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c46d1ce
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5766729
added dataset
Browse files- .gitattributes +1 -0
- Dataset/01-Introduction to Facebook AI Similarity Search (Faiss) | Pinecone.pdf +3 -0
- Dataset/02-Nearest Neighbor Indexes for Similarity Search | Pinecone.pdf +3 -0
- Dataset/03-Locality Sensitive Hashing (LSH): The Illustrated Guide | Pinecone.pdf +3 -0
- Dataset/04-Random Projection for Locality Sensitive Hashing | Pinecone.pdf +3 -0
- Dataset/05-Product Quantization | Pinecone.pdf +3 -0
- src/prompts.py +5 -1
- templates/template_html.j2 +0 -4
.gitattributes
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@@ -34,3 +34,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.faiss filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.faiss filter=lfs diff=lfs merge=lfs -text
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*.pdf filter=lfs diff=lfs merge=lfs -text
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Dataset/01-Introduction to Facebook AI Similarity Search (Faiss) | Pinecone.pdf
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version https://git-lfs.github.com/spec/v1
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size 5936900
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Dataset/02-Nearest Neighbor Indexes for Similarity Search | Pinecone.pdf
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version https://git-lfs.github.com/spec/v1
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oid sha256:d604b90c80899f4d65ea8432f407be47557b12af9ac583a8ac7c1186bdcb97b6
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size 1274709
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Dataset/03-Locality Sensitive Hashing (LSH): The Illustrated Guide | Pinecone.pdf
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version https://git-lfs.github.com/spec/v1
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oid sha256:4d037ac60fe63d728ceaa78e94c66d969d5da306662a7136b94e4196101f314f
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size 506228
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Dataset/04-Random Projection for Locality Sensitive Hashing | Pinecone.pdf
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version https://git-lfs.github.com/spec/v1
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oid sha256:a231cb5311a355331c9ac7c8c6d49cac3ae225ae98c8e74dbb9772026cded853
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size 1652938
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Dataset/05-Product Quantization | Pinecone.pdf
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version https://git-lfs.github.com/spec/v1
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oid sha256:8502eaf10adc26a6071fec6e47855eea94239a286b023caf28b9c16c9b5bf7d7
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size 2575929
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src/prompts.py
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@@ -18,8 +18,12 @@ In this case your response must be "Unrelated." without any additional informati
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SYSTEM_PROMPT = """
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Your task is to answer user's questions. You must provide clear and concise answers to user's queries.
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If user provides any documents in 'Documents' section, your answer must be based on the information from these documents.
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"""
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SYSTEM_PROMPT = """
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Your task is to answer user's questions. You must provide clear and concise answers to user's queries.
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If user provides any documents in 'Documents' section, your answer must be based on the information from these documents.
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Keep in mind, that documents are not always relevant to the user's query and may have irrelevant information, so you must use the most relevant parts of the documents to answer user's questions.
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If 'Documents' section is empty, it means that user asks follow-up questions or questions that are not related to any specific topic.
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Answer these questions based on your knowledge and common sense.
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"""
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templates/template_html.j2
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</head>
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<body>
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<div class="prose svelte-1ybaih5" id="component-6">
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<h2>Prompt</h2>
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Below is the prompt that is given to the model. <hr>
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{#<h2>Instructions</h2>#}
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{# <span class="instructions">{{ instructions }}</span>#}
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<h2>Query</h2>
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<span class="query">{{ query }}</span>
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<h2>Context</h2>
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</head>
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<body>
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<div class="prose svelte-1ybaih5" id="component-6">
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<h2>Query</h2>
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<span class="query">{{ query }}</span>
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<h2>Context</h2>
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