Avo-k commited on
Commit
7498c33
1 Parent(s): 3fff807

prompt are now open source

Browse files

+ got rid of tqdm bars for every retriever call

Files changed (1) hide show
  1. app.py +36 -12
app.py CHANGED
@@ -13,17 +13,44 @@ import numpy as np
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  from datetime import datetime
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  from azure.storage.fileshare import ShareServiceClient
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- # from dotenv import load_dotenv
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- # load_dotenv()
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-
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- print(os.environ["content"], os.environ["sources"], sep="\n-\n" * 2)
20
 
21
  theme = gr.themes.Soft(
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  primary_hue="sky",
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  font=[gr.themes.GoogleFont("Inter"), "ui-sans-serif", "system-ui", "sans-serif"],
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  )
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- system_template = {"role": "system", "content": os.environ["content"]}
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  openai.api_type = "azure"
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  openai.api_key = os.environ["api_key"]
@@ -37,6 +64,7 @@ retrieve_all = EmbeddingRetriever(
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  ),
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  embedding_model="sentence-transformers/multi-qa-mpnet-base-dot-v1",
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  model_format="sentence_transformers",
 
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  )
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  retrieve_giec = EmbeddingRetriever(
@@ -88,7 +116,7 @@ def chat(
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  reformulated_query = openai.Completion.create(
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  engine="climateGPT",
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- prompt=f"Reformulate the following user message to be a short standalone question in English, in the context of an educationnal discussion about climate change.\n---\nquery: La technologie nous sauvera-t-elle ?\nstandalone question: Can technology help humanity mitigate the effects of climate change?\n---\nquery: what are our reserves in fossil fuel?\nstandalone question: What are the current reserves of fossil fuels and how long will they last?\n---\nquery: {query}\nstandalone question: ",
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  temperature=0,
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  max_tokens=128,
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  stop=["\n---\n", "<|im_end|>"],
@@ -105,7 +133,7 @@ def chat(
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  for i, d in enumerate(docs, 1)
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  ]
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  )
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- messages.append({"role": "system", "content": f"{os.environ['sources']}\n\n{sources}"})
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  response = openai.Completion.create(
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  engine="climateGPT",
@@ -255,11 +283,7 @@ Version 0.2-beta - This tool is under active development
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  with gr.Column(scale=1, variant="panel"):
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  gr.Markdown("### Sources")
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  sources_textbox = gr.Textbox(interactive=False, show_label=False, max_lines=50)
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- # reports_select = gr.Dropdown(
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- # ["IPCC only", "All available"],
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- # default="All available",
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- # label="Select reports",
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- # ),
263
  ask.submit(
264
  fn=chat,
265
  inputs=[
 
13
  from datetime import datetime
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  from azure.storage.fileshare import ShareServiceClient
15
 
 
 
 
 
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  theme = gr.themes.Soft(
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  primary_hue="sky",
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  font=[gr.themes.GoogleFont("Inter"), "ui-sans-serif", "system-ui", "sans-serif"],
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  )
21
 
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+ init_prompt = (
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+ "You are ClimateGPT, an AI Assistant by Ekimetrics. "
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+ "You are given extracted parts of IPCC reports and a question."
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+ " Provide a clear and structured answer based on the context provided. "
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+ "When relevant, use bullet points and lists to structure your answers."
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+ )
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+ sources_prompt = (
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+ "When relevant, use facts and numbers from the following documents in your answer. "
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+ "Whenever you use information from a document, reference it at the end of the sentence (ex: [doc 2]). "
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+ "You don't have to use all documents, only if it makes sense in the conversation. "
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+ "If no relevant information to answer the question is present in the documents, "
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+ "just say you don't have enough information to answer."
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+ )
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+
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+
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+ def get_reformulation_prompt(query: str) -> str:
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+ return f"""Reformulate the following user message to be a short standalone question in English, in the context of an educationnal discussion about climate change.
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+ ---
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+ query: La technologie nous sauvera-t-elle ?
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+ standalone question: Can technology help humanity mitigate the effects of climate change?
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+ ---
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+ query: what are our reserves in fossil fuel?
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+ standalone question: What are the current reserves of fossil fuels and how long will they last?
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+ ---
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+ query: {query}
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+ standalone question:"""
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+
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+
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+ system_template = {
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+ "role": "system",
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+ "content": init_prompt,
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+ }
54
 
55
  openai.api_type = "azure"
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  openai.api_key = os.environ["api_key"]
 
64
  ),
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  embedding_model="sentence-transformers/multi-qa-mpnet-base-dot-v1",
66
  model_format="sentence_transformers",
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+ progress_bar=False,
68
  )
69
 
70
  retrieve_giec = EmbeddingRetriever(
 
116
 
117
  reformulated_query = openai.Completion.create(
118
  engine="climateGPT",
119
+ prompt=get_reformulation_prompt(query),
120
  temperature=0,
121
  max_tokens=128,
122
  stop=["\n---\n", "<|im_end|>"],
 
133
  for i, d in enumerate(docs, 1)
134
  ]
135
  )
136
+ messages.append({"role": "system", "content": f"{sources_prompt}\n\n{sources}"})
137
 
138
  response = openai.Completion.create(
139
  engine="climateGPT",
 
283
  with gr.Column(scale=1, variant="panel"):
284
  gr.Markdown("### Sources")
285
  sources_textbox = gr.Textbox(interactive=False, show_label=False, max_lines=50)
286
+
 
 
 
 
287
  ask.submit(
288
  fn=chat,
289
  inputs=[