76,6 @@ def bot(history, system_prompt=""):
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prompt = template.render(documents=documents, query=query)
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md_prompt = md_template.render(documents=documents, query=query)
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# # Query LLM with prompt based on relevant documents
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# llm_start = perf_counter()
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# result = generate(prompt=prompt, history='')
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# llm_time = llm_start - perf_counter()
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# times = (document_time, llm_time)
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history[-1][1] = ""
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for character in generate(prompt, history[:-1]):
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history[-1][1] = character
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from time import perf_counter
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import gradio as gr
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from jinja2 import Template
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from backend.query_llm import generate
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from backend.semantic_search import qd_retriever
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template_string = """
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template = Template(template_string)
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md_template = Template(md_template_string)
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def add_text(history, text):
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prompt = template.render(documents=documents, query=query)
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md_prompt = md_template.render(documents=documents, query=query)
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history[-1][1] = ""
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for character in generate(prompt, history[:-1]):
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history[-1][1] = character
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backend/retrieval_augmented_generation.py
DELETED
@@ -1,38 +0,0 @@
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from time import perf_counter
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from jinja2 import Template
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from backend.query_llm import generate
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from backend.semantic_search import qd_retriever
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template_string = """
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Use the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer.
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Context:
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---
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{% for doc in documents %}
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{{ doc.content }}
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---
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{% endfor %}
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Query: {{ query }}
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"""
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template = Template(template_string)
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def rag(query, top_k=5):
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# Retrieve documents relevant to query
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document_start = perf_counter()
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documents = qd_retriever.retrieve(query, top_k=top_k)
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document_time = document_start - perf_counter()
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# Create Prompt
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prompt = template.render(documents=documents, query=query)
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# Query LLM with prompt based on relevant documents
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llm_start = perf_counter()
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result = generate(prompt=prompt, history='')
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llm_time = llm_start - perf_counter()
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times = (document_time, llm_time)
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return prompt, result
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