app.py
CHANGED
@@ -10,35 +10,30 @@ from utils import (
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system_template = {"role": "system", "content": os.environ["content"]}
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-
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)
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document_store = FAISSDocumentStore.load(
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index_path="./documents/climate_gpt.faiss",
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config_path="./documents/climate_gpt.json",
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)
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-
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document_store=
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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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def gen_conv(query: str, history=[system_template], report_type="All available", threshold=0.56):
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""
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Args:
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query (str): the user message
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history (list, optional): history of the chat messages. Defaults to [system_template].
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ipcc (bool, optional): _description_. Defaults to True.
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Returns:
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_type_: _description_
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"""
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messages = history + [{"role": "user", "content": query}]
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docs = retriever.retrieve(query=query, top_k=10)
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sources = "\n\n".join(
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f"doc {i}: {d.meta['file_name']} page {d.meta['page_number']}\n{d.content}"
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for i, d in enumerate(docs, 1)
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)
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system_template = {"role": "system", "content": os.environ["content"]}
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+
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retrieve_all = EmbeddingRetriever(
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document_store=FAISSDocumentStore.load(
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index_path="./documents/climate_gpt.faiss",
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config_path="./documents/climate_gpt.json",
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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(
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document_store=FAISSDocumentStore.load(
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index_path="./documents/climate_gpt_only_giec.faiss",
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config_path="./documents/climate_gpt_only_giec.json",
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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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def gen_conv(query: str, history: list = [system_template], report_type="All available", threshold=0.56):
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retriever = retrieve_all if report_type=="All available" else retrieve_giec
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docs = retriever.retrieve(query=query, top_k=10)
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messages = history + [{"role": "user", "content": query}]
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sources = "\n\n".join(
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f"doc {i}: {d.meta['file_name']} page {d.meta['page_number']}\n{d.content}"
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for i, d in enumerate(docs, 1)
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